diff --git a/.DS_Store b/.DS_Store index 7ca72387..28ad8ea3 100644 Binary files a/.DS_Store and b/.DS_Store differ diff --git a/explore-assistant-examples/.env b/explore-assistant-examples/.env index 1a5759fd..db2f1a27 100644 --- a/explore-assistant-examples/.env +++ b/explore-assistant-examples/.env @@ -1,5 +1,5 @@ ##Update the variables in this environment file to automate the bash scripts for loading & updating the examples -PROJECT_ID="PROJECT_ID" ##Required. The Google Cloud project ID where your BigQuery dataset resides. -DATASET_ID="DATASET_ID" ##The ID of the BigQuery dataset. Defaults to explore_assistant. -EXPLORE_ID="MODEL:EXPLORE_ID" ##Required. A unique identifier for the dataset rows related to a specific use case or query (used in deletion and insertion). +PROJECT_ID=seraphic-ripsaw-360618 +DATASET_ID=explore_assistant +EXPLORE_ID=nabc:spins_nlp diff --git a/explore-assistant-examples/.ipynb_checkpoints/convert_examples-checkpoint.ipynb b/explore-assistant-examples/.ipynb_checkpoints/convert_examples-checkpoint.ipynb new file mode 100644 index 00000000..50ca2548 --- /dev/null +++ b/explore-assistant-examples/.ipynb_checkpoints/convert_examples-checkpoint.ipynb @@ -0,0 +1,56 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "plaintext" + } + }, + "outputs": [], + "source": [ + "#Convert CSV to JSON\n", + "import csv\n", + "import json\n", + "\n", + "\n", + "def csv_to_json(csv_file, json_file):\n", + " \"\"\"Converts a CSV file to a JSON file.\n", + "\n", + "\n", + " Args:\n", + " csv_file: The path to the CSV file.\n", + " json_file: The path to the output JSON file.\n", + " \"\"\"\n", + "\n", + "\n", + " data = []\n", + " with open(csv_file, 'r') as csvfile:\n", + " csvreader = csv.DictReader(csvfile)\n", + " for row in csvreader:\n", + " data.append(dict(row))\n", + "\n", + "\n", + " with open(json_file, 'w') as jsonfile:\n", + " json.dump(data, jsonfile, indent=4)\n", + "\n", + "\n", + "\n", + "\n", + "# Example usage\n", + "csv_file = 'DMi EA Prompts - Explore Assistant Order Details - Cleansed.csv'\n", + "json_file = 'dmi_examples.json'\n", + "csv_to_json(csv_file, json_file)\n", + "print(f\"CSV converted to JSON: {json_file}\")" + ] + } + ], + "metadata": { + "language_info": { + "name": "python" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/explore-assistant-examples/convert_examples.ipynb b/explore-assistant-examples/convert_examples.ipynb new file mode 100644 index 00000000..37da9ea2 --- /dev/null +++ b/explore-assistant-examples/convert_examples.ipynb @@ -0,0 +1,56 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "plaintext" + } + }, + "outputs": [], + "source": [ + "#Convert CSV to JSON\n", + "import csv\n", + "import json\n", + "\n", + "\n", + "def csv_to_json(csv_file, json_file):\n", + " \"\"\"Converts a CSV file to a JSON file.\n", + "\n", + "\n", + " Args:\n", + " csv_file: The path to the CSV file.\n", + " json_file: The path to the output JSON file.\n", + " \"\"\"\n", + "\n", + "\n", + " data = []\n", + " with open(csv_file, 'r') as csvfile:\n", + " csvreader = csv.DictReader(csvfile)\n", + " for row in csvreader:\n", + " data.append(dict(row))\n", + "\n", + "\n", + " with open(json_file, 'w') as jsonfile:\n", + " json.dump(data, jsonfile, indent=4)\n", + "\n", + "\n", + "\n", + "\n", + "# Example usage\n", + "csv_file = '/Users/kalib/Downloads/NABC Examples - examples_cleansed.csv'\n", + "json_file = 'nabc_examples.json'\n", + "csv_to_json(csv_file, json_file)\n", + "print(f\"CSV converted to JSON: {json_file}\")" + ] + } + ], + "metadata": { + "language_info": { + "name": "python" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/explore-assistant-examples/load_examples.sh b/explore-assistant-examples/load_examples.sh old mode 100644 new mode 100755 index ddccc652..c3fdd68b --- a/explore-assistant-examples/load_examples.sh +++ b/explore-assistant-examples/load_examples.sh @@ -2,7 +2,7 @@ source .env TABLE_ID="explore_assistant_examples" ##The ID of the BigQuery table where the data will be inserted. Set to explore_assistant_examples. -JSON_FILE="examples.json" ##The path to the JSON file containing the data to be loaded. Set to examples.json. +JSON_FILE="nabc_examples.json" ##The path to the JSON file containing the data to be loaded. Set to examples.json. python load_examples.py \ --project_id $PROJECT_ID \ diff --git a/explore-assistant-examples/nabc_examples.json b/explore-assistant-examples/nabc_examples.json new file mode 100644 index 00000000..ad233fee --- /dev/null +++ b/explore-assistant-examples/nabc_examples.json @@ -0,0 +1,1022 @@ +[ + { + "input": "How many pounds of frozen blueberries were sold on promotion over this winter versus last winter?", + "output": "fields=spins_nlp.rma_units_incremental_promo_any_sum,spins_nlp.product_type,spins_nlp.period_ending_year&pivots=spins_nlp.period_ending_year&fill_fields=spins_nlp.period_ending_year&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.period_ending_date]=2+year+ago+for+2+year&f[spins_nlp.period_ending_month_name]=December%2CJanuary%2CFebruary&sorts=spins_nlp.period_ending_year,spins_nlp.rma_units_incremental_promo_any_sum+desc+0" + }, + { + "input": "How many dollars of frozen blueberries were sold on promotion over this fall versus last fall?", + "output": "fields=spins_nlp.rma_units_incremental_promo_any_sum,spins_nlp.product_type,spins_nlp.period_ending_year&pivots=spins_nlp.period_ending_year&fill_fields=spins_nlp.period_ending_year&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.period_ending_date]=2+year+ago+for+2+year&f[spins_nlp.period_ending_month_name]=September%2COctober%2CNovember&sorts=spins_nlp.period_ending_year,spins_nlp.rma_units_incremental_promo_any_sum+desc+0" + }, + { + "input": "What parent companies sell the most Frozen Blueberries by pounds?", + "output": "fields=spins_nlp.parent_company,spins_nlp.total_lbs&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.geography_type]=&f[spins_nlp.product_type]=FZ+FRUIT+-+BLUEBERRIES%25&f[spins_nlp.total_units]=&sorts=spins_nlp.total_lbs+desc" + }, + { + "input": "Show all the sales by units at Albertson stores", + "output": "fields=spins_nlp.total_units&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=%25ALBERTSON%25&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.geography_abbreviated]=&sorts=spins_nlp.total_units+desc+0" + }, + { + "input": "How many pounds of blueberries were sold last month compared to the year prior?", + "output": "fields=spins_nlp.geography_filter,spins_nlp.date_in_period_month,spins_nlp.total_lbs,spins_nlp.total_lbs_prior&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&sorts=spins_nlp.date_in_period_month+desc" + }, + { + "input": "Is total US blueberry sales up this year versus last year for January? ", + "output": "fields=spins_nlp.total_dollars,spins_nlp.period_ending_year,spins_nlp.period_ending_month_name&pivots=spins_nlp.period_ending_year&fill_fields=spins_nlp.period_ending_year&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_month]=after+2023%2F01%2F01&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%25%2CFZ+FRUIT+-+BLUEBERRIES%25&f[spins_nlp.period_ending_month_name]=January&sorts=spins_nlp.period_ending_year,spins_nlp.total_dollars+desc+0" + }, + { + "input": "What parent companies sell the most Fresh Blueberries by units?", + "output": "fields=spins_nlp.parent_company,spins_nlp.total_units&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.geography_type]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%25&f[spins_nlp.total_units]=&sorts=spins_nlp.total_units+desc" + }, + { + "input": "What parent companies sell no Frozen Blueberries?", + "output": "fields=spins_nlp.parent_company,spins_nlp.total_units&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.geography_type]=&f[spins_nlp.product_type]=FZ+FRUIT+-+BLUEBERRIES%25&f[spins_nlp.total_units]=0&sorts=spins_nlp.total_units+desc" + }, + { + "input": "What parent companies sell no Fresh Blueberries?", + "output": "fields=spins_nlp.parent_company,spins_nlp.total_units&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.geography_type]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%25&f[spins_nlp.total_units]=0&sorts=spins_nlp.total_units+desc" + }, + { + "input": "How many blueberries were sold in January 2024 in the US?", + "output": "fields=spins_nlp.total_units,spins_nlp.geography_filter,spins_nlp.period_ending_month_name&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.period_ending_month]=2024%2F01%2F01+to+2024%2F02%2F01" + }, + { + "input": "What are the top 5 regions for Fresh and Frozen Blueberry sales in the last year by pounds sold?", + "output": "fields=spins_nlp.total_lbs,spins_nlp.geography_filter&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.geography_type]=Market&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&sorts=spins_nlp.total_lbs+desc+0" + }, + { + "input": "What is the sales volume comparison between organic and conventional blueberries?", + "output": "fields=spins_nlp.total_dollars,spins_nlp.geography_filter&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.period_ending_year]=2024%2F01%2F01+to+2025%2F01%2F01&sorts=spins_nlp.total_dollars+desc+0" + }, + { + "input": "What is the most popular product description by pounds sold?", + "output": "fields=spins_nlp.total_lbs,spins_nlp.product_description&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.geography_abbreviated]=&sorts=spins_nlp.total_lbs+desc" + }, + { + "input": "What is the rate of change in blueberry sales volume?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.rma_lbs_sum&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How has the quantity of blueberries sold changed in the past year?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.rma_lbs_sum&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Do blueberry sales volumes peak during specific seasons?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.rma_lbs_sum&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Have there been seasonal fluctuations in blueberry sales volume?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.rma_lbs_sum&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Are there any notable trends in the volume of blueberries sold?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.rma_lbs_sum&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Have economic factors played a role in blueberry sales volume trends?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.rma_lbs_sum&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What has been the overall volume trend for blueberry sales?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.rma_lbs_sum&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "When are blueberries typically sold in the largest quantities?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.rma_lbs_sum&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Have changes in consumer preferences affected the volume of blueberries sold?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.rma_lbs_sum&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What is the general pattern of blueberry sales volume over the last 12 months?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.rma_lbs_sum&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How have weather conditions impacted blueberry production and sales volume?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.rma_lbs_sum&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Are blueberry sales volumes increasing, decreasing, or remaining stable?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.rma_lbs_sum&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Have there been significant changes in blueberry sales volume?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.rma_lbs_sum&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How have seasonal sales volume patterns for blueberries changed in the past year?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.rma_lbs_sum&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How has the quantity of blueberries sold evolved over the past year?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.rma_lbs_sum&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Are there any regional variations in blueberry sales volume seasonality?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.rma_lbs_sum&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How has the quantity of blueberries sold per unit of time evolved?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.rma_lbs_sum&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "2. Volume Trends: What is the trend in sales volume for blueberries over the last year?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.rma_lbs_sum&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What factors have influenced blueberry sales volume trends?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.rma_lbs_sum&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "By how much have blueberry sales volumes increased or decreased?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.rma_lbs_sum&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Are there any regional-specific factors driving blueberry sales volume patterns?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.rma_lbs_sum&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Which regions have shown the highest sales growth for blueberries?", + "output": "fields=spins_nlp.total_dollars,spins_nlp.geography_filter,spins_nlp.total_dollars_prior&f[spins_nlp.geography_type]=Region&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.current_date_range]=1+years&sorts=spins_nlp.total_dollars+desc+0" + }, + { + "input": "How many organic blueberries were sold in 2023?", + "output": "fields=spins_nlp.total_units,spins_nlp.geography_filter,spins_nlp.period_ending_year&f[spins_nlp.period_ending_year]=2023%2F01%2F01+to+2024%2F01%2F01&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.geography]=TOTAL+US+-+NATURAL+CHANNEL" + }, + { + "input": "Do price differences between different blueberry packaging types impact sales?", + "output": "fields=spins_nlp.base_size,spins_nlp.total_dollars,spins_nlp.total_lbs&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Which blueberry packaging format is the most widely available?", + "output": "fields=spins_nlp.base_size,spins_nlp.total_dollars,spins_nlp.total_lbs&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Is the demand for any particular blueberry packaging type growing or declining?", + "output": "fields=spins_nlp.base_size,spins_nlp.total_dollars,spins_nlp.total_lbs&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How has the popularity of different blueberry packaging formats changed over time?", + "output": "fields=spins_nlp.base_size,spins_nlp.total_dollars,spins_nlp.total_lbs&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Which packaging type for blueberries has a larger market share?", + "output": "fields=spins_nlp.base_size,spins_nlp.total_dollars,spins_nlp.total_lbs&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Are there any innovative packaging solutions for blueberries gaining traction?", + "output": "fields=spins_nlp.base_size,spins_nlp.total_dollars,spins_nlp.total_lbs&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What is the relative demand for different blueberry packaging types?", + "output": "fields=spins_nlp.base_size,spins_nlp.total_dollars,spins_nlp.total_lbs&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Are there any regional variations in the popularity of different blueberry packaging formats?", + "output": "fields=spins_nlp.base_size,spins_nlp.total_dollars,spins_nlp.total_lbs&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Which packaging types for blueberries are most in demand?", + "output": "fields=spins_nlp.base_size,spins_nlp.total_dollars,spins_nlp.total_lbs&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Which blueberry packaging types have the highest sales volume?", + "output": "fields=spins_nlp.base_size,spins_nlp.total_dollars,spins_nlp.total_lbs&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What factors influence the popularity of different blueberry packaging types?", + "output": "fields=spins_nlp.base_size,spins_nlp.total_dollars,spins_nlp.total_lbs&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What is the most popular way to package blueberries for sale?", + "output": "fields=spins_nlp.base_size,spins_nlp.total_dollars,spins_nlp.total_lbs&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How do the sales of bulk blueberries compare to pre-packaged blueberries?", + "output": "fields=spins_nlp.base_size,spins_nlp.total_dollars,spins_nlp.total_lbs&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What are the preferred packaging options for blueberries among consumers?", + "output": "fields=spins_nlp.base_size,spins_nlp.total_dollars,spins_nlp.total_lbs&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Are there significant differences in popularity between bulk and pre-packaged blueberries?", + "output": "fields=spins_nlp.base_size,spins_nlp.total_dollars,spins_nlp.total_lbs&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What are the future prospects for different blueberry packaging types?", + "output": "fields=spins_nlp.base_size,spins_nlp.total_dollars,spins_nlp.total_lbs&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How do consumer preferences affect the choice of blueberry packaging?", + "output": "fields=spins_nlp.base_size,spins_nlp.total_dollars,spins_nlp.total_lbs&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How do supply chain factors influence the availability and popularity of different blueberry packaging types?", + "output": "fields=spins_nlp.base_size,spins_nlp.total_dollars,spins_nlp.total_lbs&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Are there any emerging trends in blueberry packaging preferences?", + "output": "fields=spins_nlp.base_size,spins_nlp.total_dollars,spins_nlp.total_lbs&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Which blueberry packaging formats are most successful in the market?", + "output": "fields=spins_nlp.base_size,spins_nlp.total_dollars,spins_nlp.total_lbs&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "9. Packaging Preferences: What packaging types (e.g., bulk, pre-packaged) are most popular based on sales?", + "output": "fields=spins_nlp.base_size,spins_nlp.total_dollars,spins_nlp.total_lbs&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How have total blueberry sales trended by quarter over the past year across different regions?", + "output": "fields=spins_nlp.geography_filter,spins_nlp.total_dollars,spins_nlp.period_ending_quarter&f[spins_nlp.geography_type]=Region&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.current_date_range]=1+years&sorts=spins_nlp.period_ending_quarter" + }, + { + "input": "How did blueberries stack up against other fresh fruit products in 2023 in the conventional grow method?", + "output": "fields=spins_nlp.rma_units_sum,spins_nlp.product_type&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_month]=after+2023%2F01%2F01&f[spins_nlp.product_type]=FRESH+FRUIT%25&sorts=spins_nlp.rma_units_sum+desc" + }, + { + "input": "How do supply and demand dynamics influence the sales volume differences between different blueberry formats?", + "output": "fields=spins_nlp.rma_lbs_sum,spins_nlp.product_type&pivots=spins_nlp.product_type&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "By how much do the sales volumes of different blueberry formats differ?", + "output": "fields=spins_nlp.rma_lbs_sum,spins_nlp.product_type&pivots=spins_nlp.product_type&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How do consumer preferences affect the sales volumes of fresh, frozen, and dried blueberries?", + "output": "fields=spins_nlp.rma_lbs_sum,spins_nlp.product_type&pivots=spins_nlp.product_type&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What is the ratio of sales volume among fresh, frozen, and dried blueberries?", + "output": "fields=spins_nlp.rma_lbs_sum,spins_nlp.product_type&pivots=spins_nlp.product_type&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How do the sales volumes of different blueberry formats compare?", + "output": "fields=spins_nlp.rma_lbs_sum,spins_nlp.product_type&pivots=spins_nlp.product_type&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How do the sales volumes of different blueberry formats stack up against each other?", + "output": "fields=spins_nlp.rma_lbs_sum,spins_nlp.product_type&pivots=spins_nlp.product_type&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Which blueberry format has the highest sales volume?", + "output": "fields=spins_nlp.rma_lbs_sum,spins_nlp.product_type&pivots=spins_nlp.product_type&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How has the sales volume gap between different blueberry formats evolved?", + "output": "fields=spins_nlp.rma_lbs_sum,spins_nlp.product_type&pivots=spins_nlp.product_type&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What is the percentage difference in sales volume between fresh, frozen, and dried blueberries?", + "output": "fields=spins_nlp.rma_lbs_sum,spins_nlp.product_type&pivots=spins_nlp.product_type&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Are there significant differences in sales volume between different blueberry formats?", + "output": "fields=spins_nlp.rma_lbs_sum,spins_nlp.product_type&pivots=spins_nlp.product_type&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Are there any trends in the market share of fresh, frozen, and dried blueberries?", + "output": "fields=spins_nlp.rma_lbs_sum,spins_nlp.product_type&pivots=spins_nlp.product_type&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What is the sales volume distribution among fresh, frozen, and dried blueberries?", + "output": "fields=spins_nlp.rma_lbs_sum,spins_nlp.product_type&pivots=spins_nlp.product_type&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Which blueberry format has the largest market share?", + "output": "fields=spins_nlp.rma_lbs_sum,spins_nlp.product_type&pivots=spins_nlp.product_type&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Are there any regional variations in the sales volume comparison among different blueberry formats?", + "output": "fields=spins_nlp.rma_lbs_sum,spins_nlp.product_type&pivots=spins_nlp.product_type&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Do price differences between different blueberry formats impact sales volumes?", + "output": "fields=spins_nlp.rma_lbs_sum,spins_nlp.product_type&pivots=spins_nlp.product_type&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Is the sales volume of any blueberry format increasing or decreasing relative to the others?", + "output": "fields=spins_nlp.rma_lbs_sum,spins_nlp.product_type&pivots=spins_nlp.product_type&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Is the demand for any blueberry format growing faster or slower than the others?", + "output": "fields=spins_nlp.rma_lbs_sum,spins_nlp.product_type&pivots=spins_nlp.product_type&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What factors influence the sales volume differences between different blueberry formats?", + "output": "fields=spins_nlp.rma_lbs_sum,spins_nlp.product_type&pivots=spins_nlp.product_type&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "6. Product Formats: How do sales volumes compare for different blueberry formats (fresh, frozen, dried)?", + "output": "fields=spins_nlp.rma_lbs_sum,spins_nlp.product_type&pivots=spins_nlp.product_type&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How have the sales volumes of different blueberry formats changed over time?", + "output": "fields=spins_nlp.rma_lbs_sum,spins_nlp.product_type&pivots=spins_nlp.product_type&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What is the relative popularity of fresh, frozen, and dried blueberries in terms of sales?", + "output": "fields=spins_nlp.rma_lbs_sum,spins_nlp.product_type&pivots=spins_nlp.product_type&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What market saw the lowest retail sales in fresh blueberries in the last 12 weeks?", + "output": "fields=spins_nlp.geography_filter,spins_nlp.rma_dollars_sum&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY&f[spins_nlp.period_ending_week]=12+weeks&f[spins_nlp.geography_type]=Market&sorts=spins_nlp.rma_dollars_sum" + }, + { + "input": "What parent companies sell the most Fresh Blueberries by pounds?", + "output": "fields=spins_nlp.parent_company,spins_nlp.total_lbs&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_month]=after+2023%2F01%2F01&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%25&sorts=spins_nlp.total_lbs+desc" + }, + { + "input": "What is the trend in sales volume for blueberries over the last year?", + "output": "fields=spins_nlp.total_dollars,spins_nlp.period_ending_quarter&fill_fields=spins_nlp.period_ending_quarter&f[spins_nlp.geography_type]=Region&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.current_date_range]=1+years&sorts=spins_nlp.period_ending_quarter" + }, + { + "input": "how many pounds of blueberries were sold in March of 2023 by week in the total US?", + "output": "fields=spins_nlp.geography_filter,spins_nlp.period_ending_date,spins_nlp.total_lbs&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.period_ending_month]=2023%2F03%2F01+to+2023%2F04%2F01&sorts=spins_nlp.period_ending_date" + }, + { + "input": "What retail market saw the most growth in fresh blueberry sales by dollars in the last 12 weeks?", + "output": "fields=spins_nlp.geography_filter,spins_nlp.rma_dollars_sum&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY&f[spins_nlp.period_ending_week]=12+weeks&f[spins_nlp.geography_type]=Market&sorts=spins_nlp.rma_dollars_sum+desc" + }, + { + "input": "Which Blueberry manufacturer sells the most units of Blueberries in NYC?", + "output": "fields=spins_nlp.total_units,spins_nlp.parent_company&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.geography_abbreviated]=%25NEW+YORK%5E%2C+NY%25&sorts=spins_nlp.total_units+desc+0" + }, + { + "input": "What are the bottom 5 markets for Blueberry sales in total pounds?", + "output": "fields=spins_nlp.geography_abbreviated,spins_nlp.total_lbs&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.geography_abbreviated]=&f[spins_nlp.geography_type]=Market&sorts=spins_nlp.total_lbs" + }, + { + "input": "What is the most popular brand of blueberries?", + "output": "fields=spins_nlp.total_dollars,spins_nlp.geography_filter,spins_nlp.parent_company&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.period_ending_year]=2024%2F01%2F01+to+2025%2F01%2F01&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&sorts=spins_nlp.total_dollars+desc+0&limit=50" + }, + { + "input": "What are the total sales in Florida in the last two years by units sold?", + "output": "fields=spins_nlp.total_units&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.period_ending_week]=2+year+ago+for+2+year&f[spins_nlp.geography_abbreviated]=%25FL%25&f[spins_nlp.geography_type]=Market" + }, + { + "input": "What package size is the most popular for organic fresh blueberries in 2023 by total units sold?", + "output": "fields=spins_nlp.total_units,spins_nlp.base_size_filter&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FZ+FRUIT+-+BLUEBERRIES%2CFRESH+FRUIT+-+BLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_year]=2023&sorts=spins_nlp.total_units+desc+0" + }, + { + "input": "Are there any regional-specific factors driving blueberry price patterns?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.total_dollars&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Are there any notable trends in blueberry price fluctuations?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.total_dollars&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What is the rate of change in blueberry prices?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.total_dollars&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How have blueberry prices fluctuated over the years?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.total_dollars&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What is the general pattern of blueberry price changes?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.total_dollars&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How have blueberry prices changed per unit of time?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.total_dollars&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Have there been significant changes in blueberry prices?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.total_dollars&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Have economic factors played a role in blueberry price trends?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.total_dollars&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "By how much have blueberry prices increased or decreased?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.total_dollars&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "3. Price Trends: How have average prices for blueberries changed over time?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.total_dollars&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Do blueberry prices peak during specific seasons?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.total_dollars&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Are blueberry prices increasing, decreasing, or remaining stable?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.total_dollars&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How have weather conditions impacted blueberry production and prices?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.total_dollars&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How have blueberry prices evolved over time?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.total_dollars&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Have there been seasonal fluctuations in blueberry prices?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.total_dollars&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How have seasonal price patterns for blueberries changed over time?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.total_dollars&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Are there any regional variations in blueberry price seasonality?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.total_dollars&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What has been the overall trend in blueberry prices?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.total_dollars&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Have changes in consumer preferences affected blueberry prices?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.total_dollars&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What factors have influenced blueberry price trends?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.total_dollars&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "When are blueberry prices typically highest?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.total_dollars&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Can you show me the trend of blueberry sales over the last 3 years by month?", + "output": "fields=spins_nlp.total_dollars,spins_nlp.period_ending_month&fill_fields=spins_nlp.period_ending_month&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.period_ending_year]=2022%2F01%2F01+to+2025%2F01%2F01&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&sorts=spins_nlp.period_ending_month" + }, + { + "input": "What parent company sells the most Fresh and Frozen Blueberries in the Florida market by Units sold?", + "output": "fields=spins_nlp.total_units,spins_nlp.parent_company&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.geography_abbreviated]=%25FL%25&f[spins_nlp.geography_type]=Market&sorts=spins_nlp.total_units+desc+0" + }, + { + "input": "What are the worst 5 regions for Fresh and Frozen Blueberry sales in the last year by pounds sold?", + "output": "fields=spins_nlp.total_lbs,spins_nlp.geography_filter&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.period_ending_date]=1+year+ago+for+1+year&f[spins_nlp.geography_type]=Market&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&sorts=spins_nlp.total_lbs" + }, + { + "input": "What is the most popular product size in Florida by total units?", + "output": "fields=spins_nlp.total_units,spins_nlp.base_size_filter&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.geography_abbreviated]=%25FL%25&f[spins_nlp.geography_type]=Market&sorts=spins_nlp.total_units+desc+0" + }, + { + "input": "How do the sales volumes of organic and conventional blueberries compare?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.total_lbs&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=-TOTAL+US+-+FOOD&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Which type of blueberry has higher sales volume, organic or conventional?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.total_lbs&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=-TOTAL+US+-+FOOD&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What factors influence the sales volume difference between organic and conventional blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.total_lbs&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=-TOTAL+US+-+FOOD&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What is the difference in sales volume between organic and conventional blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.total_lbs&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=-TOTAL+US+-+FOOD&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What is the ratio of sales volume between organic and conventional blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.total_lbs&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=-TOTAL+US+-+FOOD&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What is the percentage difference in sales volume between organic and conventional blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.total_lbs&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=-TOTAL+US+-+FOOD&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "By how much do the sales volumes of organic and conventional blueberries differ?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.total_lbs&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=-TOTAL+US+-+FOOD&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How do supply and demand dynamics influence the sales volume difference between organic and conventional blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.total_lbs&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=-TOTAL+US+-+FOOD&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How does the sales volume of organic blueberries compare to that of conventional blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.total_lbs&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=-TOTAL+US+-+FOOD&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Is the demand for organic blueberries growing faster or slower than that for conventional blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.total_lbs&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=-TOTAL+US+-+FOOD&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How has the sales volume gap between organic and conventional blueberries evolved?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.total_lbs&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=-TOTAL+US+-+FOOD&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What is the relative sales volume of organic and conventional blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.total_lbs&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=-TOTAL+US+-+FOOD&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Do price differences between organic and conventional blueberries impact sales volumes?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.total_lbs&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=-TOTAL+US+-+FOOD&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Are there significant differences in sales volume between organic and conventional blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.total_lbs&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=-TOTAL+US+-+FOOD&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Are there any regional variations in the sales volume comparison between organic and conventional blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.total_lbs&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=-TOTAL+US+-+FOOD&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "5. Organic vs. Conventional: What is the sales volume comparison between organic and conventional blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.total_lbs&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=-TOTAL+US+-+FOOD&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Which type of blueberry has a larger market share, organic or conventional?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.total_lbs&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=-TOTAL+US+-+FOOD&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How do consumer preferences affect the sales volumes of organic and conventional blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.total_lbs&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=-TOTAL+US+-+FOOD&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Is the sales volume of organic blueberries increasing or decreasing relative to conventional blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.total_lbs&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=-TOTAL+US+-+FOOD&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How have the sales volumes of organic and conventional blueberries changed over time?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.total_lbs&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=-TOTAL+US+-+FOOD&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Are there any trends in the market share of organic and conventional blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.total_lbs&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=-TOTAL+US+-+FOOD&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What are the bottom 5 regions for Fresh and Frozen Blueberry sales in the last complete year by units sold?", + "output": "fields=spins_nlp.geography_filter,spins_nlp.total_units&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.period_ending_date]=1+year+ago+for+1+year&f[spins_nlp.geography_type]=Market&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&sorts=spins_nlp.total_units" + }, + { + "input": "How do sales volumes compare for different blueberry formats (fresh, frozen, dried)?", + "output": "fields=spins_nlp.total_dollars,spins_nlp.geography_filter,spins_nlp.product_type&f[spins_nlp.geography_type]=US+Total&f[spins_nlp.period_ending_year]=2024%2F01%2F01+to+2025%2F01%2F01&f[spins_nlp.product_type]=DRIED+FRUIT+-+BLUEBERRY%2CFRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&sorts=spins_nlp.total_dollars+desc+0" + }, + { + "input": "How have seasonal sales patterns for blueberries changed in the past year?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.geography,spins_nlp.rma_dollars_sum&pivots=spins_nlp.geography&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Where have blueberry sales declined the most in the past year?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.geography,spins_nlp.rma_dollars_sum&pivots=spins_nlp.geography&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Do blueberry sales peak during specific seasons in different parts of the country?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.geography,spins_nlp.rma_dollars_sum&pivots=spins_nlp.geography&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Which regions have experienced the largest growth in blueberry sales?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.geography,spins_nlp.rma_dollars_sum&pivots=spins_nlp.geography&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How have blueberry sales been by dollars over the past year across different regions?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.geography,spins_nlp.rma_dollars_sum&pivots=spins_nlp.geography&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What factors have influenced blueberry sales trends in different regions?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.geography,spins_nlp.rma_dollars_sum&pivots=spins_nlp.geography&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Have there been seasonal fluctuations in blueberry sales across different regions?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.geography,spins_nlp.rma_dollars_sum&pivots=spins_nlp.geography&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How have weather conditions impacted blueberry production and sales?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.geography,spins_nlp.rma_dollars_sum&pivots=spins_nlp.geography&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Have economic factors played a role in blueberry sales trends?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.geography,spins_nlp.rma_dollars_sum&pivots=spins_nlp.geography&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How have blueberry sales trended over the past year across different regions?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.geography,spins_nlp.rma_dollars_sum&pivots=spins_nlp.geography&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Have changes in consumer preferences affected blueberry sales?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.geography,spins_nlp.rma_dollars_sum&pivots=spins_nlp.geography&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How have blueberry sales by dollars over the past year across different regions?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.geography,spins_nlp.rma_dollars_sum&pivots=spins_nlp.geography&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What is the general sales trend for blueberries on a regional basis?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.geography,spins_nlp.rma_dollars_sum&pivots=spins_nlp.geography&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Are there significant regional differences in blueberry sales trends?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.geography,spins_nlp.rma_dollars_sum&pivots=spins_nlp.geography&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How have blueberry sales been over the past year across different regions?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.geography,spins_nlp.rma_dollars_sum&pivots=spins_nlp.geography&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How have blueberry sales been by dollars over the past year across different regions?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.geography,spins_nlp.rma_dollars_sum&pivots=spins_nlp.geography&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Are there any regional-specific factors driving blueberry sales patterns?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.geography,spins_nlp.rma_dollars_sum&pivots=spins_nlp.geography&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What has been the overall sales trajectory for blueberries in the past year?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.geography,spins_nlp.rma_dollars_sum&pivots=spins_nlp.geography&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "When are blueberries typically most popular in various regions?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.geography,spins_nlp.rma_dollars_sum&pivots=spins_nlp.geography&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Are there any regional variations in blueberry sales seasonality?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.geography,spins_nlp.rma_dollars_sum&pivots=spins_nlp.geography&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How have blueberry sales dollars over the past year across different regions?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.geography,spins_nlp.rma_dollars_sum&pivots=spins_nlp.geography&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How have blueberry sales evolved across various regions in the last 12 months?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.geography,spins_nlp.rma_dollars_sum&pivots=spins_nlp.geography&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How do blueberry sales in the northern regions compare to those in the southern regions?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.geography,spins_nlp.rma_dollars_sum&pivots=spins_nlp.geography&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Are there any notable regional disparities in blueberry sales patterns?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.geography,spins_nlp.rma_dollars_sum&pivots=spins_nlp.geography&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What is the overall pattern of blueberry sales across the country?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.geography,spins_nlp.rma_dollars_sum&pivots=spins_nlp.geography&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Have blueberry sales increased, decreased, or remained stable in different regions?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.geography,spins_nlp.rma_dollars_sum&pivots=spins_nlp.geography&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_week]=52+weeks&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What are the bottom 5 regions for Fresh and Frozen Blueberry sales in the last complete year by dollars sold?", + "output": "fields=spins_nlp.geography_filter,spins_nlp.total_dollars&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.period_ending_date]=1+year+ago+for+1+year&f[spins_nlp.geography_type]=Market&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&sorts=spins_nlp.total_dollars" + }, + { + "input": "What are the top 5 regions for Fresh and Frozen Blueberry sales in the last complete year by total units sold?", + "output": "fields=spins_nlp.geography_filter,spins_nlp.total_units&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.period_ending_date]=1+year+ago+for+1+year&f[spins_nlp.geography_type]=Market&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&sorts=spins_nlp.total_units+desc" + }, + { + "input": "What are the least popular package sizes when looking at units sold?", + "output": "fields=spins_nlp.total_lbs,spins_nlp.base_size_filter&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.geography_abbreviated]=&f[spins_nlp.geography_type]=&f[spins_nlp.base_size_filter]=-NULL&sorts=spins_nlp.total_lbs" + }, + { + "input": "What are the top 5 regions for Fresh and Frozen Blueberry sales in the last complete year by dollars sold?", + "output": "fields=spins_nlp.geography_filter,spins_nlp.total_dollars&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.period_ending_date]=1+year+ago+for+1+year&f[spins_nlp.geography_type]=Market&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&sorts=spins_nlp.total_dollars+desc+0" + }, + { + "input": "What retailer sold the lowest amount of Blueberry units in the last two complete years?", + "output": "fields=spins_nlp.geography_abbreviated,spins_nlp.total_units&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.period_ending_date]=2+year+ago+for+2+year&f[spins_nlp.geography_type]=Total+Retailer&sorts=spins_nlp.total_units" + }, + { + "input": "What retailer sells the most Blueberries on promotion?", + "output": "fields=spins_nlp.rma_units_incremental_promo_any_sum,spins_nlp.geography_abbreviated&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.geography_type]=Total+Retailer&sorts=spins_nlp.rma_units_incremental_promo_any_sum+desc+0" + }, + { + "input": "Which Target Division sells the most Blueberries?", + "output": "fields=spins_nlp.geography_abbreviated,spins_nlp.total_units&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.geography_abbreviated]=%25TARGET+CORP%25%2C%25TARGET+CORP+TTL%25%2C%25TARGET+SUPER+TARGET%25&sorts=spins_nlp.total_units+desc+0" + }, + { + "input": "What market sold the highest number of pounds of 16 oz Blueberry containers?", + "output": "fields=spins_nlp.geography_abbreviated,spins_nlp.total_lbs&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.geography_abbreviated]=&f[spins_nlp.geography_type]=Market&f[spins_nlp.base_size_filter]=16+OUNCE&sorts=spins_nlp.total_lbs+desc+0" + }, + { + "input": "How do sales figures compare between organic and conventional blueberries? Is there a growing preference for organic options? - Need to create a % of total market measure", + "output": "fields=spins_nlp.geography_filter,spins_nlp.rma_tdp_sum&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.geography_type]=Market&f[spins_nlp.comparison_period]=Period&f[spins_nlp.current_date_range]=365+days&sorts=spins_nlp.rma_tdp_sum+desc" + }, + { + "input": "What product descriptions sold zero pounds in the last two years?", + "output": "fields=spins_nlp.total_lbs,spins_nlp.product_description&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.period_ending_week]=2+year+ago+for+2+year&f[spins_nlp.geography_abbreviated]=&f[spins_nlp.total_lbs]=0&sorts=spins_nlp.total_lbs+desc" + }, + { + "input": "How does the last 12 months of Blueberry sales compare to other fresh berries by pounds sold at Meijer?", + "output": "fields=spins_nlp.product_type,spins_nlp.total_lbs&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=%25MEIJER%25&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFRESH+FRUIT+-+BLACKBERRY%2CFRESH+FRUIT+-+RASPBERRY%2CFRESH+FRUIT+-+STRAWBERRY&f[spins_nlp.period_ending_date]=1+year+ago+for+1+year&sorts=spins_nlp.total_lbs+desc+0" + }, + { + "input": "How does the last 12 months of Blueberry sales compare to other fresh berries by pounds sold at Publix?", + "output": "fields=spins_nlp.product_type,spins_nlp.total_lbs&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=%25PUBLIX%25&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFRESH+FRUIT+-+BLACKBERRY%2CFRESH+FRUIT+-+RASPBERRY%2CFRESH+FRUIT+-+STRAWBERRY&f[spins_nlp.period_ending_date]=12+month+ago+for+12+month&sorts=spins_nlp.total_lbs+desc+0" + }, + { + "input": "How does the last 12 months of Blueberry sales compare to other fresh berries by pounds sold at Albertsons?", + "output": "fields=spins_nlp.product_type,spins_nlp.total_lbs&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=%25ALBERTSON%25&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFRESH+FRUIT+-+BLACKBERRY%2CFRESH+FRUIT+-+RASPBERRY%2CFRESH+FRUIT+-+STRAWBERRY&f[spins_nlp.period_ending_date]=12+month+ago+for+12+month&sorts=spins_nlp.total_lbs+desc+0" + }, + { + "input": "Do the ratios of frozen unit sales to fresh blueberry unit sales differ from different markets?", + "output": "fields=spins_nlp.rma_units_sum,spins_nlp.product_type,spins_nlp.geography_filter&pivots=spins_nlp.product_type&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.geography_type]=Region&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%25%2CFZ+FRUIT+-+BLUEBERRIES%25&sorts=spins_nlp.product_type,percent_of_total_sales+desc+1" + }, + { + "input": "What are the sales of Fresh Blueberries vs Frozen Blueberries in Florida by Units sold?", + "output": "fields=spins_nlp.total_units,spins_nlp.product_type&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.period_ending_week]=2+year+ago+for+2+year&f[spins_nlp.geography_abbreviated]=%25FL%25&f[spins_nlp.geography_type]=Market&sorts=spins_nlp.product_type" + }, + { + "input": "What are the top 5 markets for Blueberry sales in total pounds?", + "output": "fields=spins_nlp.geography_abbreviated,spins_nlp.total_lbs&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.period_ending_week]=2+year+ago+for+2+year&f[spins_nlp.geography_abbreviated]=&f[spins_nlp.geography_type]=Market&sorts=spins_nlp.total_lbs+desc+0" + }, + { + "input": "What geography buys the most pounds of Blueberries?", + "output": "fields=spins_nlp.geography_abbreviated,spins_nlp.total_lbs&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.period_ending_week]=2+year+ago+for+2+year&f[spins_nlp.geography_abbreviated]=&f[spins_nlp.geography_type]=Market&sorts=spins_nlp.total_lbs+desc+0" + }, + { + "input": "When were the most retail units sold on promotion for fresh blueberries in the last 2 years?", + "output": "fields=spins_nlp.period_ending_week,spins_nlp.rma_units_incremental_promo_any_sum&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY&f[spins_nlp.period_ending_date]=2+year+ago+for+2+year&f[spins_nlp.rma_units_incremental_promo_any_sum]=NOT+NULL&sorts=spins_nlp.rma_units_incremental_promo_any_sum+desc" + }, + { + "input": "What are the forcasted total distribution points for the next 3 months?", + "output": "fields=spins_nlp.rma_tdp_sum,spins_nlp.period_ending_month&fill_fields=spins_nlp.period_ending_month&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.geography_type]=Market&f[spins_nlp.period_ending_month]=after+2023%2F01%2F01&sorts=spins_nlp.period_ending_month+desc" + }, + { + "input": "What market has the highest dollar amount of bagged Blueberry sales?", + "output": "fields=spins_nlp.geography_abbreviated,spins_nlp.total_dollars&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.geography_abbreviated]=&f[spins_nlp.geography_type]=Market&f[spins_nlp.base_size_filter]=&f[spins_nlp.packaging_type_primary]=BAG&sorts=spins_nlp.total_dollars+desc+0" + }, + { + "input": "How does the last 12 months of Blueberry sales in dollars compare to other fresh berries when on promotion?", + "output": "fields=spins_nlp.rma_units_incremental_promo_any_sum,spins_nlp.product_type&pivots=spins_nlp.product_type&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFRESH+FRUIT+-+BLACKBERRY%2CFRESH+FRUIT+-+RASPBERRY%2CFRESH+FRUIT+-+STRAWBERRY&f[spins_nlp.period_ending_date]=12+month+ago+for+12+month&sorts=spins_nlp.product_type" + }, + { + "input": "What yearly quarter has the lowest blueberry sales by dollars?", + "output": "fields=spins_nlp.period_ending_quarter_of_year,spins_nlp.total_dollars&fill_fields=spins_nlp.period_ending_quarter_of_year&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_month]=8+quarter+ago+for+8+quarter&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%25%2CFZ+FRUIT+-+BLUEBERRIES%25&sorts=spins_nlp.total_dollars" + }, + { + "input": "What parent company sells the most Fresh Blueberries by total pounds?", + "output": "fields=spins_nlp.product_type,spins_nlp.parent_company,spins_nlp.total_lbs&pivots=spins_nlp.product_type&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_month]=after+2023%2F01%2F01&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%25%2CFZ+FRUIT+-+BLUEBERRIES%25&sorts=spins_nlp.product_type,spins_nlp.total_lbs+desc+0" + }, + { + "input": "What yearly quarter has the highest blueberry sales by dollars over the last two years?", + "output": "fields=spins_nlp.period_ending_quarter_of_year,spins_nlp.total_dollars&fill_fields=spins_nlp.period_ending_quarter_of_year&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_month]=8+quarter+ago+for+8+quarter&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%25%2CFZ+FRUIT+-+BLUEBERRIES%25&sorts=spins_nlp.total_dollars+desc+0" + }, + { + "input": "What yearly quarter has the highest blueberry sales by RMA dollars?", + "output": "fields=spins_nlp.period_ending_quarter_of_year,spins_nlp.rma_dollars_sum&fill_fields=spins_nlp.period_ending_quarter_of_year&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_month]=8+quarter+ago+for+8+quarter&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%25%2CFZ+FRUIT+-+BLUEBERRIES%25&sorts=spins_nlp.rma_dollars_sum+desc" + }, + { + "input": "What yearly quarter has the highest blueberry sales by RMA dollars?", + "output": "fields=spins_nlp.period_ending_quarter_of_year,spins_nlp.rma_dollars_sum&fill_fields=spins_nlp.period_ending_quarter_of_year&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.geography_type]=&f[spins_nlp.period_ending_month]=8+quarter+ago+for+8+quarter&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%25%2CFZ+FRUIT+-+BLUEBERRIES%25&sorts=spins_nlp.rma_dollars_sum+desc+0" + }, + { + "input": "What retailers sell no Fresh or Frozen Blueberries on promotion?", + "output": "fields=spins_nlp.rma_units_incremental_promo_any_sum,spins_nlp.geography_abbreviated&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.period_ending_date]=2+year+ago+for+2+year&f[spins_nlp.geography_type]=Total+Retailer&f[spins_nlp.rma_units_incremental_promo_any_sum]=0&sorts=spins_nlp.rma_units_incremental_promo_any_sum" + }, + { + "input": "What is the percent change year over year in pounds sold?", + "output": "fields=spins_nlp.total_lbs_current,spins_nlp.total_lbs_prior,spins_nlp.total_lbs_perc_change&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FZ+FRUIT+-+BLUEBERRIES%2CFRESH+FRUIT+-+BLUEBERRY&f[spins_nlp.comparison_period]=Period&f[spins_nlp.current_date_range]=365+days&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_year]=2023&sorts=spins_nlp.total_lbs_perc_change+desc" + }, + { + "input": "How do blueberry sales vary throughout the year, and are there any specific weeks or months that see a significant increase or decrease?", + "output": "fields=spins_nlp.period_ending_week_of_year,spins_nlp.total_lbs_current,spins_nlp.total_lbs_prior&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.geography_type]=Market&f[spins_nlp.comparison_period]=Period&f[spins_nlp.current_date_range]=365+days&f[spins_nlp.total_lbs_current]=NOT+NULL&sorts=spins_nlp.total_lbs_current+desc+0" + }, + { + "input": "Compare sales of Fresh and Frozen Blueberries in the last two complete years by total pounds sold", + "output": "fields=spins_nlp.product_type,spins_nlp.period_ending_year,spins_nlp.total_lbs&pivots=spins_nlp.period_ending_year&fill_fields=spins_nlp.period_ending_year&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FZ+FRUIT+-+BLUEBERRIES%2CFRESH+FRUIT+-+BLUEBERRY&f[spins_nlp.period_ending_date]=2+year+ago+for+2+year&f[spins_nlp.period_ending_month_name]=&sorts=spins_nlp.period_ending_year,spins_nlp.total_lbs+desc+0" + }, + { + "input": "What was the largest region in blueberry sales?", + "output": "fields=spins_nlp.total_dollars,spins_nlp.geography_filter&f[spins_nlp.geography_type]=Region&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&sorts=spins_nlp.total_dollars+desc+0" + }, + { + "input": "Which region realized the greatest growth percentage in blueberry pounds sold in 2023?", + "output": "fields=spins_nlp.total_lbs_current,spins_nlp.total_lbs_prior,spins_nlp.geography_filter,spins_nlp.total_lbs_perc_change&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FZ+FRUIT+-+BLUEBERRIES%2CFRESH+FRUIT+-+BLUEBERRY&f[spins_nlp.comparison_period]=Period&f[spins_nlp.current_date_range]=365+days&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_year]=2023&sorts=spins_nlp.total_lbs_perc_change+desc" + }, + { + "input": "Compare sales of Fresh and Frozen Blueberries in the last two complete years by units sold", + "output": "fields=spins_nlp.product_type,spins_nlp.period_ending_year,spins_nlp.total_units&pivots=spins_nlp.period_ending_year&fill_fields=spins_nlp.period_ending_year&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FZ+FRUIT+-+BLUEBERRIES%2CFRESH+FRUIT+-+BLUEBERRY&f[spins_nlp.period_ending_date]=2+year+ago+for+2+year&f[spins_nlp.period_ending_month_name]=&sorts=spins_nlp.period_ending_year,spins_nlp.total_units+desc+0" + }, + { + "input": "Compare sales of Fresh and Frozen Blueberries in the last two complete years by total dollars sold", + "output": "fields=spins_nlp.product_type,spins_nlp.period_ending_year,spins_nlp.total_dollars&pivots=spins_nlp.period_ending_year&fill_fields=spins_nlp.period_ending_year&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FZ+FRUIT+-+BLUEBERRIES%2CFRESH+FRUIT+-+BLUEBERRY&f[spins_nlp.period_ending_date]=2+year+ago+for+2+year&f[spins_nlp.period_ending_month_name]=&sorts=spins_nlp.period_ending_year,spins_nlp.total_dollars+desc+0" + }, + { + "input": "What is the forcasted total distribution points for the next 3 months by region?", + "output": "fields=spins_nlp.rma_tdp_sum,spins_nlp.period_ending_month,spins_nlp.geography_filter&pivots=spins_nlp.geography_filter&fill_fields=spins_nlp.period_ending_month&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.geography_type]=Region&f[spins_nlp.period_ending_month]=after+2023%2F01%2F01&sorts=spins_nlp.geography_filter,spins_nlp.period_ending_month+desc" + }, + { + "input": "How have seasonal blueberry sales trends changed over time?", + "output": "fields=spins_nlp.period_ending_month_name&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How do seasonal sales fluctuations for blueberries compare to other fruits?", + "output": "fields=spins_nlp.period_ending_month_name&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "When are blueberries typically most popular in terms of sales?", + "output": "fields=spins_nlp.period_ending_month_name&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "When do blueberry sales reach their peak?", + "output": "fields=spins_nlp.period_ending_month_name&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "When do blueberry sales experience their lowest points?", + "output": "fields=spins_nlp.period_ending_month_name&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Are there any pronounced seasonal highs and lows in blueberry sales?", + "output": "fields=spins_nlp.period_ending_month_name&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Are there any regional variations in seasonal blueberry sales patterns?", + "output": "fields=spins_nlp.period_ending_month_name&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What is the difference in sales volume between peak and off-peak seasons?", + "output": "fields=spins_nlp.period_ending_month_name&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Are there significant seasonal differences in blueberry sales?", + "output": "fields=spins_nlp.period_ending_month_name&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What is the seasonal sales cycle for blueberries?", + "output": "fields=spins_nlp.period_ending_month_name&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What factors influence the seasonal fluctuations in blueberry sales?", + "output": "fields=spins_nlp.period_ending_month_name&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Do weather conditions impact seasonal blueberry sales?", + "output": "fields=spins_nlp.period_ending_month_name&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Are there any seasonal variations in blueberry production that affect sales?", + "output": "fields=spins_nlp.period_ending_month_name&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "What is the seasonal sales pattern for blueberries?", + "output": "fields=spins_nlp.period_ending_month_name&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How do consumer preferences affect seasonal blueberry demand?", + "output": "fields=spins_nlp.period_ending_month_name&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "7. Seasonal Trends: How do sales volumes fluctuate seasonally for blueberries?", + "output": "fields=spins_nlp.period_ending_month_name&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How do blueberry sales fluctuate between peak and off-peak periods?", + "output": "fields=spins_nlp.period_ending_month_name&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Are there any emerging patterns in seasonal blueberry sales?", + "output": "fields=spins_nlp.period_ending_month_name&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "Is the seasonality of blueberry sales becoming more or less pronounced?", + "output": "fields=spins_nlp.period_ending_month_name&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How do blueberry sales vary throughout the year?", + "output": "fields=spins_nlp.period_ending_month_name&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How do seasonal pricing strategies influence blueberry sales fluctuations?", + "output": "fields=spins_nlp.period_ending_month_name&f[spins_nlp.geography]=&f[spins_nlp.category]=PRODUCE&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.geography_type]=Region&f[spins_nlp.rma_dollars_sum]=NOT+NULL" + }, + { + "input": "How are total unit sales the week of the Christmas compared to other weeks? (has custom chart config settings)", + "output": "fields=spins_nlp.total_units,spins_nlp.period_ending_week,spins_nlp.is_week_before_christmas&pivots=spins_nlp.is_week_before_christmas&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.period_ending_week]=2+year+ago+for+2+year&f[spins_nlp.geography_abbreviated]=&f[spins_nlp.total_units]=NOT+NULL&sorts=spins_nlp.is_week_before_christmas,spins_nlp.period_ending_week+desc" + }, + { + "input": "What are the top 5 regions for Fresh and Frozen Blueberry sales in the last year by units sold?", + "output": "fields=spins_nlp.total_units,spins_nlp.geography_filter,spins_nlp.period_ending_year&f[spins_nlp.period_ending_year]=1+years&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.geography_type]=Region" + }, + { + "input": "What parent company sells the most Frozen Blueberries by weight?", + "output": "fields=spins_nlp.parent_company,spins_nlp.total_lbs&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.geography_type]=&f[spins_nlp.product_type]=FZ+FRUIT+-+BLUEBERRIES%25&sorts=spins_nlp.total_lbs+desc" + }, + { + "input": "What parent companies sell the most Frozen Blueberries by units?", + "output": "fields=spins_nlp.parent_company,spins_nlp.total_units&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.geography_type]=&f[spins_nlp.product_type]=FZ+FRUIT+-+BLUEBERRIES%25&sorts=spins_nlp.total_units+desc" + }, + { + "input": "What parent company sells the most Frozen Blueberries by unit?", + "output": "fields=spins_nlp.parent_company,spins_nlp.total_units&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.geography_type]=&f[spins_nlp.product_type]=FZ+FRUIT+-+BLUEBERRIES%25&sorts=spins_nlp.total_units+desc" + }, + { + "input": "How are sales the week before the Fourth of July compared to other weeks? (has custom chart config settings)", + "output": "fields=spins_nlp.total_units,spins_nlp.period_ending_week,spins_nlp.is_week_before_fourth_of_july&pivots=spins_nlp.is_week_before_fourth_of_july&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%2CFZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.period_ending_week]=2+year+ago+for+2+year&f[spins_nlp.geography_abbreviated]=&f[spins_nlp.total_units]=NOT+NULL&sorts=spins_nlp.is_week_before_fourth_of_july,spins_nlp.period_ending_week+desc" + }, + { + "input": "What parent company sells the most Fresh Blueberries by unit?", + "output": "fields=spins_nlp.parent_company,spins_nlp.total_units&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.geography_type]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%25&sorts=spins_nlp.total_units+desc" + }, + { + "input": "What parent company sells the most Fresh Blueberries by dollars in the conventional grow method?", + "output": "fields=spins_nlp.parent_company,spins_nlp.total_dollars&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.geography_type]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY&sorts=spins_nlp.total_dollars+desc" + }, + { + "input": "Are there significant price differences between organic and conventional blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.price_usd_lb&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.period_ending_week]=52+weeks" + }, + { + "input": "Is the price premium for organic blueberries sustainable?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.price_usd_lb&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.period_ending_week]=52+weeks" + }, + { + "input": "How do consumer preferences affect the price that consumers are willing to pay for organic blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.price_usd_lb&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.period_ending_week]=52+weeks" + }, + { + "input": "17. Organic Premium: What is the price premium for organic blueberries compared to conventional?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.price_usd_lb&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.period_ending_week]=52+weeks" + }, + { + "input": "How much more expensive are organic blueberries than conventional blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.price_usd_lb&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.period_ending_week]=52+weeks" + }, + { + "input": "Are there any trends in the price premium for organic blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.price_usd_lb&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.period_ending_week]=52+weeks" + }, + { + "input": "Is the price gap between organic and conventional blueberries widening or narrowing?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.price_usd_lb&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.period_ending_week]=52+weeks" + }, + { + "input": "How has the price difference between organic and conventional blueberries evolved?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.price_usd_lb&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.period_ending_week]=52+weeks" + }, + { + "input": "How much more do organic blueberries cost compared to conventional blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.price_usd_lb&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.period_ending_week]=52+weeks" + }, + { + "input": "What is the price difference between organic and conventional blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.price_usd_lb&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.period_ending_week]=52+weeks" + }, + { + "input": "How do supply and demand dynamics influence the price premium for organic blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.price_usd_lb&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.period_ending_week]=52+weeks" + }, + { + "input": "How have the price premiums for organic blueberries changed over time?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.price_usd_lb&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.period_ending_week]=52+weeks" + }, + { + "input": "By how much do organic blueberries cost more than conventional blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.price_usd_lb&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.period_ending_week]=52+weeks" + }, + { + "input": "What is the price markup for organic blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.price_usd_lb&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.period_ending_week]=52+weeks" + }, + { + "input": "What is the percentage price difference between organic and conventional blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.price_usd_lb&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.period_ending_week]=52+weeks" + }, + { + "input": "What is the price ratio between organic and conventional blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.price_usd_lb&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.period_ending_week]=52+weeks" + }, + { + "input": "How much of a premium do consumers pay for organic blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.price_usd_lb&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.period_ending_week]=52+weeks" + }, + { + "input": "What is the price premium for organic blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.price_usd_lb&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.period_ending_week]=52+weeks" + }, + { + "input": "What factors influence the price premium for organic blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.price_usd_lb&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.period_ending_week]=52+weeks" + }, + { + "input": "Do production costs for organic blueberries differ significantly from those for conventional blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.price_usd_lb&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.period_ending_week]=52+weeks" + }, + { + "input": "Are there any regional variations in the price premium for organic blueberries?", + "output": "fields=spins_nlp.labeled_organic,spins_nlp.price_usd_lb&pivots=spins_nlp.labeled_organic&f[spins_nlp.geography]=TOTAL+US+-+MULO%2CTOTAL+US+-+NATURAL+CHANNEL&f[spins_nlp.commodity]=BLUEBERRIES%2CBLUEBERRY&f[spins_nlp.period_ending_week]=52+weeks" + }, + { + "input": "What parent companies sell the most Frozen Blueberries by dollars?", + "output": "fields=spins_nlp.parent_company,spins_nlp.total_dollars&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.geography_type]=&f[spins_nlp.product_type]=FZ+FRUIT+-+BLUEBERRIES%25&sorts=spins_nlp.total_dollars+desc" + }, + { + "input": "What parent company sells the most Frozen Blueberries by dollars in the conventional grow method?", + "output": "fields=spins_nlp.parent_company,spins_nlp.total_dollars&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.geography_type]=&f[spins_nlp.product_type]=FZ+FRUIT+-+BLUEBERRIES%25&sorts=spins_nlp.total_dollars+desc" + }, + { + "input": "What parent companies sell the most Fresh Blueberries by dollars?", + "output": "fields=spins_nlp.parent_company,spins_nlp.total_dollars&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.geography_type]=&f[spins_nlp.product_type]=FRESH+FRUIT+-+BLUEBERRY%25&sorts=spins_nlp.total_dollars+desc" + }, + { + "input": "What markets saw a decrease in Blueberry sales Year over Year? (None)", + "output": "fields=spins_nlp.total_lbs_current,spins_nlp.total_lbs_prior,spins_nlp.total_lbs_perc_change,spins_nlp.geography_abbreviated&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FZ+FRUIT+-+BLUEBERRIES%2CFRESH+FRUIT+-+BLUEBERRY&f[spins_nlp.comparison_period]=Period&f[spins_nlp.current_date_range]=365+days&f[spins_nlp.geography_type]=Market&f[spins_nlp.period_ending_year]=2023&f[spins_nlp.total_lbs_perc_change]=%3C0&sorts=spins_nlp.total_lbs_perc_change" + }, + { + "input": "How many pounds of frozen blueberries were sold on promotion over this spring versus last spring?", + "output": "fields=spins_nlp.rma_units_incremental_promo_any_sum,spins_nlp.product_type,spins_nlp.period_ending_year&pivots=spins_nlp.period_ending_year&fill_fields=spins_nlp.period_ending_year&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.period_ending_date]=2+year+ago+for+2+year&f[spins_nlp.period_ending_month_name]=March%2CApril%2CMay&sorts=spins_nlp.period_ending_year,spins_nlp.rma_units_incremental_promo_any_sum+desc+0" + }, + { + "input": "How many dollars of frozen blueberries were sold on promotion over this summer versus last summer?", + "output": "fields=spins_nlp.rma_units_incremental_promo_any_sum,spins_nlp.product_type,spins_nlp.period_ending_year&pivots=spins_nlp.period_ending_year&fill_fields=spins_nlp.period_ending_year&f[spins_nlp.labeled_organic]=CONVENTIONAL&f[spins_nlp.geography_filter]=&f[spins_nlp.product_type]=FZ+FRUIT+-+BLUEBERRIES&f[spins_nlp.period_ending_date]=2+year+ago+for+2+year&f[spins_nlp.period_ending_month_name]=June%2CJuly%2CAugust&sorts=spins_nlp.period_ending_year,spins_nlp.rma_units_incremental_promo_any_sum+desc+0" + } +] \ No newline at end of file diff --git a/explore-assistant-examples/samples.json b/explore-assistant-examples/samples.json index 084278bb..18c31009 100644 --- a/explore-assistant-examples/samples.json +++ b/explore-assistant-examples/samples.json @@ -1,14 +1,14 @@ [ { - "category": "Cohorting", - "prompt": "Count of Users by first purchase date" + "category": "Performance", + "prompt": "What parent companies sell the most Fresh Blueberries by units?" }, { - "category": "Audience Building", - "prompt":"Users who have purchased more than 100 dollars worth of Calvin Klein products and have purchased in the last 30 days" + "category": "Volume Trends", + "prompt":"What is the trend in sales volume for blueberries over the last year?" }, { - "category": "Period Comparison", - "prompt": "Total revenue by category this year compared to last year in a line chart with year pivoted" + "category": "Seasonality", + "prompt": "Do blueberry sales volumes peak during specific seasons?" } ] \ No newline at end of file diff --git a/explore-assistant-examples/update_refinements.sh b/explore-assistant-examples/update_refinements.sh old mode 100644 new mode 100755 diff --git a/explore-assistant-examples/update_samples.sh b/explore-assistant-examples/update_samples.sh old mode 100644 new mode 100755 diff --git a/explore-assistant-extension/.DS_Store b/explore-assistant-extension/.DS_Store index ef3b32cb..d4dba18d 100644 Binary files a/explore-assistant-extension/.DS_Store and b/explore-assistant-extension/.DS_Store differ diff --git a/explore-assistant-extension/src/documents/looker_filters_interval_tf.ts b/explore-assistant-extension/src/documents/looker_filters_interval_tf.md similarity index 98% rename from explore-assistant-extension/src/documents/looker_filters_interval_tf.ts rename to explore-assistant-extension/src/documents/looker_filters_interval_tf.md index e7d2be14..954a7fa2 100644 --- a/explore-assistant-extension/src/documents/looker_filters_interval_tf.ts +++ b/explore-assistant-extension/src/documents/looker_filters_interval_tf.md @@ -1,5 +1,3 @@ -export const looker_filters_interval_tf:string= ` - ## Intervals Interval options @@ -134,7 +132,4 @@ This will split up each second into intervals with the specified number of milli 2014-09-01 01:00:00.500 2014-09-01 01:00:00.750 To give an example, a row with a time of 2014-09-01 01:00:00.333 would have a millisecond250 of 2014-09-01 01:00:00.250. -` - - -export default looker_filters_interval_tf; \ No newline at end of file + | \ No newline at end of file diff --git a/explore-assistant-extension/src/documents/looker_pivots_url_parameters_doc.md b/explore-assistant-extension/src/documents/looker_pivots_url_parameters_doc.md new file mode 100644 index 00000000..18ec0e89 --- /dev/null +++ b/explore-assistant-extension/src/documents/looker_pivots_url_parameters_doc.md @@ -0,0 +1,88 @@ +# Expanded URL generation + +JSON Payload Fields: + +fields: fields=view.field_1,view.field_2,view.count + This parameter specifies the list of fields to be included in the results. In this example, the explore will return data for view.field_1, view.field_2, and the count of rows (view.count). + +f[]: &f[view.filter_1_dimension]={{ value }} & &f[view.filter_2_on_date]=last+60+days + This parameter defines filters for the explore. The f[] syntax is used to declare a filter on a specific dimension (view.filter_1_dimension and view.filter_2_on_date in this case). The {{ value }} placeholder indicates a dynamic value that can be passed through the URL. The second filter uses a Looker expression (last+60+days) to filter data for the past 60 days. + +pivots: pivots=view.field_2 This parameter defines the dimension to pivot on. In this example, view.field_2 will be used to create a pivot table. + +limit: limit=50 This parameter sets the maximum number of rows to be returned by the explore. The default limit is 5000, but here it's explicitly set to 50. + +column_limit: column_limit=20 This parameter sets the maximum number of columns to be displayed in the pivot table. This parameter only has an effect when a pivot dimension is specified (as seen with pivots). The column_limit can be between 1 and 200. Dimensions, dimension table calculations, row total columns, and measure table calculations outside of pivots are not counted toward the column limit. Pivoted groups each count as one column toward the column limit. + +total: total=true This parameter controls whether to display column totals in the explore results. Here, true indicates that column totals will be shown. + +row_total: row_total=right This parameter controls whether to display row totals in the explore results. Here, right specifies that the row totals will be displayed on the right side. Only use row totals if the chart contains pivots. + +sorts: sorts=view.field_1,view.count+desc This parameter defines the order in which the results should be sorted. The first field (view.field_1) is sorted by default in ascending order. The second sort (view.count+desc) sorts the results by view.count in descending order. The +desc syntax specifies descending order. + +filter_config: The filter_config parameter contains detailed JSON objects that control the filtering aspects of the query. The filter_config represents the state of the filter UI on the explore page for a given query. When running a query via the Looker UI, this parameter takes precedence over "filters". + +Vis: The vis parameter contains detailed JSON objects that control the visualization properties of the query. These properties are typically opaque and differ based on the type of visualization used. There is no specified set of allowed keys. The values can be any type supported by JSON. A "type" key with a string value is often present, and is used by Looker to determine which visualization to present. Visualizations ignore unknown vis_config properties. + +Query_timezone: User's timezone, string value. + +Subtotals: When using a table visualization and your data table contains at least two dimensions, you can apply subtotals. Subtotals are not available when you filter on a measure or when the Explore uses the sql_always_having parameter. List of fields to run the subtotals. The leftmost subtotal is always sorted. When you sort by multiple columns, subtotal columns are given precedence. Fields on which to run subtotals. + +# Pivot table reference + +In Looker, pivots allow you to turn a selected dimension into several columns, which creates a matrix of your data similar to a pivot table in spreadsheet software. This is very useful for analyzing metrics by different groupings of your data, such as getting counts for category or label in your dataset. + +When you pivot on a dimension, each unique possible value of that dimension becomes its own column header. Any measures are then repeated under each column header. + +Pivots make it much easier to compare a measure accross dimensions. It also shows you gaps in your data, where you don’t have any numeric values for a particular dimension field. In summary, pivots allow you to create and display a matrix of your data, similar to a pivot table in spreadsheet software. Specifically, pivots turn a selected dimension into several columns and are applied only to the visual display of your results. + +With pivots, Looker allows you to regroup your data, so that you can easily compare results by different groupings and identify potential gaps, all while leaving your underlying data unaffected. + +Whenever you have a question involving one dimension “by” another dimension, that’s a clue that a pivot might come in handy. + +When two time dimensions are in a report and a pivot is required, always pivot by the least granular time dimension. + +|Example | Pivoted Dimension | +|--------------------------------------------------------------------------|----------------------------------| +| What were the hourly total sales by day in the past 3 days? | Day | +| What were the daily total sales by week in the past 3 weeks? | Week | +| What were the total sales by day each week in the past 2 weeks? | Week | +| What were the total sales by day of week each week in the past 2 weeks? | Week | +| What were the weekly total sales by month in the past 2 months? | Month | +| What were the monthly total sales by quarter in the past 2 quarters? | Quarter | +| What were the monthly total sales by quarter in the past 2 years? | Year | +| What were the total sales by week of year each year in the past 2 years? | Year | +| What were the monthly total sales by year in the past 2 years? | Year | +| What were the weekly total sales by quarter in the past 3 years? | Quarter | + +# Looker API JSON Fields + +|application/JSON | Datatype | Description +|--------------------------|------------------------|------------------------------------------------------------------------------------------ +| can | Hash[boolean] | Operations the current user is able to perform on this object +| id | string | Unique Id +| model | string | Model +| view | string | Explore Name +| fields | string[] | Fields +| pivots | string[] | Pivots +| fill_fields | string[] | Fill Fields +| filters | Hash[string] | Filters will contain data pertaining to complex filters that do not contain "or" conditions. When "or" conditions are present, filter data will be found on the filter_expression property. +| filter_expression | string | Filter Expression +| sorts | string[] | Sorting for the query results. Use the format ["view.field", ...] to sort on fields in ascending order. Use the format ["view.field desc", ...] to sort on fields in descending order. Use ["__UNSORTED__"] (2 underscores before and after) to disable sorting entirely. Empty sorts [] will trigger a default sort. +| limit | string | Row limit. To download unlimited results, set the limit to -1 (negative one). +| column_limit | string | Column Limit +| total | boolean | Total +| row_total | string | Raw Total +| subtotals | string[] | Fields on which to run subtotals +| vis_config | Hash[any] | Visualization configuration properties. These properties are typically opaque and differ based on the type of visualization used. There is no specified set of allowed keys. The values can be any type supported by JSON. A "type" key with a string value is often present, and is used by Looker to determine which visualization to present. Visualizations ignore unknown vis_config properties. +| filter_config | Hash[any] | The filter_config represents the state of the filter UI on the explore page for a given query. When running a query via the Looker UI, this parameter takes precedence over "filters". When creating a query or modifying an existing query, "filter_config" should be set to null. Setting it to any other value could cause unexpected filtering behavior. The format should be considered opaque. +| visible_ui_sections | string | Visible UI Sections +| slug | string | Slug +| dynamic_fields | string | Dynamic Fields +| client_id | string | Client Id: used to generate shortened explore URLs. If set by client, must be a unique 22 character alphanumeric string. Otherwise one will be generated. +| share_url | string | Share Url +| expanded_share_url | string | Expanded Share Url +| url | string | Expanded Url +| query_timezone | string | Query Timezone +| has_table_calculations | boolean | Has Table Calculations + | \ No newline at end of file diff --git a/explore-assistant-extension/src/hooks/useSendVertexMessage.ts b/explore-assistant-extension/src/hooks/useSendVertexMessage.ts index 842b5ff5..53570c76 100644 --- a/explore-assistant-extension/src/hooks/useSendVertexMessage.ts +++ b/explore-assistant-extension/src/hooks/useSendVertexMessage.ts @@ -9,7 +9,8 @@ import { AssistantState } from '../slices/assistantSlice' import looker_filter_doc from '../documents/looker_filter_doc.md' import looker_visualization_doc from '../documents/looker_visualization_doc.md' -import looker_filters_interval_tf from '../documents/looker_filters_interval_tf' +import looker_filters_interval_tf from '../documents/looker_filters_interval_tf.md' +import looker_pivots_url_parameters_doc from '../documents/looker_pivots_url_parameters_doc.md' import { ModelParameters } from '../utils/VertexHelper' import { BigQueryHelper } from '../utils/BigQueryHelper' @@ -182,6 +183,7 @@ ${exploreRefinementExamples && } let exampleText = '' if (exploreGenerationExamples && exploreGenerationExamples.length > 0) { + console.log("Line",exploreGenerationExamples) exampleText = exploreGenerationExamples.map((item) => `input: "${item.input}" ; output: ${JSON.stringify(parseLookerURL(item.output))}`).join('\n') } return ` @@ -192,6 +194,29 @@ ${exploreRefinementExamples && ${looker_filters_interval_tf} Here is general documentation on visualizations: ${looker_visualization_doc} + Here is general documentation on Looker JSON fields and pivots + ${looker_pivots_url_parameters_doc} + + ## Format of query object + + | Field | Type | Description | + |--------------------|--------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| + | model | string | Model | + | view | string | Explore Name | + | fields | string[] | Fields | + | pivots | string[] | Pivots | + | fill_fields | string[] | Fill Fields | + | filters | object | Filters | + | filter_expression | string | Filter Expression | + | sorts | string[] | Sorts | + | limit | string | Limit | + | column_limit | string | Column Limit | + | total | boolean | Total | + | row_total | string | Raw Total | + | subtotals | string[] | Subtotals | + | vis_config | object | Visualization configuration properties. These properties are typically opaque and differ based on the type of visualization used. There is no specified set of allowed keys. The values can be any type supported by JSON. A "type" key with a string value is often present, and is used by Looker to determine which visualization to present. Visualizations ignore unknown vis_config properties. | + | filter_config | object | The filter_config represents the state of the filter UI on the explore page for a given query. When running a query via the Looker UI, this parameter takes precedence over "filters". When creating a query or modifying an existing query, "filter_config" should be set to null. Setting it to any other value could cause unexpected filtering behavior. The format should be considered opaque. | + # End Documentation @@ -327,6 +352,7 @@ ${exploreRefinementExamples && const parseLookerURL = (url: string): { [key: string]: any } => { // Split URL and extract model & explore + console.log("Line 331",url) const urlSplit = url.split("?"); let model = "" let explore = ""