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+---
+title: Playing with Data Types
+tags: [datatypes, int, float, str, list, dictionary]
+---
+
+# Problem Statement
+You are given the following:
+
+1. First name and last name of a person in lower-case. Make only the first character of each upper-case and contatenate them to make the full name.
+
+2. The person's monthly salary and performance bonus percentage. Calculate the bonus amount and total salary for the month.
+
+3. A comma-seperated string of the person's projects. Find the number of projects he's worked on without using a loop.
+
+Return a dictionary of the format:
+{
+ "full_name": str,
+ "bonus": float,
+ "salary_after_bonus": float,
+ "number_of_projects": int,
+ "projects": list,
+}
+
+# Solution
+```python test.py -r 'python test.py'
+<prefix>
+# some prefix   
+</prefix>
+<template>
+def employee_records(first_name: str, last_name: str, salary: int, bonus_percent: float, projects: str) -> dict:
+    '''
+    Write a function employee_records(first_name, last_name, salary, bonus_percent, projects). Capitalise the first character of first name and last name and contatenate to get full name, calculate bonus amount and total salary after bonus and create list of projects and count number of projects without using a loop.
+
+    Arguments:
+    first_name: str
+    last_name: str
+    salary: int
+    bonus_percent: float
+    projects: str
+
+    Return: a dictionary in the form {
+                    "full_name": str,
+                    "bonus": float,
+                    "salary_after_bonus": float,
+                    "number_of_projects": int,
+                    "projects": list,
+                }
+    '''
+    
+    <los>...</los>
+    <sol>
+    return {
+        "full_name": first_name[0].upper() + first_name[1:] + ' ' + last_name[0].upper() + last_name[1:],
+        "bonus": salary*bonus_percent/100,
+        "salary_after_bonus": salary + salary*bonus_percent/100,
+        "number_of_projects": len(projects.split(',')),
+        "projects": projects.split(','),
+    }
+    </sol>
+    test = <los>...</los><sol>'test'</sol> #tests
+</template>
+<suffix>
+# some suffix
+</suffix>
+<suffix_invisible>
+{% include '../function_type_and_modify_check_suffix.py.jinja' %}
+</suffix_invisible>
+```
+
+# Public Test Cases
+
+## Input 1
+```
+first_name = 'vineet'
+last_name = 'solanki'
+salary = 45000
+bonus_percent = 8.356
+projects = "DigiCop,eSuraksha,KaviSammelan"
+```
+
+## Output 1
+```
+{'full_name': 'Vineet Solanki', 'bonus': 3760.2, 'salary_after_bonus': 48760.2, 'number_of_projects': 3, 'projects': ['DigiCop', 'eSuraksha', 'KaviSammelan']}
+```
+
+
+# Private Test Cases
+
+
+## Input 1
+```
+first_name = 'ayushi'
+last_name = 'saha'
+salary = 72758
+bonus_percent = 9
+projects = "NLP-ChatBot,ClientHelp"
+```
+
+## Output 1
+```
+{'full_name': 'Ayushi Saha', 'bonus': 6548.22, 'salary_after_bonus': 79306.22, 'number_of_projects': 2, 'projects': ['NLP-ChatBot', 'ClientHelp']}
+```
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diff --git a/Questions by Shivaditya Bhattacharya (22f3000819)/q2_data_processing.md b/Questions by Shivaditya Bhattacharya (22f3000819)/q2_data_processing.md
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+---
+title: Daily shop records
+tags: [aggregation, filtering, I/O, definite input]
+---
+
+# Problem Statement
+You are provided with a list of dictionaries where each dictionary contains information about a shopper, including their name, age, and a dictionary of items they have bought, with item names as keys and quantities as values.
+
+Return a dictionary having the format: 
+{
+&emsp;"shoppers": list of names,
+&emsp;"filtered_by_age": Shoppers above the given age filter,
+&emsp;"average_age": Average age of shoppers,
+&emsp;"sorted_shoppers": Shoppers sorted by age,
+&emsp;"items_group": Group shopper names by items bought,
+&emsp;"unique_items": Set of unique items bought from the shop
+}
+
+# Solution
+```python test.py -r 'python test.py'
+<prefix>
+# some prefix   
+</prefix>
+<template>
+def process_shoppers(shoppers: list[dict], age_filter: int) -> dict:
+    '''
+    Write a function process_shoppers(shoppers, age_filter) that takes the inputs 
+    and returns a list of dictionaries containing records after performing basic aggregation 
+    and filtering operations and result dictionary must be in the given format.
+
+    Arguments:
+    shoppers: list[dict]
+    age_filter: int
+
+    Return: a dictionary in the form {
+                "shoppers": list of names,
+                "filtered_by_age": Shoppers above the given age filter,
+                "average_age": Average age of shoppers,
+                "sorted_shoppers": Shoppers sorted by age,
+                "items_group": Group shopper names by items bought,
+                "unique_items": Set of unique items bought from the shop
+            }
+    '''
+    
+    <los>...</los>
+    <sol>
+    names = [shopper['name'] for shopper in shoppers]
+    
+    filtered_shoppers = [shopper['name'] for shopper in shoppers if shopper['age'] > age_filter]
+    
+    ages = [shopper['age'] for shopper in shoppers]
+    average_age = sum(ages)/len(ages)
+    
+    sorted_shoppers = sorted(shoppers, key=lambda x: x['age'])
+    
+    items_group = dict()
+    for shopper in shoppers:
+        for item in shopper['items_bought']:
+            if item not in items_group.keys():
+                items_group[item] = []
+            items_group[item].append(shopper['name'])
+    
+    unique_items = set()
+    for shopper in shoppers:
+        unique_items.update(shopper['items_bought'].keys())
+    
+    # Returning all results as a dictionary
+    return {
+        "shoppers": names,
+        "filtered_by_age": filtered_shoppers,
+        "average_age": average_age,
+        "sorted_shoppers": sorted_shoppers,
+        "items_group": dict(items_group),
+        "unique_items": unique_items
+    }
+    </sol>
+    test = <los>...</los><sol>'test'</sol> #tests
+</template>
+<suffix>
+# some suffix
+</suffix>
+<suffix_invisible>
+{% include '../function_type_and_modify_check_suffix.py.jinja' %}
+</suffix_invisible>
+```
+
+# Public Test Cases
+
+## Input 1
+```
+shoppers = [
+    {"name": "Alice", "age": 25, "items_bought": {"Apples": 3, "Bananas": 5}},
+    {"name": "Bob", "age": 35, "items_bought": {"Oranges": 2, "Milk": 1}},
+    {"name": "Charlie", "age": 30, "items_bought": {"Apples": 1, "Bread": 2}},
+    {"name": "David", "age": 22, "items_bought": {"Milk": 2, "Eggs": 12}},
+    {"name": "Eve", "age": 28, "items_bought": {"Bananas": 4, "Oranges": 3}},
+]
+age_filter = 25
+```
+
+## Output 1
+```
+shoppers: ['Alice', 'Bob', 'Charlie', 'David', 'Eve']
+filtered_by_age: ['Bob', 'Charlie', 'Eve']
+average_age: 28.0
+sorted_shoppers: [{'name': 'David', 'age': 22, 'items_bought': {'Milk': 2, 'Eggs': 12}}, {'name': 'Alice', 'age': 25, 'items_bought': {'Apples': 3, 'Bananas': 5}}, {'name': 'Eve', 'age': 28, 'items_bought': {'Bananas': 4, 'Oranges': 3}}, {'name': 'Charlie', 'age': 30, 'items_bought': {'Apples': 1, 'Bread': 2}}, {'name': 'Bob', 'age': 35, 'items_bought': {'Oranges': 2, 'Milk': 1}}]
+items_group: {'Apples': ['Alice', 'Charlie'], 'Bananas': ['Alice', 'Eve'], 'Oranges': ['Bob', 'Eve'], 'Milk': ['Bob', 'David'], 'Bread': ['Charlie'], 'Eggs': ['David']}
+unique_items: {'Bananas', 'Oranges', 'Bread', 'Eggs', 'Milk', 'Apples'}
+```
+
+# Private Test Cases
+
+
+## Input 1
+```
+shoppers = [
+    {"name": "Alice", "age": 25, "items_bought": {"Apples": 3, "Bananas": 5, "Oranges": 2, "Milk": 1}},
+    {"name": "Bob", "age": 35, "items_bought": {"Oranges": 2, "Milk": 1, "Cheese": 1, "Bread": 2}},
+    {"name": "Charlie", "age": 30, "items_bought": {"Apples": 1, "Bread": 2, "Eggs": 6, "Butter": 1}},
+    {"name": "David", "age": 22, "items_bought": {"Milk": 2, "Eggs": 12, "Bread": 3, "Cheese": 1}},
+    {"name": "Eve", "age": 28, "items_bought": {"Bananas": 4, "Oranges": 3, "Tomatoes": 5, "Cucumbers": 2}},
+    {"name": "Frank", "age": 40, "items_bought": {"Cheese": 2, "Wine": 1, "Apples": 3, "Bread": 4}},
+    {"name": "Grace", "age": 27, "items_bought": {"Oranges": 5, "Apples": 3, "Bread": 2, "Butter": 1}},
+    {"name": "Hank", "age": 32, "items_bought": {"Milk": 3, "Cereal": 2, "Eggs": 4, "Tomatoes": 6}},
+    {"name": "Ivy", "age": 38, "items_bought": {"Eggs": 6, "Bread": 4, "Milk": 2, "Tomatoes": 3}},
+    {"name": "Jack", "age": 29, "items_bought": {"Bananas": 5, "Tomatoes": 4, "Milk": 1, "Oranges": 2}},
+    {"name": "Karen", "age": 33, "items_bought": {"Apples": 2, "Oranges": 4, "Bananas": 3, "Bread": 1}},
+    {"name": "Louis", "age": 24, "items_bought": {"Milk": 1, "Cereal": 3, "Bread": 2, "Eggs": 5}},
+]
+
+```
+
+## Output 1
+```
+shoppers: ['Alice', 'Bob', 'Charlie', 'David', 'Eve', 'Frank', 'Grace', 'Hank', 'Ivy', 'Jack', 'Karen', 'Louis']
+filtered_by_age: ['Bob', 'Charlie', 'Eve', 'Frank', 'Grace', 'Hank', 'Ivy', 'Jack', 'Karen']
+average_age: 30.25
+sorted_shoppers: [{'name': 'David', 'age': 22, 'items_bought': {'Milk': 2, 'Eggs': 12, 'Bread': 3, 'Cheese': 1}}, {'name': 'Louis', 'age': 24, 'items_bought': {'Milk': 1, 'Cereal': 3, 'Bread': 2, 'Eggs': 5}}, {'name': 'Alice', 'age': 25, 'items_bought': {'Apples': 3, 'Bananas': 5, 'Oranges': 2, 'Milk': 1}}, {'name': 'Grace', 'age': 27, 'items_bought': {'Oranges': 5, 'Apples': 3, 'Bread': 2, 'Butter': 1}}, {'name': 'Eve', 'age': 28, 'items_bought': {'Bananas': 4, 'Oranges': 3, 'Tomatoes': 5, 'Cucumbers': 2}}, {'name': 'Jack', 'age': 29, 'items_bought': {'Bananas': 5, 'Tomatoes': 4, 'Milk': 1, 'Oranges': 2}}, {'name': 'Charlie', 'age': 30, 'items_bought': {'Apples': 1, 'Bread': 2, 'Eggs': 6, 'Butter': 1}}, {'name': 'Hank', 'age': 32, 'items_bought': {'Milk': 3, 'Cereal': 2, 'Eggs': 4, 'Tomatoes': 6}}, {'name': 'Karen', 'age': 33, 'items_bought': {'Apples': 2, 'Oranges': 4, 'Bananas': 3, 'Bread': 1}}, {'name': 'Bob', 'age': 35, 'items_bought': {'Oranges': 2, 'Milk': 1, 'Cheese': 1, 'Bread': 2}}, {'name': 'Ivy', 'age': 38, 'items_bought': {'Eggs': 6, 'Bread': 4, 'Milk': 2, 'Tomatoes': 3}}, {'name': 'Frank', 'age': 40, 'items_bought': {'Cheese': 2, 'Wine': 1, 'Apples': 3, 'Bread': 4}}]
+items_group: {'Apples': ['Alice', 'Charlie', 'Frank', 'Grace', 'Karen'], 'Bananas': ['Alice', 'Eve', 'Jack', 'Karen'], 'Oranges': ['Alice', 'Bob', 'Eve', 'Grace', 'Jack', 'Karen'], 'Milk': ['Alice', 'Bob', 'David', 'Hank', 'Ivy', 'Jack', 'Louis'], 'Cheese': ['Bob', 'David', 'Frank'], 'Bread': ['Bob', 'Charlie', 'David', 'Frank', 'Grace', 'Ivy', 'Karen', 'Louis'], 'Eggs': ['Charlie', 'David', 'Hank', 'Ivy', 'Louis'], 'Butter': ['Charlie', 'Grace'], 'Tomatoes': ['Eve', 'Hank', 'Ivy', 'Jack'], 'Cucumbers': ['Eve'], 'Wine': ['Frank'], 'Cereal': ['Hank', 'Louis']}
+unique_items: {'Bananas', 'Cucumbers', 'Cheese', 'Cereal', 'Tomatoes', 'Apples', 'Milk', 'Oranges', 'Butter', 'Eggs', 'Bread', 'Wine'}
+```
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