Skip to content

namannpatel/Data-Handling-Using-Python

BranchesTags

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

22 Commits
1. Create a panda’s series from a dictionary of values and a ndarray.py
1. Create a panda’s series from a dictionary of values and a ndarray.py
 
 
10. Replace all negative values in a data frame with a 0.py
10. Replace all negative values in a data frame with a 0.py
 
 
11. Create a Data Frame quarterly sales where each row contains the item category, item name, and expenditure. Group the rows by the category and print the total expenditure per category.py
11. Create a Data Frame quarterly sales where each row contains the item category, item name, and expenditure. Group the rows by the category and print the total expenditure per category.py
 
 
12. Create a data frame based on e-commerce data and generate descriptive statistics (mean, median, mode, quartile, and variance).py
12. Create a data frame based on e-commerce data and generate descriptive statistics (mean, median, mode, quartile, and variance).py
 
 
13. Write a program to iterate over a data-frame containing names and marks, which then calculates grades as per marks and adds them to the grade column.py
13. Write a program to iterate over a data-frame containing names and marks, which then calculates grades as per marks and adds them to the grade column.py
 
 
14. Real World Data Analysis of an Automobile Dataset (Automobile_data.csv).py
14. Real World Data Analysis of an Automobile Dataset (Automobile_data.csv).py
 
 
2. Given a Series, print all the elements that are above the 75th percentile.py
2. Given a Series, print all the elements that are above the 75th percentile.py
 
 
3. Create a Data Frame quarterly sales where each row contains the item category, item name, and expenditure. Group the rows by the category and print the total expenditure per category.pypy
3. Create a Data Frame quarterly sales where each row contains the item category, item name, and expenditure. Group the rows by the category and print the total expenditure per category.pypy
 
 
4. Create a data frame for examination result and display row labels, column labels data types of each column and the dimensions.py
4. Create a data frame for examination result and display row labels, column labels data types of each column and the dimensions.py
 
 
5. Filter out rows based on different criteria such as duplicate rows.py
5. Filter out rows based on different criteria such as duplicate rows.py
 
 
6. Importing and exporting data between pandas and CSV file.py
6. Importing and exporting data between pandas and CSV file.py
 
 
7. Find the sum of each column, or find the column with the lowest mean.py
7. Find the sum of each column, or find the column with the lowest mean.py
 
 
8. Locate the 3 largest values in a data frame.py
8. Locate the 3 largest values in a data frame.py
 
 
9. Subtract the mean of a row from each element of the row in a Data Frame.py
9. Subtract the mean of a row from each element of the row in a Data Frame.py
 
 
Automobile_data.csv
Automobile_data.csv
 
 
README.md
README.md
 
 

Repository files navigation

Data-Handling-Using-Python

Steps to Install Python on Windows are:

  1. Visit Official Python Website
  2. Select the version of Python
  3. Download Python Executable Installer
  4. Run the Setup of Python Installer
  5. Check Python is Install
  6. Check Pip is Install
  7. Install IDE or code editor for Python

Steps to Open Python IDLE on Windows are:

  1. Click start button.
  2. Click All Programs.
  3. Under Python Suite (Python 3.10) select IDLE (Python 3.10 64-bits).

Steps to Run a Python Program are:

  1. Go to the File Menu and Save your program.
  2. To run the script, go to the Run > Run Module or simply click F5.

About

No description, website, or topics provided.

Resources

Readme
Activity

Stars

0 stars

Watchers

1 watching

Forks

0 forks
Report repository

Releases

No releases published

Packages

 
 
 

Contributors

Languages