Python Pandas – Python Library For Data Analysis

Learn Python DataFrame Operations

Python Pandas is a library for data analysis.

What you’ll learn

  • How to use python pandas library.
  • Doing data analysis with pandas.
  • Doing all operations with DataFrame.
  • Creating DataFrame From CSV and doing all operations.

Course Content

  • Python Panda DataFrame –> 12 lectures • 57min.

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Python Pandas is a library for data analysis.

In Pandas library DataFrame is used to do all operations related to data analysis.

A Pandas DataFrame is a 2 dimensional data structure with rows and columns.

In this course you will learn how to do all operations with pandas DataFrame.


Through this course you will learn the following :-


1. Creating DataFrame

How to create DataFrame from different python data structures.


2. Adding Columns and Rows to DataFrame

How to add data(column,row) to the DataFrame


3. Deleting Rows and Columns From DataFrame

How to delete rows and columns from DataFrame


4. DataFrame Attributes

Attributes which gives information about DataFrame


5. DataFrame Functions

Functions that will help in data analysis


6. DataFrame Grouping

How to group data in the DataFrame


7. Locating data in DataFrame

How to locate data based on columns and rows


7. DataFrame Filtering

How to filter data from DataFrame


8. DataFrame and CSV

How to create DataFrame from CSV files and how to convert DataFrame to CSV files.


9. DataFrame to HTML

How to convert DataFrame to HTML file


10. Data Cleaning

How to clean unwanted data


After completing this course , you will learn how to create DataFrame from large CSV files and to analyse the data.

Once the DataFrame is created we can add columns, and rows of data to it. We can also delete columns and rows from the

DataFrame . We have various functions that helps us in doing data analysis on DataFrame data.  We have support for filtering and grouping data . We can also delete unwanted data from the DataFrame.

You will learn how to convert the DataFrame to different files ,CSV and HTML.

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