*With this post, we will learn how to perform **read** and **write** operations on different formats of data.*

- CSV
- EXCEL
- HTML
- SQL

*Note:- For examples here, I have stored the files like csv and excel in the same folder where the codes are written or where the jupyter notebook file is. If you want, you can download the same files as i have used here, from my **github repo**.*

**1) CSV- comma separated values**

A comma separated values (CSV) file is a text file that has a specific format that allows data to be saved in a table structured format.

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(Advice:- It’s always good to know at least basics of NumPy/ Matplotlib before jumping to Pandas)

Key Contents:-

- 3 W’s of Pandas (What/ Why/ Where)
- Installing Pandas
- Data Structures (Data Frame, Series)- Basic
- Important Questions

*What is Pandas?*

Pandas is an **open source**, **BSD-licensed **library which provides easy to use data structures, data analysis, data manipulation tools for the python programming language. It’s built on top of two core libraries of Python — matplotlib (used for data visualization) and NumPy (used for mathematical Operations).

Pandas is like excel of Python. **Data Frame **is analogous to a **table** and** Series **is…

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