Pandas is the most essential library when it comes to data analytics. It is used to work with the datasets. It makes the process of data analyzing & structuring way more easier.

Here, In this blog post I will guide you with 11 steps which you can learn & use in pandas.

***Note* :- All the following 11 steps are extremely useful, please do not try to skip the learning any of the steps. **

[Please use Jupyter Notebook, If you haven't configured it yet then please go & configure the Jupyter Notebook first]

Step 1:-
import Pandas, load the data & checkout the shape of your dataframe
[By loading the data you will be able to print & analyze the data from the selected dataframe]

Step 2:-
Learn more about dataframes & series objects

Step 3:-
How to create & use custom indexes using Pandas

Step 4:-
Basics of filtering dataframes & series objects

Step 5:-
Alter the existing rows & columns in the dataframe

Step 6:-
Add & Remove Columns from the dataframe

Step 7:-
Sort data in Pandas, Sorting single columns, sorting multiple columns & wrapping the largest & smallest values from different rows

Step 8:-
Grouping & Aggregating the data

Step 9:-
Handle missing values & data cleaning

Step 10:-
Work with date & time series data with Pandas

Step 11:-
Read & Write data to different sources

Bonus :-
My favourite location to learn about pandas is Corey Schafer's YouTube channel. His playlist is a treasure for those newbies that wish to discover Pandas library.

Link :-
https://www.youtube.com/playlist?list=PL-osiE80TeTsWmV9i9c58mdDCSskIFdDS

Thank you for reading the blog till the end. I wish you all the best for your journey of learning data analytics.