Learn PANDAS with Real Code Examples

Learn Python basics and NumPy arrays

Understand Series and DataFrame structures

Practice data cleaning, filtering, and selection

Explore grouping, pivoting, and time-series operations

Integrate with visualization and ML workflows

Week 1: DataFrames, Series, and basic operations

Week 2: Indexing, slicing, filtering

Week 3: Aggregations, groupby, pivot tables

Week 4: Time-series and advanced manipulations

Week 5: Integration with visualization and ML pipelines

What are the main data structures in Pandas?

How do you handle missing data?

Explain groupby and pivot_table functionality

How do you merge or join datasets?

What are best practices for memory optimization in Pandas?

pd.read_csv() = load CSV file

df.head() = first 5 rows

df.describe() = summary statistics

df.groupby('column').sum() = aggregation

df.merge(df2, on='key') = join datasets

Python for Data Analysis by Wes McKinney

Pandas Cookbook by Theodore Petrou

Effective Pandas by Matt Harrison

Mastering Pandas by Ashish Kumar

Hands-On Data Analysis with Pandas by Stefanie Molin

Pandas official tutorials

DataCamp Pandas courses

Kaggle Pandas exercises

YouTube Pandas tutorials

Books and blog posts on Pandas

https://pandas.pydata.org/

https://pandas.pydata.org/docs/

https://github.com/pandas-dev/pandas

Pandas GitHub

StackOverflow Pandas tag

Reddit /r/datascience

Pandas official forums

MOOCs and online tutorials

Pandas GitHub repository

StackOverflow Pandas tag

Reddit /r/datascience

Pandas official documentation

MOOCs, blogs, and tutorial sites