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What we are going to learn in this pandas Tutorial series. So here are the main points

Data Handling using Pandas -I     

Introduction to Python libraries- Pandas, Matplotlib.

Data structures in Pandas – Series and Data Frames.  Series: Creation of Series from – ndarray, dictionary, scalar value; mathematical operations; Head and Tail functions; Selection, Indexing and Slicing.

Data Frames: creation – from the dictionary of Series, list of dictionaries, Text/CSV files; display; iteration;

Operations on rows and columns: add, select, delete, rename; Head and Tail functions; Indexing using Labels, Boolean Indexing; Joining, Merging and Concatenation.

Importing/Exporting Data between CSV files and Data Frames.

Data handling using Pandas – II   

Descriptive Statistics: max, min, count, sum, mean, median, mode, quartile, Standard deviation, variance.

DataFrame operations:  Aggregation, group by,  Sorting, Deleting and Renaming Index, Pivoting. Handling missing values – dropping and filling.  Importing/Exporting Data between MySQL database and Pandas.

Pre-requisite to learn Pandas

We are assuming here that you are already aware of python and the basic working of the computer system and one RDBMS software like MySQL. You are also aware of how to install a python module using pip.

You have a basic understanding of  Numpy – a Python Module for Numerical Processing.


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