Pandas Overview

A Pandas dataframe is essentially a matrix with headers and a unique index. My most common use case is to create a Pandas dataframe from a csv file.

Look up here, if you want a hint on, for instance,

• How do I create a Pandas dataframe from lists?
• How do I change a column in a Pandas dataframe on condition?
• How do I insert a row in a Pandas dataframe?

Pandas - How do I … ?

Getting to Pandas Dataframes

Wrangling starts with creating a dataframe.

The most common options might be

• Create a dataframe from a Python list or dictionary
• Create a dataframe when reading data from a local filesystem
• Create a dataframe when downloading data from the internet

You might also want to save, delete, … a dataframe.

For the details, see Listing on Create Pandas Dataframes

Working on a Pandas dataframe

Once you have got your dataframe, you might want to

• Work on the complete dataframe
• Work on columns
• Work on rows

For the details, see Listing on Operate on Pandas Dataframes

For preparing the visualization, some Pandas operations are typically needed. These operations are however not different from those listed above.