Pandas Dataframe

A pandas dataframe is an extension of the Panda Series to have n-dimensions. This allows for a robust tabular structure of acccessing data. Much like a matrix, we can apply transformations to a dataframe as we would on a matrix.Below is an example of defining a dataframe object.

Defining a Dataframe Object

import pandasdf = pd.DataFrame( {'Country': ['USA', 'Canada', 'Mexico'],
            'Population': [325, 36, 127],
            'Year': [2018, 2017, 2017]})
df as pd

df = pd.DataFrame( {'Country': ['USA', 'Canada', 'Mexico'],
            'Population': [325, 36, 127],
            'Year': [2018, 2017, 2017]})
df

We see above the tabular structure of the dataframe. let’s change the index

Changing Index

df.set_index('Country', inplace=True)

df

What is the use of inplace in pandas?

When inplace = True is used, it performs operation on data and nothing is returned. When inplace=False is used, it performs operation on data and returns a new copy of data.