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Unveiling the Power of Data Manipulation with Pandas

Grouping in PandasGrouping in Pandas

Grouping in pandas involves dividing a DataFrame into groups based on the values in one or more columns. You can then apply a function to each group to compute a summary statistic, such as the mean, sum, or count.

To group a DataFrame in pandas, use the .groupby() method. This method accepts a column name or a list of column names and returns a groupby object.

Here is an example:

This example demonstrates how to calculate the mean for each group formed based on the values in 'column_name'.

Task

  1. Group the data DataFrame by 'DEPARTMENT_NAME' and compute the mean, minimum, and maximum of the 'MANAGER_ID' column for each group.

Mark tasks as Completed

Everything was clear?

Section 1. Chapter 5
AVAILABLE TO ULTIMATE ONLY
course content

Course Content

Unveiling the Power of Data Manipulation with Pandas

Grouping in PandasGrouping in Pandas

Grouping in pandas involves dividing a DataFrame into groups based on the values in one or more columns. You can then apply a function to each group to compute a summary statistic, such as the mean, sum, or count.

To group a DataFrame in pandas, use the .groupby() method. This method accepts a column name or a list of column names and returns a groupby object.

Here is an example:

This example demonstrates how to calculate the mean for each group formed based on the values in 'column_name'.

Task

  1. Group the data DataFrame by 'DEPARTMENT_NAME' and compute the mean, minimum, and maximum of the 'MANAGER_ID' column for each group.

Mark tasks as Completed

Everything was clear?

Section 1. Chapter 5
AVAILABLE TO ULTIMATE ONLY
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