Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.
Filtering the DataFrame | Unveiling the Power of Data Manipulation with Pandas
Unveiling the Power of Data Manipulation with Pandas
course content

Course Content

Unveiling the Power of Data Manipulation with Pandas

Filtering the DataFrame

Filtering a pandas DataFrame refers to selecting rows based on a specific condition. You can filter a DataFrame using the [] operator with conditions inside, such as df[df['column'] > value], or the .query() method, like df.query('column > value').

For example, suppose you have a DataFrame df with columns "Name", "Age", and "Gender", and you want to select all rows where the values of the "Age" column are greater than 30. You can use the following code to filter the DataFrame:

You can also use the "&" (logical and) and "|" (logical or) operators to combine multiple conditions.

Task

  1. Filter the data DataFrame using multiple conditions (use the logical and operator to combine them):
    • The value of the 'MANAGER_ID' column is greater than 100.
    • The value of the 'LOCATION_ID' column is equal to 1700.

Task

  1. Filter the data DataFrame using multiple conditions (use the logical and operator to combine them):
    • The value of the 'MANAGER_ID' column is greater than 100.
    • The value of the 'LOCATION_ID' column is equal to 1700.

Mark tasks as Completed

Everything was clear?

Filtering a pandas DataFrame refers to selecting rows based on a specific condition. You can filter a DataFrame using the [] operator with conditions inside, such as df[df['column'] > value], or the .query() method, like df.query('column > value').

For example, suppose you have a DataFrame df with columns "Name", "Age", and "Gender", and you want to select all rows where the values of the "Age" column are greater than 30. You can use the following code to filter the DataFrame:

You can also use the "&" (logical and) and "|" (logical or) operators to combine multiple conditions.

Task

  1. Filter the data DataFrame using multiple conditions (use the logical and operator to combine them):
    • The value of the 'MANAGER_ID' column is greater than 100.
    • The value of the 'LOCATION_ID' column is equal to 1700.

Mark tasks as Completed
Section 1. Chapter 4
AVAILABLE TO ULTIMATE ONLY
We're sorry to hear that something went wrong. What happened?
some-alt