Conditional Formatting

When exploring data, using pandas you can also apply conditional formatting similar to how you did using spreadsheets. Say, for instance, you only want to display related to a specific city, state, movie genre, or name, you can do so!

We will begin by identifying rows based on a condition using one column of data.

Example

# import pandas
import pandas as pd

# Create a pandas DataFrame using a dictionary
movies = {'Name': ["Interstellar", "Pride and Prejudice", "Inception", "Barbie"],'Release': [2014, 2005, 2010, 2003], 'Genre': ["Science Fiction", "Novel", "Science Fiction", "Comedy"]}

movies_dataframe = pd.DataFrame(movies)

# Select only movies from the Science Fiction genre
science_fiction = movies_dataframe[movies_dataframe['Genre'] == "Science Fiction"]

# Print the data
print(science_fiction)

Output

           Name  Release            Genre
0  Interstellar     2014  Science Fiction
2     Inception     2010  Science Fiction

Multiple Conditions

In the below example we will apply conditional formatting based on the data in multiple columns. This is very useful when you are trying to identify a particular set of data so that you can properly analyze, clean, and prepare for further analysis like visualization!

Example

# import pandas
import pandas as pd

# Create a pandas DataFrame using a dictionary
movies = {'Name': ["Interstellar", "Pride and Prejudice", "Inception", "Barbie"],'Release': [2014, 2005, 2010, 2003], 'Genre': ["Science Fiction", "Novel", "Science Fiction", "Comedy"]}

movies_dataframe = pd.DataFrame(movies)

# Select only movies from the Science Fiction genre
science_fiction = movies_dataframe[(movies_dataframe['Genre'] == "Science Fiction") & (movies_dataframe['Release'] <= 2010)]

# Print the data
print(science_fiction)

Output

        Name  Release            Genre
2  Inception     2010  Science Fiction

Check Your Understanding

Question

True or False: Conditional formatting can be applied using data from multiple columns.