Turning this all into a DataFrame

You've zipped lists together, created a function to house your code, and even used the function in a list comprehension to generate a list of dictionaries. That was a lot of work and you did a great job!

You will now use all of these to convert the list of dictionaries into a pandas DataFrame. You will see how convenient it is to generate a DataFrame from dictionaries with the DataFrame() function from the pandas package.

The lists2dict() function, feature_names list, and row_lists list have been preloaded for this exercise.

Go for it!

This exercise is part of the course

Python Toolbox

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Exercise instructions

To use the DataFrame() function you need, first import the pandas package with the alias pd.
Create a DataFrame from the list of dictionaries in list_of_dicts by calling pd.DataFrame(). Assign the resulting DataFrame to df.
Inspect the contents of df printing the head of the DataFrame. Head of the DataFrame df can be accessed by calling df.head().

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Import the pandas package


# Turn list of lists into list of dicts: list_of_dicts
list_of_dicts = [lists2dict(feature_names, sublist) for sublist in row_lists]

# Turn list of dicts into a DataFrame: df
df = ____

# Print the head of the DataFrame

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