Using pandas to import flat files as DataFrames (1)

In the last exercise, you were able to import flat files containing columns with different datatypes as numpy arrays. However, the DataFrame object in pandas is a more appropriate structure in which to store such data and, thankfully, we can easily import files of mixed data types as DataFrames using the pandas functions read_csv() and read_table().

This exercise is part of the course

Introduction to Importing Data in Python

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Exercise instructions

Import the pandas package using the alias pd.
Read titanic.csv into a DataFrame called df. The file name is already stored in the file object.
In a print() call, view the head of the DataFrame.

Hands-on interactive exercise

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

# Import pandas as pd
____

# Assign the filename: file
file = 'titanic.csv'

# Read the file into a DataFrame: df
df = pd.read_csv(____)

# View the head of the DataFrame
print(____)

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