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
Exercise instructions
- Import the
pandas
package using the aliaspd
. - Read
titanic.csv
into a DataFrame calleddf
. The file name is already stored in thefile
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(____)