Interpolate debt/GDP and compare to unemployment

Since you have learned how to interpolate time series, you can now apply this new skill to the quarterly debt/GDP series, and compare the result to the monthly unemployment rate.

This exercise is part of the course

Manipulating Time Series Data in Python

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Exercise instructions

We have imported pandas as pd and matplotlib.pyplot as plt for you.

Use pd.read_csv() to import 'debt_unemployment.csv', creating a DateTimeIndex from the 'date' column using parse_dates and index_col, and assign the result to data. print() the .info() of the data.
Apply .interpolate() to data and assign this to interpolated, then inspect the result.
Plot interpolated with 'Unemployment' on the secondary_y axis.

Hands-on interactive exercise

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

# Import & inspect data here
data = ____
print(____)

# Interpolate and inspect here
interpolated = ____
print(____)

# Plot interpolated data here

Edit and Run Code