Compare annual stock price trends

In the video, you have seen how to select sub-periods from a time series.

You'll use this to compare the performance for three years of Yahoo stock prices.

This exercise is part of the course

Manipulating Time Series Data in Python

Exercise instructions

We have already imported pandas as pd and matplotlib.pyplot as plt and we have already loaded the 'yahoo.csv' file in a variable yahoo with DateTimeIndex and a single column price.

Create an empty pd.DataFrame() called prices.
Iterate over a list containing the three years, 2013, 2014, and 2015, as string, and in each loop:
- Use the iteration variable to select the data for this year and the column price.
- Use .reset_index() with drop=True to remove the DatetimeIndex.
- Rename the column price column to the appropriate year.
- Use pd.concat() to combine the yearly data with the data in prices along axis=1.
Plot prices.

Hands-on interactive exercise

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

# Create dataframe prices here
prices = ____

# Select data for each year and concatenate with prices here 
for year in [___, ___, ___]:
    price_per_year = yahoo.loc[___, [___]].reset_index(drop=True)
    price_per_year.rename(columns={___: year}, inplace=True)
    prices = pd.concat([prices, ___], axis=1)

# Plot prices

Edit and Run Code