[FIXED] How to turn a DataFrame of average film runtimes by year into a bar plot?

Issue

I'm currently working on a quick project to look at film runtimes over the years. The data comes from a Netflix dataset, which I have filtered to get the information I'm interested in. I've also taken the average film length in minutes by year with groupby() and mean(), but when I attempt to create a bar plot I get an error.

import pandas as pd
import matplotlib.pyplot as plt

# read the csv files - turn into dataframes
netflix = pd.read_csv('titles.csv')
print(netflix)

# we just want to consider movies with over 60 minutes of runtime
movie_filter = netflix[(netflix["type"] == "MOVIE") &
                       (netflix["runtime"] > 60)]

# now lets factor in averages 
averages_over_time = movie_filter.groupby("release_year")["runtime"].mean()
average_film_runtime = pd.DataFrame(averages_over_time)
plt.plot(average_film_runtime["release_year"], average_film_runtime["runtime"])
plt.show()

The following is the error that I get.

Traceback (most recent call last):
  File "c:\Users\matth\Dropbox\Python Code\Netflix Analysis\netflix.py", line 16, in <module>
    plt.plot(average_film_runtime["release_year"], average_film_runtime["runtime"])
             ~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^
  File "C:\Users\matth\AppData\Roaming\Python\Python312\site-packages\pandas\core\frame.py", line 3893, in __getitem__
    indexer = self.columns.get_loc(key)
              ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\matth\AppData\Roaming\Python\Python312\site-packages\pandas\core\indexes\base.py", line 3797, in get_loc
    raise KeyError(key) from err
KeyError: 'release_year'
PS C:\Users\matth\Dropbox\Python Code\Netflix Analysis> 

I'm still new at working with Pandas and I've been stuck on this problem for almost an hour now so I apologize if the answer is obvious.

Thank you for your help.

Solution

I think your issue is coming from the fact that when you do groupby and then run pd.DataFrame() over that grouped-by object, the new object uses your original column as the index, not as a column.

That is to say, average_film_runtime does not have two columns called 'release_year' and 'runtime', but it has an index that is 'release_year' and one column (a Series) called 'runtime'.

You should be able to fix this by do average_film_runtime = average_film_runtime.reset_index() and then running it through plt.plot()

Answered By - scotscotmcc