show/print plot of frequency table/ result of value_counts()

Question

Looking through the site I found;

fig, ax = plt.subplots()
data.value_counts().plot(ax=ax, kind='bar')
plt.show()

where data is my series. The code runs but doesn't print/show the plot. Why?

So far I've run the following in a colab notebook.

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt 
import matplotlib as mpl
import seaborn as sns
sns.set()
%matplotlib notebook

# define series 
data=pd.Series([15,10,17,11,15,.....,17,15,14,13,16])
data.value_counts()

then the above.

Answer 1

So I kept searching and turned my series into a dataframe and created a bar chart from that which illustrates the mode. So for other complete utter newbies create a dataframe not a series....

 pd.DataFrame([15,10,17,11,.....,15,14,13,16])
 df = pd.DataFrame(data, columns = ['GamesAttended'])
 df

which printed/showed the column

from plotnine import *
ggplot(data = df) + geom_bar(mapping = aes(x = 'GamesAttended'))

which gave me a lovely bar chart.

So I've not answered my original question which is why the code ran but didn't show/print. And I still haven't managed to turn the frequency table/output of value_count() in to a chart but I managed to create a bar chart showing the mode which is what I was supposed to be doing.