pandas - How to plot two different features while counting them?

Question

Suppose I have a DataFrame like this:

*Age* *RemoteWork*
18  Sometimes
24  Never
30  Sometimes
15  Never
24  Sometimes

and it goes on like that.

How would I plot a graph for example "which shows HOW MANY 24 year olds are in Never group"?

Suppose there are more ages and remote work values. I am basically trying to create a histogram of age which shows remote work value and count.

I am sorry if this is not very clear. If you need anymore info please tell me.

question from:https://stackoverflow.com/questions/65649505/how-to-plot-two-different-features-while-counting-them

Answer 1

Clearly your sample data set is limited and does not have additional attributes. You really need to consider how you want to visualise, then it's straight forward. Using matplotlib two examples.

1. a scatter where have factorized y-axis (not needed just for demonstration)
2. a stacked bar putting ages into age ranges

import matplotlib.pyplot as plt

df = pd.read_csv(io.StringIO("""*Age* *RemoteWork*
18  Sometimes
24  Never
30  Sometimes
15  Never
24  Sometimes"""), sep="s+")


fig, ax = plt.subplots(1,2, figsize=[10,5],
                      sharey=False, sharex=False, gridspec_kw={"hspace":0.3})

(df
 .assign(a=lambda dfa: ((dfa["*Age*"]//10)*10).astype(str)+"-"+(((dfa["*Age*"]//10)*10)+9).astype(str))
 .groupby(["a","*RemoteWork*"])
 .agg("count")
 .unstack(0)
 .droplevel([0], axis=1)
 .plot(ax=ax[1],kind="bar", stacked=True)
)
ax[1].set_xlabel("Stacked", weight='bold', fontsize=12)


(df
 .assign(y=lambda dfa: pd.factorize(dfa["*RemoteWork*"])[0])
 .plot(ax=ax[0],kind="scatter", x="*Age*", y="y", c="*Age*", s="*Age*", colormap="jet")
)
ax[0].set_xlabel("Scatter", weight='bold', fontsize=12)