CODEWITHSUNDEEP
pythonpandasnumpymatplotlibseaborn
Paulfryy
Paulfryy

Reputation: 65

How to plot multiple column barplots under same labels

I'm looking to plot my dataframe, which contains many columns each with a "TRUE" or "FALSE" label (imported from Excel).

A small example of something similar would be this:

df = pd.DataFrame({"a":["TRUE","FALSE","FALSE","TRUE","FALSE"],
"b":["TRUE","TRUE","FALSE","TRUE","TRUE"],
"c":["TRUE","FALSE","FALSE","FALSE","TRUE"],
"d":["FALSE","FALSE","TRUE","TRUE","FALSE"]})

I'm looking for a way to concisely summarize how the TRUE and FALSE values are distributed between the columns. Ideally, a graph like something below would be created:

Example of what I'm looking for

but I'm unsure how to create this. I've tried list comprehension, like trying

sns.barplot([list(df[i].value_counts()) for i in df.columns])

but get something entirely different. I don't even need to know how to make the legend, I just included it in the example to hopefully better portray what I'm getting after.

Upvotes: 1

Views: 56

Answers (2)

user3483203
user3483203

Reputation: 51165

You had the more efficient approach already in your attempt. You should be computing the value_counts on each series if you want to scale this to larger frames. You just need a change to the plot.

f = pd.concat(
      [df[s].value_counts() for s in df], axis=1, sort=False)

f.plot(kind='bar')

Upvotes: 2

Quang Hoang
Quang Hoang

Reputation: 150725

Here you go:

df.stack().groupby(level=1).value_counts().unstack(0).plot.bar()

Output:

enter image description here

Upvotes: 2

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