Pandas plotting dataframe specific column count as bar

Question

If I have a data frame as below

column1                column2
key1Str         valueAsString1
key2Str         valueasString2
key2Str         valueasString1
key1Str         valueasString2
key3Str         valueasString1
key1Str         valueasString2

I wanted to plot this as bar graph where x-axis is each key and each value and y should be count of each value in data frame. I'm fairly new to python and tried to do as follows.

plot summary as (key1 - value1Count, value2Count, key2- value1Count, value2Count....)

fig, ax = plt.subplots()
for key in df['column1'].unique():
    data_=df[df['column1']==key]
    data_['column2'].values_count().plot(kind='bar', ax=ax)
plt.show()

it just shows one graph at the end, what's the better way to do this?

MaxU - stand with Ukraine · Accepted Answer · 2017-05-02 23:09:23Z

4

IIUC:

import seaborn as sns

sns.barplot(x='column1', y='cnt', hue='column2',
            data=df.groupby(df.columns.tolist()).size().to_frame('cnt').reset_index())

edited May 2, 2017 at 23:09

answered May 2, 2017 at 22:52

MaxU - stand with Ukraine

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4 Comments

SKR Over a year ago

Thankx MaxU, this works per key count, I wanted to have separate bars per value as well, since the values are also shared across all keys and very limited

MaxU - stand with Ukraine Over a year ago

@SKR, do you mean something like: df.groupby(['column1','column2']).size().plot.bar()?

SKR Over a year ago

Thanks, yes group by both columns worked as expected, but through seaborn is much cleaner.

MaxU - stand with Ukraine Over a year ago

@SKR, glad I could help :-)

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