Pandas plotting dataframe specific column count as bar

matplotlib, pandas, python

Solution

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())

Problem

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?

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