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I create a dataset like that,

Gender response female yes male yes female yes female no male yes female no male yes male no female no

I like to count the yes responses and no responses genderwise. Like there are two females who said No and 2 females who said yes. There are three males said yes and one said no.

I tried to implement this using pandas dataframe.

So far I have tried to write down the query like

df.loc[df['Gender'] == 'female' & (df['response'] == 'yes')]

But I got error. How could I write it down?

Thank you.

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  • The error you are getting is because you missed putting the first condition inside a bracket. Anyways the line you are looking for is df.groupby(['Gender', 'response'], as_index=False).size() Commented Oct 29, 2022 at 6:04

3 Answers 3

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You can use value_counts with groupby method like this:

df.groupby('Gender')['response'].value_counts()

Response:

Gender response female no 3 yes 2 male yes 3 no 1
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2

Please cross tabulate

pd.crosstab(df['Gender'], df['response']).reset_index()
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1

You can group and count each category like this too:

counts = df.groupby(['Gender','response']).size() print(counts['female']['yes']) # Show the number of females who responded yes
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