pandas dataframe group by values of a column

Question

I have the following dataframe:

id	expNumber	attempt	finished	successful
1	1	1	true	false
1	1	2	false	false
1	1	3	true	true
1	2	1	false	false
1	2	2	true	false
1	2	3	true	true
1	4	1	false	false
1	4	2	false	false

id,expNumber,attempt,finished,successful,
1,1,1,true,false,
1,1,2,false,false,
1,1,3,true,true,
1,2,1,false,false,
1,2,2,true,false,
1,2,3,true,true,
1,4,1,false,false,
1,4,2,false,false,

And I want to create a dataframe which counts the data grouped by the value of the column. Here is what I expect:


true	4
false	4

I tried the following code but when I print the result, its just empty.

df = df.groupby('finished'.sum())
print("test", df)

jezrael · Accepted Answer · 2022-10-26 10:46:59Z

1

Select columns for count and use value_counts:

df = df[['finished','successful']].apply(pd.value_counts)
print("test", df)
test        finished  successful
False         4           6
True          4           2

answered Oct 26, 2022 at 10:46

jezrael

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Comments

Borja_042 · Accepted Answer · 2022-10-26 10:46:40Z

1

You can do either of the following:

df.groupby("finished").count()

Or:

df["finished"].value_counts()

answered Oct 26, 2022 at 10:46

Borja_042

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