Summing up a Pandas dataframe, single column

Question

I have a dataframe with a single column and 1200 rows. There are a total of 3 possible values in each row - 'No difference', 'Opposite sex' or 'Same sex'. The column header is 'Friends' I'm trying to sum up the total number of results for each value using

df2 = df1.groupby(['Friends']).sum()

but I end up with an empty dataframe as the result (df2)

Welcome so stack overflow! If you have a single column, then you have a series, not a dataframe. Perhaps the `series.value_counts()` method might help here — G. Anderson, Jan 08 '20 at 20:48
Does this answer your question? [count the frequency that a value occurs in a dataframe column](https://stackoverflow.com/questions/22391433/count-the-frequency-that-a-value-occurs-in-a-dataframe-column) — AMC, Jan 08 '20 at 21:44

hchw · Accepted Answer · 2020-01-08T23:53:31.013

1

try

df2 = df1['Friends'].value_counts()

edited Jan 08 '20 at 23:53

answered Jan 08 '20 at 20:56

hchw

1,388
8
14

I think you have a period at the wrong place – Nicolas Gervais Jan 08 '20 at 23:34
@NicolasGervais thanks! – hchw Jan 08 '20 at 23:53
That did it - thank you – Dwayne Dibly Jan 09 '20 at 01:09

Summing up a Pandas dataframe, single column

1 Answers1