I currently have a Dataframe that looks something like this:
The unique values are ['Somewhat Interested', 'Not at all Interested', nan,'Very Interested']
How would I go about creating a new dataframe that would have the same columns as above but for the index values 'Somewhat Interested', 'Not at all Interested', nan,'Very Interested' and the values inside the cell are the counts of each type of response. Im thinking a pivot table might do the trick but Im not sure.
What I want
In person meet ups | alumni webinars | alumni webinars | etc... | |
---|---|---|---|---|
Some what interested | 24 | 32 | 12 | |
Not interested | 32 | 42 | 4 | |
very intersted | 21 | 31 | 53 |
CodePudding user response:
Combine value_counts
with apply
to do it per column:
df.apply(pd.value_counts)
CodePudding user response:
Actually, you can just apply
pd.Series.value_counts
for each column:
counts = df.fillna('NaN').apply(pd.Series.value_counts).fillna(0).astype(int)