pandas convert columns to percentages of the totals

Question

I have a dataframe with 4 columns an ID and three categories that results fell into

  <80% 80-90 >90
id
1   2     4    4
2   3     6    1
3   7     0    3

I would like to convert it to percentages ie:

   <80% 80-90 >90
id
1   20%   40%  40%
2   30%   60%  10%
3   70%    0%  30%

this seems like it should be within pandas capabilities but I just can’t figure it out.

Thanks in advance!

Asked By: DTATSO

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Source

Answer 1

You can do this using basic pandas operators .div and .sum, using the axis argument to make sure the calculations happen the way you want:

cols = ['<80%', '80-90', '>90']
df[cols] = df[cols].div(df[cols].sum(axis=1), axis=0).multiply(100)

Calculate the sum of each column (df[cols].sum(axis=1). axis=1 makes the summation occur across the rows, rather than down the columns.
Divide the dataframe by the resulting series (df[cols].div(df[cols].sum(axis=1), axis=0). axis=0 makes the division happen across the columns.
To finish, multiply the results by 100 so they are percentages between 0 and 100 instead of proportions between 0 and 1 (or you can skip this step and store them as proportions).

Answered By: ASGM

Answer 2

df/df.sum()

If you want to divide the sum of rows, transpose it first.

Answered By: Tim Tian

Answer 3

Tim Tian’s answer pretty much worked for me, but maybe this helps if you have a df with several columns and want to do a % column wise.

df_pct = df/df[df.columns].sum()*100

I was having trouble because I wanted to have the result of a pd.pivot_table expressed as a %, but couldn’t get it to work. So I just used that code on the resulting table itself and it worked.

Answered By: FDV

Answer 4

You could use the .apply() method:

df = df.apply(lambda x: x/sum(x)*100, axis=1)

Answered By: PigSpider

pandas convert columns to percentages of the totals

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