Mean by row of a dataframe with a column containing a string of numbers separated by commas

Question

I have a DF containing a column with numbers separated by commas (it's a string field).

I need to calculate the mean by row of every value contained in that column.

Example:

"COLUMN 1"
2,18,10
10
80,20

Expected result:

"MEAN"
10
10
50

https://stackoverflow.com/questions/20109391/how-to-make-good-reproducible-pandas-examples — Paul H, Apr 05 '23 at 23:46

score 0 · Accepted Answer · edited Apr 06 '23 at 08:57

You can split the comma separated string into list then convert list of string to multiple columns and last calculate the mean along columns.

df['Mean'] = (pd.DataFrame(df['COLUMN 1'].str.split(',').tolist())
              .astype('float').mean(axis=1))
# or
df['Mean'] = (df['COLUMN 1'].str.split(',')
              .apply(pd.Series).astype('float').mean(axis=1))

  COLUMN 1  Mean
0  2,18,10  10.0
1       10  10.0
2    80,20  50.0

Mean by row of a dataframe with a column containing a string of numbers separated by commas

1 Answers1