Create Dataframe column that increases count based on another columns value

Question

I need to add a column to my dataframe that will add a number each time a value in another column surpasses a limit. Example below:

Original DF:

ColA   ColB
 4      1.4
 10     0.5
 1      2.3
 3      12.2
 8.8    8.5
 2      5.2
 0.6    0.33
 9      3
 4      144
 33     8

Desired DF: Where value in ColB surpasses 10, ColC count = count +1

ColA   ColB     ColC
 4      1.4       1
 10     0.5       1
 1      2.3       1
 3      12.2      2
 8.8    8.5       2
 2      5.2       2
 0.6    0.33      2
 9      3         2
 4      144       3
 33     8         3

thank you for the help!

Andrej Kesely · Accepted Answer · 2020-11-02 19:02:21Z

1

df['ColC'] = (df['ColB'] > 10).cumsum() + 1
print(df)

Prints:

   ColA    ColB  ColC
0   4.0    1.40     1
1  10.0    0.50     1
2   1.0    2.30     1
3   3.0   12.20     2
4   8.8    8.50     2
5   2.0    5.20     2
6   0.6    0.33     2
7   9.0    3.00     2
8   4.0  144.00     3
9  33.0    8.00     3

answered Nov 2, 2020 at 19:02

Andrej Kesely

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2 Comments

dmd7 Over a year ago

Thanks for your comment. This works but I forgot to add that I have another column that I will need to groupby then use this function. How can I groupby another column and apply this function?

Andrej Kesely Over a year ago

@dmd7 you can do df['ColC'] = df.groupby('<column name>')['ColB'].transform(lambda x: (x > 10).cumsum()+1)

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