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pythonpandasdataframecountstatistics
JodeCharger100
JodeCharger100

Reputation: 1059

Count the number of columns that have a value above a threshold

Assuming I have the following toy model, df:

product    customer1    customer2    customer3      
apple           40           110          120
banana         200           150          180
coconut         10             5           25
daq            120            10           30
eclair          45           190           35

I would like to add a column to df that counts the number of customers that bought at least a hundred of the items listed:

product    customer1    customer2    customer3   atleast100    
apple           40           110          120             2
banana         200           150          180             3
coconut         10             5           25             0
daq            120            10           30             1
eclair          45           190           35             1

Upvotes: 1

Views: 119

Answers (2)

cottontail
cottontail

Reputation: 23321

Among the customer columns, count the number of values greater or equal to 100 in each row using ge().sum().

df['atleast100'] = df.filter(like='customer').ge(100).sum(axis=1)
print(df)

   product  customer1  customer2  customer3  atleast100
0    apple         40        110        120           2
1   banana        200        150        180           3
2  coconut         10          5         25           0
3      daq        120         10         30           1
4   eclair         45        190         35           1

Upvotes: 5

Rabinzel
Rabinzel

Reputation: 7923

Try this:

df['atleast100'] = df[df.columns[1:]].gt(100).sum(axis=1)
print(df)

   product  customer1  customer2  customer3  atleast100
0    apple         40        110        120           2
1   banana        200        150        180           3
2  coconut         10          5         25           0
3      daq        120         10         30           1
4   eclair         45        190         35           1

Upvotes: 3

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