python pandas – dividing column by another column

Question

I’m trying to add a column to my DataFrame which is the product of division of two other columns, like so:

df['$/hour'] = df['$']/df['hours']

This works fine, but if the value in ['hours'] is less than 1, then the ['$/hour'] value is greater than the value in ['$'], which is not what I want.

Is there a way of controlling the operation so that if ['hours'] < 1 then df['$/hour'] = df['$']?

Asked By: Charon

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Source

Answer 1

df['$/hour'] = df.apply(lambda x: x['$'] if x['$'] < 1 else x['$']/x['hours'], axis=1)

Answered By: Brian Huey

Answer 2

You can use numpy.where:

print df
    hours  $
0       0  8
1       0  9
2       0  9
3       3  6
4       6  4
5       3  7
6       5  5
7      10  1
8       9  3
9       3  6
10      5  4
11      5  7

df['$/hour'] = np.where(df['hours'] < 1, df['hours'], df['$']/df['hours'])
print df
    hours  $    $/hour
0       0  8  0.000000
1       0  9  0.000000
2       0  9  0.000000
3       3  6  2.000000
4       6  4  0.666667
5       3  7  2.333333
6       5  5  1.000000
7      10  1  0.100000
8       9  3  0.333333
9       3  6  2.000000
10      5  4  0.800000
11      5  7  1.400000

Answered By: jezrael

Answer 3

You can also filter and select the indexes to set with DataFrame.loc:

df['$/hour'].loc[df['hours']>=1] = df['$']/df['hours']
df['$/hour'].loc[df['hours']<1] = df['$']

Answered By: agold

Answer 4

You can also use mask:

df['$/hour'] = (df['$'] / df['hours']).mask(df['hours'] < 1, df['$'])

If the condition df['hours'] < 1 is met the values from column $ are taken, otherwise $ is divided by hours.

Answered By: rachwa

python pandas – dividing column by another column

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