CODEWITHSUNDEEP
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Stacey
Stacey

Reputation: 5107

Dividing data-frame columns and getting ZeroDivisionError: float division by zero

I have a data frame dayData which includes the columns the following columns 'ratio' and 'first_power' with the following types:

Name: ratio, dtype: float64 first power  
Name: first_power, dtype: object average power

  ratio   average_power
0     5            8.0
1     6            4.0
2     7            0.0
3     0            6.0
4     8            5.0
5     9            4.0
6     8            2.0
7     7            8.0
8     6            0.0
9     5            5.0
10    8            4.0

The next stage in my process is to create a second step power by dividing the 2 columns using the following formula:

dayData["second_step_power"] = np.where(dayData.average_power == 0.0, 0, dayData.first_power/dayData.average_power)

Obviously you can't divide by zero so in the event the average_power is zero I am trying to set the second_step_power to be 0, however I get the error:

ZeroDivisionError: float division by zero

What is the correct way of handling zeros?

My ideal output would be:

  ratio   average_power   second_step_power
0     5            8.0                0.625
1     6            4.0                1.500
2     7            0.0                0.000
3     0            6.0                0.000
4     8            5.0                1.600
5     9            4.0                2.250
6     8            2.0                4.000
7     7            8.0                0.875
8     6            0.0                0.000
9     5            5.0                1.000
10    8            4.0                2.000

Upvotes: 2

Views: 752

Answers (1)

Alexander
Alexander

Reputation: 109546

You can initially set all values to zero, then create a mask locating all rows with a valid denominator, i.e. where power is greater than zero (gt(0)). Finally, use the mask together with loc to calculate second_step_power.

df['second_step_power'] = 0
mask = df.average_power.gt(0)
df.loc[mask, 'second_step_power'] = \
    df.loc[mask, 'first_power'] / df.loc[mask, 'average_power']

Upvotes: 4

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