How to save or overwrite column values in a dataframe following for loop calculation

Question

I have 3 columns in my dataframe, date time and snowfall. The snowfall data needs transforming from kg m-3 s-1 to mm/day. To do this, I divide by the density of snow and multiply by seconds in the day. (n/70)*86400

I would like to do this by overwriting the the snowfall column in the dataframe with the calculation for plotting.

I have the loop function which transforms the values but will not append the result to the list (which is the basic version of what I was looking for), but ideally I would like to have it simply overwrite the column in the dataframe for ease of plotting.

def snowfallconverter(in1):
    snowfall_fix = []
    for ii in in1:
        snowfall_mm = (ii/70)*8600
        snowfall_fix.append(snowfall_mm)

The dataset looks like:

date       time     snowfall
01/11/2017 12:00:00 -4.43e-06
02/11/2017 12:00:00 -9.04e-08

Thank you in advance.

jezrael · Accepted Answer · 2019-07-13 14:35:20Z

1

Loop here is not necessary, divide and multiple column by scalars only:

df['snowfall_mm'] = df['snowfall'] / 70 * 8600
print (df)
         date      time      snowfall  snowfall_mm
0  01/11/2017  12:00:00 -4.430000e-06    -0.000544
1  02/11/2017  12:00:00 -9.040000e-08    -0.000011

Or overwrite same column:

df['snowfall'] = df['snowfall'] / 70 * 8600
print (df)
        date      time  snowfall
0  01/11/2017  12:00:00 -0.000544
1  02/11/2017  12:00:00 -0.000011

edited Jul 13, 2019 at 14:35

answered Jul 13, 2019 at 14:27

jezrael

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