Subtraction if condition for Pandas dataframe

Question

I have temperature data that looks like this:

Date        State  Temperature (F)
2018-10-6   AL     15
2018-10-7   AL     45
2018-10-8   AL     67
2018-10-9   AL     25
2018-10-10  AL     55
2018-10-11  AL     77
.
.

I'd like to give a conditional statement that calculates a simple subtraction that creates a new column like this:

if df[Temperature, i] < 65:
     df[Calculation, i] = 65 - df[Temperature, i]
else:
     df[Calculation, i] = 0

So the output would be:

Date        State  Temperature (F)   Calculation
2018-10-6   AL     15                0
2018-10-7   AL     45                0
2018-10-8   AL     67                2
2018-10-9   AL     25                0
2018-10-10  AL     55                0
2018-10-11  AL     77                12
.
.

I'm not sure how to simply iterate over the column with this type of loop.

Is there an easy way to do this?

You don't iterate, you might as well be using base Python otherwise. `df['Calculation'] = np.where(df['Temperature'] < 65, 65 - df['Temperature'], 0)` — roganjosh, Jan 07 '19 at 20:48

score 3 · Accepted Answer · edited May 14 '21 at 13:43

IIUC clip_lower

df['Temperature(F)'].sub(65).clip_lower(0)
Out[377]: 
0     0
1     0
2     2
3     0
4     0
5    12
Name: Temperature(F), dtype: int64

UPDATE 14.05.2021:

instead of clip_lower(0) the documentation for pandas 0.25.3 https://pandas.pydata.org/pandas-docs/version/0.25.3/reference/api/pandas.DataFrame.clip_lower.html states:

Deprecated since version 0.24.0: Use clip(lower=threshold) instead.

so the answer would be:

df['Temperature (F)'].sub(65).clip(lower = 0)
Out[6]:
0     0
1     0
2     2
3     0
4     0
5    12
Name: Temperature (F), dtype: int64

Subtraction if condition for Pandas dataframe

1 Answers1