CODEWITHSUNDEEP
pythonpandasnumpydata-science
StackUser
StackUser

Reputation: 475

Datetime to seasons

I have an example data as :

datetime.            column1

2021-04-01 01:00.     11
2021-04-05 02:00.     10
2021-04-12 03:00.      1
2021-04-11 04:00.      5
2021-04-07 05:00.      20

I would like to create a new column called season which outputs cooling season if the datetime values is between the month of May and September, while heating season if the datetime values are between october and April. The example output should look like this:

datetime.            column1.  seasons

2021-01-01 01:00.     11.       Heating season
2021-05-01 02:00.     10.       Cooling season
2021-12-01 03:00.      1.       Heating season
2021-11-01 04:00.      5.       Heating season
2021-07-01 05:00.      20.      Cooling season

Upvotes: 1

Views: 699

Answers (2)

Utsav
Utsav

Reputation: 5918

There are many ways,

df['datetime'] = pd.to_datetime(df.datetime)

With np.select with specific conditions for months

conditions = [
    df.datetime.dt.month.isin(np.arange(5,10)),
    (df.datetime.dt.month.isin(np.arange(1,5))) | (df.datetime.dt.month.isin(np.arange(10,13))),
]
choices = ['Cooling season','Heating season']
df['seasons'] = np.select(conditions, choices)
df

With np.select with a default

conditions = [
    df.datetime.dt.month.isin(np.arange(5,10)),
]
choices = ['Cooling season']
df['seasons'] = np.select(conditions, choices, default='Heating season')
df

With np.where

df['seasons'] = np.where(df.datetime.dt.month.isin(np.arange(5,10)), 'Cooling season','Heating season')
df

Output

    datetime            column1     seasons
0   2021-01-01 01:00:00 11      Heating season
1   2021-05-01 02:00:00 10      Cooling season
2   2021-12-01 03:00:00 1       Heating season
3   2021-11-01 04:00:00 5       Heating season
4   2021-07-01 05:00:00 20      Cooling season

Upvotes: 3

Corralien
Corralien

Reputation: 120439

df["seasons"] = np.where((df["datetime"].dt.month >= 5) 
                          & (df["datetime"].dt.month <= 9),
                         "Cooling season", "Heating season")

>>> df
             datetime  column1         seasons
0 2021-01-01 01:00:00       11  Heating season
1 2021-05-05 02:00:00       10  Cooling season
2 2021-12-12 03:00:00        1  Heating season
3 2021-11-11 04:00:00        5  Heating season
4 2021-07-07 05:00:00       20  Cooling season

Upvotes: 1

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