CODEWITHSUNDEEP
pythonpandasdatetime
Starbucks
Starbucks

Reputation: 1568

Adding Future Dates to DataFrame

How do I add future dates to a data frame? This datetime delta only adds deltas to adjacent columns.

import pandas as pd
from datetime import timedelta
df = pd.DataFrame({
    'date': ['2001-02-01','2001-02-02','2001-02-03', '2001-02-04'],
    'Monthly Value': [100, 200, 300, 400]
})

df["future_date"] = df["date"] + timedelta(days=4)

print(df)

  date                future_date
0 2001-02-01 00:00:00 2001-02-05 00:00:00
1 2001-02-02 00:00:00 2001-02-06 00:00:00
2 2001-02-03 00:00:00 2001-02-07 00:00:00
3 2001-02-04 00:00:00 2001-02-08 00:00:00

Desired dataframe:

  date                future_date
0 2001-02-01 00:00:00 2001-02-01 00:00:00
1 2001-02-02 00:00:00 2001-02-02 00:00:00
2 2001-02-03 00:00:00 2001-02-03 00:00:00
3 2001-02-04 00:00:00 2001-02-04 00:00:00
4                     2001-02-05 00:00:00
5                     2001-02-06 00:00:00
6                     2001-02-07 00:00:00
7                     2001-02-08 00:00:00

Upvotes: 1

Views: 3783

Answers (3)

Umar.H
Umar.H

Reputation: 23099

If I understand you correctly,

we can create a new dataframe using the min of your date, and max + 4 days.

we just concat this back using axis = 1.

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

fdates = pd.DataFrame(
    pd.date_range(df["date"].min(), df["date"].max() + pd.DateOffset(days=4))
,columns=['future_date'])

df_new = pd.concat([df,fdates],axis=1)

print(df_new[['date','future_date','Monthly Value']])

0 2001-02-01  2001-02-01          100.0
1 2001-02-02  2001-02-02          200.0
2 2001-02-03  2001-02-03          300.0
3 2001-02-04  2001-02-04          400.0
4        NaT  2001-02-05            NaN
5        NaT  2001-02-06            NaN
6        NaT  2001-02-07            NaN
7        NaT  2001-02-08            NaN

Upvotes: 1

Starbucks
Starbucks

Reputation: 1568

I found that this also works:

df.append(pd.DataFrame({'date': pd.date_range(start=df.date.iloc[-1], periods= 4, freq='d', closed='right')}))

Upvotes: 2

YOLO
YOLO

Reputation: 21719

You can do the following:

# set to timestamp
df['date'] = pd.to_datetime(df['date'])

# create a future date df
ftr =  (df['date'] + pd.Timedelta(4, unit='days')).to_frame()
ftr['Monthly Value'] = None

# join the future data
df1 = pd.concat([df, ftr], ignore_index=True)

        date Monthly Value
0 2001-02-01           100
1 2001-02-02           200
2 2001-02-03           300
3 2001-02-04           400
4 2001-02-05          None
5 2001-02-06          None
6 2001-02-07          None
7 2001-02-08          None

Upvotes: 3

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