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pythondatepandas
Pythonista anonymous
Pythonista anonymous

Reputation: 8950

Python pandas: create a dataframe of dates from existing columns

I have a pandas dataframe with a column for years and one for months. How can I create a new date column based on these two (I can assume day = 15).

I tried the following:

import pandas as pd
import numpy as np
import datetime  

df = pd.DataFrame()
df['year'] = np.arange(2000,2010)

df['mydate']= datetime.date( df['year'].apply(lambda x: int(x)) , 1 , 1)

but I get this error message:

df['mydate']= datetime.date( df['year'].apply(lambda x: int(x)) , 1 , 1)   File "C:\Anaconda\lib\site-packages\pandas\core\series.py",

line 77, in wrapper "cannot convert the series to {0}".format(str(converter))) TypeError: cannot convert the series to

which I don't understand because I explictly convert x to int.

Thanks!

Upvotes: 0

Views: 5623

Answers (1)

Dov Grobgeld
Dov Grobgeld

Reputation: 4983

You can build another column based on the existing columns by using df.apply(fnc, axis=1).

In your case this becomes:

df = pd.DataFrame()
df['year'] = np.arange(2000,2010)
df['month'] = 6

df['date_time']= df.apply(lambda row :
                          datetime.date(row.year,row.month,15), 
                          axis=1)

Upvotes: 2

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