Using assign and lambda to combine year and month columns into 1 date column

Question

I have an Excel file with the following columns that I read into a pandas dataframe:

Year    Month   Day   Hour
2012    1       1     0
2012    1       1     1
2012    1       1     2
2012    1       1     3`

I'm trying to combine these 3 columns into a datetime column using the following code:

df1 = df.assign(Dt = lambda row: datetime.datetime(row['Year'].astype(int), row['Month'].astype(int)...))

This code gives the following error: Type Error: Cannot convert the series to (Type 'int')

I know I can just combine these columns into a string and use strptime to convert to datetime . HoweverI i want to try to understand what i'm doing wrong with assign and lambda here.

Answer 1

All your columns are appropriately named to use pd.to_datetime directly on the df

df.assign(Dt=pd.to_datetime(df))

   Year  Month  Day  Hour                  Dt
0  2012      1    1     0 2012-01-01 00:00:00
1  2012      1    1     1 2012-01-01 01:00:00
2  2012      1    1     2 2012-01-01 02:00:00
3  2012      1    1     3 2012-01-01 03:00:00

which simplifies to:

df.assign(Dt=pd.to_datetime)

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From the docs

The passed callable is not called once per row as you think.