Python: extracting datetime to year, month, and day result in float

Question

My data has a datetime index like this 2016-11-05 23:40:00.
I want to extract the datetime elements into three new columns of the year, month, and day. I use the following

import datetime as dt
df['year'] = df.index.year
df['month'] = df.index.month
df['day'] = df.index.day

But the results are in float

year    month   day
2016.0  11.0    5.0

I want

year    month   day
2016    11      5

Any help is appreciated.

Answer 1

I think reason for floats are missing values, so if use pandas 0.24+ is possible use Nullable Integer Data Type:

df['year'] = df.index.year.astype('Int64')
df['month'] = df.index.month.astype('Int64')
df['day'] = df.index.day.astype('Int64')

Answer 2

Just use astype:

import datetime as dt
df['year'] = df.index.year.astype(int)
df['month'] = df.index.month.astype(int)
df['day'] = df.index.day.astype(int)

If there are Nan's then use errors parameter:

df['year'] = df.index.year.astype(int, errors='ignore')

This will return nans for the columns with null index

Answer 3

convert it on int

import datetime as dt
df['year'] = int(df.index.year)
df['month'] = int(df.index.month)
df['day'] = int(df.index.day)

Answer 4

Or if you have a lot of columns, easiest may well be after all the code for constructing data-frame:

df = df.astype(int)