Pandas: Convert Timestamp to datetime.date

Solution 1:

Use the .date method:

In [11]: t = pd.Timestamp('2013-12-25 00:00:00')

In [12]: t.date()
Out[12]: datetime.date(2013, 12, 25)

In [13]: t.date() == datetime.date(2013, 12, 25)
Out[13]: True

To compare against a DatetimeIndex (i.e. an array of Timestamps), you'll want to do it the other way around:

In [21]: pd.Timestamp(datetime.date(2013, 12, 25))
Out[21]: Timestamp('2013-12-25 00:00:00')

In [22]: ts = pd.DatetimeIndex([t])

In [23]: ts == pd.Timestamp(datetime.date(2013, 12, 25))
Out[23]: array([ True], dtype=bool)

Solution 2:

As of pandas 0.20.3, use .to_pydatetime() to convert any pandas.DateTimeIndex instances to Python datetime.datetime.

Solution 3:

You can convert a datetime.date object into a pandas Timestamp like this:

#!/usr/bin/env python3
# coding: utf-8

import pandas as pd
import datetime

# create a datetime data object
d_time = datetime.date(2010, 11, 12)

# create a pandas Timestamp object
t_stamp = pd.to_datetime('2010/11/12')

# cast `datetime_timestamp` as Timestamp object and compare
d_time2t_stamp = pd.to_datetime(d_time)

# print to double check
print(d_time)
print(t_stamp)
print(d_time2t_stamp)

# since the conversion succeds this prints `True`
print(d_time2t_stamp == t_stamp)

Solution 4:

Assume time column is in timestamp integer msec format

1 day = 86400000 ms

Here you go:

day_divider = 86400000

df['time'] = df['time'].values.astype(dtype='datetime64[ms]') # for msec format

df['time'] = (df['time']/day_divider).values.astype(dtype='datetime64[D]') # for day format