I have a pandas column of Timestamp data
In [27]: train["Original_Quote_Date"][6] Out[27]: Timestamp('2013-12-25 00:00:00') How can check equivalence of these objects to datetime.date objects of the type
datetime.date(2013, 12, 25) 5 Answers
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) As of pandas 0.20.3, use .to_pydatetime() to convert any pandas.DateTimeIndex instances to Python datetime.datetime.
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) 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 So, got this from an IBM coursera tutorial.
data['date'] = data['TimeStamp'].apply(lambda d: datetime.date.fromtimestamp(d)) 
