熊猫: 将 Timestamp 转换为 datetime.date

我有一个时间戳数据的熊猫专栏

In [27]: train["Original_Quote_Date"][6]
Out[27]: Timestamp('2013-12-25 00:00:00')

如何检查这些对象与该类型的 datetime.date对象的等价性

datetime.date(2013, 12, 25)
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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)
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最佳答案

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

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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
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So, got this from an IBM coursera tutorial.

data['date'] = data['TimeStamp'].apply(lambda d: datetime.date.fromtimestamp(d))
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I've used the way recommended by Filomeno Gonzalez, albeit with a slight twist:

 data['date'] = data['date'].apply(lambda x: x.date())
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If I have a pandas DataFrame with timestamp column (1546300800000, 1546301100000, 1546301400000, 1546301700000, 1546302000000) and I want to convert this into date time format

import datetime


df['date'] = df['date'].apply(lambda x: datetime.datetime.fromtimestamp(x/1000.0))

This will return a column with the format 2019-01-01 00:00:00, 2019-01-01 00:05:00, 2019-01-01 00:10:00, 2019-01-01 00:15:00, 2019-01-01 00:20:00...etc

Dividing by 1000 to convert from ms to s as explained here


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