将 pandas.tslib.Timestamp 转换为日期时间 python

Converting pandas.tslib.Timestamp to datetime python

提问by user1234440

I have a dftime series. I extracted the indexes and want to convert them each to datetime. How do you go about doing that? I tried to use pandas.to_datetime(x)but it doesn't convert it when I check after using type()

我有一个df时间序列。我提取了索引并希望将它们每个都转换为datetime. 你打算怎么做？我尝试使用pandas.to_datetime(x)但在使用后检查时它没有转换它type()

采纳答案by GoingMyWay

Just try to_datetime()

试试to_datetime()

>>> import pandas as pd
>>> t = pd.tslib.Timestamp('2016-03-03 00:00:00')
>>> type(t)
pandas.tslib.Timestamp
>>> t.to_datetime()
datetime.datetime(2016, 3, 3, 0, 0)
>>> t.to_pydatetime()
datetime.datetime(2016, 3, 3, 0, 0)

Change to datetime.datetype

更改为datetime.date类型

>>> t.date()
datetime.date(2016, 3, 3)

update

更新

Thanks, @mjp, to_datetime()will be deprecated in the future, use to_pydatetime()instead!

谢谢，@ mjp，to_datetime()将来会被弃用，请to_pydatetime()改用！

In [4]: t.to_datetime()
/Users/qiuwei/Library/Python/2.7/lib/python/site-packages/IPython/core/interactiveshell.py:2881: FutureWarning: to_datetime is deprecated. Use self.to_pydatetime()
  exec(code_obj, self.user_global_ns, self.user_ns)
Out[4]: datetime.datetime(2016, 3, 3, 0, 0)

回答by aikramer2

Assuming you are trying to convert pandas timestamp objects, you can just extract the relevant data from the timestamp:

假设您正在尝试转换 pandas 时间戳对象，您可以从时间戳中提取相关数据：

#Create the data
data = {1: tslib.Timestamp('2013-01-03 00:00:00', tz=None), 2: tslib.Timestamp('2013-01-04 00:00:00', tz=None), 3: tslib.Timestamp('2013-01-03 00:00:00', tz=None)}

#convert to df
df = pandas.DataFrame.from_dict(data, orient = 'index')
df.columns = ['timestamp']

#generate the datetime
df['datetime'] = df['timestamp'].apply(lambda x: datetime.date(x.year,x.month,x.day))

Of course, if you need seconds, minutes, and hours, you can include those as arguments for the function datetime.datetime as well.

当然，如果您需要秒、分和小时，您也可以将它们作为函数 datetime.datetime 的参数包含在内。

回答by sharon

I had the same issue, and tried the solution from @aikramer2, to add a column to my df of type 'datetime.datetime', but again i got a pandas data type:

我遇到了同样的问题，并尝试了@aikramer2 的解决方案，将一列添加到我的“datetime.datetime”类型的 df 中，但我再次得到了一个 Pandas 数据类型：

#libraries used -
import pandas as pd
import datetime as dt

#loading data into a pandas df, from a local file. note column [1] contains a datetime column -
savedtweets = pd.read_csv('/Users/sharon/Documents/ipython/twitter_analysis/conftwit.csv', sep='\t', 
                      names=['id', 'created_at_string', 'user.screen_name', 'text'], 
                      parse_dates={"created_at" : [1]})
print int(max(savedtweets['id'])) #535073416026816512
print type(savedtweets['created_at'][0]) # result is <class 'pandas.tslib.Timestamp'>

# add a column specifically using datetime.datetime library -
savedtweets['datetime'] = savedtweets['created_at'].apply(lambda x: dt.datetime(x.year,x.month,x.day))
print type(savedtweets['datetime'][0]) # result is <class 'pandas.tslib.Timestamp'>

i suspect pandas df cannot store a datetime.datetime data type. I got success when i made a plain python list to store the datetime.datetime values:

我怀疑 pandas df 无法存储 datetime.datetime 数据类型。当我制作一个简单的 python 列表来存储 datetime.datetime 值时，我获得了成功：

savedtweets = pd.read_csv('/Users/swragg/Documents/ipython/twitter_analysis/conftwit.csv', sep='\t', 
                      names=['id', 'created_at_string', 'user.screen_name', 'text'], 
                      parse_dates={"created_at" : [1]})
print int(max(savedtweets['id'])) #535073416026816512
print type(savedtweets['created_at'][0]) # <class 'pandas.tslib.Timestamp'>
savedtweets_datetime= [dt.datetime(x.year,x.month,x.day,x.hour,x.minute,x.second) for x in savedtweets['created_at']]
print savedtweets_datetime[0] # 2014-11-19 14:13:38
print savedtweets['created_at'][0] # 2014-11-19 14:13:38
print type(dt.datetime(2014,3,5,2,4)) # <type 'datetime.datetime'>
print type(savedtweets['created_at'][0].year) # <type 'int'>
print type(savedtweets_datetime) # <type 'list'>

回答by Kostyantyn

import time
time.strftime("%H:%M",  time.strptime(str(x), "%Y-%m-%d %H:%M:%S"))

Note: x should be pandas.tslib.Timestamp (as it is in the question)

注意：x 应该是 pandas.tslib.Timestamp （因为它在问题中）

回答by giovannivl

This works for me, to create date for insertin MySQL, please try:

这对我insert有用，要在 MySQL 中创建日期，请尝试：

pandas_tslib = pandas_tslib.to_pydatetime()
pandas_tslib = "'" + pandas_tslib.strftime('%Y-%m-%d') + "'"

回答by Morris wong

Just an update to the question, I have tried the most upvoted answer, and it gives me this warning

只是对问题的更新，我尝试了最受好评的答案，它给了我这个警告

usr/local/lib/python3.5/dist-packages/IPython/core/interactiveshell.py:2910: FutureWarning: to_datetime is deprecated. Use self.to_pydatetime() exec(code_obj, self.user_global_ns, self.user_ns)

usr/local/lib/python3.5/dist-packages/IPython/core/interactiveshell.py:2910: FutureWarning: to_datetime 已弃用。使用 self.to_pydatetime() exec(code_obj, self.user_global_ns, self.user_ns)

And suggest me to use to_pydatetime()

并建议我使用to_pydatetime()

For example

例如

sample = Timestamp('2018-05-02 10:08:54.774000')

sample = Timestamp('2018-05-02 10:08:54.774000')

sample.to_datetime()will return datetime.datetime(2018, 4, 30, 10, 8, 54, 774000)

sample.to_datetime()将返回 datetime.datetime(2018, 4, 30, 10, 8, 54, 774000)

回答by smontanaro

You can convert a Timestamp to a Python datetime object with to_pydatetime(), but it seems that when applied to an entire column that conversion is thwarted:

您可以使用 to_pydatetime() 将时间戳转换为 Python 日期时间对象，但似乎当应用于整个列时，转换会受阻：

>>> ts = pd.tslib.Timestamp.now()
>>> type(ts)
<class 'pandas._libs.tslibs.timestamps.Timestamp'>
>>> type(ts.to_pydatetime())
<class 'datetime.datetime'>
>>> df = pd.DataFrame({"now": [datetime.datetime.utcnow()] * 10})
>>> type(df['now'].iloc[0])
<class 'pandas._libs.tslibs.timestamps.Timestamp'>
>>> df['now2'] = df['now'].apply(lambda dt: dt.to_pydatetime())
>>> type(df['now2'].iloc[0])
<class 'pandas._libs.tslibs.timestamps.Timestamp'>

Not sure what to make of that. (There are some situations where Pandas' Timestamp object isn't a perfect replacement for Python's datetime object, and you want the real thing.)

不知道该怎么做。（在某些情况下，Pandas 的 Timestamp 对象不是 Python 的 datetime 对象的完美替代品，而您想要真实的东西。）

回答by gies0r

As an alternative solution if you have two separate fields(one for date; one for time):

如果您有两个单独的字段（一个用于日期；一个用于时间），作为替代解决方案：

Convert to datetime.date

转换为datetime.date

df['date2'] = pd.to_datetime(df['date']).apply(lambda x: x.date())

Convert to datetime.time

转换为datetime.time

df['time2'] = pd.to_datetime(df['time']).apply(lambda x: x.time())

Afterwards you can combine them:

之后你可以组合它们：

df['datetime'] = df.apply(lambda r : pd.datetime.combine(r['date2'],r['time2']),1)

Adapted this post

改编了这篇文章

回答by Francesco Boi

In my case I could not get a correct output even when specifying the format: I used to get always the year 1970.

就我而言，即使指定格式，我也无法获得正确的输出：我过去总是得到 1970 年。

Actually what solved my problem was to specify the unitparameter to the function since my timestamps have seconds granularity:

实际上，解决我的问题的是指定unit函数的参数，因为我的时间戳具有秒粒度：

df_new = df
df_new['time'] = pandas.to_datetime(df['time'], unit='s')