Python:将小时添加到 pandas 时间戳
Python: Adding hours to pandas timestamp
我将一个 csv 文件读入 pandas 数据框 df
并得到以下信息:
df.columns
Index([u'TDate', u'Hour', u'SPP'], dtype='object')
>>> type(df['TDate'][0])
<class 'pandas.tslib.Timestamp'>
type(df['Hour'][0])
<type 'numpy.int64'>
>>> type(df['TradingDate'])
<class 'pandas.core.series.Series'>
>>> type(df['Hour'])
<class 'pandas.core.series.Series'>
Hour
和 TDate
列都有 100 个元素。我想在TDate中加入Hour对应的元素
我尝试了以下方法:
import pandas as pd
from datetime import date, timedelta as td
z3 = pd.DatetimeIndex(df['TDate']).to_pydatetime() + td(hours = df['Hour'])
但我收到错误消息,因为 td 似乎没有将数组作为参数。如何将 Hour
的每个元素添加到 TDate
.
的相应元素
我想你可以添加到第 TDate
列 Hour
转换 to_timedelta
与 unit='h'
:
df = pd.DataFrame({'TDate':['2005-01-03','2005-01-04','2005-01-05'],
'Hour':[4,5,6]})
df['TDate'] = pd.to_datetime(df.TDate)
print (df)
Hour TDate
0 4 2005-01-03
1 5 2005-01-04
2 6 2005-01-05
df['TDate'] += pd.to_timedelta(df.Hour, unit='h')
print (df)
Hour TDate
0 4 2005-01-03 04:00:00
1 5 2005-01-04 05:00:00
2 6 2005-01-05 06:00:00
我将一个 csv 文件读入 pandas 数据框 df
并得到以下信息:
df.columns
Index([u'TDate', u'Hour', u'SPP'], dtype='object')
>>> type(df['TDate'][0])
<class 'pandas.tslib.Timestamp'>
type(df['Hour'][0])
<type 'numpy.int64'>
>>> type(df['TradingDate'])
<class 'pandas.core.series.Series'>
>>> type(df['Hour'])
<class 'pandas.core.series.Series'>
Hour
和 TDate
列都有 100 个元素。我想在TDate中加入Hour对应的元素
我尝试了以下方法:
import pandas as pd
from datetime import date, timedelta as td
z3 = pd.DatetimeIndex(df['TDate']).to_pydatetime() + td(hours = df['Hour'])
但我收到错误消息,因为 td 似乎没有将数组作为参数。如何将 Hour
的每个元素添加到 TDate
.
我想你可以添加到第 TDate
列 Hour
转换 to_timedelta
与 unit='h'
:
df = pd.DataFrame({'TDate':['2005-01-03','2005-01-04','2005-01-05'],
'Hour':[4,5,6]})
df['TDate'] = pd.to_datetime(df.TDate)
print (df)
Hour TDate
0 4 2005-01-03
1 5 2005-01-04
2 6 2005-01-05
df['TDate'] += pd.to_timedelta(df.Hour, unit='h')
print (df)
Hour TDate
0 4 2005-01-03 04:00:00
1 5 2005-01-04 05:00:00
2 6 2005-01-05 06:00:00