Python 将日期时间索引透视到开始和结束列

Python 将日期时间索引透视到开始和结束列,python,pandas,datetime,Python,Pandas,Datetime,我在切换此数据时遇到问题: datetime transmission # 2019-07-12 00:03:06 124 2019-07-12 00:04:56 124 2019-07-12 00:20:10 125 2019-07-12 00:21:33 125 使用python模块创建如下格式: transmission # start end 124 2019-07-12

我在切换此数据时遇到问题:

datetime               transmission #
2019-07-12 00:03:06    124
2019-07-12 00:04:56    124
2019-07-12 00:20:10    125
2019-07-12 00:21:33    125
使用python模块创建如下格式:

transmission #   start                  end
124              2019-07-12 00:03:06    2019-07-12 00:04:56
125              2019-07-12 00:20:10    2019-07-12 00:21:33
起初,我认为我可以用一个轴来实现这一点,其中索引是transmission,值是
datetime
,但我似乎无法让它工作

print(df.pivot(index = 'ConnectDisconnect', columns=['start', 'end'], values='data_point_time'))
ConnectDisconnect是
变速箱
。我以为这会奏效,但它只是输出

Traceback (most recent call last):
  File "data.py", line 28, in <module>
    print(df.pivot(index = 'ConnectDisconnect', columns=['start', 'end'], values='data_point_time'))
  File "C:\Program Files (x86)\Python37-32\lib\site-packages\pandas\core\generic.py", line 5067, in __getattr__
    return object.__getattribute__(self, name)
AttributeError: 'Series' object has no attribute 'pivot'
回溯(最近一次呼叫最后一次):
文件“data.py”,第28行,在
打印(df.pivot(索引='ConnectDisconnect',列=['start','end'],值='data\u point\u time'))
文件“C:\Program Files(x86)\Python37-32\lib\site packages\pandas\core\generic.py”,第5067行,位于\uuu getattr__
返回对象。\uuuGetAttribute(self,name)
AttributeError:“Series”对象没有属性“pivot”
如果有人能帮我解决这个问题,我将不胜感激

df = pd.read_csv('test.csv', sep=r'\s{2,}', engine='python')
n = len(df.index)//2
x = df['datetime']
# drop the column of 'datetime'
df = df.drop('datetime', axis=1)
# Remove the duplicated row
df = df.drop_duplicates()
df.index=range(n) 
start = x[0::2]
start.index=range(n)
end = x[1::2]
end.index = range(n)
df['start'] =start 
df['end']=end 
print(df.to_string(index=False)) 
输出为

transmission #                start                  end
           124  2019-07-12 00:03:06  2019-07-12 00:04:56
           125  2019-07-12 00:20:10  2019-07-12 00:21:33

谢谢你,这很有效。如果将datetime作为索引列,则需要使用df.reset_index()来引用类似df['datetime']的列。