python datetime dataframe 如果缺少我想要的日期，则添加一些日期

Question

我有两个数据文件，并且都有不同的日期时间段。

如下图，第一个'Date'是从2013-10-14到2015-11-25，第二个'Date'是从2014-01-01到2015- 11-27.

如果我想把日期从 2013-10-14 设为 2015-11-27 并填空 np.nan，我需要在代码中做什么？

如果你知道怎么做或者有什么想法，请告诉我。

dvv :  Date
2013-10-14   -0.038875
2013-10-15   -0.038875
2013-10-16   -0.038875
2013-10-17   -0.038875
2013-10-18   -0.038875
  
2015-11-21    0.081939
2015-11-22   -0.097986
2015-11-23   -0.096201
2015-11-24   -0.033913
2015-11-25   -0.050553
Name: dvv, Length: 773, dtype: float64
           Stations Sensor      EL      GL  Pressure   Temp     EC  Barometa
Date                                                                        
2014-01-01    JRee3    S11     NaN     NaN       NaN    NaN    NaN       NaN
2014-01-02    JRee3    S11     NaN     NaN       NaN    NaN    NaN       NaN
2014-01-02    JRee3    S11     NaN     NaN       NaN    NaN    NaN       NaN
2014-01-04    JRee3    S11     NaN     NaN       NaN    NaN    NaN       NaN
2014-01-05    JRee3    S11     NaN     NaN       NaN    NaN    NaN       NaN
            ...    ...     ...     ...       ...    ...    ...       ...
2015-11-23    JRee3    S11  213.46  202.21     99.83  14.22  105.0   1008.13
2015-11-24    JRee3    S11  213.36  202.31     99.73  14.22  105.0   1008.36
2015-11-25    JRee3    S11  213.34  202.33     99.71  14.22  105.0   1004.40
2015-11-26    JRee3    S11  213.30  202.37     99.67  14.22  105.0   1003.13
2015-11-27    JRee3    S11  213.24  202.44     99.61  14.21  105.0   1011.00
[696 rows x 8 columns]

Answer 1

您可以通过这种方式生成新日期（用足够的数字替换句点）：

days = pd.date_range('14/10/2013', periods=365, freq='D')

你会得到类似这样的东西，你可以将它添加到你的数据框中：

DatetimeIndex(['2013-10-14', '2013-10-15', '2013-10-16', '2013-10-17',
               '2013-10-18', '2013-10-19', '2013-10-20', '2013-10-21',
               '2013-10-22', '2013-10-23',
               ...
               '2014-10-04', '2014-10-05', '2014-10-06', '2014-10-07',
               '2014-10-08', '2014-10-09', '2014-10-10', '2014-10-11',
               '2014-10-12', '2014-10-13'],
              dtype='datetime64[ns]', length=365, freq='D')

Answer 2

假设日期中没有缺失值，那么您可以简单地利用 pandas.date_range 和 outer 连接。

下面的玩具示例：

import pandas as pd
dates1 = pd.date_range('2013-10-14', '2015-11-25', freq='D')
dates2 = pd.date_range('2014-01-01', '2015-11-27', freq='D')

df1 = pd.DataFrame(data=[1]*len(dates1), index=dates1, columns=['var'])
df2 = pd.DataFrame(data=[2]*len(dates2), index=dates2, columns=['var'])

df1.merge(df2, left_index=True, right_index=True, how='outer')

python datetime dataframe 如果缺少我想要的日期，则添加一些日期

python datetime dataframe add some dates if there are lack of dates than I want

python

datetime

period

dataframe

pandas