Question

数据帧如下（3项...原始数以百计）：

                    Log1     Date2      Log2    Date3       Log3
           Date1
          01.01.2000 1000     02.01.2000 2000    01.01.2000  3000
          02.01.2000 1050     03.01.2000 1950    02.01.2000  3020
          03.01.2000 1100     04.01.2000 2000    03.01.2000  3000

所需的前景，对齐日期：

                   Log1  Log2  Log3  
          Date     
      01.01.2000 1,000   nan 3,000
      02.01.2000 1,050 2,000 3,020
      03.01.2000 1,100 1,950 3,000
      04.01.2000   nan 2,000   nan

问题：如何按日期对齐？

数据框的简短示例：

                BBAS3   Data.1      PETR4   Data.2     TRSD      Data.3   JKHD
    Data                            
    2020-10-05  30.15   2020-10-05  19.91   2020-10-05  30.15   2020-10-05  19.91
    2020-10-02  29.71   2020-10-02  19.02   2020-10-02  29.71   2020-10-01  19.85
    2020-10-01  29.79   2020-10-01  19.85   2020-10-01  29.79   2020-09-30  19.61
    2020-09-30  29.62   2020-09-30  19.61   2020-09-30  29.62   2020-09-29  19.31
    2020-09-29  29.76   2020-09-29  19.31   2020-09-29  29.76   2020-09-28  19.63

Answer 1

如果输入数据具有DatetimeIndex循环不成对并配对列名称的想法，请一起创建Series和concat：

#convert Datetimeindex to column
df1 = df.reset_index()

zipped = zip(df1.columns[::2], df1.columns[1::2])
df1 = pd.concat([df1.set_index(a)[b] for a, b in zipped], axis=1)
df1.index = pd.to_datetime(df1.index)
df1 = df1.sort_index()

print (df1)
            BBAS3  PETR4   TRSD   JKHD
2020-09-28    NaN    NaN    NaN  19.63
2020-09-29  29.76  19.31  29.76  19.31
2020-09-30  29.62  19.61  29.62  19.61
2020-10-01  29.79  19.85  29.79  19.85
2020-10-02  29.71  19.02  29.71    NaN
2020-10-05  30.15  19.91  30.15  19.91

编辑：

#sample data generate error - because duplicated dates in soem column like here in Data
print (df)
             BBAS3      Data.1  PETR4      Data.2   TRSD      Data.3   JKHD
Data                                                                       
2020-10-05  200.00  2020-10-05  19.91  2020-10-05  30.15  2020-10-05  19.91
2020-10-05  100.00  2020-10-02  19.02  2020-10-02  29.71  2020-10-01  19.85
2020-10-01   29.79  2020-10-01  19.85  2020-10-01  29.79  2020-09-30  19.61
2020-09-30   29.62  2020-09-30  19.61  2020-09-30  29.62  2020-09-29  19.31
2020-09-29   29.76  2020-09-29  19.31  2020-09-29  29.76  2020-09-28  19.63

df1 = df.reset_index()

zipped = zip(df1.columns[::2], df1.columns[1::2])
df1 = pd.concat([df1.groupby(a)[b].sum() for a, b in zipped], axis=1)
df1.index = pd.to_datetime(df1.index)
df1 = df1.sort_index()

print (df1)
             BBAS3  PETR4   TRSD   JKHD
2020-09-28     NaN    NaN    NaN  19.63
2020-09-29   29.76  19.31  29.76  19.31
2020-09-30   29.62  19.61  29.62  19.61
2020-10-01   29.79  19.85  29.79  19.85
2020-10-02     NaN  19.02  29.71    NaN
2020-10-05  300.00  19.91  30.15  19.91

按日期对齐熊猫列数据框

1 个答案: