按索引和列排序

Question

我正在尝试按索引和列排序，但无济于事。

部分数据集

            ID         Element  Data_Value
Date            
2005-01-01  USW00004848 TMIN    0
2005-01-01  USC00207320 TMAX    150
2005-01-01  USC00207320 TMIN    -11
2005-01-01  USW00014833 TMIN    -44
2005-01-01  USW00014833 TMAX    33

索引列

DatetimeIndex(['2005-01-01', '2005-01-01', '2005-01-01', '2005-01-01',
               '2005-01-01', '2005-01-01', '2005-01-01', '2005-01-01',
               '2005-01-01', '2005-01-01',
               ...
               '2015-12-31', '2015-12-31', '2015-12-31', '2015-12-31',
               '2015-12-31', '2015-12-31', '2015-12-31', '2015-12-31',
               '2015-12-31', '2015-12-31'],
              dtype='datetime64[ns]', name='Date', length=165002, freq=None)

我的尝试

df2 = df2.rename_axis(df2.index).sort_values(by = [df2.index, 'ID'], ascending = [False, True])

上面的输出： ValueError：新名称的长度必须为 1，得到 165002

df2 = df2.rename_axis("Date").sort_values(by = ["Date", "ID"], ascending = [False, True])

上面的输出： KeyError：'Date'

df2 = df2.sort_values(by = [df2.index, 'ID'], ascending = [False, True])

上面的输出： KeyError："DatetimeIndex(['2005-01-01', '2005-01-01', '2005-01-01', '2005-01-01',\n '2005-01-01', '2005-01-01', '2005-01-01', '2005-01-01',\n '2005-01-01', '2005-01-01',\n ...\n '2015-12-31', '2015-12-31', '2015-12-31', '2015-12-31',\n '2015-12-31', '2015-12-31', '2015-12-31', '2015-12-31',\n '2015-12-31', '2015-12-31'],\n dtype='datetime64[ns]', name='Date', length=165002, freq=None) not in index"

df2 = df2.sort_values(by = ["Date", "ID"], ascending = [False, True])

上面的输出： KeyError：'Date'

df2 = df2.sort_values(by = [df2.index.Date, 'ID'], ascending = [False, True])

上面的输出： AttributeError: 'DatetimeIndex' object has no attribute 'Date'

Answer 1

在上一个 pandas 版本中 0.23+ 这个工作很好：

print (df2.index)
DatetimeIndex(['2005-01-01', '2005-01-01', '2005-01-01', '2005-01-01',
               '2005-01-01'],
              dtype='datetime64[ns]', name='Date', freq=None)


df2 = df2.sort_values(by = ["Date", "ID"], ascending = [False, True])
print (df2)
                     ID Element  Data_Value
Date                                       
2005-01-01  USC00207320    TMAX         150
2005-01-01  USC00207320    TMIN         -11
2005-01-01  USW00004848    TMIN           0
2005-01-01  USW00014833    TMIN         -44
2005-01-01  USW00014833    TMAX          33

另一个在一些较旧的 pandas 版本中也有效的解决方案是首先将 DatetimeIndex 转换为列，然后排序并转换回来：

df2 = (df2.reset_index()
          .sort_values(by = ["Date", "ID"], ascending = [False, True])
          .set_index('Date'))

感谢@Alexander 的选择：

df2 = (df.set_index('ID', append=True)
         .sort_index(ascending=[False, True])
         .reset_index('ID'))

print (df2)
                     ID Element  Data_Value
Date                                       
2005-01-01  USC00207320    TMAX         150
2005-01-01  USC00207320    TMIN         -11
2005-01-01  USW00004848    TMIN           0
2005-01-01  USW00014833    TMIN         -44
2005-01-01  USW00014833    TMAX          33

按索引和列排序

Sort by index and column

python

sorting

datetime

pandas

datetimeindex