按索引选择 MultiIndex 数据框中的行而不会丢失任何级别答案

【问题标题】：Selecting rows in a MultiIndex dataframe by index without losing any levels按索引选择 MultiIndex 数据框中的行而不会丢失任何级别
【发布时间】：2018-06-01 20:30:53
【问题描述】：

我想选择一个名为“Mid”的行，而不会丢失它的索引“Site”

以下代码显示了数据框：

m.commodity

                         price  max  maxperstep
Site  Commodity Type
Mid   Biomass   Stock     6.0  inf         inf
      CO2       Env       0.0  inf         inf
      Coal      Stock     7.0  inf         inf
      Elec      Demand    NaN  NaN         NaN
      Gas       Stock    27.0  inf         inf
      Hydro     SupIm     NaN  NaN         NaN
      Lignite   Stock     4.0  inf         inf
      Slack     Stock   999.0  inf         inf
      Solar     SupIm     NaN  NaN         NaN
      Wind      SupIm     NaN  NaN         NaN
North Biomass   Stock     6.0  inf         inf
      CO2       Env       0.0  inf         inf
      Coal      Stock     7.0  inf         inf
      Elec      Demand    NaN  NaN         NaN
      Gas       Stock    27.0  inf         inf
      Hydro     SupIm     NaN  NaN         NaN
      Lignite   Stock     4.0  inf         inf
      Slack     Stock   999.0  inf         inf
      Solar     SupIm     NaN  NaN         NaN
      Wind      SupIm     NaN  NaN         NaN
South Biomass   Stock     6.0  inf         inf
      CO2       Env       0.0  inf         inf
      Coal      Stock     7.0  inf         inf
      Elec      Demand    NaN  NaN         NaN
      Gas       Stock    27.0  inf         inf
      Hydro     SupIm     NaN  NaN         NaN
      Lignite   Stock     4.0  inf         inf
      Slack     Stock   999.0  inf         inf
      Solar     SupIm     NaN  NaN         NaN
      Wind      SupIm     NaN  NaN         NaN

期望的结果如下：

                         price  max  maxperstep
Site  Commodity Type
Mid   Biomass   Stock     6.0  inf         inf
      CO2       Env       0.0  inf         inf
      Coal      Stock     7.0  inf         inf
      Elec      Demand    NaN  NaN         NaN
      Gas       Stock    27.0  inf         inf
      Hydro     SupIm     NaN  NaN         NaN
      Lignite   Stock     4.0  inf         inf
      Slack     Stock   999.0  inf         inf
      Solar     SupIm     NaN  NaN         NaN
      Wind      SupIm     NaN  NaN         NaN

以下答案给出了预期的结果：

m.commodity.xs('Mid', drop_level=False)
m.commodity.loc[['Mid']]
m.commodity.loc['Mid', :, :]

请回答 MaxU、COLDSPEED 和 jezrael :)

【问题讨论】：

标签： python pandas dataframe multi-index

【解决方案1】：

您也可以使用带有双括号的loc。

df.loc[['Mid']]

                       price  max  maxperstep
Site Commodity Type
Mid  Biomass   Stock     6.0  inf         inf
     CO2       Env       0.0  inf         inf
     Coal      Stock     7.0  inf         inf
     Elec      Demand    NaN  NaN         NaN
     Gas       Stock    27.0  inf         inf
     Hydro     SupIm     NaN  NaN         NaN
     Lignite   Stock     4.0  inf         inf
     Slack     Stock   999.0  inf         inf
     Solar     SupIm     NaN  NaN         NaN
     Wind      SupIm     NaN  NaN         NaN

在你的情况下，我想应该是m.commodity.loc[['Mid']]。

当谈论 loc 与 ix 是后者已被弃用时，请使用 loc/iloc/iat/xs 进行索引。

ix 对传递的内容进行假设，并接受标签或位置。 loc 纯粹基于标签，而iloc 纯粹是索引（基于位置）

【讨论】：

简洁优雅！

【解决方案2】：

In [59]: df.loc['Mid', :, :]
Out[59]:
                       price  max  maxperstep
Site Commodity Type
Mid  Biomass   Stock     6.0  inf         inf
     CO2       Env       0.0  inf         inf
     Coal      Stock     7.0  inf         inf
     Elec      Demand    NaN  NaN         NaN
     Gas       Stock    27.0  inf         inf
     Hydro     SupIm     NaN  NaN         NaN
     Lignite   Stock     4.0  inf         inf
     Slack     Stock   999.0  inf         inf
     Solar     SupIm     NaN  NaN         NaN
     Wind      SupIm     NaN  NaN         NaN

【讨论】：

【解决方案3】：

相信你需要xs:

df = m.commodity.xs('Mid', drop_level=False)

print (df)
b                       price  max  maxperstep
Site Commodity Type                          
Mid  Biomass   Stock     6.0  inf         inf
     CO2       Env       0.0  inf         inf
     Coal      Stock     7.0  inf         inf
     Elec      Demand    NaN  NaN         NaN
     Gas       Stock    27.0  inf         inf
     Hydro     SupIm     NaN  NaN         NaN
     Lignite   Stock     4.0  inf         inf
     Slack     Stock   999.0  inf         inf
     Solar     SupIm     NaN  NaN         NaN
     Wind      SupIm     NaN  NaN         NaN

对于您来说，最好检查pandas iloc vs ix vs loc explanation 或Loc vs. iloc vs. ix vs. at vs. iat。

【讨论】：