多指标df的变化指标

Question

我有以下index1年份和index2类型的df。

                data
     year type  

     2017 A     1.23
          B     5.51
     2018 A     1.53
          B     0.89

我想重命名索引年，使其表示年份0和年份1。

我尝试了以下几点：

    index_years = []
    for i in range(len(df.index.levels[0])):
        index_years.append("Year " + str(i))
    df.index.levels[0] = index_years

但我得到了以下错误：

ERROR GIVEN: 'FrozenList' does not support mutable operations.

然后我试了一下

    pd.MultiIndex.from_tuples([(x[0].apply("Year " + str(i) for i in range(len(df.index.levels[0]))), x[1]) for x in df.index])

但是它给出了一个错误"int" boject is not subscriptible

我想得到的结果是：

                    data

     year    type  

     Year 0   A     1.23
              B     5.51
     Year 1   A     1.53
              B     0.89

Answer 1

您已经间接地这样做了，参见here (顺便说一句，这是对其他问题的重复)

# remove 'year' and 'type' from index
df = df.reset_index()
# do changes to year
df.year = df.year.apply(lambda x: 'Year %i' %(x-2017))
# set 'year' and 'type'as indices
df = df.set_index(['year', 'type'])

Answer 2

有一个名为index.names的属性，您可以使用它来设置名称。下面是一个示例：

import pandas as pd
df = pd.DataFrame({'year':['2017','2017', '2018', '2018'], 
                   'type':['A', 'B', 'A', 'B'], 
                   'data':[1.23,5.51, 1.53, 0.89]
                 })
df = df.set_index(['year', 'type'])

# Here is the code to modify the DataFrame as you wanted
df = df.reset_index() #reset index so you can access the year as a column and have an integer index you can use
df.year = df.index.map(lambda x: f'year {x}') #map using a function to create new values for year that you need

df = df.set_index(['year', 'type']) #recreate the multilevel index
df