pandas 基于年份索引的层次索引切片

Question

我有一个数据集，data1。我正在尝试使用基于 input

的索引切片

其中 data1 =

                  stats
gender  year    
        
women   2003    cellphone use
        2007    height
        2007    cigarette use
        2008    weight
        2009    cellphone use
        2015    cigarette use
        2018    weight
        2020    height

这是我对索引切片的尝试：

 isvalid_yr = False
 while not isvalid_yr:
     year_input = int(input("Input the year you want to compare data from: "))
     if year_input in data1.index.get_level_values('year') 
         idx = pd.IndexSlice
         isvalid_yr = True
         new_data1 = data1.loc(axis = 0)[idx[year_input:year_input], idx[:]]
     else:
          isvalid_yr = False
     try:
         if isvalid_yr ==True:
             pass
         else:
             raise ValueError("Year not in data!")
         except ValueError as err:
             print("Year not in data!")

它给了我这个我不想要的输出。

Empty DataFrame
Columns: [stats]
Index: []

我想要实现的最终期望输出如下所示

Input the year you want to compare data from: 2007

new_data1 =

的结果

                  stats
gender  year    

women   
        2007    height
        2007    cigarette use

Answer 1

使用xs获取DataFrame的横截面：

res = df.xs(2007, axis=0, level='year', drop_level=False)

res:

                     stats
gender year               
women  2007         height
       2007  cigarette use

有用户输入：

while True:
    try:
        year_input = int(
            input("Input the year you want to compare data from: ")
        )
        res = df.xs(year_input, axis=0, level='year', drop_level=False)
        break
    except KeyError:
        print("Year not in data!")
    except ValueError:
        print("Please enter a valid year")

df 使用：

df = pd.DataFrame({
    'gender': ['women', 'women', 'women', 'women', 'women', 'women', 'women',
               'women'],
    'year': [2003, 2007, 2007, 2008, 2009, 2015, 2018, 2020],
    'stats': ['cellphone use', 'height', 'cigarette use', 'weight',
              'cellphone use', 'cigarette use', 'weight', 'height']
}).set_index(['gender', 'year'])

df:

                     stats
gender year               
women  2003  cellphone use
       2007         height
       2007  cigarette use
       2008         weight
       2009  cellphone use
       2015  cigarette use
       2018         weight
       2020         height

pandas 基于年份索引的层次索引切片

pandas hierarchical index slicing based on year index

python

indexing

hierarchical

pandas