Python pandas.map()用法及代碼示例

pandas.map()用於映射來自同一列的兩個係列的值。為了映射兩個係列，第一個係列的最後一列應與第二個係列的索引列相同，並且值也應唯一。

用法:

Series.map(arg, na_action=None)

參數：

arg:function, dict, or Series

na_action:{None, ‘ignore’} If ‘ignore’, propagate NA values, without passing them to the mapping correspondence. na_action checks the NA value and ignores it while mapping in case of ‘ignore’

返回類型：

Pandas Series with same as index as caller

範例1：
在下麵的示例中，兩個序列由相同的數據組成。 pokemon_names列和pokemon_types索引列相同，因此Pandas.map()與其餘兩列匹配並返回一個新係列。

Note:
-> 2nd column of caller of map function must be same as index column of passed series.
-> The values of common column must be unique too.

import pandas as pd 
  
#reading csv files 
pokemon_names = pd.read_csv("pokemon.csv", usecols = ["Pokemon"], 
                                                  squeeze = True) 
  
#usecol is used to use selected columns 
#index_col is used to make passed column as index 
pokemon_types = pd.read_csv("pokemon.csv", index_col = "Pokemon", 
                                                  squeeze = True) 
  
#using pandas map function 
new=pokemon_names.map(pokemon_types) 
  
print (new)

輸出：

範例2：

此函數僅適用於Series。傳遞數據幀將導致屬性錯誤。傳遞不同長度的序列將使輸出序列的長度與調用者相同。