更換熊貓數據框中的值時出現問題？

Question

我有以下的熊貓數據框：

在：

df = pd.DataFrame({'Fruits':['this should be a pinneapple', 
           'this should be an apple', 
           'this should be a tomato', 'this should 3 grapes', 
          'this should be an orange', 
           'this should be an 01', 
          'this should be an 02']}) 

df 

日期：

Fruits 
0 this should be a pinneapple 
1 this should be an apple 
2 this should be a tomato 
3 this should 3 grapes 
4 this should be an orange 
5 this should be an 01 
6 this should be an 02 

我想用一個id替換所有的水果（例如01到nn）。爲此，我與熊貓試圖替換功能：

df['Fruits'] = df['Fruits'].replace(['pinneapple', 'apple', 'tomato', 'grapes', 'orange'],\ 
                     ['01', '02', '03', '04', '05']) 

然而，當我做上述分配不採取措施的專欄中，我有興趣來調整。因此，如何將每個單詞替換爲預定義的數字？

Answer 1

您可以Series.replace使用參數regex=True：

df['Fruits'] = df['Fruits'].replace(['pinneapple', 'apple', 'tomato', 'grapes', 'orange'],\ 
            ['01', '02', '03', '04', '05'], regex=True) 
print (df) 
       Fruits 
0 this should be a 01 
1 this should be an 02 
2 this should be a 03 
3  this should 3 04 
4 this should be an 05 
5 this should be an 01 
6 this should be an 02 

您還可以使用list comprehension爲codes：

fruits = ['pinneapple', 'apple', 'tomato', 'grapes', 'orange'] 
codes = [str(i + 1).zfill(2) for i, c in enumerate(fruits)] 
print (codes) 
['01', '02', '03', '04', '05'] 

df['Fruits'] = df['Fruits'].replace(fruits,codes, regex=True) 
print (df) 

       Fruits 
0 this should be a 01 
1 this should be an 02 
2 this should be a 03 
3  this should 3 04 
4 this should be an 05 
5 this should be an 01 
6 this should be an 02 

Answer 2

嘗試使用重置值如下：

df['Fruits'] = pd.DataFrame() 

然後再次分配新值