从列表列表创建pandas数据框，但有不同的分隔符

Question

我有一份清单清单：

     [['1', 'Toy Story (1995)', "Animation|Children's|Comedy"],
     ['2', 'Jumanji (1995)', "Adventure|Children's|Fantasy"],
     ['3', 'Grumpier Old Men (1995)', 'Comedy|Romance']]

我想最终得到一个包含这些列的pandas数据帧。

cols = ['MovieID', 'Name', 'Year', 'Adventure', 'Children', 'Comedy', 'Fantasy', 'Romance']

对于'Adventure', 'Children', 'Comedy', 'Fantasy', 'Romance'栏目，数据将为1或0。

我试过了：

for row in movies_list:
    for element in row:
        if '|' in element:
            element = element.split('|')

然而，原始列表没有任何反应..完全难倒在这里。

Answer 1

使用带有str.get_dummies DataFrame构造str.get_dummies ：

L = [['1', 'Toy Story (1995)', "Animation|Children's|Comedy"],
     ['2', 'Jumanji (1995)', "Adventure|Children's|Fantasy"],
     ['3', 'Grumpier Old Men (1995)', 'Comedy|Romance']]
df = pd.DataFrame(L, columns=['MovieID','Name','Data'])


df1 = df['Data'].str.get_dummies()
print (df1)
   Adventure  Animation  Children's  Comedy  Fantasy  Romance
0          0          1           1       1        0        0
1          1          0           1       0        1        0
2          0          0           0       1        0        1

对于列， Name和Year需要split和rstrip for remove trailing ) ， Year也会转换为int 。

df[['Name','Year']] = df['Name'].str.split('\s\(', expand=True)
df['Year'] = df['Year'].str.rstrip(')').astype(int)

最后删除列Data并通过join将df1添加到original：

df = df.drop('Data', axis=1).join(df1)
print (df)
  MovieID              Name  Year  Adventure  Animation  Children's  Comedy  \
0       1         Toy Story  1995          0          1           1       1   
1       2           Jumanji  1995          1          0           1       0   
2       3  Grumpier Old Men  1995          0          0           0       1   

   Fantasy  Romance  
0        0        0  
1        1        0  
2        0        1  

Answer 2

这是我的版本，对于一行答案还不够好，但希望它可以帮到你！

import pandas as pd
import numpy as np

data = [['1', 'Toy Story (1995)', "Animation|Children's|Comedy"],
     ['2', 'Jumanji (1995)', "Adventure|Children's|Fantasy"],
     ['3', 'Grumpier Old Men (1995)', 'Comedy|Romance']]
cols = ['MovieID', 'Name', 'Year', 'Adventure', 'Children', 'Comedy', 'Fantasy', 'Romance']
final = []
for x in data:
    output = []
    output.append(x[0])
    output.append(x[1].split("(")[0].lstrip().rstrip())
    output.append(x[1].split("(")[1][:4])
    for h in ['Adventure', 'Children', 'Comedy', 'Fantasy', 'Romance']:
        output.append(h in x[2])
    final.append(output)

df = pd.DataFrame(final, columns=cols)
print(df)

OUTPUT：

  MovieID              Name  Year  Adventure  Children  Comedy  Fantasy  \
0       1         Toy Story  1995      False      True    True    False   
1       2           Jumanji  1995       True      True   False     True   
2       3  Grumpier Old Men  1995      False     False    True    False   

   Romance  
0    False  
1    False  
2     True