我有一个数据框：
df ={'date' : ['2020-08-05', '2020-08-05', '2020-08-05'], 'values_a':['jbl_1;jbl2', 'jbl44;jbl441;imax76;wer43', 'macbook12;iphone43;micromax12;ios11'], 'types' : ['connector1','connector1','connector1'], 'connection' : ['working','working','working']}
df = pd.DataFrame(df)
date values_a types connection
0 2020-08-05 jbl_1;jbl2 connector1 working
1 2020-08-05 jbl44;jbl441;imax76;wer43 connector1 working
2 2020-08-05 macbook12;iphone43;micromax12;ios11 connector1 working我要找的是：
?
?
我想使用分隔符拆分values_a列，并生成额外的列：
我尝试过的：
def generate_one_hot(df):
# make a list of all unique columns values
all_columns = reduce(operator.concat,[column.split(';') for column in df['values_a']])
# fill one hot values
all_values = [[1 if column_name in value else 0 for value in df['values_a']] for column_name in all_columns]
# map it
dataframe = pd.DataFrame({col_name:col_val for col_name, col_val in zip(all_columns,all_values)})
return pd.concat([df,dataframe],1)我该如何使用原生pandas函数优化这段代码呢？
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