使用pandas或scikit learn在多维数组上进行一次热编码

您可以使用:

#create list with one item values
df = df.applymap(lambda x: x if isinstance(x, list) else [x])
print (df)
       location                        menu price
0  [NY, CA, MI]            [Italian, Greek]  [$$]
1          [CA]                  [Japanese]  [$$]
2  [NY, CA, MA]  [Italian, Greek, Japanese]   [$]

from sklearn.preprocessing import MultiLabelBinarizer

mlb = MultiLabelBinarizer()
#create Series for each column by list comprehension
vals = [pd.Series(mlb.fit_transform(df[x]).tolist()) for x in df.columns]
#concat to df
df2 = pd.concat(vals, keys=df.columns, axis=1)
print (df2)

       location       menu   price
0  [1, 0, 1, 1]  [1, 1, 0]  [0, 1]
1  [1, 0, 0, 0]  [0, 0, 1]  [0, 1]
2  [1, 1, 0, 1]  [1, 1, 1]  [1, 0]