[英]Loop column names in get_dummies for pandas?
對於熊貓,我已經編寫了以下代碼,以便轉換所有分類功能。 但是,在數據集上運行它並檢查數據類型之后,沒有任何變化。
先感謝您。
碼:
def dummy_conv(data):
names=data.select_dtypes(exclude=['number']).columns
for c in names:
data=pd.get_dummies(data,columns=[c],drop_first=True)
dummy_conv(data_train)
data_train.dtypes # object features are not converted
不需要循環,按列列表過濾,也不要忘記return
:
data_train = pd.DataFrame({'A':list('abcdef'),
'B':[4,5,4,5,5,4],
'C':[7,8,9,4,2,3],
'D':[1,3,5,7,1,0],
'E':[5,3,6,9,2,4],
'F':list('aaabbb')})
print (data_train)
A B C D E F
0 a 4 7 1 5 a
1 b 5 8 3 3 a
2 c 4 9 5 6 a
3 d 5 4 7 9 b
4 e 5 2 1 2 b
5 f 4 3 0 4 b
def dummy_conv(data):
names=data.select_dtypes(exclude=['number']).columns
return pd.get_dummies(data[names], drop_first=True)
df = dummy_conv(data_train)
print (df)
A_b A_c A_d A_e A_f F_b
0 0 0 0 0 0 0
1 1 0 0 0 0 0
2 0 1 0 0 0 0
3 0 0 1 0 0 1
4 0 0 0 1 0 1
5 0 0 0 0 1 1
如果只想轉換非數字列:
def dummy_conv(data):
return pd.get_dummies(data,drop_first=True)
#same output like
#names=data.select_dtypes(exclude=['number']).columns
#return pd.get_dummies(data,columns=names,drop_first=True)
df = dummy_conv(data_train)
print (df)
B C D E A_b A_c A_d A_e A_f F_b
0 4 7 1 5 0 0 0 0 0 0
1 5 8 3 3 1 0 0 0 0 0
2 4 9 5 6 0 1 0 0 0 0
3 5 4 7 9 0 0 1 0 0 1
4 5 2 1 2 0 0 0 1 0 1
5 4 3 0 4 0 0 0 0 1 1
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