Panda .loc or .iloc to select the columns from a dataset

Question

I have been trying to select a particular set of columns from a dataset for all the rows. I tried something like below.

train_features = train_df.loc[,[0,4,5         


        

Answer 1

If need select by positions use iloc:

train_features = train_df.iloc[:, [0,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18]]
print (train_features)
   age  default  housing  loan  equities  contact  duration  campaign  pdays  \
0   56        1        1     1         1        0       261         1    999   
1   37        1        0     1         1        0       226         1    999   
2   56        1        1     0         1        0       307         1    999   

   previous  poutcome  emp.var.rate  cons.price.idx  cons.conf.idx  euribor3m  \
0         0         2           1.1          93.994          -36.4   3.299552   
1         0         2           1.1          93.994          -36.4   0.743751   
2         0         2           1.1          93.994          -36.4   1.282652   

   nr.employed  
0         5191  
1         5191  
2         5191  

Another solution is drop unnecessary columns:

cols= ['job','marital','education','y']
train_features = train_df.drop(cols, axis=1)
print (train_features)
   age  default  housing  loan  equities  contact  duration  campaign  pdays  \
0   56        1        1     1         1        0       261         1    999   
1   37        1        0     1         1        0       226         1    999   
2   56        1        1     0         1        0       307         1    999   

   previous  poutcome  emp.var.rate  cons.price.idx  cons.conf.idx  euribor3m  \
0         0         2           1.1          93.994          -36.4   3.299552   
1         0         2           1.1          93.994          -36.4   0.743751   
2         0         2           1.1          93.994          -36.4   1.282652   

   nr.employed  
0         5191  
1         5191  
2         5191