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[,[0,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18]]
I want to mention that all rows are inclusive but only need the numbered columns.
Is there any better way to approach this.
sample data:
age job marital education default housing loan equities contact duration campaign pdays previous poutcome emp.var.rate cons.price.idx cons.conf.idx euribor3m nr.employed y
56 housemaid married basic.4y 1 1 1 1 0 261 1 999 0 2 1.1 93.994 -36.4 3.299552287 5191 1
37 services married high.school 1 0 1 1 0 226 1 999 0 2 1.1 93.994 -36.4 0.743751247 5191 1
56 services married high.school 1 1 0 1 0 307 1 999 0 2 1.1 93.994 -36.4 1.28265179 5191 1
I'm trying to neglect job, marital, education and y column in my dataset. y column is the target variable.
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