In following line of code
X = np.array(df.drop(['label'], 1))
Could you please explain what does number 1 do?
From documentation I understand that DataFrame.drop function drops desired column named 'label' from dataframe and returns new dataframe without this column. But I dont understand what does this particular integer parameter 1 do.
It is parameter axis in drop. It is same as axis=1. And it means you need remove columns from DataFrame which are specify in first parameter labels:
labels is omited most times.
Parameter axis can be removed if need remove row with index, because by default axis=0.
Parameter axis=1 is sometimes replaced by 1, because less text, but it is worse readable.
Sample:
import pandas as pd
df = pd.DataFrame({'label':[1,2,3],
'label1':[4,5,6],
'label2':[7,8,9]})
print (df)
label label1 label2
0 1 4 7
1 2 5 8
2 3 6 9
print (df.drop(['label'], 1))
label1 label2
0 4 7
1 5 8
2 6 9
#most commonly used
print (df.drop(['label'], axis=1))
label1 label2
0 4 7
1 5 8
2 6 9
print (df.drop(labels=['label'], axis=1))
label1 label2
0 4 7
1 5 8
2 6 9
You wanna drop data called 'age' and you'll have to point it's a column.
So when you drop 'age' from data type
x = np.array(data.drop([predict], 1)).
If age is axis x
x = np.array(data.drop([predict], 0))
