This code was working until I upgrade my python 2.x to 3.x. I have a df consisting of 3 columns ipk1, ipk2, ipk3. ipk1, ipk2, ipk3 consisting of float numbers 0 - 4.0, I would like to bin them into string.
The data looks something like this:
ipk1 ipk2 ipk3 ipk4 ipk5 jk
0 3.25 3.31 3.31 3.31 3.34 P
1 3.37 3.33 3.36 3.33 3.41 P
2 3.41 3.47 3.59 3.55 3.60 P
3 3.23 3.10 3.05 2.98 2.97 L
4 3.24 3.40 3.22 3.23 3.25 L
on python 2.x this code works but after I upgrade it into python 3 it isn't. Is there any other way to bin it into string ? I have tried using while it also not help anything.
train1.loc[train1['ipk1'] > 3.6, 'ipk1'] = 'A',
train1.loc[(train1['ipk1']>3.2) & (train1['ipk1']<=3.6),'ipk1']='B',
train1.loc[(train1['ipk1']>2.8) & (train1['ipk1']<=3.2),'ipk1']='C',
train1.loc[(train1['ipk1']>2.4) & (train1['ipk1']<=2.8),'ipk1']='D',
train1.loc[(train1['ipk1']>2.0) & (train1['ipk1']<=2.4),'ipk1']='E',
train1.loc[(train1['ipk1']>1.6) & (train1['ipk1']<=2.0),'ipk1']='F',
train1.loc[(train1['ipk1']>1.2) & (train1['ipk1']<=1.6),'ipk1']='G',
train1.loc[train1['ipk1'] <= 1.2, 'ipk1'] = 'H'
The error I receive:
TypeError: '>' not supported between instances of 'str' and 'float'
My expected output:
ipk1 ipk2 ipk3 ipk4 ipk5 jk
0 B 3.31 3.31 3.31 3.34 P
1 B 3.33 3.36 3.33 3.41 P
2 B 3.47 3.59 3.55 3.60 P
3 B 3.10 3.05 2.98 2.97 L
4 B 3.40 3.22 3.23 3.25 L
This is a good use case for pandas.cut:
bins = [-np.inf, 1.2, 1.6, 2.0, 2.4, 2.8, 3.2, 3.6, np.inf]
labels = ['H', 'G', 'F', 'E', 'D', 'C', 'B', 'A']
df['ipk1'] = pd.cut(df['ipk1'], bins=bins, labels=labels)