I was wondering how for the following dataframe can make a new column (for example B), and for each row define if its value is A1: x>2, A2: between(2,0), A3: between(0,-2), or A4: x<-2.
imprt pandas as pd
imort numpy as np
df = pd.DataFrame({'A':[-4,-3.5,-2.5,-1,1,1.5,2,2.5,3.5]})
I tried the following code but it didnt work.
df['B'] = np.where((df['A']>2), 'A1',
np.where(df['A'].between(2,0),'A2',
np.where(df['A'].between(0,-2),'A3',
np.where(df['A']<-2), 'A4'))
Your solution is possible if change ():
df['B'] = np.where(df['A']>2,'A1',
np.where(df['A'].between(0,2),'A2',
np.where(df['A'].between(-2,0),'A3',
np.where(df['A']<-2, 'A4',''))))
Alternative with cut:
df['B1'] = pd.cut(df['A'], bins=(-np.inf,-2,0,2,np.inf), labels=('A4','A3','A2','A1'))
print (df)
A B B1
0 -4.0 A4 A4
1 -3.5 A4 A4
2 -2.5 A4 A4
3 -1.0 A3 A3
4 1.0 A2 A2
5 1.5 A2 A2
6 2.0 A2 A2
7 2.5 A1 A1
8 3.5 A1 A1
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