df12.head()
COMPONENT_ID PSRO binned PSRO_SPEED
4080 11S02CY383YH1934794910 7.470 (7.4, 7.65] (7.4, 7.65]
4722 11S02CY388YH1934786330 7.491 (7.4, 7.65] (7.4, 7.65]
4708 11S02CY388YH1934782718 7.497 (7.4, 7.65] (7.4, 7.65]
4726 11S02CY388YH1934786336 7.564 (7.4, 7.65] (7.4, 7.65]
4707 11S02CY388YH1934782709 7.581 (7.4, 7.65] (7.4, 7.65]
I want that binned data to map to different values. I tried
df12['PSRO_SPEED']=df12['PSRO_SPEED'].map({'(7.4,7.65]': 'high_speed'})
But this is not working. It is changing df12['PSRO_SPEED'] to NAN.
I think it is Interval, not string, so possible solution is:
i = pd.Interval(7.4,7.65, closed='right')
df12['PSRO_SPEED']=df12['PSRO_SPEED'].map({i: 'high_speed'})
Or for your solution is necessary convert column to strings:
df12['PSRO_SPEED']=df12['PSRO_SPEED'].astype(str).map({'(7.4,7.65]': 'high_speed'})
But better should be add parameter label to cut:
bins = [7.4,7.65,7.9,8.15,8.4,8.65]
labels = ['lowest','low','medium','great','greatest']
df12['binned'] = pd.cut(df12['PSRO'], bins=bins, labels=labels)