Is there a more pythonic way to nest conditional statements for filling a new column in a pandas df?

Question

I am new to pandas and python, I searched but couldn't find exactly my problem. I am trying to find the best way to fill a new column in a pandas data frame 'Sample Location', based on the contents of another column, 'NO', to bin them into defined collections.

The first problem is:

        if TestLocation == 'LH Duct': 
            df['Sample Location'] = df.apply(
                lambda x: samplePoint(x['NO']),
                axis=1
            )    

I am not sure is formed correctly as my dataframe is getting kind of jumbled up.

Second question - Is there a more pythonic way of doing this check:

def samplePoint(n):
    if n <= 15:
        v = 'P1 S1'
    elif n >= 20 & n <= 35:
        v = 'P1 S2'
    elif n >= 40 & n <= 55:
        v = 'P1 S3'
    elif n >= 60 & n <= 75:
        v = 'P1 S4'
    elif n >= 80 & n <= 95:
        v = 'P1 S5'
    elif n >= 100 & n <= 115:
        v = 'P1 S6'
    elif n >= 150 & n <= 165:
        v = 'P2 S1'
    elif n >= 170 & n <= 185:
        v = 'P2 S2'
    elif n >= 190 & n <= 205:
        v = 'P2 S3'
    elif n >= 210 & n <= 225:
        v = 'P2 S4'
    elif n >= 230 & n <= 245:
        v = 'P2 S5'
    elif n >= 250 & n <= 265:
        v = 'P2 S6'
    else:
        v = 'null'
    return v

I thought the whole thing could/should be done as an apply/lambda but I got a little lost. If someone could explain this or send me a good link I would be eternally grateful!

Answer 1

Possibly the value of v_code can be calculated, otherwise I would put the options in a list of dicts and I write the function samplePoint as follows:

samples = [
    {'range': (0, 15),
     'v_code': 'P1 S1'},
    {'range': (20, 35),
     'v_code': 'P1 S3'},
    {'range': (60, 75),
     'v_code': 'P1 S4'},
    {'range': (80, 95),
     'v_code': 'P1 S5'},
    {'range': (100, 115),
     'v_code': 'P1 S6'},
    {'range': (150, 165),
     'v_code': 'P2 S1'},
    {'range': (170, 185),
     'v_code': 'P2 S2'},
    {'range': (190, 205),
     'v_code': 'P2 S3'},
    {'range': (210, 225),
     'v_code': 'P2 S4'},
    {'range': (230, 245),
     'v_code': 'P2 S5'},
    {'range': (250, 265),
     'v_code': 'P2 S6'},
]


def samplepoint(n):
    for sample in samples:
        if sample['range'][0] <= n <= sample['range'][1]:
            return sample['v_code']

    return 'null'

if __name__ == '__main__':
    print(samplepoint(10))

also renaming samplePoint to samplepoint as per Python naming convention. To make the module less cluttered you can import the list samples from a config file where you keep all your constants and settings. Thus

from my_config import samples

def samplepoint(n):
    for sample in samples:
        if sample['range'][0] <= n <= sample['range'][1]:
            return sample['v_code']

    return 'null'

if __name__ == '__main__':
    print(samplepoint(100))

where the file my_config.py is

samples = [
    {'range': (0, 15),
     'v_code': 'P1 S1'},
    {'range': (20, 35),
     'v_code': 'P1 S3'},
    {'range': (60, 75),
     'v_code': 'P1 S4'},
    {'range': (80, 95),
     'v_code': 'P1 S5'},
    {'range': (100, 115),
     'v_code': 'P1 S6'},
    {'range': (150, 165),
     'v_code': 'P2 S1'},
    {'range': (170, 185),
     'v_code': 'P2 S2'},
    {'range': (190, 205),
     'v_code': 'P2 S3'},
    {'range': (210, 225),
     'v_code': 'P2 S4'},
    {'range': (230, 245),
     'v_code': 'P2 S5'},
    {'range': (250, 265),
     'v_code': 'P2 S6'},
]