Calculating NPS using Pandas
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1
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I am very, very new to Python and am playing around with how I would calculate an NPS score.
The calculation is:
(count of scores 9-10/total count of scores 0-10) - (count of scores
0-6/total count of scores 0-10) for each council.
Data Frame I am using:
The NPS would need to be calculated for each council separately.
This is my first post on here, hopefully it makes sense. If someone could point me in the right direction it would be much appreciated.
Cheers,
Ben.
python pandas
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up vote
1
down vote
favorite
I am very, very new to Python and am playing around with how I would calculate an NPS score.
The calculation is:
(count of scores 9-10/total count of scores 0-10) - (count of scores
0-6/total count of scores 0-10) for each council.
Data Frame I am using:
The NPS would need to be calculated for each council separately.
This is my first post on here, hopefully it makes sense. If someone could point me in the right direction it would be much appreciated.
Cheers,
Ben.
python pandas
Welcome to Stack Overflow! Please take the tour, look around, and read through the Help Center, in particular How do I ask a good question? If you run into a specific problem, research it thoroughly, search thoroughly here, and if you're still stuck post your code and a description of the problem. Also, remember to include Minimum, Complete, Verifiable Example. People will be glad to help
– Andreas
Nov 22 at 7:57
@ Ben, what is desired output, are you looking something where NPS is greater than equals to 9 ? However if you have tried something then put that as well as it will help what exactly you want to achieve.
– pygo
Nov 22 at 8:02
@pygo Do you mean what is the expected answer? Sorry, I am just getting to know the etiquette on Stack Overflow.
– Ben Swann
Nov 22 at 8:34
@BenSwann, yes indeed :-)
– pygo
Nov 22 at 9:25
add a comment |
up vote
1
down vote
favorite
up vote
1
down vote
favorite
I am very, very new to Python and am playing around with how I would calculate an NPS score.
The calculation is:
(count of scores 9-10/total count of scores 0-10) - (count of scores
0-6/total count of scores 0-10) for each council.
Data Frame I am using:
The NPS would need to be calculated for each council separately.
This is my first post on here, hopefully it makes sense. If someone could point me in the right direction it would be much appreciated.
Cheers,
Ben.
python pandas
I am very, very new to Python and am playing around with how I would calculate an NPS score.
The calculation is:
(count of scores 9-10/total count of scores 0-10) - (count of scores
0-6/total count of scores 0-10) for each council.
Data Frame I am using:
The NPS would need to be calculated for each council separately.
This is my first post on here, hopefully it makes sense. If someone could point me in the right direction it would be much appreciated.
Cheers,
Ben.
python pandas
python pandas
edited Nov 22 at 8:00
c-chavez
2,13321732
2,13321732
asked Nov 22 at 7:43
Ben Swann
223
223
Welcome to Stack Overflow! Please take the tour, look around, and read through the Help Center, in particular How do I ask a good question? If you run into a specific problem, research it thoroughly, search thoroughly here, and if you're still stuck post your code and a description of the problem. Also, remember to include Minimum, Complete, Verifiable Example. People will be glad to help
– Andreas
Nov 22 at 7:57
@ Ben, what is desired output, are you looking something where NPS is greater than equals to 9 ? However if you have tried something then put that as well as it will help what exactly you want to achieve.
– pygo
Nov 22 at 8:02
@pygo Do you mean what is the expected answer? Sorry, I am just getting to know the etiquette on Stack Overflow.
– Ben Swann
Nov 22 at 8:34
@BenSwann, yes indeed :-)
– pygo
Nov 22 at 9:25
add a comment |
Welcome to Stack Overflow! Please take the tour, look around, and read through the Help Center, in particular How do I ask a good question? If you run into a specific problem, research it thoroughly, search thoroughly here, and if you're still stuck post your code and a description of the problem. Also, remember to include Minimum, Complete, Verifiable Example. People will be glad to help
– Andreas
Nov 22 at 7:57
@ Ben, what is desired output, are you looking something where NPS is greater than equals to 9 ? However if you have tried something then put that as well as it will help what exactly you want to achieve.
– pygo
Nov 22 at 8:02
@pygo Do you mean what is the expected answer? Sorry, I am just getting to know the etiquette on Stack Overflow.
– Ben Swann
Nov 22 at 8:34
@BenSwann, yes indeed :-)
– pygo
Nov 22 at 9:25
Welcome to Stack Overflow! Please take the tour, look around, and read through the Help Center, in particular How do I ask a good question? If you run into a specific problem, research it thoroughly, search thoroughly here, and if you're still stuck post your code and a description of the problem. Also, remember to include Minimum, Complete, Verifiable Example. People will be glad to help
– Andreas
Nov 22 at 7:57
Welcome to Stack Overflow! Please take the tour, look around, and read through the Help Center, in particular How do I ask a good question? If you run into a specific problem, research it thoroughly, search thoroughly here, and if you're still stuck post your code and a description of the problem. Also, remember to include Minimum, Complete, Verifiable Example. People will be glad to help
– Andreas
Nov 22 at 7:57
@ Ben, what is desired output, are you looking something where NPS is greater than equals to 9 ? However if you have tried something then put that as well as it will help what exactly you want to achieve.
– pygo
Nov 22 at 8:02
@ Ben, what is desired output, are you looking something where NPS is greater than equals to 9 ? However if you have tried something then put that as well as it will help what exactly you want to achieve.
– pygo
Nov 22 at 8:02
@pygo Do you mean what is the expected answer? Sorry, I am just getting to know the etiquette on Stack Overflow.
– Ben Swann
Nov 22 at 8:34
@pygo Do you mean what is the expected answer? Sorry, I am just getting to know the etiquette on Stack Overflow.
– Ben Swann
Nov 22 at 8:34
@BenSwann, yes indeed :-)
– pygo
Nov 22 at 9:25
@BenSwann, yes indeed :-)
– pygo
Nov 22 at 9:25
add a comment |
1 Answer
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1
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Assuming data is in data.csv
:
import pandas as pd
from collections import defaultdict
df = pd.read_csv('data.csv')
high_nps = defaultdict(lambda: 0)
low_nps = defaultdict(lambda: 0)
high_nps.update(dict(df[df['NPS'] >= 9].groupby('CouncilName').count().reset_index()[['CouncilName', 'NPS']].values))
low_nps.update(dict(df[df['NPS'] <= 6].groupby('CouncilName').count().reset_index()[['CouncilName', 'NPS']].values))
total_nps = dict(df.groupby('CouncilName').count().reset_index()[['CouncilName', 'NPS']].values)
nps_score = {council: (high_nps[council] - low_nps[council]) / float(total_nps[council]) for council in total_nps}
print(nps_score)
Prints:
{'Council A': 0.0, 'Council B': -1.0, 'Council C': -1.0}
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
1
down vote
accepted
Assuming data is in data.csv
:
import pandas as pd
from collections import defaultdict
df = pd.read_csv('data.csv')
high_nps = defaultdict(lambda: 0)
low_nps = defaultdict(lambda: 0)
high_nps.update(dict(df[df['NPS'] >= 9].groupby('CouncilName').count().reset_index()[['CouncilName', 'NPS']].values))
low_nps.update(dict(df[df['NPS'] <= 6].groupby('CouncilName').count().reset_index()[['CouncilName', 'NPS']].values))
total_nps = dict(df.groupby('CouncilName').count().reset_index()[['CouncilName', 'NPS']].values)
nps_score = {council: (high_nps[council] - low_nps[council]) / float(total_nps[council]) for council in total_nps}
print(nps_score)
Prints:
{'Council A': 0.0, 'Council B': -1.0, 'Council C': -1.0}
add a comment |
up vote
1
down vote
accepted
Assuming data is in data.csv
:
import pandas as pd
from collections import defaultdict
df = pd.read_csv('data.csv')
high_nps = defaultdict(lambda: 0)
low_nps = defaultdict(lambda: 0)
high_nps.update(dict(df[df['NPS'] >= 9].groupby('CouncilName').count().reset_index()[['CouncilName', 'NPS']].values))
low_nps.update(dict(df[df['NPS'] <= 6].groupby('CouncilName').count().reset_index()[['CouncilName', 'NPS']].values))
total_nps = dict(df.groupby('CouncilName').count().reset_index()[['CouncilName', 'NPS']].values)
nps_score = {council: (high_nps[council] - low_nps[council]) / float(total_nps[council]) for council in total_nps}
print(nps_score)
Prints:
{'Council A': 0.0, 'Council B': -1.0, 'Council C': -1.0}
add a comment |
up vote
1
down vote
accepted
up vote
1
down vote
accepted
Assuming data is in data.csv
:
import pandas as pd
from collections import defaultdict
df = pd.read_csv('data.csv')
high_nps = defaultdict(lambda: 0)
low_nps = defaultdict(lambda: 0)
high_nps.update(dict(df[df['NPS'] >= 9].groupby('CouncilName').count().reset_index()[['CouncilName', 'NPS']].values))
low_nps.update(dict(df[df['NPS'] <= 6].groupby('CouncilName').count().reset_index()[['CouncilName', 'NPS']].values))
total_nps = dict(df.groupby('CouncilName').count().reset_index()[['CouncilName', 'NPS']].values)
nps_score = {council: (high_nps[council] - low_nps[council]) / float(total_nps[council]) for council in total_nps}
print(nps_score)
Prints:
{'Council A': 0.0, 'Council B': -1.0, 'Council C': -1.0}
Assuming data is in data.csv
:
import pandas as pd
from collections import defaultdict
df = pd.read_csv('data.csv')
high_nps = defaultdict(lambda: 0)
low_nps = defaultdict(lambda: 0)
high_nps.update(dict(df[df['NPS'] >= 9].groupby('CouncilName').count().reset_index()[['CouncilName', 'NPS']].values))
low_nps.update(dict(df[df['NPS'] <= 6].groupby('CouncilName').count().reset_index()[['CouncilName', 'NPS']].values))
total_nps = dict(df.groupby('CouncilName').count().reset_index()[['CouncilName', 'NPS']].values)
nps_score = {council: (high_nps[council] - low_nps[council]) / float(total_nps[council]) for council in total_nps}
print(nps_score)
Prints:
{'Council A': 0.0, 'Council B': -1.0, 'Council C': -1.0}
answered Nov 22 at 7:57
andersource
36415
36415
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Welcome to Stack Overflow! Please take the tour, look around, and read through the Help Center, in particular How do I ask a good question? If you run into a specific problem, research it thoroughly, search thoroughly here, and if you're still stuck post your code and a description of the problem. Also, remember to include Minimum, Complete, Verifiable Example. People will be glad to help
– Andreas
Nov 22 at 7:57
@ Ben, what is desired output, are you looking something where NPS is greater than equals to 9 ? However if you have tried something then put that as well as it will help what exactly you want to achieve.
– pygo
Nov 22 at 8:02
@pygo Do you mean what is the expected answer? Sorry, I am just getting to know the etiquette on Stack Overflow.
– Ben Swann
Nov 22 at 8:34
@BenSwann, yes indeed :-)
– pygo
Nov 22 at 9:25