How do I select counts using two or more specific conditions in a dataframe?
So I have a dataset of clinics in different zipcodes in a city from different time frames. How Do I count the number of clinics in each zipcode for the timeframe 2018-2019? So far, I can only count the number of clinics in total for each timeframe. I also want to add a new column or array for the result. Please see the code below:
df.groupby('Season')['Postal Code','Facility ID'].nunique()
This is the result:
Also, can anyone tell me the equivalents of WHERE, GROUP BY and HAVING in SQL for Dataframes in python.
python pandas dataframe count pandas-groupby
edited Nov 15 '18 at 22:11
jpp
102k2164115
asked Nov 15 '18 at 21:48
cheenacheena
2410
add a comment |
So I have a dataset of clinics in different zipcodes in a city from different time frames. How Do I count the number of clinics in each zipcode for the timeframe 2018-2019? So far, I can only count the number of clinics in total for each timeframe. I also want to add a new column or array for the result. Please see the code below:
df.groupby('Season')['Postal Code','Facility ID'].nunique()
This is the result:
Also, can anyone tell me the equivalents of WHERE, GROUP BY and HAVING in SQL for Dataframes in python.
python pandas dataframe count pandas-groupby
edited Nov 15 '18 at 22:11
jpp
102k2164115
asked Nov 15 '18 at 21:48
cheenacheena
2410
add a comment |
So I have a dataset of clinics in different zipcodes in a city from different time frames. How Do I count the number of clinics in each zipcode for the timeframe 2018-2019? So far, I can only count the number of clinics in total for each timeframe. I also want to add a new column or array for the result. Please see the code below:
df.groupby('Season')['Postal Code','Facility ID'].nunique()
This is the result:
Also, can anyone tell me the equivalents of WHERE, GROUP BY and HAVING in SQL for Dataframes in python.
python pandas dataframe count pandas-groupby
edited Nov 15 '18 at 22:11
jpp
102k2164115
asked Nov 15 '18 at 21:48
cheenacheena
2410
So I have a dataset of clinics in different zipcodes in a city from different time frames. How Do I count the number of clinics in each zipcode for the timeframe 2018-2019? So far, I can only count the number of clinics in total for each timeframe. I also want to add a new column or array for the result. Please see the code below:
df.groupby('Season')['Postal Code','Facility ID'].nunique()
This is the result:
Also, can anyone tell me the equivalents of WHERE, GROUP BY and HAVING in SQL for Dataframes in python.
python pandas dataframe count pandas-groupby
python pandas dataframe count pandas-groupby
edited Nov 15 '18 at 22:11
jpp
102k2164115
asked Nov 15 '18 at 21:48
cheenacheena
2410
edited Nov 15 '18 at 22:11
jpp
102k2164115
asked Nov 15 '18 at 21:48
cheenacheena
2410
edited Nov 15 '18 at 22:11
jpp
102k2164115
edited Nov 15 '18 at 22:11
jpp
102k2164115
edited Nov 15 '18 at 22:11
jpp
102k2164115
102k2164115
asked Nov 15 '18 at 21:48
cheenacheena
2410
asked Nov 15 '18 at 21:48
cheenacheena
2410
asked Nov 15 '18 at 21:48
cheenacheena
2410
2410
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
Slice by Season, then group by Postal Code:
res = df.loc[df['Season'] == '2018-2019']
.groupby('Postal Code')['Facility ID'].nunique()
Your question on SQL equivalents is too broad: you may find the Pandas documentation helpful.
answered Nov 15 '18 at 21:53
jppjpp
102k2164115
thanks jpp but how can I create a new dataframe so that I can add the values generated to each column in a new dataframe for each season?
– cheena
Nov 15 '18 at 23:42
@cheena, Not sure exactly what you mean. I suggest you ask a new question.
– jpp
Nov 15 '18 at 23:44
thanks @jpp but how do i create a new dataframe and add this counts as data in new columns for each season. E.g a new sheet that shows all zipcodes and counts for 2018, then 2017, then 2016...and so on in a table
– cheena
Nov 15 '18 at 23:45
Trydf['count'] = df.groupby('Postal Code')['Facility ID'].transform('nunique'), or ask a new question.
– jpp
Nov 15 '18 at 23:46
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
Slice by Season, then group by Postal Code:
res = df.loc[df['Season'] == '2018-2019']
.groupby('Postal Code')['Facility ID'].nunique()
Your question on SQL equivalents is too broad: you may find the Pandas documentation helpful.
answered Nov 15 '18 at 21:53
jppjpp
102k2164115
thanks jpp but how can I create a new dataframe so that I can add the values generated to each column in a new dataframe for each season?
– cheena
Nov 15 '18 at 23:42
@cheena, Not sure exactly what you mean. I suggest you ask a new question.
– jpp
Nov 15 '18 at 23:44
thanks @jpp but how do i create a new dataframe and add this counts as data in new columns for each season. E.g a new sheet that shows all zipcodes and counts for 2018, then 2017, then 2016...and so on in a table
– cheena
Nov 15 '18 at 23:45
Trydf['count'] = df.groupby('Postal Code')['Facility ID'].transform('nunique'), or ask a new question.
– jpp
Nov 15 '18 at 23:46
add a comment |
Slice by Season, then group by Postal Code:
res = df.loc[df['Season'] == '2018-2019']
.groupby('Postal Code')['Facility ID'].nunique()
Your question on SQL equivalents is too broad: you may find the Pandas documentation helpful.
answered Nov 15 '18 at 21:53
jppjpp
102k2164115
thanks jpp but how can I create a new dataframe so that I can add the values generated to each column in a new dataframe for each season?
– cheena
Nov 15 '18 at 23:42
@cheena, Not sure exactly what you mean. I suggest you ask a new question.
– jpp
Nov 15 '18 at 23:44
thanks @jpp but how do i create a new dataframe and add this counts as data in new columns for each season. E.g a new sheet that shows all zipcodes and counts for 2018, then 2017, then 2016...and so on in a table
– cheena
Nov 15 '18 at 23:45
Trydf['count'] = df.groupby('Postal Code')['Facility ID'].transform('nunique'), or ask a new question.
– jpp
Nov 15 '18 at 23:46
add a comment |
Slice by Season, then group by Postal Code:
res = df.loc[df['Season'] == '2018-2019']
.groupby('Postal Code')['Facility ID'].nunique()
Your question on SQL equivalents is too broad: you may find the Pandas documentation helpful.
answered Nov 15 '18 at 21:53
jppjpp
102k2164115
Slice by Season, then group by Postal Code:
res = df.loc[df['Season'] == '2018-2019']
.groupby('Postal Code')['Facility ID'].nunique()
Your question on SQL equivalents is too broad: you may find the Pandas documentation helpful.
answered Nov 15 '18 at 21:53
jppjpp
102k2164115
answered Nov 15 '18 at 21:53
jppjpp
102k2164115
answered Nov 15 '18 at 21:53
jppjpp
102k2164115
answered Nov 15 '18 at 21:53
jppjpp
102k2164115
102k2164115
thanks jpp but how can I create a new dataframe so that I can add the values generated to each column in a new dataframe for each season?
– cheena
Nov 15 '18 at 23:42
@cheena, Not sure exactly what you mean. I suggest you ask a new question.
– jpp
Nov 15 '18 at 23:44
thanks @jpp but how do i create a new dataframe and add this counts as data in new columns for each season. E.g a new sheet that shows all zipcodes and counts for 2018, then 2017, then 2016...and so on in a table
– cheena
Nov 15 '18 at 23:45
Trydf['count'] = df.groupby('Postal Code')['Facility ID'].transform('nunique'), or ask a new question.
– jpp
Nov 15 '18 at 23:46
add a comment |
thanks jpp but how can I create a new dataframe so that I can add the values generated to each column in a new dataframe for each season?
– cheena
Nov 15 '18 at 23:42
@cheena, Not sure exactly what you mean. I suggest you ask a new question.
– jpp
Nov 15 '18 at 23:44
thanks @jpp but how do i create a new dataframe and add this counts as data in new columns for each season. E.g a new sheet that shows all zipcodes and counts for 2018, then 2017, then 2016...and so on in a table
– cheena
Nov 15 '18 at 23:45
Trydf['count'] = df.groupby('Postal Code')['Facility ID'].transform('nunique'), or ask a new question.
– jpp
Nov 15 '18 at 23:46
thanks jpp but how can I create a new dataframe so that I can add the values generated to each column in a new dataframe for each season?
– cheena
Nov 15 '18 at 23:42
thanks jpp but how can I create a new dataframe so that I can add the values generated to each column in a new dataframe for each season?
– cheena
Nov 15 '18 at 23:42
@cheena, Not sure exactly what you mean. I suggest you ask a new question.
– jpp
Nov 15 '18 at 23:44
@cheena, Not sure exactly what you mean. I suggest you ask a new question.
– jpp
Nov 15 '18 at 23:44
thanks @jpp but how do i create a new dataframe and add this counts as data in new columns for each season. E.g a new sheet that shows all zipcodes and counts for 2018, then 2017, then 2016...and so on in a table
– cheena
Nov 15 '18 at 23:45
thanks @jpp but how do i create a new dataframe and add this counts as data in new columns for each season. E.g a new sheet that shows all zipcodes and counts for 2018, then 2017, then 2016...and so on in a table
– cheena
Nov 15 '18 at 23:45
Try
df['count'] = df.groupby('Postal Code')['Facility ID'].transform('nunique'), or ask a new question.– jpp
Nov 15 '18 at 23:46
Try
df['count'] = df.groupby('Postal Code')['Facility ID'].transform('nunique'), or ask a new question.– jpp
Nov 15 '18 at 23:46
add a comment |
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