Validate Pandas dataframe column based on hierarchy












0















I have a dataframe like this



df1 = pd.DataFrame({'Site': ["S1", "S2", "S3", "S4", "S5", "S6","S7","S8","S9"],  
'Sitelink': [" ","S1","S2","S6","S4"," ","S8"," ","S7"],
'level': ["R", "T", "P", "T", "P", "R","T","R","P"],
'Weight':["55","55","55","85","85","80","150","190","200"]})


column 'Site' will be always unique



column 'Sitelink' captures the next lower level site to each Site



column 'level' has 3 values- R, T, P where the hierarchy is R < T < P.



column 'Weight' can be any value.



The output should satisfy the condition that weight of a higher level site should be always lesser than or equal to lower level site. Expected result dataframe should be like



Output Dataframe



I'm trying to loop the dataframe and compare each site with next level. Is there a better approach to do this?










share|improve this question




















  • 2





    why row number 5 S5 S4 , value is equal , but return the error

    – W-B
    Nov 22 '18 at 17:55











  • @W-B Yes, you're right. Corrected the question

    – Osceria
    Nov 22 '18 at 22:42
















0















I have a dataframe like this



df1 = pd.DataFrame({'Site': ["S1", "S2", "S3", "S4", "S5", "S6","S7","S8","S9"],  
'Sitelink': [" ","S1","S2","S6","S4"," ","S8"," ","S7"],
'level': ["R", "T", "P", "T", "P", "R","T","R","P"],
'Weight':["55","55","55","85","85","80","150","190","200"]})


column 'Site' will be always unique



column 'Sitelink' captures the next lower level site to each Site



column 'level' has 3 values- R, T, P where the hierarchy is R < T < P.



column 'Weight' can be any value.



The output should satisfy the condition that weight of a higher level site should be always lesser than or equal to lower level site. Expected result dataframe should be like



Output Dataframe



I'm trying to loop the dataframe and compare each site with next level. Is there a better approach to do this?










share|improve this question




















  • 2





    why row number 5 S5 S4 , value is equal , but return the error

    – W-B
    Nov 22 '18 at 17:55











  • @W-B Yes, you're right. Corrected the question

    – Osceria
    Nov 22 '18 at 22:42














0












0








0








I have a dataframe like this



df1 = pd.DataFrame({'Site': ["S1", "S2", "S3", "S4", "S5", "S6","S7","S8","S9"],  
'Sitelink': [" ","S1","S2","S6","S4"," ","S8"," ","S7"],
'level': ["R", "T", "P", "T", "P", "R","T","R","P"],
'Weight':["55","55","55","85","85","80","150","190","200"]})


column 'Site' will be always unique



column 'Sitelink' captures the next lower level site to each Site



column 'level' has 3 values- R, T, P where the hierarchy is R < T < P.



column 'Weight' can be any value.



The output should satisfy the condition that weight of a higher level site should be always lesser than or equal to lower level site. Expected result dataframe should be like



Output Dataframe



I'm trying to loop the dataframe and compare each site with next level. Is there a better approach to do this?










share|improve this question
















I have a dataframe like this



df1 = pd.DataFrame({'Site': ["S1", "S2", "S3", "S4", "S5", "S6","S7","S8","S9"],  
'Sitelink': [" ","S1","S2","S6","S4"," ","S8"," ","S7"],
'level': ["R", "T", "P", "T", "P", "R","T","R","P"],
'Weight':["55","55","55","85","85","80","150","190","200"]})


column 'Site' will be always unique



column 'Sitelink' captures the next lower level site to each Site



column 'level' has 3 values- R, T, P where the hierarchy is R < T < P.



column 'Weight' can be any value.



The output should satisfy the condition that weight of a higher level site should be always lesser than or equal to lower level site. Expected result dataframe should be like



Output Dataframe



I'm trying to loop the dataframe and compare each site with next level. Is there a better approach to do this?







pandas dataframe






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited Nov 22 '18 at 22:41







Osceria

















asked Nov 22 '18 at 17:24









OsceriaOsceria

479




479








  • 2





    why row number 5 S5 S4 , value is equal , but return the error

    – W-B
    Nov 22 '18 at 17:55











  • @W-B Yes, you're right. Corrected the question

    – Osceria
    Nov 22 '18 at 22:42














  • 2





    why row number 5 S5 S4 , value is equal , but return the error

    – W-B
    Nov 22 '18 at 17:55











  • @W-B Yes, you're right. Corrected the question

    – Osceria
    Nov 22 '18 at 22:42








2




2





why row number 5 S5 S4 , value is equal , but return the error

– W-B
Nov 22 '18 at 17:55





why row number 5 S5 S4 , value is equal , but return the error

– W-B
Nov 22 '18 at 17:55













@W-B Yes, you're right. Corrected the question

– Osceria
Nov 22 '18 at 22:42





@W-B Yes, you're right. Corrected the question

– Osceria
Nov 22 '18 at 22:42












1 Answer
1






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oldest

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0














If i understand correctly, you would like to to check if for each row the weight of the site is lower than or equal to the weight of the site marked as the Sitelink.



The code for a single row would than be:



def is_error(row):
if row['Sitelink'] == " ":
return 'No Error'
site_link = df.loc[df['Site'] == row['Sitelink']]
if int(row['Weight']) <= int(site_link['Weight']):
return 'No Error'
else:
return 'Higher than lower'


Therefore we could apply this line for each row using the apply function:



df['Error'] = df.apply(is_error, axis=1)





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    1 Answer
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    0














    If i understand correctly, you would like to to check if for each row the weight of the site is lower than or equal to the weight of the site marked as the Sitelink.



    The code for a single row would than be:



    def is_error(row):
    if row['Sitelink'] == " ":
    return 'No Error'
    site_link = df.loc[df['Site'] == row['Sitelink']]
    if int(row['Weight']) <= int(site_link['Weight']):
    return 'No Error'
    else:
    return 'Higher than lower'


    Therefore we could apply this line for each row using the apply function:



    df['Error'] = df.apply(is_error, axis=1)





    share|improve this answer






























      0














      If i understand correctly, you would like to to check if for each row the weight of the site is lower than or equal to the weight of the site marked as the Sitelink.



      The code for a single row would than be:



      def is_error(row):
      if row['Sitelink'] == " ":
      return 'No Error'
      site_link = df.loc[df['Site'] == row['Sitelink']]
      if int(row['Weight']) <= int(site_link['Weight']):
      return 'No Error'
      else:
      return 'Higher than lower'


      Therefore we could apply this line for each row using the apply function:



      df['Error'] = df.apply(is_error, axis=1)





      share|improve this answer




























        0












        0








        0







        If i understand correctly, you would like to to check if for each row the weight of the site is lower than or equal to the weight of the site marked as the Sitelink.



        The code for a single row would than be:



        def is_error(row):
        if row['Sitelink'] == " ":
        return 'No Error'
        site_link = df.loc[df['Site'] == row['Sitelink']]
        if int(row['Weight']) <= int(site_link['Weight']):
        return 'No Error'
        else:
        return 'Higher than lower'


        Therefore we could apply this line for each row using the apply function:



        df['Error'] = df.apply(is_error, axis=1)





        share|improve this answer















        If i understand correctly, you would like to to check if for each row the weight of the site is lower than or equal to the weight of the site marked as the Sitelink.



        The code for a single row would than be:



        def is_error(row):
        if row['Sitelink'] == " ":
        return 'No Error'
        site_link = df.loc[df['Site'] == row['Sitelink']]
        if int(row['Weight']) <= int(site_link['Weight']):
        return 'No Error'
        else:
        return 'Higher than lower'


        Therefore we could apply this line for each row using the apply function:



        df['Error'] = df.apply(is_error, axis=1)






        share|improve this answer














        share|improve this answer



        share|improve this answer








        edited Nov 22 '18 at 23:07

























        answered Nov 22 '18 at 22:16









        Gal AvineriGal Avineri

        15210




        15210






























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