if nan python pandas loop












0















This is a bit weird and I don't have a sample data frame but if anyone can help that would be great.



I have 3 columns A, B and C.



C might be blank / nan.



I was to say, if C is blank and A and B equal the same values as A and B of the row above. Then set C to the same value as C of the row above.



this is what I have so far. Its running but not changing the values of C.



for i, row in df.iterrows():



    if df['C'][i]==np.nan:

        if df[['A','B']][i]==df[['A','B']][i-1]:

            df['C'][i]=df['C'][i-1]

        else:

            pass

    else:

        pass


Does anyone see why this might not be working?



Many thanks



I've also tried this but this code is not working at all



 for i, row in df.iterrows():



    if df['C'][i]==np.nan & df[['A','B']][i]==df[['A','B']][i-1]:

            df['C'][i]=df['C'][i-1]



    else:

        pass


so df:



A    B    C

w    4    t

w    4

a   r     c


Output should be :



  A    B    C

    w    4    t

    w    4    t

    a   r     c





pandas loops if-statement







share|improve this question

























  • Got the answer thanks to the guys below. If anyone see what's wrong with the loop please do comment, as I'm really curious now

    – fred.schwartz
    Nov 22 '18 at 10:25
















0















This is a bit weird and I don't have a sample data frame but if anyone can help that would be great.



I have 3 columns A, B and C.



C might be blank / nan.



I was to say, if C is blank and A and B equal the same values as A and B of the row above. Then set C to the same value as C of the row above.



this is what I have so far. Its running but not changing the values of C.



for i, row in df.iterrows():



    if df['C'][i]==np.nan:

        if df[['A','B']][i]==df[['A','B']][i-1]:

            df['C'][i]=df['C'][i-1]

        else:

            pass

    else:

        pass


Does anyone see why this might not be working?



Many thanks



I've also tried this but this code is not working at all



 for i, row in df.iterrows():



    if df['C'][i]==np.nan & df[['A','B']][i]==df[['A','B']][i-1]:

            df['C'][i]=df['C'][i-1]



    else:

        pass


so df:



A    B    C

w    4    t

w    4

a   r     c


Output should be :



  A    B    C

    w    4    t

    w    4    t

    a   r     c





pandas loops if-statement







share|improve this question

























  • Got the answer thanks to the guys below. If anyone see what's wrong with the loop please do comment, as I'm really curious now

    – fred.schwartz
    Nov 22 '18 at 10:25














0












0








0








This is a bit weird and I don't have a sample data frame but if anyone can help that would be great.



I have 3 columns A, B and C.



C might be blank / nan.



I was to say, if C is blank and A and B equal the same values as A and B of the row above. Then set C to the same value as C of the row above.



this is what I have so far. Its running but not changing the values of C.



for i, row in df.iterrows():



    if df['C'][i]==np.nan:

        if df[['A','B']][i]==df[['A','B']][i-1]:

            df['C'][i]=df['C'][i-1]

        else:

            pass

    else:

        pass


Does anyone see why this might not be working?



Many thanks



I've also tried this but this code is not working at all



 for i, row in df.iterrows():



    if df['C'][i]==np.nan & df[['A','B']][i]==df[['A','B']][i-1]:

            df['C'][i]=df['C'][i-1]



    else:

        pass


so df:



A    B    C

w    4    t

w    4

a   r     c


Output should be :



  A    B    C

    w    4    t

    w    4    t

    a   r     c





pandas loops if-statement







share|improve this question
















This is a bit weird and I don't have a sample data frame but if anyone can help that would be great.



I have 3 columns A, B and C.



C might be blank / nan.



I was to say, if C is blank and A and B equal the same values as A and B of the row above. Then set C to the same value as C of the row above.



this is what I have so far. Its running but not changing the values of C.



for i, row in df.iterrows():



    if df['C'][i]==np.nan:

        if df[['A','B']][i]==df[['A','B']][i-1]:

            df['C'][i]=df['C'][i-1]

        else:

            pass

    else:

        pass


Does anyone see why this might not be working?



Many thanks



I've also tried this but this code is not working at all



 for i, row in df.iterrows():



    if df['C'][i]==np.nan & df[['A','B']][i]==df[['A','B']][i-1]:

            df['C'][i]=df['C'][i-1]



    else:

        pass


so df:



A    B    C

w    4    t

w    4

a   r     c


Output should be :



  A    B    C

    w    4    t

    w    4    t

    a   r     c





pandas loops if-statement




pandas loops if-statement






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited Nov 22 '18 at 10:13







fred.schwartz

















asked Nov 22 '18 at 10:06









fred.schwartzfred.schwartz

42210




42210













  • Got the answer thanks to the guys below. If anyone see what's wrong with the loop please do comment, as I'm really curious now

    – fred.schwartz
    Nov 22 '18 at 10:25



















  • Got the answer thanks to the guys below. If anyone see what's wrong with the loop please do comment, as I'm really curious now

    – fred.schwartz
    Nov 22 '18 at 10:25

















Got the answer thanks to the guys below. If anyone see what's wrong with the loop please do comment, as I'm really curious now

– fred.schwartz
Nov 22 '18 at 10:25





Got the answer thanks to the guys below. If anyone see what's wrong with the loop please do comment, as I'm really curious now

– fred.schwartz
Nov 22 '18 at 10:25












2 Answers
2






active

oldest

votes


















1














You should try np.where and DataFrame.shift:



df = pd.DataFrame({'A':np.random.randint(0, 20, size = 100),

                  'B': np.random.randint(0, 20, size = 100),

                   'C':np.random.randint(0, 20, size = 100)})



   A    B   C

0   9   0   16

1   15  15  13

2   9   1   4

3   14  13  18

4   4   14  10







df['C'] = np.where((df['A'] == df['A'].shift(1)) & (df['B'] == df['B'].shift(1))& (df['C'] == np.nan), df['C_shift'], df['C'])



np.sum(df['C'] == df['C'].shift(

>>3





share|improve this answer


























  • Worked perfectly. Thanks a lot

    – fred.schwartz
    Nov 22 '18 at 10:24











  • @fred.schwartz Happy to help :}

    – Mohit Motwani
    Nov 22 '18 at 10:25



















1














You can use:



df['C'] = np.where((df['A']==df['A'].shift()) & (df['B']==df['B'].shift()) & (df['C'].isnull()), df['C'].shift(), df['C'] )





share|improve this answer
























  • This worked. Thanks a lot

    – fred.schwartz
    Nov 22 '18 at 10:25











  • @fred.schwartz you are welcome!

    – Joe
    Nov 22 '18 at 10:26











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2 Answers
2






active

oldest

votes








2 Answers
2






active

oldest

votes









active

oldest

votes






active

oldest

votes









1














You should try np.where and DataFrame.shift:



df = pd.DataFrame({'A':np.random.randint(0, 20, size = 100),

                  'B': np.random.randint(0, 20, size = 100),

                   'C':np.random.randint(0, 20, size = 100)})



   A    B   C

0   9   0   16

1   15  15  13

2   9   1   4

3   14  13  18

4   4   14  10







df['C'] = np.where((df['A'] == df['A'].shift(1)) & (df['B'] == df['B'].shift(1))& (df['C'] == np.nan), df['C_shift'], df['C'])



np.sum(df['C'] == df['C'].shift(

>>3





share|improve this answer


























  • Worked perfectly. Thanks a lot

    – fred.schwartz
    Nov 22 '18 at 10:24











  • @fred.schwartz Happy to help :}

    – Mohit Motwani
    Nov 22 '18 at 10:25
















1














You should try np.where and DataFrame.shift:



df = pd.DataFrame({'A':np.random.randint(0, 20, size = 100),

                  'B': np.random.randint(0, 20, size = 100),

                   'C':np.random.randint(0, 20, size = 100)})



   A    B   C

0   9   0   16

1   15  15  13

2   9   1   4

3   14  13  18

4   4   14  10







df['C'] = np.where((df['A'] == df['A'].shift(1)) & (df['B'] == df['B'].shift(1))& (df['C'] == np.nan), df['C_shift'], df['C'])



np.sum(df['C'] == df['C'].shift(

>>3





share|improve this answer


























  • Worked perfectly. Thanks a lot

    – fred.schwartz
    Nov 22 '18 at 10:24











  • @fred.schwartz Happy to help :}

    – Mohit Motwani
    Nov 22 '18 at 10:25














1












1








1







You should try np.where and DataFrame.shift:



df = pd.DataFrame({'A':np.random.randint(0, 20, size = 100),

                  'B': np.random.randint(0, 20, size = 100),

                   'C':np.random.randint(0, 20, size = 100)})



   A    B   C

0   9   0   16

1   15  15  13

2   9   1   4

3   14  13  18

4   4   14  10







df['C'] = np.where((df['A'] == df['A'].shift(1)) & (df['B'] == df['B'].shift(1))& (df['C'] == np.nan), df['C_shift'], df['C'])



np.sum(df['C'] == df['C'].shift(

>>3





share|improve this answer















You should try np.where and DataFrame.shift:



df = pd.DataFrame({'A':np.random.randint(0, 20, size = 100),

                  'B': np.random.randint(0, 20, size = 100),

                   'C':np.random.randint(0, 20, size = 100)})



   A    B   C

0   9   0   16

1   15  15  13

2   9   1   4

3   14  13  18

4   4   14  10







df['C'] = np.where((df['A'] == df['A'].shift(1)) & (df['B'] == df['B'].shift(1))& (df['C'] == np.nan), df['C_shift'], df['C'])



np.sum(df['C'] == df['C'].shift(

>>3






share|improve this answer














share|improve this answer



share|improve this answer








edited Nov 22 '18 at 10:26

























answered Nov 22 '18 at 10:21









Mohit MotwaniMohit Motwani

2,2151725




2,2151725













  • Worked perfectly. Thanks a lot

    – fred.schwartz
    Nov 22 '18 at 10:24











  • @fred.schwartz Happy to help :}

    – Mohit Motwani
    Nov 22 '18 at 10:25



















  • Worked perfectly. Thanks a lot

    – fred.schwartz
    Nov 22 '18 at 10:24











  • @fred.schwartz Happy to help :}

    – Mohit Motwani
    Nov 22 '18 at 10:25

















Worked perfectly. Thanks a lot

– fred.schwartz
Nov 22 '18 at 10:24





Worked perfectly. Thanks a lot

– fred.schwartz
Nov 22 '18 at 10:24













@fred.schwartz Happy to help :}

– Mohit Motwani
Nov 22 '18 at 10:25





@fred.schwartz Happy to help :}

– Mohit Motwani
Nov 22 '18 at 10:25













1














You can use:



df['C'] = np.where((df['A']==df['A'].shift()) & (df['B']==df['B'].shift()) & (df['C'].isnull()), df['C'].shift(), df['C'] )





share|improve this answer
























  • This worked. Thanks a lot

    – fred.schwartz
    Nov 22 '18 at 10:25











  • @fred.schwartz you are welcome!

    – Joe
    Nov 22 '18 at 10:26
















1














You can use:



df['C'] = np.where((df['A']==df['A'].shift()) & (df['B']==df['B'].shift()) & (df['C'].isnull()), df['C'].shift(), df['C'] )





share|improve this answer
























  • This worked. Thanks a lot

    – fred.schwartz
    Nov 22 '18 at 10:25











  • @fred.schwartz you are welcome!

    – Joe
    Nov 22 '18 at 10:26














1












1








1







You can use:



df['C'] = np.where((df['A']==df['A'].shift()) & (df['B']==df['B'].shift()) & (df['C'].isnull()), df['C'].shift(), df['C'] )





share|improve this answer













You can use:



df['C'] = np.where((df['A']==df['A'].shift()) & (df['B']==df['B'].shift()) & (df['C'].isnull()), df['C'].shift(), df['C'] )






share|improve this answer












share|improve this answer



share|improve this answer










answered Nov 22 '18 at 10:23









JoeJoe

6,10421530




6,10421530













  • This worked. Thanks a lot

    – fred.schwartz
    Nov 22 '18 at 10:25











  • @fred.schwartz you are welcome!

    – Joe
    Nov 22 '18 at 10:26



















  • This worked. Thanks a lot

    – fred.schwartz
    Nov 22 '18 at 10:25











  • @fred.schwartz you are welcome!

    – Joe
    Nov 22 '18 at 10:26

















This worked. Thanks a lot

– fred.schwartz
Nov 22 '18 at 10:25





This worked. Thanks a lot

– fred.schwartz
Nov 22 '18 at 10:25













@fred.schwartz you are welcome!

– Joe
Nov 22 '18 at 10:26





@fred.schwartz you are welcome!

– Joe
Nov 22 '18 at 10:26


















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