Pandas: counter increasing each time conditions are met











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I have a dataframe with some conditions and a Counter that Counts when condition A is met.



 date                      condition        count   
01,01,2018 08:00 A 1
01,01,2018 08:01 A 2
01,01,2018 08:03 A 3
01,01,2018 08:04 B 0
01,01,2018 08:07 B 0
01,01,2018 08:10 B 0
01,01,2018 08:13 B 0
01,01,2018 08:22 A 1
01,01,2018 08:24 A 2
01,01,2018 08:25 B 0
01,01,2018 08:27 B 0
01,01,2018 08:29 B 0
01,01,2018 08:30 A 1


I would like that the Count doesn't reset each time condition changes.



date                      condition        count   
01,01,2018 08:00 A 1
01,01,2018 08:01 A 2
01,01,2018 08:03 A 3
01,01,2018 08:04 B 3
01,01,2018 08:07 B 3
01,01,2018 08:10 B 3
01,01,2018 08:13 B 3
01,01,2018 08:22 A 4
01,01,2018 08:24 A 5
01,01,2018 08:25 B 5
01,01,2018 08:27 B 5
01,01,2018 08:29 B 5
01,01,2018 08:30 A 6


At the Moment the code for the Count Looks like:



df['count']= df.groupby((df['condition'] = 'A').cumsum()).cumcount()


Thanks!










share|improve this question


























    up vote
    2
    down vote

    favorite












    I have a dataframe with some conditions and a Counter that Counts when condition A is met.



     date                      condition        count   
    01,01,2018 08:00 A 1
    01,01,2018 08:01 A 2
    01,01,2018 08:03 A 3
    01,01,2018 08:04 B 0
    01,01,2018 08:07 B 0
    01,01,2018 08:10 B 0
    01,01,2018 08:13 B 0
    01,01,2018 08:22 A 1
    01,01,2018 08:24 A 2
    01,01,2018 08:25 B 0
    01,01,2018 08:27 B 0
    01,01,2018 08:29 B 0
    01,01,2018 08:30 A 1


    I would like that the Count doesn't reset each time condition changes.



    date                      condition        count   
    01,01,2018 08:00 A 1
    01,01,2018 08:01 A 2
    01,01,2018 08:03 A 3
    01,01,2018 08:04 B 3
    01,01,2018 08:07 B 3
    01,01,2018 08:10 B 3
    01,01,2018 08:13 B 3
    01,01,2018 08:22 A 4
    01,01,2018 08:24 A 5
    01,01,2018 08:25 B 5
    01,01,2018 08:27 B 5
    01,01,2018 08:29 B 5
    01,01,2018 08:30 A 6


    At the Moment the code for the Count Looks like:



    df['count']= df.groupby((df['condition'] = 'A').cumsum()).cumcount()


    Thanks!










    share|improve this question
























      up vote
      2
      down vote

      favorite









      up vote
      2
      down vote

      favorite











      I have a dataframe with some conditions and a Counter that Counts when condition A is met.



       date                      condition        count   
      01,01,2018 08:00 A 1
      01,01,2018 08:01 A 2
      01,01,2018 08:03 A 3
      01,01,2018 08:04 B 0
      01,01,2018 08:07 B 0
      01,01,2018 08:10 B 0
      01,01,2018 08:13 B 0
      01,01,2018 08:22 A 1
      01,01,2018 08:24 A 2
      01,01,2018 08:25 B 0
      01,01,2018 08:27 B 0
      01,01,2018 08:29 B 0
      01,01,2018 08:30 A 1


      I would like that the Count doesn't reset each time condition changes.



      date                      condition        count   
      01,01,2018 08:00 A 1
      01,01,2018 08:01 A 2
      01,01,2018 08:03 A 3
      01,01,2018 08:04 B 3
      01,01,2018 08:07 B 3
      01,01,2018 08:10 B 3
      01,01,2018 08:13 B 3
      01,01,2018 08:22 A 4
      01,01,2018 08:24 A 5
      01,01,2018 08:25 B 5
      01,01,2018 08:27 B 5
      01,01,2018 08:29 B 5
      01,01,2018 08:30 A 6


      At the Moment the code for the Count Looks like:



      df['count']= df.groupby((df['condition'] = 'A').cumsum()).cumcount()


      Thanks!










      share|improve this question













      I have a dataframe with some conditions and a Counter that Counts when condition A is met.



       date                      condition        count   
      01,01,2018 08:00 A 1
      01,01,2018 08:01 A 2
      01,01,2018 08:03 A 3
      01,01,2018 08:04 B 0
      01,01,2018 08:07 B 0
      01,01,2018 08:10 B 0
      01,01,2018 08:13 B 0
      01,01,2018 08:22 A 1
      01,01,2018 08:24 A 2
      01,01,2018 08:25 B 0
      01,01,2018 08:27 B 0
      01,01,2018 08:29 B 0
      01,01,2018 08:30 A 1


      I would like that the Count doesn't reset each time condition changes.



      date                      condition        count   
      01,01,2018 08:00 A 1
      01,01,2018 08:01 A 2
      01,01,2018 08:03 A 3
      01,01,2018 08:04 B 3
      01,01,2018 08:07 B 3
      01,01,2018 08:10 B 3
      01,01,2018 08:13 B 3
      01,01,2018 08:22 A 4
      01,01,2018 08:24 A 5
      01,01,2018 08:25 B 5
      01,01,2018 08:27 B 5
      01,01,2018 08:29 B 5
      01,01,2018 08:30 A 6


      At the Moment the code for the Count Looks like:



      df['count']= df.groupby((df['condition'] = 'A').cumsum()).cumcount()


      Thanks!







      python pandas






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      asked Nov 19 at 17:02









      Luca91

      1618




      1618
























          2 Answers
          2






          active

          oldest

          votes

















          up vote
          4
          down vote



          accepted










          Why not



          df['count']=df['condition'].eq('A').cumsum()





          share|improve this answer





















          • what if I have 2 conditions but I want to restart the Count each time are both met?? at the Moment I am trying df['count']= df.groupby(((df.condition1<50)&(df.condition2 < 10)).cumsum()).cumcount()+1 but it doesn't work, it simply start counting from the beginning to the end ignoring the conditions...can you help me with this please?
            – Luca91
            Nov 20 at 8:46


















          up vote
          1
          down vote













          I think groupby.cumsum is what you're looking for



          df['count']= df.groupby((df['Date']['condition']).cumsum())


          and then later subset the df based on required condition.






          share|improve this answer





















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            2 Answers
            2






            active

            oldest

            votes








            2 Answers
            2






            active

            oldest

            votes









            active

            oldest

            votes






            active

            oldest

            votes








            up vote
            4
            down vote



            accepted










            Why not



            df['count']=df['condition'].eq('A').cumsum()





            share|improve this answer





















            • what if I have 2 conditions but I want to restart the Count each time are both met?? at the Moment I am trying df['count']= df.groupby(((df.condition1<50)&(df.condition2 < 10)).cumsum()).cumcount()+1 but it doesn't work, it simply start counting from the beginning to the end ignoring the conditions...can you help me with this please?
              – Luca91
              Nov 20 at 8:46















            up vote
            4
            down vote



            accepted










            Why not



            df['count']=df['condition'].eq('A').cumsum()





            share|improve this answer





















            • what if I have 2 conditions but I want to restart the Count each time are both met?? at the Moment I am trying df['count']= df.groupby(((df.condition1<50)&(df.condition2 < 10)).cumsum()).cumcount()+1 but it doesn't work, it simply start counting from the beginning to the end ignoring the conditions...can you help me with this please?
              – Luca91
              Nov 20 at 8:46













            up vote
            4
            down vote



            accepted







            up vote
            4
            down vote



            accepted






            Why not



            df['count']=df['condition'].eq('A').cumsum()





            share|improve this answer












            Why not



            df['count']=df['condition'].eq('A').cumsum()






            share|improve this answer












            share|improve this answer



            share|improve this answer










            answered Nov 19 at 17:09









            W-B

            96.7k73162




            96.7k73162












            • what if I have 2 conditions but I want to restart the Count each time are both met?? at the Moment I am trying df['count']= df.groupby(((df.condition1<50)&(df.condition2 < 10)).cumsum()).cumcount()+1 but it doesn't work, it simply start counting from the beginning to the end ignoring the conditions...can you help me with this please?
              – Luca91
              Nov 20 at 8:46


















            • what if I have 2 conditions but I want to restart the Count each time are both met?? at the Moment I am trying df['count']= df.groupby(((df.condition1<50)&(df.condition2 < 10)).cumsum()).cumcount()+1 but it doesn't work, it simply start counting from the beginning to the end ignoring the conditions...can you help me with this please?
              – Luca91
              Nov 20 at 8:46
















            what if I have 2 conditions but I want to restart the Count each time are both met?? at the Moment I am trying df['count']= df.groupby(((df.condition1<50)&(df.condition2 < 10)).cumsum()).cumcount()+1 but it doesn't work, it simply start counting from the beginning to the end ignoring the conditions...can you help me with this please?
            – Luca91
            Nov 20 at 8:46




            what if I have 2 conditions but I want to restart the Count each time are both met?? at the Moment I am trying df['count']= df.groupby(((df.condition1<50)&(df.condition2 < 10)).cumsum()).cumcount()+1 but it doesn't work, it simply start counting from the beginning to the end ignoring the conditions...can you help me with this please?
            – Luca91
            Nov 20 at 8:46












            up vote
            1
            down vote













            I think groupby.cumsum is what you're looking for



            df['count']= df.groupby((df['Date']['condition']).cumsum())


            and then later subset the df based on required condition.






            share|improve this answer

























              up vote
              1
              down vote













              I think groupby.cumsum is what you're looking for



              df['count']= df.groupby((df['Date']['condition']).cumsum())


              and then later subset the df based on required condition.






              share|improve this answer























                up vote
                1
                down vote










                up vote
                1
                down vote









                I think groupby.cumsum is what you're looking for



                df['count']= df.groupby((df['Date']['condition']).cumsum())


                and then later subset the df based on required condition.






                share|improve this answer












                I think groupby.cumsum is what you're looking for



                df['count']= df.groupby((df['Date']['condition']).cumsum())


                and then later subset the df based on required condition.







                share|improve this answer












                share|improve this answer



                share|improve this answer










                answered Nov 19 at 17:21









                Ken Dekalb

                15911




                15911






























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