CODEWITHSUNDEEP
pythonpandasdataframe
S.Peters
S.Peters

Reputation: 185

Capturing a change in value of a column in consecutive rows

I currently have the following dataframe

enter image description here

and need to create a new binary data frame which applies the following logic:

-If value in any column is >=1.5 and the preceeding value is <1.5, then show 1.

-Continue to show 1 unless the value drops <=0, then put 0.

So applying this to the above should yield:

enter image description here

Any idea how to do this most efficiently?

Upvotes: 0

Views: 149

Answers (1)

Shashi Tunga
Shashi Tunga

Reputation: 516

Here is the approach I think should work. First create new columns for each of the existing columns which will contain the existing column shifted upwards by one column. ie if A is 0 1 1.5 create A1 to 1 1.5 nan U can use pandas shift to do that. do it for all columns Then, if df is the name of your dataFrame

not_found_zero=1
for row in df.iterrows():
   if(not_found_zero):
        if row['A']<=0:
           row['A']=0
           flag=0
         else:
            row['A'] =(row['A']>=1.5) & (row['A1']>=1.5))   
    else:
       row['A']=0

Do this for all columns,and remember after u shift ,last column of A1 will be nan. Delete the temperory rows after completion.

Upvotes: 1

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