Python – How to change the value of a looping dataframe based on the previous data

Question

**
I’m trying to perform a value substitution for a fairly large dataframe.

C = Dataframe in question. It has value for the time 00:00 and I want the same value to be repeated 24 times when there is, so that it is the same at all times.

I try to loop through the dataframe and assign it the previous data when the value is 0.0. Since the value that appears is the average of the day.**

C = q.merge(ss, how='right',left_index=True, right_index=True)
C = C.fillna(0)
for index, row in C['H04_PEDRO_MARIN'].iteritems():
    if row == 0.0:
        C.replace({'H04_PEDRO_MARIN':{0.0:'Valor Anterior'}),inplace = True)
       
    else:
        None

C: 
29/07/11 21:00  0
29/07/11 22:00  0
29/07/11 23:00  0
30/07/11 00:00  27658,625
30/07/11 01:00  0
30/07/11 02:00  0
30/07/11 03:00  0
30/07/11 04:00  0
30/07/11 05:00  0
30/07/11 06:00  0
30/07/11 07:00  0
30/07/11 08:00  0
30/07/11 09:00  0
30/07/11 10:00  0
30/07/11 11:00  0
30/07/11 12:00  0
30/07/11 13:00  0
30/07/11 14:00  0
30/07/11 15:00  0
30/07/11 16:00  0
30/07/11 17:00  0
30/07/11 18:00  0
30/07/11 19:00  0
30/07/11 20:00  0
30/07/11 21:00  0
30/07/11 22:00  0
30/07/11 23:00  0
31/07/11 00:00  32617,125
31/07/11 01:00  0
31/07/11 02:00  0
31/07/11 03:00  0`

I would like to have a solution like this one:

C:
29/07/11 21:00  0
29/07/11 22:00  0
29/07/11 23:00  0
30/07/11 00:00  27658,625
30/07/11 01:00  27658,625
30/07/11 02:00  27658,625
30/07/11 03:00  27658,625
30/07/11 04:00  27658,625
30/07/11 05:00  27658,625
30/07/11 06:00  27658,625
30/07/11 07:00  27658,625
30/07/11 08:00  27658,625
30/07/11 09:00  27658,625
30/07/11 10:00  27658,625
30/07/11 11:00  27658,625
30/07/11 12:00  27658,625
30/07/11 13:00  27658,625
30/07/11 14:00  27658,625
30/07/11 15:00  27658,625
30/07/11 16:00  27658,625
30/07/11 17:00  27658,625
30/07/11 18:00  27658,625
30/07/11 19:00  27658,625
30/07/11 20:00  27658,625
30/07/11 21:00  27658,625
30/07/11 22:00  27658,625
30/07/11 23:00  27658,625
31/07/11 00:00  32617,125
31/07/11 01:00  32617,125
31/07/11 02:00  32617,125

…

Asked By: Guille GL

||

Source

Answer 1

Check the column dtype. I think you have string and not numeric values (because the thousand separator ‘,’).

Replace 0 or (‘0’) by np.nan then front fill values:

df['H04_PEDRO_MARIN2'] = df.replace('0', np.nan).ffill().fillna(0)
print(df)

# Output
               H04_PEDRO_MARIN H04_PEDRO_MARIN2
29/07/11 21:00               0                0
29/07/11 22:00               0                0
29/07/11 23:00               0                0
30/07/11 00:00       27658,625        27658,625
30/07/11 01:00               0        27658,625
30/07/11 02:00               0        27658,625
30/07/11 03:00               0        27658,625
30/07/11 04:00               0        27658,625
30/07/11 05:00               0        27658,625
30/07/11 06:00               0        27658,625
30/07/11 07:00               0        27658,625
30/07/11 08:00               0        27658,625
30/07/11 09:00               0        27658,625
30/07/11 10:00               0        27658,625
30/07/11 11:00               0        27658,625
30/07/11 12:00               0        27658,625
30/07/11 13:00               0        27658,625
30/07/11 14:00               0        27658,625
30/07/11 15:00               0        27658,625
30/07/11 16:00               0        27658,625
30/07/11 17:00               0        27658,625
30/07/11 18:00               0        27658,625
30/07/11 19:00               0        27658,625
30/07/11 20:00               0        27658,625
30/07/11 21:00               0        27658,625
30/07/11 22:00               0        27658,625
30/07/11 23:00               0        27658,625
31/07/11 00:00       32617,125        32617,125
31/07/11 01:00               0        32617,125
31/07/11 02:00               0        32617,125
31/07/11 03:00               0        32617,125

Answered By: Corralien

Python – How to change the value of a looping dataframe based on the previous data

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