I have a large dataframe and what I want to do is overwrite X entries of that dataframe with a new value I set. The new entries have to be at a random position, but they have to be in order. Like I have a Column with random numbers, and want to overwrite 20 of them in a row with the new value x.
I tried df.sample(x)
and then update the dataframe, but I only get individual entries. But I need the X new entries in a row (consecutively).
Somebody got a solution? I'm quite new to Python and have to get into it for my master thesis.
CLARIFICATION:
My dataframe has 5 columns with almost 60,000 rows, each row for 10 minutes of the year.
- One Column is 'output' with electricity production values for that 10 minutes.
- For 2 consecutive hours (120 consecutive minutes, hence 12 consecutive rows) of the year I want to lower that production to 60%. I want it to happen at a random time of the year.
- Another column is 'status', with information about if the production is reduced or not.
I tried:
df_update = df.sample(12)
df_update.status = 'reduced'
df.update(df_update)
df.loc[('status) == 'reduced', ['production']] *=0.6
which does the trick for the total amount of time (12*10 minutes), but I want 120 consecutive minutes and not separated.