Clash Royale CLAN TAG#URR8PPP

Getting previous row based using conditional shift

I am converting an XML into a dataframe which looks something this:

I want the page number tag which is in the pageflag column to be copied for all the text boxes in that page which in this case would be pageflag value in row 1 copied into row 9,10 and 11

For this purpose i am using Dataframe.shift using a condition something like this:

df['pageflag'] = np.where(df['pageflag']==0,df['pageflag'].shift(1),df['pageflag'])


It should be based on this condition so as to avoid the shift for rows which already have a value like in this case it is row 13 where a new page attribute is present.

The issue i am facing is that the shift occurs only for one row after the page number tag which in my case is row 9.row 10 and 11 will still have the value zero which is not what i was expecting.

This can be achieved using a for loop as below:

for i in range(1, len(df)):
if df['pageflag'][i] == 0:
df['pageflag'][i] = df['pageflag'][i - 1]
else:
df['pageflag'][i] = df['pageflag'][i]


but this is something i want to avoid due to performance issues for large dataframes.

Any suggestions on how this can be achieved in the most efficient way?

1 Answer
1

You can use pd.Series.ffill after converting your 0 values to NaN via pd.Series.mask:

pd.Series.ffill

0

NaN

pd.Series.mask

df['pageflag'] = df['pageflag'].mask(df['pageflag'] == 0).ffill()


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