drop a row while looping in pandas dataframe

Question

I want to drop a row in dataframe in loop/iteration after I use the row for some calculation and generate new rows , here is code for the iteration:

for i,row in df_1_filtered.iterrows():
    if row.notnull()['Slutdato']: 
        date_range =row['Slutdato']-row['Indrykningsdato']
        for d in range(date_range.days+1):
            #generate rows with data from the row
            df_temp=pd.DataFrame(data=d_t)
            df_1_filtered=df_1_filtered.append(df_temp)
       # if i dont have drop, the dataframe will have the row and generated rows 
        df_1_filtered.drop(df_1_filtered.index[i], inplace=True) 

If I put df_1_filtered.drop(df_1_filtered.index[i], inplace=True) befor the inner for loop, I will get a empty file , if i put df_1_filtered.drop(df_1_filtered.index[i], inplace=True) after the for loop. It remove all the rows that I have generate in the loop. Why is like that, what is the correct way to drop the row

Answer 1

I ended up with create a empty df and use if else to append all the rows.

df_spread_enddate=pd.DataFrame()
for i,row in df_1_filtered.iterrows():

    if row.notnull()['Slutdato']: 
        date_range =(row['Slutdato']-row['Indrykningsdato']).days+1
        b_avg=row['Bruttopris']/date_range
        n_abg=row['Net-net kunde']/date_range
        for d in range(date_range):
            #generate rows with data from the row
            df_temp=pd.DataFrame(data=d_t)
            df_spread_enddate=df_spread_enddate.append(df_temp)
        #df_1_filtered=df_1_filtered.drop(df_1_filtered.iloc[i:], inplace=True)
    else:
        df_spread_enddate=df_spread_enddate.append(row)