better way to create a new column instead of for loop

Question

is there any faster way to this code? i just want to calculate t_last - t_i and create a new column

time_ges = pd.DataFrame()
for i in range(0, len(df.GesamteMessung_Sec.index), 1):
    time = df.GesamteMessung_Sec.iloc[-1]-df.GesamteMessung_Sec.iloc[i]
    time_ges = time_ges.append(pd.DataFrame({'echte_Ladezeit': time}, index=[0]), ignore_index=True)

df['echte_Ladezeit'] = time_ges

this code takes a lot of computation time, is there any better way to do this? thanks, R

jezrael · Accepted Answer · 2018-10-16 13:10:31Z

2

You can subtract last value by column GesamteMessung_Sec and add to_frame for convert Series to DataFrame:

df = pd.DataFrame({'GesamteMessung_Sec':[10,2,1,5]})
print (df)
   GesamteMessung_Sec
0                  10
1                   2
2                   1
3                   5

time_ges = (df.GesamteMessung_Sec.iloc[-1] - df.GesamteMessung_Sec).to_frame('echte_Ladezeit')
print (time_ges )
   echte_Ladezeit
0              -5
1               3
2               4
3               0

If need new column of original DataFrame:

df = pd.DataFrame({'GesamteMessung_Sec':[10,2,1,5]})
df['echte_Ladezeit'] = df.GesamteMessung_Sec.iloc[-1] - df.GesamteMessung_Sec
print (df)
   GesamteMessung_Sec  echte_Ladezeit
0                  10              -5
1                   2               3
2                   1               4
3                   5               0

edited Oct 16, 2018 at 13:10

answered Oct 16, 2018 at 13:04

jezrael

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