How to make a normalizated series from pandas dataframe?

user_15772472 0
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I have the following code:

df = pd.DataFrame({
    'FR': [4.0405, 4.0963, 4.3149, 4.500],
    'GR': [1.7246, 1.7482, 1.8519, 4.100],
    'IT': [804.74, 810.01, 860.13, 872.01]},
    index=['1980-04-01', '1980-03-01', '1980-02-01', '1980-01-01'])

df = df.iloc[::-1]

df2 = df.pct_change()

df2 = df2.iloc[::-1]
df = df.iloc[::-1]

last=100
serie = []
serie.append(last)

for i in list(df.index.values[::-1][1:]):
    last = last*(1+df2['FR'][i])
    serie.append(last)                    
serie

I got what i expected:

[100, 95.88666666666667, 91.02888888888891, 89.7888888888889]

but i look for a more simple way to do that.

thanks

pandas dataframe normalization
1 Answers

Try with cumprod:

df.iloc[::-1].pct_change().add(1).fillna(1).cumprod()

Output:

                  FR        GR        IT
1980-01-01  1.000000  1.000000  1.000000
1980-02-01  0.958867  0.451683  0.986376
1980-03-01  0.910289  0.426390  0.928900
1980-04-01  0.897889  0.420634  0.922856
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