How To Calculate Percent Change Compared To The Beginning Value Using Pandas?

I have a DataFrame and need to calculate percent change compared to the beginning of the year by companies. Is there any way to use pct_change() or other method to perform this tas

Solution 1:

Sounds like you are looking for an expanding_window version of pct_change(). This doesn't exist out of the box AFAIK, but you could roll your own:

df.groupby('security')['price'].apply(lambda x: x.div(x.iloc[0]).subtract(1).mul(100))

Solution 2:

This works, assuming you're already ordered by date within each possible grouping.

def pct_change(df):
    df['pct'] = 100 * (1 - df.iloc[0].price / df.price)
    returndf

df.groupby('security').apply(pct_change)

Solution 3:

I had the same problem, but solved it his way:

(only difference was that the columns would be your company and not the row.)

for each column of my dataframe I did:

df[column] = df[column].pct_change().cumsum()

pct_change() calculates the change between now and the last value, and cumcum() adds it all together.