Calculate the percentage difference between two specific rows in Python pandas

Question

The problem is that I am trying to run a specific row I choose to calculate what percentage the specific row value is away from the intended outputs mean (which is already calculated from another column), to find what percentage it deviates from the intended outputs mean.

I want to run each item individually like so:

Below I made a dataframe column to store the result

df['pct difference'] = ((df['tertiary_tag']['price'] - df['ab roller']['mean'])/df['ab roller']['mean']) * 100 

For example, let's say the mean is 10 and I know that the item is 8 dollars, figure out whatever percentage away from the mean that product is and return that number for each items of that dataset. Return what percentage it deviates from the mean.

Keep in mind, the problem is not solved by a loop because I am sure pandas has something more practical to calculate the % difference not pct_change.

I also thought maybe to get the very specific row make a column as some indexing so I can use, and use that to access any row with in the columns by using that index and from indexing do my operation whatever you want for example to calculate difference in percentage between two rows?

I thought maybe through indexing the column of the price?

df = df.set_index(['price']) df.index = pd.to_datetime(df.index) 

Answer 1

def percent_diff(df, row1, row2):
    """
    Calculating the percentage difference between two specific rows in a dataframe
    """
    return (df.loc[row1, 'value'] - df.loc[row2, 'value']) / df.loc[row2, 'value'] * 100