遍历 Pandas Dataframe 值和索引

Question

I've got the following dataframe:

and, for every column in the dataframe, I'm attempting to calculate the following equations relating to simple linear regression:
These formulas require me to be able to reference both the values in each column (x_i) and their row index/name (y_i), along with the mean of both the row indices and the actual column values. How can I do this? I know that it's a rule of thumb never to iterate over a dataframe, but, given the small size of this frame, I really don't care how it's done.

Answer 1

You could do it via an apply() function. You can access the 'x' values and the 'y' value (index) for each row.

Sample DataFrame:

df = pd.DataFrame(index=range(1920, 1931), data={'AUS': range(15,26), 'CAN': range(12,23)})
df

      AUS  CAN
1920   15   12
1921   16   13
1922   17   14
1923   18   15
1924   19   16
1925   20   17
1926   21   18
1927   22   19
1928   23   20
1929   24   21
1930   25   22

Then access then values for each row in an apply() function:

df.apply(lambda x: [x.name, x['AUS'], x['CAN']], axis=1)

1920    [1920, 15, 12]
1921    [1921, 16, 13]
1922    [1922, 17, 14]
1923    [1923, 18, 15]
1924    [1924, 19, 16]
1925    [1925, 20, 17]
1926    [1926, 21, 18]
1927    [1927, 22, 19]
1928    [1928, 23, 20]
1929    [1929, 24, 21]
1930    [1930, 25, 22]

Knocking out those equations will be up to you.