Unexpected output from df.loc when indexing by label

[deanhystad]

There is some weird multi-indexing thing going on with 2013.

If you look at the list of index values you'll see that 2013 is suspiciously absent even though it appears in the dataframe when printed.

Output:
Index(['2014', '2015', '2016', '2017', '2018', '2019', '2020', '2021', '2022',
       'Career', '7 yrs', '2 yrs', '1 yr'],
      dtype='object')
Year       Age   Tm  Pos  No.    G   GS  Pnt    Yds   Y/P RetYds    Net  NY/P Lng  TB    TB% In20  In20% Blck  AV
2013        23  DET    P    6   16    0   72   3399  47.2    250   2949  41.0  72  10  13.9%   22  30.6%    1   3
2014        24  DET    P  6.0   16  0.0   68   3138  46.1    311   2727  40.1  71   5   7.4%   29  42.6%    0   3
2015        25  DET    P  6.0   16  0.0   80   3679  46.0    263   3356  42.0  66   3   3.8%   25  31.3%    0   3
. . . 

Then printed a row.

Output:
df.loc['2017']
Year    2013 
Age     23          27
Tm      DET        DET
Pos     P            P

This series has 2 rows. The year, and 2013. If I print the '2022' row I see the same thing. The 2022 year values and the 2013 values.

Output:
df.loc['2022']
Year    2013 
Age     23          32
Tm      DET        BUF
Pos     P            P

Why this is happening is beyond my scope. I looked at the web page, but it is too complicated for me to understand how the tables are created and why they are messing up the dataframe