Exclude Columns from pandas .mean()

Question

I have a df that contains the rank of each team in a given stat for the given year. It looks like this:

teamID  yearID  W   L   IP  WHIP    K%  BB% HR/9    ERA FIP ERA-    FIP-    K/BB+   WHIP+   K%+ BB%+    WAR
1209    Athletics   2001.0  2.0 6.0 3.0 7.0 19.0    9.0 1.0 7.0 5.0 7.0 5.0 8.0 7.0 11.0    10.0    4.0

I want to create a column with the average rank for each row, but doing df.mean(axis=1) includes the year (2001) and really throws the number off. Anybody know how to get a round this with maybe a lambda and .apply(), or is there a kwarg that can exclude certain columns? I haven't found one. I want to do this across years so that is why the yearID column is necessary.

Answer 1

Simply exclude it from your calc using loc[] and a comprehension on the columns.

df = pd.read_csv(io.StringIO("""teamID  yearID  W   L   IP  WHIP    K%  BB% HR/9    ERA FIP ERA-    FIP-    K/BB+   WHIP+   K%+ BB%+    WAR
1209    Athletics   2001.0  2.0 6.0 3.0 7.0 19.0    9.0 1.0 7.0 5.0 7.0 5.0 8.0 7.0 11.0    10.0    4.0"""), sep="\s+")

df["mean"] = df.loc[:,[c for c in df.columns if c!= "yearID"]].mean(axis=1)

output

         teamID  yearID    W    L   IP  WHIP    K%  BB%  HR/9  ERA  FIP  ERA-  FIP-  K/BB+  WHIP+   K%+  BB%+  WAR    mean
1209  Athletics  2001.0  2.0  6.0  3.0   7.0  19.0  9.0   1.0  7.0  5.0   7.0   5.0    8.0    7.0  11.0  10.0  4.0  6.9375