Finding top N columns for each row in data frame

Question

given a data frame with one descriptive column and X numeric columns, for each row I\'d like to identify the top N columns with the higher values and save it as rows on a ne

Answer 1

This might not be so elegant, but I think it pretty much gets what you want:

n = 3
df.index = pd.Index(df['index'])
del df['index']
df = df.transpose().unstack()
for i, g in df.groupby(level=0):
    g = g.sort_values(ascending=False)
    print i, list(g.index.get_level_values(1)[:n])