For example,
df = pd.DataFrame({'x':[1,1,1,2,3,3], 'y':['a','a','c','b','b','b']})
ct = pd.crosstab(df.x, df.y)
ct
y a b c
x
1 2 0 1
2 0 1 0
3 0 2 0
How do I sort the columns of ct based on the values in row1, row2, and row3 (in that order of priority)?
I've tried the following, neither of which work
ct.sort_values([1, 2, 3], axis=1)
ct.sort_values(['1','2','3'], axis=1)
This cannot currently be done with a direct call to sort_values. There is an open bug report about it.
You can still do it less nicely by transposing, sorting by columns, then transposing again:
>>> ct.T.sort_values([1, 2, 3]).T
y b c a
x
1 0 1 2
2 1 0 0
3 2 0 0
This should sort them in order of a>b>c:
df = pd.DataFrame({'x':[1,1,1,2,3,3], 'y':['a','a','c','b','b','b']})
ct = pd.crosstab(df.x, df.y)
y a b c
x
1 2 0 1
2 0 1 0
3 0 2 0
sorted_df = pd.DataFrame(ct.sort_values(by = ['a','b','c'], ascending = [False,False,False]))
y a b c
x
1 2 0 1
3 0 2 0
2 0 1 0
