A slice of my dataframe, df, is like this, so you can reproduce it.
data ={'feature_name': ['nite', 'thank', 'ok', 'havent', 'done', 'beverage', 'yup', 'lei','thanx', 'okie', '146tf150p', 'home', 'too', 'anytime',
'where', '645', 'er', 'tick', 'blank'], 'values':[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.98, 0.98] }
df = pd.DataFrame(data)
df.set_index('feature_name',inplace=True)
dfs=df.sort_index(ascending=True).sort_values(by = ['values'], ascending=False)
dfs
my output is this.
values
feature_name
146tf150p 1.00
645 1.00
where 1.00
too 1.00
thanx 1.00
thank 1.00
okie 1.00
ok 1.00
nite 1.00
lei 1.00
home 1.00
havent 1.00
er 1.00
done 1.00
beverage 1.00
anytime 1.00
yup 1.00
blank 0.98
tick 0.98
I do not quite understand why it is not like this? It really should work yet it does not work as expected.
146tf150p 1.00
645 1.00
anytime 1.00
beverage 1.00
done 1.00
er 1.00
haven't 1.00
home 1.00
...
How can I fix this?
Get rid of the set_index and use sort_values on both values and feature_name:
print (df.sort_values(by = ['values',"feature_name"], ascending=(False, True)))
feature_name values
10 146tf150p 1.00
15 645 1.00
13 anytime 1.00
5 beverage 1.00
4 done 1.00
16 er 1.00
3 havent 1.00
11 home 1.00
7 lei 1.00
0 nite 1.00
2 ok 1.00
9 okie 1.00
1 thank 1.00
8 thanx 1.00
12 too 1.00
14 where 1.00
6 yup 1.00
18 blank 0.98
17 tick 0.98