pandas Series.value_counts returns inconsistent order for equal count strings

Question

When I run the code below:

s = pandas.Series([\'c\', \'a\', \'b\', \'a\', \'b\'])
print(s.value_counts())

Sometimes I get this:

<         


        

Answer 1

You could use sort_index:

print(df.value_counts().sort_index())

Output:

a    1
b    1
dtype: int64

Please see the documentation if you want to use parameters (like ascending=True etc.)

sort_index vs reindex(df.unique()) (as suggested by @Wen) seem to be perform quite similar:

df.value_counts().sort_index():         1000 loops, best of 3: 636 µs per loop
df.value_counts().reindex(df.unique()): 1000 loops, best of 3: 880 µs per loop