Pandas series sort by month index

Answer 1

You can use sorted CategoricalIndex with sort_index:

cats = ['Jan', 'Feb', 'Mar', 'Apr','May','Jun', 'Jul', 'Aug','Sep', 'Oct', 'Nov', 'Dec']
df.index = pd.CategoricalIndex(df.index, categories=cats, ordered=True)
df = df.sort_index()

print (df)
     date
Jan     2
Feb     1
Apr     1
May     1
Jun     1
Jul     1
Aug     2
Sep     2
Oct    14
Nov    36
Dec    47

Or use DataFrame.reindex - but if some value is missing add NaNs rows:

df = df.reindex(cats)

Answer 2

Adding to the very helpful answer by @jezrael:

In pandas 0.25.1 sorted has been replaced by ordered per pandas.CategoricalIndex

Old way:

df.index = pd.CategoricalIndex(df.index, 
                               categories=['Jan', 'Feb', 'Mar', 'Apr','May','Jun', 'Jul', 'Aug','Sep', 'Oct', 'Nov', 'Dec'], 
                               sorted=True)
df = df.sort_index()

Error

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-468-3f0ab66734d4> in <module>
      2 net.index = pd.CategoricalIndex(net.index, 
      3                                categories=['Jan', 'Feb', 'Mar', 'Apr','May','Jun', 'Jul', 'Aug','Sep', 'Oct', 'Nov', 'Dec'],
----> 4                                sorted=True)
      5 net = net.sort_index()
      6 net

TypeError: __new__() got an unexpected keyword argument 'sorted'

New way:

df.index = pd.CategoricalIndex(df.index, 
                               categories=['Jan', 'Feb', 'Mar', 'Apr','May','Jun', 'Jul', 'Aug','Sep', 'Oct', 'Nov', 'Dec'], 
                               ordered=True)
df = df.sort_index()

Answer 3

Okay it was not very complex. I'm sure Categorical would have worked just that I was unable to solve the problem using Categorical. What I did was-

1. Sort by month while months were being represented as integers
2. To the resulting series applied a mapper on the index to convert the integer month into an abbreviated string

I'm sure there are more efficient ways of solving this, so if you have a better way please post the same.

    import calendar
    months = release_dates[release_dates.title.str.contains('Christmas') & (release_dates.country=='USA')].date.dt.month
    counts = months.value_counts()
    counts.sort_index(inplace=True)
    counts.index = map(lambda x: calendar.month_abbr[x], counts.index)
    counts.plot.bar()