Sorting the order of bars in pandas/matplotlib bar plots

I know this response is late, but a simplistic solution to the two cases presented, without use of a dictionary/mappings would be something like I've posted below.

Setting 'day' as an index enables you to use .loc to select data in a specific order

1) For the two separate plots

df=pd.DataFrame({'group':['a','a','a','a','a','a','a','b','b','b','b','b','b','b'],
     'day':['Mon','Tues','Fri','Thurs','Sat','Sun','Weds','Fri','Sun','Thurs','Sat','Weds','Mon','Tues'],
     'amount':[1,2,4,2,1,1,2,4,5,3,4,2,1,3]})

order = ['Mon', 'Tues', 'Weds','Thurs','Fri','Sat','Sun']`
df.set_index('day').loc[order].groupby('group').plot(kind='bar')

2) For the pivot example with the dodged plot:

order = ['Mon', 'Tues', 'Weds','Thurs','Fri','Sat','Sun']
df.pivot('day','group','amount').loc[order].plot(kind='bar')

note that pivot results in day being in the index already so you can use .loc here again.

Edit: it is best practice to use .loc instead of .ix in these solutions, .ix will be deprecated and can have weird results when column names and indexes are numbers.

You'll have to provide a mapping to specify how to order the day names. (If they were stored as proper dates, there would be other ways to do this.)

Updated:

Build the key. You could write out a dictionary explicitly or use something clever like this dict comprehension.

weekdays = ['Mon', 'Tues', 'Weds', 'Thurs', 'Fri', 'Sat', 'Sun']
mapping = {day: i for i, day in enumerate(weekdays)}
key = df['day'].map(mapping)

And the sorting is simple:

df.iloc[key.argsort()]