How to sort pandas data frame using values from several columns?

Question

I have the following data frame:

df = pandas.DataFrame([{\'c1\':3,\'c2\':10},{\'c1\':2, \'c2\':30},{\'c1\':1,\'c2\':20},{\'c1\':2,\'c2\':15},{\'c1\':2,\'c2\'         


        

Answer 1

I have found this to be really useful:

df = pd.DataFrame({'A' : range(0,10) * 2, 'B' : np.random.randint(20,30,20)})

# A ascending, B descending
df.sort(**skw(columns=['A','-B']))

# A descending, B ascending
df.sort(**skw(columns=['-A','+B']))

Note that unlike the standard columns=,ascending= arguments, here column names and their sort order are in the same place. As a result your code gets a lot easier to read and maintain.

Note the actual call to .sort is unchanged, skw (sortkwargs) is just a small helper function that parses the columns and returns the usual columns= and ascending= parameters for you. Pass it any other sort kwargs as you usually would. Copy/paste the following code into e.g. your local utils.py then forget about it and just use it as above.

# utils.py (or anywhere else convenient to import)
def skw(columns=None, **kwargs):
    """ get sort kwargs by parsing sort order given in column name """
    # set default order as ascending (+)
    sort_cols = ['+' + col if col[0] != '-' else col for col in columns]
    # get sort kwargs
    columns, ascending = zip(*[(col.replace('+', '').replace('-', ''), 
                                False if col[0] == '-' else True) 
                               for col in sort_cols])
    kwargs.update(dict(columns=list(columns), ascending=ascending))
    return kwargs