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

DataFrame.sort is deprecated; use DataFrame.sort_values.

>>> df.sort_values(['c1','c2'], ascending=[False,True])
   c1   c2
0   3   10
3   2   15
1   2   30
4   2  100
2   1   20
>>> df.sort(['c1','c2'], ascending=[False,True])
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/ampawake/anaconda/envs/pseudo/lib/python2.7/site-packages/pandas/core/generic.py", line 3614, in __getattr__
    return object.__getattribute__(self, name)
AttributeError: 'DataFrame' object has no attribute 'sort'

Use of sort can result in warning message. See github discussion. So you might wanna use sort_values, docs here

Then your code can look like this:

df = df.sort_values(by=['c1','c2'], ascending=[False,True])

The dataframe.sort() method is - so my understanding - deprecated in pandas > 0.18. In order to solve your problem you should use dataframe.sort_values() instead:

f.sort_values(by=["c1","c2"], ascending=[False, True])

The output looks like this:

    c1  c2
    3   10
    2   15
    2   30
    2   100
    1   20

In my case, the accepted answer didn't work:

f.sort_values(by=["c1","c2"], ascending=[False, True])

Only the following worked as expected:

f = f.sort_values(by=["c1","c2"], ascending=[False, True])

If you are writing this code as a script file then you will have to write it like this:

df = df.sort(['c1','c2'], ascending=[False,True])

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

Note : Everything up here is correct,just replace sort --> sort_values() So, it becomes:

 import pandas as pd
 df = pd.read_csv('data.csv')
 df.sort_values(ascending=False,inplace=True)

Refer to the official website here.