apply a function to a pandas Dataframe whose returned value is based on other rows

Question

I have a Dataframe looking like this:

>>> import pandas
>>> df = pandas.DataFrame({\'region\' : [\'east\', \'west\', \'south\', \'west\',
.         


        

Answer 1

Ok, I think this does what you want:

Make a dictionary of your regional weights:

In [1]: weights = {'east':1,'west':2,'south':3}

The following function maps values from a Series to the value found in the weights dictionary. x is the row value of region and w is the region series after it has been mapped to the weights dict.

In [2]: def f(x):
   ...:     w = x.map(weights)
   ...:     return w / w.sum().astype(float)

Here, we groupby ['item','price'] and apply the function above. The output is a series of relative weights for the unique combinations of item and price.

In [3]: df.groupby(['item','price']).region.apply(f)
Out[3]:
0    0.333333
1    0.666667
2    1.000000
3    1.000000
4    0.333333
5    0.666667
6    1.000000
7    1.000000

Finally, you can multiply df.quantity by the above series to calculate your weight-adjusted quantities.

In [4]: df['wt_quant'] = df.groupby(['item','price']).region.apply(f) * df.quantity

In [5]: df
Out[5]:
    item  price  quantity region  wt_quant
0    one     50         3   east  1.000000
1    one     50         3   west  2.000000
2    two     12         4  south  4.000000
3  three     35         5   west  5.000000
4    two     10        12   east  4.000000
5    two     10        14   west  9.333333
6    one     12         3   east  3.000000
7  three     12         8   west  8.000000