Build table from for loop values

Question

I have a for loop that does calculations from multiple columns in a dataframe with multiple criteria that prints float values I need to arrange in a table.

   demolist = ['P13+', 'P18-34']
   impcount = ['<1M', '1-5M']
   for imp in impcount:
        print(imp)
        for d in demolist:
            print(d)
            target_ua = df.loc[(df['target'] == d) & (df['IMP Count'] == imp), 'in_target_ua_digital'].sum()
            target_pop = df.loc[(df['target'] == d) & (df['IMP Count'] == imp), 'in_target_pop'].sum()

            target_reach = target_ua / target_pop
            print(target_reach)

The output looks like this:

<1M
P13+
0.10
P18-34
0.12
1-5M
P13+
0.92
P18-34
0.53

The code is working correctly, but I need the output to be arranged in a new dataframe with impcount in the columns and demolist in the rows

         <1M        1-5M
P13+     0.10       0.92
P18-34   0.12       0.53

rojeeer · Accepted Answer · 2017-08-11 23:12:19Z

It is just a matter of how to arrange your data. A table is a 2D data structure, which is often represented as a list of list (tuple) in python, e.g. [[1,2], [3, 4]]. For your case, you could collect your data row by row to build the table data, meaning that generate a tuple or list for each element of the row, then for the whole row we get a list of list (the table).

Here is an example showing how to form a table when each value of each cell could be calculated (here is a random value)

In [53]: x = list('abc')
    ...: y = list('123')
    ...: 
    ...: data=[]
    ...: for i in x:
    ...:     row=[]
    ...:     for j in y:
    ...:         row.append(np.random.rand())
    ...:     data.append(row)
    ...: 
    ...: df = pd.DataFrame(data, index=x, columns=y)
    ...: 

In [54]: df
Out[54]: 
          1         2         3
a  0.107659  0.840387  0.642285
b  0.184508  0.641443  0.475105
c  0.503608  0.379945  0.933735

Vladimir Shevyakov · Accepted Answer · 2017-08-11 22:53:39Z

0

Try this:

demolist = ['P13+', 'P18-34']
impcount = ['<1M', '1-5M']

imp_str = '\t'
for imp in impcount:
    imp_str += imp + '\t'
print(imp_str.rstrip())

imp_counter = 0
for imp in impcount:
    demo_str = demolist[imp_counter]+'\t'
    for d in demolist:
        target_ua = df.loc[(df['target'] == d) & (df['IMP Count'] == imp), 'in_target_ua_digital'].sum()
        target_pop = df.loc[(df['target'] == d) & (df['IMP Count'] == imp), 'in_target_pop'].sum()
        target_reach = target_ua / target_pop
        demo_str += str(target_reach)+'\t'
    print(demo_str.rstrip())
    imp_counter += 1

Hope this helps!

answered Aug 11, 2017 at 22:53

Vladimir Shevyakov

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