Python – Pandas – Count the number of lines of the function – for each input line

I have a data frame that needs to be added to a column. The column needs to be the count of all other rows in the table that meet the criteria that accept input from the Input row and the Output row.

For example, if it is a data frame describing people, I want to make a column to count how many people are taller and lighter than the current row.

I want the height and weight of the row, and the

height and weight of the other rows in the function, so I can do this:

def example_function(height1, weight1, height2, weight2):
    if height1 > height2 and weight1 < weight2:
        return True
    else:
        return False

It summarizes all True and gives that sum in the column.

Is such a thing possible?

Thanks in advance for any ideas!

Edit: Example input:

id   name    height   weight   country
0    Adam    70       180      USA
1    Bill    65       190      CANADA
2    Chris   71       150      GERMANY
3    Eric    72       210      USA
4    Fred    74       160      FRANCE
5    Gary    75       220      MEXICO
6    Henry   61       230      SPAIN

The result needs to be:

id   name    height   weight   country   new_column
0    Adam    70       180      USA       1
1    Bill    65       190      CANADA    1
2    Chris   71       150      GERMANY   3
3    Eric    72       210      USA       1
4    Fred    74       160      FRANCE    4
5    Gary    75       220      MEXICO    1
6    Henry   61       230      SPAIN     0

I

believe it needs some kind of functionality because the actual logic I need to use is more complicated.

Edit 2: Fix typos

You can add the bool value like this:

count = ((df.height1 > df.height2) & (df.weight1 < df.weight2)).sum()

Edit:

I tested it a bit and then changed the condition with a custom function:

def f(x):
    #check boolean mask 
    #print ((df.height > x.height) & (df.weight < x.weight))
    return ((df.height < x.height) & (df.weight > x.weight)).sum()

df['new_column'] = df.apply(f, axis=1)
print (df)
   id   name  height  weight  country  new_column
0   0   Adam      70     180      USA           2
1   1   Bill      65     190   CANADA           1
2   2  Chris      71     150  GERMANY           3
3   3   Eric      72     210      USA           1
4   4   Fred      74     160   FRANCE           4
5   5   Gary      75     220   MEXICO           1
6   6  Henry      61     230    SPAIN           0

Explanation:

For each row, compare the value and count the simple sum value True.