Sample  Dog Cat Tarsier
A47 1   7   2
A48 3   3   4
A51 2   1   8
A53 0   0   0
A54 1   7   2
A57 0   0   10

Cat   Tarsier
A47    7       2

struct row{
    char *name;
    int animal[3]; //id 0 is dog, 1 is cat and 2 is tarsier
}

int i;
float sum=0; //we need float to force the result to be float
for (i=0;i<3;i++){
    sum += row.animal[i]; //count the total row population
}
for (i=0;i<3;i++){ //for every animal
    if (row.animal[i]/sum <= 0.1){ //if this animal is equal or less than 10% of the row population
        row.animal[i]=0; //set his population to 0
    }
}

import csv

def getvals(file):
    """
        gets the val's from a file of whitespace separated values, and
        turns them into easy to use Python var's
    """
    samples = csv.reader(open(file))
    s = []
    n = 0
    for row in samples:
        r = [row[0].split()]
        s += r
        n+=1
    return s

[
 ['Sample', 'Dog', 'Cat', 'Tarsier'],
 ['A47', '1', '7', '2'],
 ['A48', '3', '3', '4'],
 ['A51', '2', '1', '8'],
 ['A53', '0', '0', '0'],
 ['A54', '1', '7', '2'],
 ['A57', '0', '0', '10']
]

>>> data = np.genfromtxt('data.txt', delimiter="t", names=True, dtype=None)

data = array([('A47', 1, 7, 2), ('A48', 3, 3, 4), ('A51', 2, 1, 8),
       ('A53', 0, 0, 0), ('A54', 1, 7, 2), ('A57', 0, 0, 10)],
      dtype=[('Sample', '|S3'), ('Dog', '<i8'), ('Cat', '<i8'), ('Tarsier', '<i8')])

>>> data[["Cat","Tarsier"]]
array([(7, 2), (3, 4), (1, 8), (0, 0), (7, 2), (0, 10)],
  dtype=[('Cat', '<i8'), ('Tarsier', '<i8')])

>>> data[[0,2]]
array([('A47', 1, 7, 2), ('A51', 2, 1, 8)],
     dtype=[('Sample', '|S3'), ('Dog', '<i8'), ('Cat', '<i8'), ('Tarsier', '<i8')])

>>> data["Dog"].mean()
1.1666667