In python, there are multiple solutions to read a csv (comma separated values) file:

Important note: use only numpy to read a csv file if it contains only one type of data (for example a csv file with numbers only). If the csv file contains columns with different types like strings and integers, a better solution is to pandas then, see how to read a csv file using pandas in python

### Read a csv file using numpy loadtxt

Let's try to read the following github csv file:

`https://raw.githubusercontent.com/edbullen/Hypothesis/master/ages.csv`

to do that a solution is to use loadtxt:

`ages = np.loadtxt('https://raw.githubusercontent.com/edbullen/Hypothesis/master/ages.csv', skiprows=0, delimiter=',')`

returns here

`array([32., 34., 29., 29., 22., 39., 38., 37., 38., 36., 30., 26., 22.,`

`22.])`

Notes that:

`type(ages)`

returns

`numpy.ndarray`

and

`ages.dtype`

returns

`dtype('float64')`

### Read a csv file using numpy genfromtxt

Another solution is to use genfromtxt

`ages = np.genfromtxt('https://raw.githubusercontent.com/edbullen/Hypothesis/master/ages.csv', delimiter=',')`