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=',')