Question

I have data stored in a CSV where the first row is strings (column names) and the remaining rows are numbers. How do I store this to a numpy array? All I can find is how to set data type for columns but not for rows.

Right now I’m just skipping the headers to do the calculations but I need to have the headers in the final version. But if I leave the headers in it sets the whole array as string and the calculations fail.

This is what I have:

 data = np.genfromtxt(path_to_csv, dtype=None, delimiter=',', skip_header=1) 

Answer 1

You can keep the column names if you use the names=True argument in the function np.genfromtxt

 data = np.genfromtxt(path_to_csv, dtype=float, delimiter=',', names=True) 

Please note the dtype=float, that will convert your data to float. This is more efficient than using dtype=None, that asks np.genfromtxt to guess the datatype for you.

The output will be a structured array, where you can access individual columns by their name. The names will be taken from your first row. Some modifications may occur, spaces in a column name will be changed to _ for example. The documentation should cover most questions you could have.