That’s how I’d do it: import os directory = os.path.join(“c:\\”,”path”) for root,dirs,files in os.walk(directory): for file in files: if file.endswith(“.csv”): f=open(file, ‘r’) # perform calculation f.close()
You can use pandas (the becoming default library for working with dataframes (heterogeneous data) in scientific python) for this. It’s read_csv can handle this. From the docs: quotechar : string The character to used to denote the start and end of a quoted item. Quoted items can include the delimiter and it will be ignored. … Read more
What is returned is called a structured ndarray, see e.g. here: http://docs.scipy.org/doc/numpy/user/basics.rec.html. This is because your data is not homogeneous, i.e. not all elements have the same type: the data contains both strings (the first two columns) and floats. Numpy arrays have to be homogeneous (see here for an explanation). The structured array ‘solves’ this … Read more
Use numpy.genfromtxt() by setting the delimiter kwarg to a comma: from numpy import genfromtxt my_data = genfromtxt(‘my_file.csv’, delimiter=”,”)