How do I read CSV data into a record array in NumPy?

Question

I wonder if there is a direct way to import the contents of a CSV file into a record array, much in the way that R\'s read.table(), read.delim(), a

Answer 1

I would recommend the read_csv function from the pandas library:

import pandas as pd
df=pd.read_csv('myfile.csv', sep=',',header=None)
df.values
array([[ 1. ,  2. ,  3. ],
       [ 4. ,  5.5,  6. ]])

This gives a pandas DataFrame - allowing many useful data manipulation functions which are not directly available with numpy record arrays.

DataFrame is a 2-dimensional labeled data structure with columns of potentially different types. You can think of it like a spreadsheet or SQL table...

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I would also recommend genfromtxt. However, since the question asks for a record array, as opposed to a normal array, the dtype=None parameter needs to be added to the genfromtxt call:

Given an input file, myfile.csv:

1.0, 2, 3
4, 5.5, 6

import numpy as np
np.genfromtxt('myfile.csv',delimiter=',')

gives an array:

array([[ 1. ,  2. ,  3. ],
       [ 4. ,  5.5,  6. ]])

and

np.genfromtxt('myfile.csv',delimiter=',',dtype=None)

gives a record array:

array([(1.0, 2.0, 3), (4.0, 5.5, 6)], 
      dtype=[('f0', '

This has the advantage that file with multiple data types (including strings) can be easily imported.