How to Convert a NumPy Array to a CSV File in Python?

How to write a NumPy array to a CSV file in Python?

To write a NumPy array to a CSV file, use the np.savetxt() function and pass the filename as a string, as well as the array into it. Optionally, you can specific the file format, the delimiter such as comma or semicolon, and other arguments to obtain the desired file format.

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Let’s dive into this and other approaches to “dump” a NumPy array to a CSV file.

Method 1: np.savetxt()

To write a NumPy array to a CSV file, use the np.savetxt(filename, array, delimiter=',') function and pass the filename as a string, the array, and the delimiter into it.

Here’s an example:

import numpy as np

a = np.array([[1, 2, 3], [4, 5, 6]])
np.savetxt('my_file.csv', a, delimiter=',')

If you open the file, it looks like this:

All values are automatically converted into a floating point representation that may not be what you have expected.

Method 2: np.savetxt() with format specification

The np.savetxt() function allows you to specify the desired format of the values to be written in the file using the fmt argument. To write a NumPy array to a file, you can use the expression np.savetxt('my_file.csv', a, fmt='%.1f', delimiter=','). Unlike the default formatting, this will not use the scientific data type notation with a gazillion precision.

Here’s the simplified code to convert the array to a formatted CSV:

import numpy as np

a = np.array([[1, 2, 3], [4, 5, 6]])
np.savetxt('my_file.csv', a, fmt='%.1f', delimiter=',')

This code snippet leads to the following simplified output (CSV):

Optionally, you can specific the file format, the delimiter such as comma or semicolon, and other arguments to obtain the desired file format.

Method 3: Pandas to_csv()

The pandas.to_csv() function converts a DataFrame to a CSV file. The most simple way is to call the function on the DataFrame to be written in the file, and passing the filename and index=False into it to avoid using a column header line. To obtain the DataFrame from the NumPy array, use the pandas.DataFrame(array) constructor.

Here’s a minimal example:

import numpy as np
import pandas as pd

a = np.array([[1, 2, 3], [4, 5, 6]])
df = pd.DataFrame(a)
df.to_csv('my_file.csv', index=False)

The output is the following CSV file:

Method 4: NumPy array.tofile()

When used with a separator argument sep, the NumPy array.tofile(filename, sep=',') method writes the array to a file as a textual representation. The multi-dimensional array is flattened before it is written in the file.

Here’s an example for a 2D array:

import numpy as np

a = np.array([[1, 2, 3], [4, 5, 6]])
a.tofile('my_file.csv', sep=',')

Output file:

To show you that the array is indeed flattened before written in the file, here’s an example for a 3D array:

import numpy as np

a = np.array([[[1, 2, 3], [4, 5, 6]],
              [[7, 8, 9], [0, 0, 0]]])
a.tofile('my_file.csv', sep=',')

Output file:

Method 5: Vanilla Python with File I/O and Python Tricks

To write the array to a CSV in Python, you can iterate over each row in the array and use the print() function’s file argument to append the row to the output file.

To find a comma-separated representation of the row, simply unpack all row values into the print() function using the asterisk operator *row and use the separator argument sep=','.

Here’s how that looks like:

import numpy as np

a = np.array([[1, 2, 3], [4, 5, 6]])

with open('my_file.csv', 'w') as out:
    for row in a:
        print(*row, sep=',', file=out)

The output is as clean as it can get:

Summary

We proposed the following five ways to write a NumPy array to a CSV file: