How to Convert a CSV to NumPy Array in Python?

Problem Formulation

Given a CSV file (e.g., stored in the file with name 'my_file.csv').

INPUT: file 'my_file.csv'
9,8,7
6,5,4
3,2,1

Challenge: How to convert it to a NumPy Array?

OUTPUT: 2D NumPy Array
[[9. 8. 7.]
 [6. 5. 4.]
 [3. 2. 1.]]

Method 1: np.loadtxt()

You can convert a CSV file to a NumPy array simply by calling np.loadtxt() with two arguments: the filename and the delimiter string. For example, the expression np.loadtxt('my_file.csv', delimiter=',') returns a NumPy array from the 'my_file.csv' with delimiter symbols ','.

Here’s an example:

import numpy as np

array = np.loadtxt('my_file.csv', delimiter=',')
print(array)

Output:

[[9. 8. 7.]
 [6. 5. 4.]
 [3. 2. 1.]]

Method 2: np.loadtxt() with Header

You can convert a CSV file with first-line header to a NumPy array by calling np.loadtxt() with three arguments: the filename, skiprows=1 to skip the first line (header), and the delimiter string. For example, the expression np.loadtxt('my_file.csv', skiprows=1, delimiter=',') returns a NumPy array from the 'my_file.csv' with delimiter symbols ',' while skipping the first line.

Here’s an example:

import numpy as np

array = np.loadtxt('my_file.csv', skiprows=1, delimiter=',')
print(array)

Output:

[[9. 8. 7.]
 [6. 5. 4.]
 [3. 2. 1.]]

Method 3: CSV Reader

To convert a CSV file 'my_file.csv' into a list of lists in Python, use the csv.reader(file_obj) method to create a CSV file reader. Then convert the resulting object to a list using the list() constructor. As a final step, you can convert the nested list to a NumPy array by using the np.array(list) constructor.

Here’s an example:

import numpy as np
import csv


csv_filename = 'my_file.csv'

with open(csv_filename) as f:
    reader = csv.reader(f)
    lst = list(reader)
    print(lst)

The output is the list of lists:

[['9', '8', '7'], ['6', '5', '4'], ['3', '2', '1']]

Now, if you need to convert it to a NumPy array, you can simply use the np.array() function on the newly-created list like so:

array = np.array(lst)
print(array)

Output:

[['9' '8' '7']
 ['6' '5' '4']
 ['3' '2' '1']]

🌎 Related Tutorial: How to Convert CSV to List of Lists in Python

Method 4: np.genfromtxt()

You can convert a CSV file to a NumPy array simply by calling np.genfromtxt() with two arguments: the filename and the delimiter string. For example, the expression np.genfromtxt('my_file.csv', delimiter=',') returns a NumPy array from the 'my_file.csv' with delimiter symbol ','.

Here’s an example:

import numpy as np

array = np.loadtxt('my_file.csv', delimiter=',')
print(array)

Output:

[[9. 8. 7.]
 [6. 5. 4.]
 [3. 2. 1.]]

Method 5: Pandas read_csv() and df.to_numpy()

A quick and efficient way to read a CSV to a NumPy array is to combine Pandas’ pd.read_csv() function to read a given CSV file to a DataFrame with the df.to_numpy() function to convert the Pandas DataFrame to a NumPy array.

Here’s an example:

import pandas as pd

df = pd.read_csv('my_file.csv', header=None)
array = df.to_numpy()

print(array)

Output:

[[9 8 7]
 [6 5 4]
 [3 2 1]]

🌎 Related Tutorial: 17 Ways to Read a CSV File to a Pandas DataFrame

Summary

We have seen five ways to convert a CSV file to a 2D NumPy array:

• Method 1: np.loadtxt()
• Method 2: np.loadtxt() with Header
• Method 3: CSV Reader
• Method 4: np.genfromtxt()
• Method 5: Pandas read_csv() and df.to_numpy()

Our preferred way is np.loadtxt() for its simplicity and Pandas for its extensibility.

More Python CSV Conversions

🐍 Learn More: I have compiled an “ultimate guide” on the Finxter blog that shows you the best method, respectively, to convert a CSV file to JSON, Excel, dictionary, Parquet, list, list of lists, list of tuples, text file, DataFrame, XML, NumPy array, and list of dictionaries.