×

Python Tutorial

Python Basics

Python I/O

Python Operators

Python Conditions & Controls

Python Functions

Python Strings

Python Modules

Python Lists

Python OOPs

Python Arrays

Python Dictionary

Python Sets

Python Tuples

Python Exception Handling

Python NumPy

Python Pandas

Python File Handling

Python WebSocket

Python GUI Programming

Python Image Processing

Python Miscellaneous

Python Practice

Python Programs

How to read CSV data into a record array in NumPy?

In this tutorial, we will learn how to read CSV data into a record array in NumPy? By Pranit Sharma Last updated : May 23, 2023

CSV files or Comma Separated Values files are plain text files but the format of CSV files is tabular in nature. As the name suggests, in a CSV file, each specific value inside the CSV file is generally separated by a comma. The first line identifies the name of a data column. The further subsequent lines identify the values in rows.

Col_1_value, col_2_value , col_3_value
Row1_value1 , row_1_value2 , row_1_value3
Row1_value1 , row_1_value2 , row_1_value3

Here, the separator character (,) is called a delimiter. There are some more popular delimiters. E.g.: tab(\t), colon (:), semi-colon (;) etc.

Reading CSV data into a record array in NumPy

To read CSV data into a record array in NumPy, you can use pandas.read_csv() by passing the file name in it. The method reads a comma-separated values (csv) file into DataFrame and then convert it into an array.

Let us understand with the help of an example,

Python program to read CSV data into a record array in NumPy

# Import numpy
import numpy as np

# Import pandas
import pandas as pd

# Load csv file
data = pd.read_csv('appended_csv.csv')

# Display Original data
print("Original Data:\n",data,"\n")

# converting data into array
res = data.values

# Display Result
print("Result:\n",res,"\n")

Output

The output of the above program is:

Example: How to read CSV data into a record array in NumPy?frame

Python NumPy Programs »

Advertisement
Advertisement

Comments and Discussions!

Load comments ↻


Advertisement
Advertisement
Advertisement

Copyright © 2025 www.includehelp.com. All rights reserved.