Python add row to array

Add a new row to an empty numpy array in Python

This tutorial will cover how we can generate an empty NumPy array, and various methods to add specific rows to this empty array in Python.

Create an empty Numpy Array and append rows in Python

We will do this using three different methods. Let’s see them one by one.

Method 1: Using numpy.append()

There are occasions when we need to append rows to an empty array. By utilizing the numpy.append() function, Numpy gives the ability to append a row to an empty Numpy array.

Example: Adding new rows to an empty 2-D array

import numpy as np #creating a 2D empty array empty= np.empty((0,2), int) # printing empty array print("The array : ", str(empty)) # Using append() method to add new array to the rows of our empty array empty = np.append(empty, np.array([[14,40]]), axis=0) empty = np.append(empty, np.array([[34,53]]), axis=0) print("\narray is:") print(empty)

numpy.empty()

numpy.empty(shape, dtype=float, order='C')

Shape and data type are accepted as arguments. Then, without initializing entries, it returns a new array with the specified shape and data type.

numpy.append()

numpy.append(arr, values, axis=None)

It accepts the parameters listed below,
arr : A copy of the array to which a value must be added.
Array values must be attached to any axis, The shape must match the arr.
axis : value-appending axis along which values must be added. Appending as a row is equal to 0 while appending as a column is equal to 1.

The output will be:

The array : [] array is: [[14 40] [34 53]]

Similarly, you can create an empty 3D array and append row-wise values in that array.

Method 2: Using np.vstack()

The series of input arrays are stacked vertically using the numpy.vstack() method to create a single array.

The Python Code will be:

import numpy as np #creating a 2D empty array empty= np.empty((0,3), int) # printing empty array print("The array : ", str(empty)) row = np.array([1, 2, 3]) result = np.vstack ((empty, row) ) # printing result print ("resultant array", str(result))

The output will be:

The array : [] resultant array [[1 2 3]]

Method 3 : Using np.r_ method

Python Code:

import numpy as np #creating a 2D empty array empty= np.empty((0,3), int) # printing empty array print("The array : ", str(empty)) row = np.array([1, 2, 3]) result = np.r_[empty,[row]] # printing result print ("resultant array", str(result))

The output will be:

The array : [] resultant array [[1 2 3]]

So these are some methods through which we can add a new row to an empty NumPy array in Python.

Читайте также:  Jira search issues python

Источник

Add Row to NumPy Array in Python

In this article, we will learn how to add a row to a 2D NumPy Array in python.

Given a NumPy array, we need to add a row to the array. For example,

Example: Given array: [[1 2 3 4 5 ], [5 4 3 2 1 ]] row = [ 6 7 8 9 1 ] After adding row to the array: [[1 2 3 4 5], [5 4 3 2 1], [6 7 8 9 1]]

There are multiple ways to Add a Row to a NumPy Array. Let’s discuss all the methods one by one with a proper approach and a working code example

1. Using append() method to Add a Row to a NumPy Array

Numpy module in python, provides a function numpy.append() to append objects to the end of an array, The object should be an array like entity. The append() method will take an array, object to be appended as arguments. It returns a copy of the numpy array, with given values appended at the end.

Syntax of append()

numpy.append(arr, values, axis=None)

Parameters:

arr = The array to be passed to the function. values = array_like object to appended to the array. axis = int, optional, Axis along which to append values.

Return:

Returns array with values appended at the end.

In this case, to add a row to a 2D NumPy array we need to pass the numpy array and row to the append() method and set the axis = 0. It will return a copy of array with the added row.

Frequently Asked:

Approach

  1. Import numpy library and create a numpy array
  2. Pass the array, row to be added to the append() method and set axis=0.
  3. The append() method will return copy of the array by adding the row.
  4. Print the new array

Source code

import numpy as np # creating numpy array arr = np.array([[1, 2, 3, 4, 5], [5, 4, 3, 2, 1]]) row = np.array([6, 7, 8, 9, 1]) # Adding row to array using append() method arr = np.append(arr, [row], axis=0) # Array after adding the row. print(arr)

OUTPUT:

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

2. Using concatenate() method to Add a Row to a NumPy Array

Numpy module in python, provides a function numpy.concatenate() to join a sequence of arrays along an existing axis. The concatenate() method will take a sequence of arrays as parameters. It will concatenate the arrays into one single array and returns the concatenated array.

Now to Add a Row to a NumPy Array, In the sequence of arrays we will pass the given array and the row to be added, The concatenate() method will return the array with the row added.

Читайте также:  Python find all symbols in string

Syntax of concatenate()

numpy.concatenate((a1, a2, . ), axis=0)

Parameters:

(a1, a2, . ) = Sequence of arrays to be passed to the function. axis = int, optional, Axis along which to concatenate arrays.

Return:

Returns a concatenated array.

Approach

  1. Import numpy library and create a numpy array
  2. Now pass the array and row to be added as a sequence of arrays to the concatenate method
  3. The method will return a copy of the array with the row added to it.
  4. Print the new array

Source code

import numpy as np # creating numpy array arr = np.array([[1, 2, 3, 4, 5], [5, 4, 3, 2, 1]]) row = np.array([6, 7, 8, 9, 1]) # Adding row to array using concatenate() arr = np.concatenate([arr, [row]]) # Array after adding the row. print(arr)

OUTPUT:

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

3. Using insert() method to Add a Row to a NumPy Array

Numpy module in python, provides a function numpy.insert() to insert values along the given axis before the given index. The insert() method will take an array, index , values to be inserted as parameters. It will insert the given value just before the specified index and returns the array.

Now, to Add a Row to a NumPy Array we need to pass the array, index, row to be inserted to the insert() method. Here we are adding row at front of the array so let’s give index = 0.

Syntax of insert()

numpy.insert(arr, obj, values, axis=None)

Parameters:

arr = The array to be passed to the function. obj = index at which value needs to be inserted values = Values or object to insert into array. axis = int, optional, Axis along which to insert values.

Return:

Returns array with value inserted at the specified index, in this case appended at the end of the array.

Approach

  • Import numpy library and create numpy array
  • Now pass the array, row to be inserted and index = 0, axis = 0 to the insert() method
  • That’s it , The insert() method will return a copy of the array with the row added.
  • Print the new array.

Source code

import numpy as np # creating numpy array arr = np.array([[1, 2, 3, 4, 5], [5, 4, 3, 2, 1]]) row = np.array([6, 7, 8, 9, 1]) # Adding row to array using insert() arr = np.insert(arr, 0, row, axis=0) # Array after adding the row. print(arr)

OUTPUT:

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

4. Using vstack() method to Add a Row to a NumPy Array

Numpy module in python, provides a function numpy.vstack() function is used to Stack arrays in sequence vertically (row-wise). i.e, concatenating into a single array. The vstack() method will take a sequence of arrays as parameters. It will stack the arrays into one single array and returns the array. The vstack is equivalent to concatenation.

Now to Add a Row to a NumPy Array, In the sequence of arrays we will pass the given array and the row to be added, The vstack() method will return the array with the row added.

Читайте также:  Invalid parameter type php

Syntax of vstack()

Parameters:

tuple = sequence of arrays to be passed to the function.

Return:

Returns The array formed by stacking the given arrays.

Approach

  • Import numpy library and create numpy array
  • Now pass the array, row to be inserted as a sequence of arrays to the vstack method
  • That’s it , The vstack() method will return a copy of the array with the row added.
  • Print the new array.

Source code

import numpy as np # creating numpy array arr = np.array([[1, 2, 3, 4, 5], [5, 4, 3, 2, 1]]) row = np.array([6,7,8,9,1]) # Adding row to array using vstack() arr = np.vstack((arr,row)) # Array after adding the row. print(arr)

OUTPUT:

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

Summary

Great! you made it, We have discussed all possible methods to Add a Row to a NumPy Array. Happy learning.

Share your love

Leave a Comment Cancel Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Terms of Use

Disclaimer

Copyright © 2023 thisPointer

To provide the best experiences, we and our partners use technologies like cookies to store and/or access device information. Consenting to these technologies will allow us and our partners to process personal data such as browsing behavior or unique IDs on this site and show (non-) personalized ads. Not consenting or withdrawing consent, may adversely affect certain features and functions.

Click below to consent to the above or make granular choices. Your choices will be applied to this site only. You can change your settings at any time, including withdrawing your consent, by using the toggles on the Cookie Policy, or by clicking on the manage consent button at the bottom of the screen.

The technical storage or access is strictly necessary for the legitimate purpose of enabling the use of a specific service explicitly requested by the subscriber or user, or for the sole purpose of carrying out the transmission of a communication over an electronic communications network.

The technical storage or access is necessary for the legitimate purpose of storing preferences that are not requested by the subscriber or user.

The technical storage or access that is used exclusively for statistical purposes. The technical storage or access that is used exclusively for anonymous statistical purposes. Without a subpoena, voluntary compliance on the part of your Internet Service Provider, or additional records from a third party, information stored or retrieved for this purpose alone cannot usually be used to identify you.

The technical storage or access is required to create user profiles to send advertising, or to track the user on a website or across several websites for similar marketing purposes.

Источник

Оцените статью