NumPy offers a comprehensive curriculum for numerical computing in Python. Our tutorials cover array operations, mathematical functions, and data processing techniques, suitable for beginners and experienced data scientists. Through hands-on labs and real-world examples, you'll gain practical experience in efficient numerical computations. Our scientific Python playground allows you to experiment with NumPy functions in real-time.

NumPy File IO

In this lab, you will learn how to use NumPy to read and write arrays to files. NumPy provides several functions for file input and output that make it easy to work with large datasets.

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NumPy Shape Manipulation

In this lab, you will learn the NumPy shape manipulation functions that allow you to manipulate the shape of NumPy arrays.

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NumPy Advanced Topics

This lab will cover some of the advanced features of NumPy, including linear algebra, random number generation, and masked arrays.

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Your First NumPy Lab

Hi there, welcome to LabEx! In this first lab, you'll learn the classic 'Hello, World!' program in NumPy.

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NumPy Upper Function

In this lab, you will learn how to use the upper() function in the char module of the NumPy library. This function is used to convert all lowercase characters of a string to uppercase. If there are no lowercase characters in the given string, it returns the original string. We will cover the syntax required to use this function, its returned values, and provide examples of its use.

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NumPy Trunc Function

In this lab, we will learn about the NumPy trunc() function in the Python language. We will understand its syntax, parameters, and how to use this function to return the truncated value of input array elements. We will also see some examples to have a better understanding.

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NumPy Right Shift Function

In this lab, we will learn about the right_shift() function in the NumPy library. This function is used to perform the right shift operation on an array-like object. The right_shift() function mainly shifts the bits in the binary representation of an operand to the right, just by the specified positions and appends an equal number of 0s from the left. The internal representation of numbers is in the binary format; thus, the right shift operation is equivalent to dividing a number by 2^x, where x is the number of bits to shift. We will cover the syntax of the right_shift() function, its parameters, and the values returned by this function along with code samples.

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Numpy Split Function

In this lab, we will cover the split() function of the char module in the Numpy library. The split() function is used to split an input string into a list of strings based on a specified separator.

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Numpy Reshape Function

The reshape() function in the NumPy library is mainly used to change the shape of an array without changing its underlying data. It helps in providing a new shape to an array that can be useful based on your use case. In this lab, we will cover the basic usage of the reshape() function and the different parameters and values it uses.

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Numpy Transpose Function

In this lab, we will learn how to use the numpy.transpose() function in Python NumPy library. We will learn how this function is used to permute or reverse the axes of an array. By the end of the lab, you will be able to use numpy.transpose() to modify arrays with ease.

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NumPy Replace Function

Numpy is one of the most powerful scientific computing libraries in Python. It provides a high-performance multidimensional array object, and tools for working with these arrays.

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Sorting NumPy Arrays with Algorithms

Sorting is a process where elements of an array are arranged in an ordered sequence based on the given criteria. In the NumPy library, there are various functions available that perform sorting operations based on different sorting algorithms such as quicksort, heapsort, and mergesort. In this lab, we will learn how to sort ndarrays in NumPy using different sorting algorithms.

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NumPy Swapcase Function

In this lab, we will cover the step-by-step process of using the Swapcase() function of the char module in the Numpy library. This tutorial is for those who want to manipulate strings in Numpy and change the cases of the characters in their string.

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NumPy STD Function

In this lab, we will cover the numpy.std() function of the NumPy library. We will understand what standard deviation means and how to use numpy.std() to calculate the standard deviation of an array.

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NumPy Startswith Function

In this lab, you will learn about the NumPy startswith() function. The startswith() function in the char module of the NumPy library returns a boolean array with values that can be either True or False. This function returns True if the given string starts with the specified prefix value in the function. It returns False if it does not start with the specified prefix.

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Using the NumPy char.lower Function

In this lab, we will cover the usage of the char.lower() function in the NumPy library. This function is used to convert all uppercase characters of a string to lowercase characters. If there are no uppercase characters in the string, then the original string will be returned.

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NumPy Array Mean Calculation

NumPy is a Python package for scientific computing that provides a high-performance array object, which is the fundamental building block for mathematical operations. The mean can easily be calculated by adding all the items of an array and dividing them by the total number of array elements. The numpy.mean() function in the NumPy library is used to compute the arithmetic mean across the specified axis of a numpy array. By default, the average is calculated over the flattened array unless the user specifies an axis.

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NumPy Matrix Multiplication

NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions. In this lab, we will cover the concept of Multiplication of two Matrix in the NumPy library.

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