 1595772895

# Numpy Tutorial (Python) - Getting Started & Installation This is a step by step tutorial of the Numpy module in python for Beginners. Learn about Numpy arrays and setting up Numpy on our system to get started.

## What is an Array?

An array is a variable that can store multiple values in itself. An array can hold a large number of values so they can be accessed using index numbers. The index always begins with 0 being the first element of the array and moving to the nth element, which will be the last. These values are of the same data type, which can be one of these strings, integer or float and also many others. Arrays can be of three types such as indexed arrays, associative arrays and multidimensional arrays.

## Definition of NumPy:

NumPy is a python based library that helps in the manipulation of the multidimensional arrays with regards to various factors. As a result, this helps in maintaining large and multidimensional arrays and matrics. NumPy stands for Numerical Python. So this open-source help in performing various mathematical functions because it is capable of solving complex problems in arrays. A NumPy array is a group of values with the same data type, and these are given their index number with only non-negative integer numbers. The dimension form up the rank of the array and also integer which gives the size of the array along with dimension form the shape of the array.

## History of NumPy:

In the early years, the Python was not supposed to be used for the numerical reason; as a result, it was not so common among the developers. In the year of 2005, Travis Oliphant was trying to develop a unified array package, and the next year it came in to use known with the name of NumPy 1.0 in the year 2006. Everyone can use it as it is open source and free to use.

I am going to discuss a few reasons why we should use NumPy:

• NumPy helps in the faster processing of the array.
• NumPy is preferred because it can perform operations like Searching and Sorting.
• It can perform all sorts of mathematical and logical operations.
• Arrays can operate fast. As a result, they are better than lists.
• It is good for data analysis.
• It is a good replacement for MATLAB and OCTAVE.
• Supports the use of vector operations.
• It is convenient to perform operations on arrays.
• NumPy is very much helpful in machine learning and data science.
• It helps in high-performance computing and simulations.

### Key Features of NumPy:

• It can handle on multidimensional arrays.
• NumPy refers to array objects as `ndarray` as a result, it provides various supporting functions.
• It can work with all the latest CPU architectures.
• It has tools for using C/C++ and Fortran Code.

### Limitations of NumPy:

• NumPy deals with the problem of missing values, but it supports ‘NAN’ which creates confusion among the users.
• Also, it creates issues while comparing values with the help of a python interpreter.
• It requires the allocation of memory for performing functions like addition and insertion, which makes it difficult to manage the space.
• This memory allocation also makes it costly to use.
• Also, it requires shifting in order to use various memory allocations.
• It focuses on working with only numerical data.

### NumPy Codebase :

The location for the source code of the NumPy is as follows: https://github.com/numpy/numpy

And also GitHub allows any number of users to use their codebase and they can work on the same codebase as it is enabled by the GitHub.

#programming #python #installation #numpy #python tutorial #setup

## Buddha Community  1619518440

## top 30 Python Tips and Tricks for Beginners

Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.

### 8) Check The Memory Usage Of An Object.

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## NumPy Installation - How to Install Numpy in Python

Python is an open-source object-oriented language. It has many features of which one is the wide range of external packages. There are a lot of packages for installation and use for expanding functionalities. These packages are a repository of functions in python script. NumPy is one such package to ease array computations. To install all these python packages we use the pip- package installer. Pip is automatically installed along with Python. We can then use pip in the command line to install packages from PyPI.

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## Install Numpy in Mac OS

Python comes pre-installed on Mac OS. However, it has an old system version the newer versions can be downloaded alongside.

1. Open the terminal in your MacBook.

2. In the terminal, we use the pip command to install the package

1. pip install numpy 3. If you use Python3, enter the pip3 command.

1. pip3 install numpy #numpy tutorials #install numpy #installing numpy #numpy installation 1595772895

## Numpy Tutorial (Python) - Getting Started & Installation This is a step by step tutorial of the Numpy module in python for Beginners. Learn about Numpy arrays and setting up Numpy on our system to get started.

## What is an Array?

An array is a variable that can store multiple values in itself. An array can hold a large number of values so they can be accessed using index numbers. The index always begins with 0 being the first element of the array and moving to the nth element, which will be the last. These values are of the same data type, which can be one of these strings, integer or float and also many others. Arrays can be of three types such as indexed arrays, associative arrays and multidimensional arrays.

## Definition of NumPy:

NumPy is a python based library that helps in the manipulation of the multidimensional arrays with regards to various factors. As a result, this helps in maintaining large and multidimensional arrays and matrics. NumPy stands for Numerical Python. So this open-source help in performing various mathematical functions because it is capable of solving complex problems in arrays. A NumPy array is a group of values with the same data type, and these are given their index number with only non-negative integer numbers. The dimension form up the rank of the array and also integer which gives the size of the array along with dimension form the shape of the array.

## History of NumPy:

In the early years, the Python was not supposed to be used for the numerical reason; as a result, it was not so common among the developers. In the year of 2005, Travis Oliphant was trying to develop a unified array package, and the next year it came in to use known with the name of NumPy 1.0 in the year 2006. Everyone can use it as it is open source and free to use.

I am going to discuss a few reasons why we should use NumPy:

• NumPy helps in the faster processing of the array.
• NumPy is preferred because it can perform operations like Searching and Sorting.
• It can perform all sorts of mathematical and logical operations.
• Arrays can operate fast. As a result, they are better than lists.
• It is good for data analysis.
• It is a good replacement for MATLAB and OCTAVE.
• Supports the use of vector operations.
• It is convenient to perform operations on arrays.
• NumPy is very much helpful in machine learning and data science.
• It helps in high-performance computing and simulations.

### Key Features of NumPy:

• It can handle on multidimensional arrays.
• NumPy refers to array objects as `ndarray` as a result, it provides various supporting functions.
• It can work with all the latest CPU architectures.
• It has tools for using C/C++ and Fortran Code.

### Limitations of NumPy:

• NumPy deals with the problem of missing values, but it supports ‘NAN’ which creates confusion among the users.
• Also, it creates issues while comparing values with the help of a python interpreter.
• It requires the allocation of memory for performing functions like addition and insertion, which makes it difficult to manage the space.
• This memory allocation also makes it costly to use.
• Also, it requires shifting in order to use various memory allocations.
• It focuses on working with only numerical data.

### NumPy Codebase :

The location for the source code of the NumPy is as follows: https://github.com/numpy/numpy

And also GitHub allows any number of users to use their codebase and they can work on the same codebase as it is enabled by the GitHub.

#programming #python #installation #numpy #python tutorial #setup 1619510796

## Lambda, Map, Filter functions in python

Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.

Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is

Syntax: x = lambda arguments : expression

Now i will show you some python lambda function examples:

#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map 1602968400

## Python Tricks Every Developer Should Know

Python is awesome, it’s one of the easiest languages with simple and intuitive syntax but wait, have you ever thought that there might ways to write your python code simpler?

In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.

### Let’s get started

Swapping value in Python

Instead of creating a temporary variable to hold the value of the one while swapping, you can do this instead

``````>>> FirstName = "kalebu"
>>> LastName = "Jordan"
>>> FirstName, LastName = LastName, FirstName
>>> print(FirstName, LastName)
('Jordan', 'kalebu')
``````

#python #python-programming #python3 #python-tutorials #learn-python #python-tips #python-skills #python-development