1635898320

How to Find The Average Of A List in Python With Step by Step Example

Average (Arithmetic mean) is a mathematical function which is calculated by adding the numeric values in the list and dividing them by the count of numbers of the list.

In this Article different approaches will be discussed to get the average of lists in Python on Linux System. Here is the list of methods mentioned below:

• Finding the average of the list by using sum() and len() Function.
• Finding the average of the list from the mean() function by importing the statistic module.
• Finding the average of the list from the mean() function by importing the numpy module.
• Finding the average of the list from reduce() by importing functools and lambda() functions.

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

1561523460

Matplotlib Cheat Sheet: Plotting in Python

This Matplotlib cheat sheet introduces you to the basics that you need to plot your data with Python and includes code samples.

Data visualization and storytelling with your data are essential skills that every data scientist needs to communicate insights gained from analyses effectively to any audience out there.

For most beginners, the first package that they use to get in touch with data visualization and storytelling is, naturally, Matplotlib: it is a Python 2D plotting library that enables users to make publication-quality figures. But, what might be even more convincing is the fact that other packages, such as Pandas, intend to build more plotting integration with Matplotlib as time goes on.

However, what might slow down beginners is the fact that this package is pretty extensive. There is so much that you can do with it and it might be hard to still keep a structure when you're learning how to work with Matplotlib.

DataCamp has created a Matplotlib cheat sheet for those who might already know how to use the package to their advantage to make beautiful plots in Python, but that still want to keep a one-page reference handy. Of course, for those who don't know how to work with Matplotlib, this might be the extra push be convinced and to finally get started with data visualization in Python.

You'll see that this cheat sheet presents you with the six basic steps that you can go through to make beautiful plots.

Check out the infographic by clicking on the button below:

With this handy reference, you'll familiarize yourself in no time with the basics of Matplotlib: you'll learn how you can prepare your data, create a new plot, use some basic plotting routines to your advantage, add customizations to your plots, and save, show and close the plots that you make.

What might have looked difficult before will definitely be more clear once you start using this cheat sheet! Use it in combination with the Matplotlib Gallery, the documentation.

Matplotlib

Matplotlib is a Python 2D plotting library which produces publication-quality figures in a variety of hardcopy formats and interactive environments across platforms.

Prepare the Data

1D Data

``````>>> import numpy as np
>>> x = np.linspace(0, 10, 100)
>>> y = np.cos(x)
>>> z = np.sin(x)``````

2D Data or Images

``````>>> data = 2 * np.random.random((10, 10))
>>> data2 = 3 * np.random.random((10, 10))
>>> Y, X = np.mgrid[-3:3:100j, -3:3:100j]
>>> U = 1 X** 2 + Y
>>> V = 1 + X Y**2
>>> from matplotlib.cbook import get_sample_data

Create Plot

``>>> import matplotlib.pyplot as plt``

Figure

``````>>> fig = plt.figure()
>>> fig2 = plt.figure(figsize=plt.figaspect(2.0))``````

Axes

``````>>> fig.add_axes()
>>> fig3, axes = plt.subplots(nrows=2,ncols=2)
>>> fig4, axes2 = plt.subplots(ncols=3)``````

Save Plot

``````>>> plt.savefig('foo.png') #Save figures
>>> plt.savefig('foo.png',  transparent=True) #Save transparent figures``````

Show Plot

``>>> plt.show()``

1D Data

``````>>> fig, ax = plt.subplots()
>>> lines = ax.plot(x,y) #Draw points with lines or markers connecting them
>>> ax.scatter(x,y) #Draw unconnected points, scaled or colored
>>> axes[0,0].bar([1,2,3],[3,4,5]) #Plot vertical rectangles (constant width)
>>> axes[1,0].barh([0.5,1,2.5],[0,1,2]) #Plot horiontal rectangles (constant height)
>>> axes[1,1].axhline(0.45) #Draw a horizontal line across axes
>>> axes[0,1].axvline(0.65) #Draw a vertical line across axes
>>> ax.fill(x,y,color='blue') #Draw filled polygons
>>> ax.fill_between(x,y,color='yellow') #Fill between y values and 0``````

2D Data

``````>>> fig, ax = plt.subplots()
>>> im = ax.imshow(img, #Colormapped or RGB arrays
cmap= 'gist_earth',
interpolation= 'nearest',
vmin=-2,
vmax=2)
>>> axes2[0].pcolor(data2) #Pseudocolor plot of 2D array
>>> axes2[0].pcolormesh(data) #Pseudocolor plot of 2D array
>>> CS = plt.contour(Y,X,U) #Plot contours
>>> axes2[2].contourf(data1) #Plot filled contours
>>> axes2[2]= ax.clabel(CS) #Label a contour plot``````

Vector Fields

``````>>> axes[0,1].arrow(0,0,0.5,0.5) #Add an arrow to the axes
>>> axes[1,1].quiver(y,z) #Plot a 2D field of arrows
>>> axes[0,1].streamplot(X,Y,U,V) #Plot a 2D field of arrows``````

Data Distributions

``````>>> ax1.hist(y) #Plot a histogram
>>> ax3.boxplot(y) #Make a box and whisker plot
>>> ax3.violinplot(z)  #Make a violin plot``````

Plot Anatomy & Workflow

Plot Anatomy

y-axis

x-axis

Workflow

The basic steps to creating plots with matplotlib are:

1 Prepare Data
2 Create Plot
3 Plot
4 Customized Plot
5 Save Plot
6 Show Plot

``````>>> import matplotlib.pyplot as plt
>>> x = [1,2,3,4]  #Step 1
>>> y = [10,20,25,30]
>>> fig = plt.figure() #Step 2
>>> ax = fig.add_subplot(111) #Step 3
>>> ax.plot(x, y, color= 'lightblue', linewidth=3)  #Step 3, 4
>>> ax.scatter([2,4,6],
[5,15,25],
color= 'darkgreen',
marker= '^' )
>>> ax.set_xlim(1, 6.5)
>>> plt.savefig('foo.png' ) #Step 5
>>> plt.show() #Step 6``````

Close and Clear

``````>>> plt.cla()  #Clear an axis
>>> plt.clf(). #Clear the entire figure
>>> plt.close(). #Close a window``````

Plotting Customize Plot

Colors, Color Bars & Color Maps

``````>>> plt.plot(x, x, x, x**2, x, x** 3)
>>> ax.plot(x, y, alpha = 0.4)
>>> ax.plot(x, y, c= 'k')
>>> fig.colorbar(im, orientation= 'horizontal')
>>> im = ax.imshow(img,
cmap= 'seismic' )``````

Markers

``````>>> fig, ax = plt.subplots()
>>> ax.scatter(x,y,marker= ".")
>>> ax.plot(x,y,marker= "o")``````

Linestyles

``````>>> plt.plot(x,y,linewidth=4.0)
>>> plt.plot(x,y,ls= 'solid')
>>> plt.plot(x,y,ls= '--')
>>> plt.plot(x,y,'--' ,x**2,y**2,'-.' )
>>> plt.setp(lines,color= 'r',linewidth=4.0)``````

Text & Annotations

``````>>> ax.text(1,
-2.1,
'Example Graph',
style= 'italic' )
>>> ax.annotate("Sine",
xy=(8, 0),
xycoords= 'data',
xytext=(10.5, 0),
textcoords= 'data',
arrowprops=dict(arrowstyle= "->",
connectionstyle="arc3"),)``````

Mathtext

``>>> plt.title(r '\$sigma_i=15\$', fontsize=20)``

Limits, Legends and Layouts

Limits & Autoscaling

``````>>> ax.margins(x=0.0,y=0.1) #Add padding to a plot
>>> ax.axis('equal')  #Set the aspect ratio of the plot to 1
>>> ax.set(xlim=[0,10.5],ylim=[-1.5,1.5])  #Set limits for x-and y-axis
>>> ax.set_xlim(0,10.5) #Set limits for x-axis``````

Legends

``````>>> ax.set(title= 'An Example Axes',  #Set a title and x-and y-axis labels
ylabel= 'Y-Axis',
xlabel= 'X-Axis')
>>> ax.legend(loc= 'best')  #No overlapping plot elements``````

Ticks

``````>>> ax.xaxis.set(ticks=range(1,5),  #Manually set x-ticks
ticklabels=[3,100, 12,"foo" ])
>>> ax.tick_params(axis= 'y', #Make y-ticks longer and go in and out
direction= 'inout',
length=10)``````

Subplot Spacing

``````>>> fig3.subplots_adjust(wspace=0.5,   #Adjust the spacing between subplots
hspace=0.3,
left=0.125,
right=0.9,
top=0.9,
bottom=0.1)
>>> fig.tight_layout() #Fit subplot(s) in to the figure area``````

Axis Spines

``````>>> ax1.spines[ 'top'].set_visible(False) #Make the top axis line for a plot invisible
>>> ax1.spines['bottom' ].set_position(( 'outward',10))  #Move the bottom axis line outward``````

Have this Cheat Sheet at your fingertips

Original article source at https://www.datacamp.com

#matplotlib #cheatsheet #python

1657107416

Find the Best Restaurant Mobile App Development Company in Abu Dhbai

The era of mobile app development has completely changed the scenario for businesses in regions like Abu Dhabi. Restaurants and food delivery businesses are experiencing huge benefits via smart business applications. The invention and development of the food ordering app have helped all-scale businesses reach new customers and boost sales and profit.

As a result, many business owners are searching for the best restaurant mobile app development company in Abu Dhabi. If you are also searching for the same, this article is helpful for you. It will let you know the step-by-step process to hire the right team of restaurant mobile app developers.

Step-by-Step Process to Find the Best Restaurant App Development Company

Searching for the top mobile app development company in Abu Dhabi? Don't know the best way to search for professionals? Don't panic! Here is the step-by-step process to hire the best professionals.

#Step 1 – Know the Company's Culture

Knowing the organization's culture is very crucial before finalizing a food ordering app development company in Abu Dhabi. An organization's personality is shaped by its common beliefs, goals, practices, or company culture. So, digging into the company culture reveals the core beliefs of the organization, its objectives, and its development team.

Now, you might be wondering, how will you identify the company's culture? Well, you can take reference from the following sources –

• Social media posts
• App development process
• Client testimonials

#Step 2 - Refer to Clients' Reviews

Another best way to choose the On-demand app development firm for your restaurant business is to refer to the clients' reviews. Reviews are frequently available on the organization's website with a tag of "Reviews" or "Testimonials." It's important to read the reviews as they will help you determine how happy customers are with the company's app development process.

You can also assess a company's abilities through reviews and customer testimonials. They can let you know if the mobile app developers create a valuable app or not.

#Step 3 – Analyze the App Development Process

Regardless of the company's size or scope, adhering to the restaurant delivery app development process will ensure the success of your business application. Knowing the processes an app developer follows in designing and producing a top-notch app will help you know the working process. Organizations follow different app development approaches, so getting well-versed in the process is essential before finalizing any mobile app development company.

#Step 4 – Consider Previous Experience

Besides considering other factors, considering the previous experience of the developers is a must. You can obtain a broad sense of the developer's capacity to assist you in creating a unique mobile application for a restaurant business.

You can also find out if the developers' have contributed to the creation of other successful applications or not. It will help you know the working capacity of a particular developer or organization. Prior experience is essential to evaluating their work. For instance, whether they haven't previously produced an app similar to yours or not.

#Step 5 – Check for Their Technical Support

As you expect a working and successful restaurant mobile app for your business, checking on this factor is a must. A well-established organization is nothing without a good technical support team. So, ensure whatever restaurant mobile app development company you choose they must be well-equipped with a team of dedicated developers, designers, and testers.

Strong tech support from your mobile app developers will help you identify new bugs and fix them bugs on time. All this will ensure the application's success.

#Step 6 – Analyze Design Standards

Besides focusing on an organization's development, testing, and technical support, you should check the design standards. An appealing design is crucial in attracting new users and keeping the existing ones stick to your services. So, spend some time analyzing the design standards of an organization. Now, you might be wondering, how will you do it? Simple! By looking at the organization's portfolio.

Whether hiring an iPhone app development company or any other, these steps apply to all. So, don't miss these steps.

#Step 7 – Know Their Location

Finally, the last yet very crucial factor that will not only help you finalize the right person for your restaurant mobile app development but will also decide the mobile app development cost. So, you have to choose the location of the developers wisely, as it is a crucial factor in defining the cost.

Summing Up!!!

Restaurant mobile applications have taken the food industry to heights none have ever considered. As a result, the demand for restaurant mobile app development companies has risen greatly, which is why businesses find it difficult to finalize the right person. But, we hope that after referring to this article, it will now be easier to hire dedicated developers under the desired budget. So, begin the hiring process now and get a well-craft food ordering app in hand.

1640973720

Beyonic API Python Examples.

The beyonic APIs Docs Reference: https://apidocs.beyonic.com/

Discuss Beyonic API on slack

The Beyonic API is a representational state transfer, REST based application programming interface that lets you extend the Beyonic dashboard features into your application and systems, allowing you to build amazing payment experiences.

With the Beyonic API you can:

• Receive and send money and prepaid airtime.
• List currencies and networks supported by the Beyonic API.
• Check whether a bank is supported by the Beyonic API.
• View your account transactions history.
• Use webhooks to send notifications to URLs on your server that when specific events occur in your Beyonic account (e.g. payments).

Getting Help

For usage, general questions, and discussions the best place to go to is Beyhive Slack Community, also feel free to clone and edit this repository to meet your project, application or system requirements.

To start using the Beyonic Python API, you need to start by downloading the Beyonic API official Python client library and setting your secret key.

Install the Beyonic API Python Official client library

``````>>> pip install beyonic
``````

To set the secrete key install the python-dotenv modeule, Python-dotenv is a Python module that allows you to specify environment variables in traditional UNIX-like “.env” (dot-env) file within your Python project directory, it helps us work with SECRETS and KEYS without exposing them to the outside world, and keep them safe during development too.

Installing python-dotenv modeule

``````>>> pip install python-dotenv
``````

Creating a .env file to keep our secrete keys.

``````>>> touch .env
``````

Inside your .env file specify the Beyonic API Token .

.env file

``````BEYONIC_ACCESS_KEY = "enter your API "
``````

You will get your API Token by clicking your user name on the bottom left of the left sidebar menu in the Beyonic web portal and selecting ‘Manage my account’ from the dropdown menu. The API Token is shown at the very bottom of the page.

getExamples.py

``````import os
import beyonic

myapi = os.environ['BEYONIC_ACCESS_KEY']

beyonic.api_key = myapi

# Listing account: Working.
accounts = beyonic.Account.list()
print(accounts)

#Listing currencies: Not working yet.
'''
supported_currencies = beyonic.Currency.list()
print(supported_currencies)

Supported currencies are: USD, UGX, KES, BXC, GHS, TZS, RWF, ZMW, MWK, BIF, EUR, XAF, GNF, XOF, XOF
'''

#Listing networks: Not working yet.
"""
networks = beyonic.Network.list()
print(networks)
"""

#Listing transactions: Working.
transactions = beyonic.Transaction.list()
print(transactions)

#Listing contact: Working.
mycontacts = beyonic.Contact.list()
print(mycontacts)

#Listing events: Not working yet.
'''
events = beyonic.Event.list()
print(events)

Error: AttributeError: module 'beyonic' has no attribute 'Event'
'''
``````

Docker file

``````FROM python:3.8-slim-buster

COPY . .

COPY ./requirements.txt ./requirements.txt

WORKDIR .

RUN pip install -r requirements.txt

CMD [ "python3", "getExamples.py" ]
``````

Build docker image called demo

``````>>> docker build -t bey .
``````

Run docker image called demo

``````>>>docker run -t -i bey
``````

Now, I’ll create a Docker compose file to run a Docker container using the Docker image we just created.

``````
version: "3.6"
services:
app:
build: .
command: python getExamples.py
volumes:
- .:/pythonBeyonicExamples
``````

Now we are going to run the following command from the same directory where the docker-compose.yml file is located. The docker compose up command will start and run the entire app.

``````
docker compose up
``````

Output

NB: The screenshot below might differ according to your account deatils and your transcations in deatils.

To stop the container running on daemon mode use the below command.

``````docker compose stop
``````

Output

Contributing to this repository. All contributions, bug reports, bug fixes, enhancements, and ideas are welcome, You can get in touch with me on twitter @HarunMbaabu.

Author: HarunMbaabu
Source Code: https://github.com/HarunMbaabu/BeyonicAPI-Python-Examples

1626775355

Why use Python for Software Development

No programming language is pretty much as diverse as Python. It enables building cutting edge applications effortlessly. Developers are as yet investigating the full capability of end-to-end Python development services in various areas.

By areas, we mean FinTech, HealthTech, InsureTech, Cybersecurity, and that's just the beginning. These are New Economy areas, and Python has the ability to serve every one of them. The vast majority of them require massive computational abilities. Python's code is dynamic and powerful - equipped for taking care of the heavy traffic and substantial algorithmic capacities.

Programming advancement is multidimensional today. Endeavor programming requires an intelligent application with AI and ML capacities. Shopper based applications require information examination to convey a superior client experience. Netflix, Trello, and Amazon are genuine instances of such applications. Python assists with building them effortlessly.

5 Reasons to Utilize Python for Programming Web Apps

Python can do such numerous things that developers can't discover enough reasons to admire it. Python application development isn't restricted to web and enterprise applications. It is exceptionally adaptable and superb for a wide range of uses.

Robust frameworks

Python is known for its tools and frameworks. There's a structure for everything. Django is helpful for building web applications, venture applications, logical applications, and mathematical processing. Flask is another web improvement framework with no conditions.

Web2Py, CherryPy, and Falcon offer incredible capabilities to customize Python development services. A large portion of them are open-source frameworks that allow quick turn of events.

Python has an improved sentence structure - one that is like the English language. New engineers for Python can undoubtedly understand where they stand in the development process. The simplicity of composing allows quick application building.

The motivation behind building Python, as said by its maker Guido Van Rossum, was to empower even beginner engineers to comprehend the programming language. The simple coding likewise permits developers to roll out speedy improvements without getting confused by pointless subtleties.

Utilized by the best

Alright - Python isn't simply one more programming language. It should have something, which is the reason the business giants use it. Furthermore, that too for different purposes. Developers at Google use Python to assemble framework organization systems, parallel information pusher, code audit, testing and QA, and substantially more. Netflix utilizes Python web development services for its recommendation algorithm and media player.

Massive community support

Python has a steadily developing community that offers enormous help. From amateurs to specialists, there's everybody. There are a lot of instructional exercises, documentation, and guides accessible for Python web development solutions.

Today, numerous universities start with Python, adding to the quantity of individuals in the community. Frequently, Python designers team up on various tasks and help each other with algorithmic, utilitarian, and application critical thinking.

Progressive applications

Python is the greatest supporter of data science, Machine Learning, and Artificial Intelligence at any enterprise software development company. Its utilization cases in cutting edge applications are the most compelling motivation for its prosperity. Python is the second most well known tool after R for data analytics.

The simplicity of getting sorted out, overseeing, and visualizing information through unique libraries makes it ideal for data based applications. TensorFlow for neural networks and OpenCV for computer vision are two of Python's most well known use cases for Machine learning applications.

Summary

Thinking about the advances in programming and innovation, Python is a YES for an assorted scope of utilizations. Game development, web application development services, GUI advancement, ML and AI improvement, Enterprise and customer applications - every one of them uses Python to its full potential.

The disadvantages of Python web improvement arrangements are regularly disregarded by developers and organizations because of the advantages it gives. They focus on quality over speed and performance over blunders. That is the reason it's a good idea to utilize Python for building the applications of the future.

#python development services #python development company #python app development #python development #python in web development #python software development