James Johnson

1650261279

Common Roadrunner Email Problems | Easy Steps 2022

One of the really common internet providers is Roadrunner Emails. It’s a free email service that’s connected millions of people at breakneck speed. Spectrum Email support personnel receive thousands of queries and requests every day due to the large customer base. We’ll go over some of the most Common Roadrunner Email Problems and how to fix them.

The following are some of the most common Roadrunner email errors:

Roadrunner Issues with sign-in and setup: To use Roadrunner’s services, you must first sign in to your account. Some customers, however, have issues setting up their accounts for the first time.

Roadrunner Email not Working: Some users have complained that they are unable to send e-mails. If you encounter an error while emailing your customers, you may need to explore to determine the source of the problem.

Problems with SPAM or Trash Mails: You may also have issues with spam and junk messages.

Android compatibility concerns: You may experience Roadrunner email issues as a result of Android compatibility issues.

Issues with iPhone compatibility: The issue of Roadrunner Email not working on iPhone is frequently brought up by users.

Follow these procedures to verify your account:

  • Go to the official webpage on your browser.
  • Answer the security question and complete the CAPTCHA.
  • If required, change your password.
  • Last but not least, confirm your changes.

Change your password by following these steps:

  • Go to https://webmail.spectrum.net/mail/auth in your browser.
  • Fill in the information for your Roadrunner Email account.
  • Go to the section under “User Management.”
  • To change your password, go to the ‘Change Password’ tab.
  • Then input both your old and new passwords.
  • To change your password, click the ‘Change Password’ option.
  • Use your new password to log in.

Just what is causing the roadrunner problems?

When utilizing roadrunner email, a user may encounter a variety of issues. It is critical to comprehend the underlying causes of the issues. The following are some of the most common causes of Common Roadrunner Email Issues:

  • Server-related issues.
  • IMAP or POP settings are incorrect due to incorrect server configuration.
  • Problems with the network
  • Typical Roadrunner Email Issues

The following are the most typical Roadrunner Email Not Working that you may encounter when accessing your Roadrunner account:

  • IMAP and POP settings that are incorrect
  • Login credentials are incorrect
  • Unsuitable server setup
  • Problems with the network
  • Have you forgotten your email address or password?
  • You are unable to send or receive any emails or messages.

So, these are some of the most typical Roadrunner Email Account Problems that may be resolved by using the remedies listed above. If you have a problem, you can speak with Roadrunner customer service representatives to get help.

Source URL:- https://rremailshelp.blogspot.com/2021/07/fix-common-roadrunner-email-problems.html

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Common Roadrunner Email Problems | Easy Steps 2022
John  Smith

John Smith

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
  • About us Page
  • 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. 

Ayan Code

1656193861

Simple Login Page in HTML and CSS | Source Code

Hello guys, Today in this post we’ll learn How to Create a Simple Login Page with a fantastic design. To create it we are going to use pure CSS and HTML. Hope you enjoy this post.

A login page is one of the most important component of a website or app that allows authorized users to access an entire site or a part of a website. You would have already seen them when visiting a website. Let's head to create it.

Whether it’s a signup or login page, it should be catchy, user-friendly and easy to use. These types of Forms lead to increased sales, lead generation, and customer growth.


Demo

Click to watch demo!

Simple Login Page HTML CSS (source code)

<!DOCTYPE html>
  <html lang="en" >
  <head>
    <meta charset="UTF-8">
    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/normalize/5.0.0/normalize.min.css">
  <link rel="stylesheet" href="styledfer.css">
  </head>

  <body>
   <div id="login-form-wrap">
    <h2>Login</h2>
    <form id="login-form">
      <p>
      <input type="email" id="email" name="email" placeholder="Email " required><i class="validation"><span></span><span></span></i>
      </p>
      <p>
      <input type="password" id="password" name="password" placeholder="Password" required><i class="validation"><span></span><span></span></i>
      </p>
      <p>
      <input type="submit" id="login" value="Login">
      </p>

      </form>
    <div id="create-account-wrap">
      <p>Don't have an accout? <a href="#">Create One</a><p>
    </div>
   </div>
    
  <script src='https://code.jquery.com/jquery-2.2.4.min.js'></script>
  <script src='https://cdnjs.cloudflare.com/ajax/libs/jquery-validate/1.15.0/jquery.validate.min.js'></script>
  </body>
</html>

CSS CODE

body {
  background-color: #020202;
  font-size: 1.6rem;
  font-family: "Open Sans", sans-serif;
  color: #2b3e51;
}
h2 {
  font-weight: 300;
  text-align: center;
}
p {
  position: relative;
}
a,
a:link,
a:visited,
a:active {
  color: #ff9100;
  -webkit-transition: all 0.2s ease;
  transition: all 0.2s ease;
}
a:focus, a:hover,
a:link:focus,
a:link:hover,
a:visited:focus,
a:visited:hover,
a:active:focus,
a:active:hover {
  color: #ff9f22;
  -webkit-transition: all 0.2s ease;
  transition: all 0.2s ease;
}
#login-form-wrap {
  background-color: #fff;
  width: 16em;
  margin: 30px auto;
  text-align: center;
  padding: 20px 0 0 0;
  border-radius: 4px;
  box-shadow: 0px 30px 50px 0px rgba(0, 0, 0, 0.2);
}
#login-form {
  padding: 0 60px;
}
input {
  display: block;
  box-sizing: border-box;
  width: 100%;
  outline: none;
  height: 60px;
  line-height: 60px;
  border-radius: 4px;
}
#email,
#password {
  width: 100%;
  padding: 0 0 0 10px;
  margin: 0;
  color: #8a8b8e;
  border: 1px solid #c2c0ca;
  font-style: normal;
  font-size: 16px;
  -webkit-appearance: none;
     -moz-appearance: none;
          appearance: none;
  position: relative;
  display: inline-block;
  background: none;
}
#email:focus,
#password:focus {
  border-color: #3ca9e2;
}
#email:focus:invalid,
#password:focus:invalid {
  color: #cc1e2b;
  border-color: #cc1e2b;
}
#email:valid ~ .validation,
#password:valid ~ .validation 
{
  display: block;
  border-color: #0C0;
}
#email:valid ~ .validation span,
#password:valid ~ .validation span{
  background: #0C0;
  position: absolute;
  border-radius: 6px;
}
#email:valid ~ .validation span:first-child,
#password:valid ~ .validation span:first-child{
  top: 30px;
  left: 14px;
  width: 20px;
  height: 3px;
  -webkit-transform: rotate(-45deg);
          transform: rotate(-45deg);
}
#email:valid ~ .validation span:last-child
#password:valid ~ .validation span:last-child
{
  top: 35px;
  left: 8px;
  width: 11px;
  height: 3px;
  -webkit-transform: rotate(45deg);
          transform: rotate(45deg);
}
.validation {
  display: none;
  position: absolute;
  content: " ";
  height: 60px;
  width: 30px;
  right: 15px;
  top: 0px;
}
input[type="submit"] {
  border: none;
  display: block;
  background-color: #ff9100;
  color: #fff;
  font-weight: bold;
  text-transform: uppercase;
  cursor: pointer;
  -webkit-transition: all 0.2s ease;
  transition: all 0.2s ease;
  font-size: 18px;
  position: relative;
  display: inline-block;
  cursor: pointer;
  text-align: center;
}
input[type="submit"]:hover {
  background-color: #ff9b17;
  -webkit-transition: all 0.2s ease;
  transition: all 0.2s ease;
}

#create-account-wrap {
  background-color: #eeedf1;
  color: #8a8b8e;
  font-size: 14px;
  width: 100%;
  padding: 10px 0;
  border-radius: 0 0 4px 4px;
}

Congratulations! You have now successfully created our Simple Login Page in HTML and CSS.

My Website: codewithayan, see this to checkout all of my amazing Tutorials.

Dylan  Iqbal

Dylan Iqbal

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:

Python Matplotlib cheat sheet

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
>>> img = np.load(get_sample_data('axes_grid/bivariate_normal.npy'))

Create Plot

>>> import matplotlib.pyplot as plt

Figure 

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

Axes 

>>> fig.add_axes()
>>> ax1 = fig.add_subplot(221) #row-col-num
>>> ax3 = fig.add_subplot(212)
>>> 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()

Plotting Routines 

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

Emails Customer Care - Change Roadrunner Email Password

Roadrunner email account is one of the most common webmail tools for managing email services to be shared with customers. Forgot roadrunner password of the email account is very common for a regular user, but after a long time those who sign up for their account will easily forget the password. The key is also often forgotten by a regular user and he has to reset it finally. Here we have another Roadrunner email account password related topic that if anyone "CHANGE ROADRUNNER EMAIL PASSWORD" and he can't complete the task of resetting the password.

Follow these simple tips given below:

How to Recover Forgot Roadrunner Email Password?

If you forget the username for your Roadrunner? Well, in such a situation, you should not panic, as recover the Roadrunner username is very fast. Everything you need to do is follow the below mentioned steps:

  • First of all, to visit the roadrunner email login page, you will have to use any compatible web browser.

You can click the "Forget TWC Email Address" button at the bottom of the account page.

  • Spectrum roadrunner will then ask you to enter the alternative ids or phone number of your Roadrunner email ID.
  • Enter email address and the contact information of the option. You will be required to answer the security question once you have entered the email id and phone number.

  Answer the safety questions. (Try using the exact answers you mentioned when creating a Roadrunner email account).

  • Your Roadrunner email address/username will appear on your computer if the responses given by you were correct.

Now, you can easily use your username to login to your roadrunner email account once you remember your email address. You can use the mentioned steps to reset the Roadrunner password to recover the roadrunner password if you don't know the password.

 

Change/Recover/Forget Roadrunner Email Password

In order to protect your roadrunner email address from online threats such as hacking, phishing, etc., Code updates are different from code recovery. Change roadrunner email password is much easier to do than recovering your username. But you need to login to Roadrunner if you want to change your roadrunner password.

  • Visit Roadrunner's login page.

Click on the Forget password link from the bottom.

  • As shown below, you will now have two options on the next page: "I know my email address and I want to change it."
  • "The password for my address I do not remember."
  • If you want 'I don't know my email address,' you will be redirected to Roadrunner password recovery.
  • If you choose "I know my email password and I want to change it," you will be asked to sign in.
  • Use your email address and password for the roadrunner to log in.
  • You will need to enter your Cable Modem MAC Address if you haven't previously used the Roadrunner password reset tool.
  • Firstly, there is a need to answer the safety question. Remember that your replies are case sensitive, so try writing the answers in upper and lower case, in exact letters.
  • At last, you need to enter the new password for your roadrunner email address.

Once you enter the new password, you are ready to go. You will be automatically logged out after changing the password. You need to log in again using the new password after changing it.

Contact Roadrunner Support Expert to Resolve All Your Issues at Instantly

We hope that if you Forgot Roadrunner Email Password, our article has helped you know the right Roadrunner email password reset procedure. But if you have experienced an incredible error and are unable to reset/change your email password for Roadrunner, you must contact our experts. To report your Roadrunner email-related query or problem, use the live chat service and leave the rest to our experts. In order to change the roadrunner password/ Recover Forget Roadrunner Password, if you are still confused, you can contact our technicians at +1-888-857-5157. We are prepared to help you 24*7*365 in the best way possible.

Source: https://sites.google.com/view/emails-customer-care/blog/change-roadrunner-email-password

#change roadrunner email password #forgot roadrunner email password #recover forgot roadrunner email password #forgot roadrunner email password

Garry Taylor

Garry Taylor

1653464648

Python Data Visualization: Bokeh Cheat Sheet

A handy cheat sheet for interactive plotting and statistical charts with Bokeh.

Bokeh distinguishes itself from other Python visualization libraries such as Matplotlib or Seaborn in the fact that it is an interactive visualization library that is ideal for anyone who would like to quickly and easily create interactive plots, dashboards, and data applications. 

Bokeh is also known for enabling high-performance visual presentation of large data sets in modern web browsers. 

For data scientists, Bokeh is the ideal tool to build statistical charts quickly and easily; But there are also other advantages, such as the various output options and the fact that you can embed your visualizations in applications. And let's not forget that the wide variety of visualization customization options makes this Python library an indispensable tool for your data science toolbox.

Now, DataCamp has created a Bokeh cheat sheet for those who have already taken the course and that still want a handy one-page reference or for those who need an extra push to get started.

In short, you'll see that this cheat sheet not only presents you with the five steps that you can go through to make beautiful plots but will also introduce you to the basics of statistical charts. 

Python Bokeh Cheat Sheet

In no time, this Bokeh cheat sheet will make you familiar with how you can prepare your data, create a new plot, add renderers for your data with custom visualizations, output your plot and save or show it. And the creation of basic statistical charts will hold no secrets for you any longer. 

Boost your Python data visualizations now with the help of Bokeh! :)


Plotting With Bokeh

The Python interactive visualization library Bokeh enables high-performance visual presentation of large datasets in modern web browsers.

Bokeh's mid-level general-purpose bokeh. plotting interface is centered around two main components: data and glyphs.

The basic steps to creating plots with the bokeh. plotting interface are:

  1. Prepare some data (Python lists, NumPy arrays, Pandas DataFrames and other sequences of values)
  2. Create a new plot
  3. Add renderers for your data, with visual customizations
  4. Specify where to generate the output
  5. Show or save the results
>>> from bokeh.plotting import figure
>>> from bokeh.io import output_file, show
>>> x = [1, 2, 3, 4, 5] #Step 1
>>> y = [6, 7, 2, 4, 5]
>>> p = figure(title="simple line example", #Step 2
x_axis_label='x',
y_axis_label='y')
>>> p.line(x, y, legend="Temp.", line_width=2) #Step 3
>>> output_file("lines.html") #Step 4
>>> show(p) #Step 5

1. Data 

Under the hood, your data is converted to Column Data Sources. You can also do this manually:

>>> import numpy as np
>>> import pandas as pd
>>> df = pd.OataFrame(np.array([[33.9,4,65, 'US'], [32.4, 4, 66, 'Asia'], [21.4, 4, 109, 'Europe']]),
                     columns= ['mpg', 'cyl',   'hp',   'origin'],
                      index=['Toyota', 'Fiat', 'Volvo'])


>>> from bokeh.models import ColumnOataSource
>>> cds_df = ColumnOataSource(df)

2. Plotting 

>>> from bokeh.plotting import figure
>>>p1= figure(plot_width=300, tools='pan,box_zoom')
>>> p2 = figure(plot_width=300, plot_height=300,
x_range=(0, 8), y_range=(0, 8))
>>> p3 = figure()

3. Renderers & Visual Customizations 

Glyphs 

Scatter Markers 
Bokeh Scatter Markers

>>> p1.circle(np.array([1,2,3]), np.array([3,2,1]), fill_color='white')
>>> p2.square(np.array([1.5,3.5,5.5]), [1,4,3],
color='blue', size=1)

Line Glyphs 

Bokeh Line Glyphs

>>> pl.line([1,2,3,4], [3,4,5,6], line_width=2)
>>> p2.multi_line(pd.DataFrame([[1,2,3],[5,6,7]]),
pd.DataFrame([[3,4,5],[3,2,1]]),
color="blue")

Customized Glyphs

Selection and Non-Selection Glyphs 

Selection Glyphs

>>> p = figure(tools='box_select')
>>> p. circle ('mpg', 'cyl', source=cds_df,
selection_color='red',
nonselection_alpha=0.1)

Hover Glyphs

Hover Glyphs

>>> from bokeh.models import HoverTool
>>>hover= HoverTool(tooltips=None, mode='vline')
>>> p3.add_tools(hover)

Color Mapping 

Bokeh Colormapping Glyphs

>>> from bokeh.models import CategoricalColorMapper
>>> color_mapper = CategoricalColorMapper(
             factors= ['US', 'Asia', 'Europe'],
             palette= ['blue', 'red', 'green'])
>>>  p3. circle ('mpg', 'cyl', source=cds_df,
            color=dict(field='origin',
                 transform=color_mapper), legend='Origin')

4. Output & Export 

Notebook

>>> from bokeh.io import output_notebook, show
>>> output_notebook()

HTML 

Standalone HTML 

>>> from bokeh.embed import file_html
>>> from bokeh.resources import CON
>>> html = file_html(p, CON, "my_plot")

>>> from  bokeh.io  import  output_file,  show
>>> output_file('my_bar_chart.html',  mode='cdn')

Components

>>> from bokeh.embed import components
>>> script, div= components(p)

PNG

>>> from bokeh.io import export_png
>>> export_png(p, filename="plot.png")

SVG 

>>> from bokeh.io import export_svgs
>>> p. output_backend = "svg"
>>> export_svgs(p,filename="plot.svg")

Legend Location 

Inside Plot Area 

>>> p.legend.location = 'bottom left'

Outside Plot Area 

>>> from bokeh.models import Legend
>>> r1 = p2.asterisk(np.array([1,2,3]), np.array([3,2,1])
>>> r2 = p2.line([1,2,3,4], [3,4,5,6])
>>> legend = Legend(items=[("One" ,[p1, r1]),("Two",[r2])], location=(0, -30))
>>> p.add_layout(legend, 'right')

Legend Background & Border 

>>> p.legend. border_line_color = "navy"
>>> p.legend.background_fill_color = "white"

Legend Orientation 

>>> p.legend.orientation = "horizontal"
>>> p.legend.orientation = "vertical"

Rows & Columns Layout

Rows

>>> from bokeh.layouts import row
>>>layout= row(p1,p2,p3)

Columns

>>> from bokeh.layouts import columns
>>>layout= column(p1,p2,p3)

Nesting Rows & Columns 

>>>layout= row(column(p1,p2), p3)

Grid Layout 

>>> from bokeh.layouts import gridplot
>>> rowl = [p1,p2]
>>> row2 = [p3]
>>> layout = gridplot([[p1, p2],[p3]])

Tabbed Layout 

>>> from bokeh.models.widgets import Panel, Tabs
>>> tab1 = Panel(child=p1, title="tab1")
>>> tab2 = Panel(child=p2, title="tab2")
>>> layout = Tabs(tabs=[tab1, tab2])

Linked Plots

Linked Axes 

Linked Axes
>>> p2.x_range = p1.x_range
>>> p2.y_range = p1.y_range

Linked Brushing 

>>> p4 = figure(plot_width = 100, tools='box_select,lasso_select')
>>> p4.circle('mpg', 'cyl' , source=cds_df)
>>> p5 = figure(plot_width = 200, tools='box_select,lasso_select')
>>> p5.circle('mpg', 'hp', source=cds df)
>>>layout= row(p4,p5)

5. Show or Save Your Plots  

>>> show(p1)
>>> show(layout)
>>> save(p1)

Have this Cheat Sheet at your fingertips

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

#python #datavisualization #bokeh #cheatsheet