Five steps to land a job in WordPress

Most people dream of becoming independent workers all day long. Wake up every morning to get to work, enjoy a cup of coffee rather than a long commute to the workplace and negotiate with your own customers rather than with managers and subordinates. Most importantly, free from any stress at work. There are so many benefits of working as your own boss!

If you would like to quit and explore jobs where you can operate according to your schedule, get flexible hours and excellent compensation, it might be a good idea to land a WordPress job. And even though you are not interested in self-employment, WordPress offers plenty of wonderful full-time jobs.

WordPress is the world’s best-known website forum. Blogs, local business websites, news websites, eCommerce stores, and many more are allowed by WordPress. Indeed, WordPress is used in almost 38% of websites - you will not run out of customers fast if you get to work in the field of WordPress! There is also plenty of material about working with WordPress, and it is easy to get started by yourself.

There are various ways to get started on WordPress, and the platform provides various domains to excel your skills on. We will discuss five steps to land a job on WordPress successfully.

Spot your career choices for WordPress

It is possible to start developing on WordPress in domains – not all of which require technological skills! Even for people who do not understand coding, WordPress offers a number of opportunities. The first approach to landing a job with WordPress is recognizing your prospects for a WordPress career and what you want. Consider the skills you have and the skills you want to grasp.

Suppose you are not sure about what career choices WordPress provides. We will mention some of the opportunities that you can avail for yourself on the platform.
WordPress Developer: Developers of WordPress need good technical expertise, which usually requires them to be adept in the programming languages such as PHP, CSS, HTML, JavaScript, etc., familiar with the WordPress interface and how it operates. Developers usually write and refine the codes, if you are a tech nerd with good coding skills then you can land a job in website development with ease.

WordPress Administrator: WordPress administrators need a strong understanding of how the site works, plus some specific technical skills. It includes management of the website and its user accounts, performance analysis, and other daily activities that ensure the site’s proper functioning.

Theme Developer: Many businesses build their own WordPress extensions or themes, which can be offered for a flat fee or a monthly subscription on the markets such as codecanyon.com, themeforest.com, etc. If you have the ability to design versatile themes and know how to code then you can enter a prominent organization developing WordPress themes and plugins. After gaining some experience you can even create better themes or extensions for your own website.

WordPress Content Writer/Manager: If you are interested in writing, this might be the perfect domain for you. This function usually includes editing or modifying the content and writing new content on different WordPress websites. This may consist of web page revisions, blog posts, product descriptions, FAQs, and other written material. Though there is no need for technological expertise, it is helpful to consider some technical aspects such as taxonomies, installation, and removal of plugins, some specific HTML to incorporate graphics, images, gifs, etc., into the content.

Now settle down and reflect about what job would best suit you based on your previous experiences, existing knowledge, and skills! Then you have an objective to which you should serve.

Note: If you want to share your story, and incident of your life but don’t know how to write it to make it engaging for others. Narrative essay is the best way to write your life events in a memorable way.

Develop and improve the required WordPress capabilities

After analyzing the career you want to pursue, the next step is developing and improving your WordPress skills. You might want to learn the skills that will help to accomplish your aims and your dreams in designing and developing WordPress. So start working on the skills that you want to leverage in your career!

For example, you need to study and understand the CCS, Python, HTML, JavaScript, and WordPress framework if you want to be a WordPress developer. You can begin by taking WordPress courses to learn the fundamentals. Then learn how to use codding and software by taking technical courses on Tuts+, Treat house, and Code Academy etc. to code your own WordPress Website.

You can also work as a graphic designer that would enable you to become familiar with using Adobe Creative Suite. To learn more about this field, you can take in-person classes or online courses to further your knowledge.

Would you like to become a content writer? Start to write! Select some online articles and attempt to generate a new article based on its content. Learn the best guidelines for content blogging and content Layout. Learn how to do analysis and get to know the WordPress CMS in order to understand how to format and upload your articles properly.

Read More: 15 high-paying, low-stress jobs that are growing in the 2021.

You would like to learn more about WordPress SEO and other digital marketing ideas, too. This can be pretty helpful when searching for a job! However, it is a good idea to familiarize yourself with the forum, no matter what career you choose. We suggest having your own website. You can launch a WordPress website free of charge and learn the essentials.

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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. 

How to Create an Image Clip Animation with Slider Controls using Only HTML & CSS

In this blog you’ll learn how to create an Image Clip Animation with Slider Controls using only HTML & CSS.

To create an Image Clip Animation with Slider Controls using only HTML & CSS. First, you need to create two Files one HTML File and another one is CSS File.

1: First, create an HTML file with the name of index.html

<!DOCTYPE html>
<html lang="en" dir="ltr">
  <head>
    <meta charset="utf-8">
    <title>Image Clip Animation | Codequs</title>
    <link rel="stylesheet" href="style.css">
  </head>
  <body>
    <div class="wrapper">
      <input type="radio" name="slide" id="one" checked>
      <input type="radio" name="slide" id="two">
      <input type="radio" name="slide" id="three">
      <input type="radio" name="slide" id="four">
      <input type="radio" name="slide" id="five">
      <div class="img img-1">
        <!-- <img src="images/img-1.jpg" alt="">
      </div>
      <div class="img img-2">
        <img src="images/img-2.jpg" alt="">
      </div>
      <div class="img img-3">
        <img src="images/img-3.jpg" alt="">
      </div>
      <div class="img img-4">
        <img src="images/img-4.jpg" alt="">
      </div>
      <div class="img img-5">
        <img src="images/img-5.jpg" alt="">
      </div>
      <div class="sliders">
        <label for="one" class="one"></label>
        <label for="two" class="two"></label>
        <label for="three" class="three"></label>
        <label for="four" class="four"></label>
        <label for="five" class="five"></label>
      </div>
    </div>
  </body>
</html>

2: Second, create a CSS file with the name of style.css

*{
  margin: 0;
  padding: 0;
  box-sizing: border-box;
}
body{
  min-height: 100vh;
  display: flex;
  align-items: center;
  justify-content: center;
  background: -webkit-linear-gradient(136deg, rgb(224,195,252) 0%, rgb(142,197,252) 100%);
}
.wrapper{
  position: relative;
  width: 700px;
  height: 400px;
}
.wrapper .img{
  position: absolute;
  width: 100%;
  height: 100%;
}
.wrapper .img img{
  height: 100%;
  width: 100%;
  object-fit: cover;
  clip-path: circle(0% at 0% 100%);
  transition: all 0.7s;
}
#one:checked ~ .img-1 img{
  clip-path: circle(150% at 0% 100%);
}
#two:checked ~ .img-1 img,
#two:checked ~ .img-2 img{
  clip-path: circle(150% at 0% 100%);
}
#three:checked ~ .img-1 img,
#three:checked ~ .img-2 img,
#three:checked ~ .img-3 img{
  clip-path: circle(150% at 0% 100%);
}
#four:checked ~ .img-1 img,
#four:checked ~ .img-2 img,
#four:checked ~ .img-3 img,
#four:checked ~ .img-4 img{
  clip-path: circle(150% at 0% 100%);
}
#five:checked ~ .img-1 img,
#five:checked ~ .img-2 img,
#five:checked ~ .img-3 img,
#five:checked ~ .img-4 img,
#five:checked ~ .img-5 img{
  clip-path: circle(150% at 0% 100%);
}
.wrapper .sliders{
  position: absolute;
  bottom: 20px;
  left: 50%;
  transform: translateX(-50%);
  z-index: 99;
  display: flex;
}
.wrapper .sliders label{
  border: 2px solid rgb(142,197,252);
  width: 13px;
  height: 13px;
  margin: 0 3px;
  border-radius: 50%;
  cursor: pointer;
  transition: all 0.3s ease;
}
#one:checked ~ .sliders label.one,
#two:checked ~ .sliders label.two,
#three:checked ~ .sliders label.three,
#four:checked ~ .sliders label.four,
#five:checked ~ .sliders label.five{
  width: 35px;
  border-radius: 14px;
  background: rgb(142,197,252);
}
.sliders label:hover{
  background: rgb(142,197,252);
}
input[type="radio"]{
  display: none;
}

Now you’ve successfully created an Image Clip Animation with Sliders using only HTML & CSS.

#html #css 

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
>>> 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

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. 

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 

>>> 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 

>>> 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 

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

Hover Glyphs

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

Color Mapping 

>>> 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

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