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As a data scientist, it’s very important to communicate the insights that we made from data through visualizations. Not only as a data scientist but also if you are a business owner you need to make decisions accurately and quickly by analyzing complex datasets. This is hard, but it can be made easier using Web-Based Dashboards.
Well, there are many online services that provide it on a monthly subscription basis like, Mixpanel, Dashboard Job Summary Web App, Dribble stats. etc. It is often very expensive for small business owners to afford since their base monthly plan costs $50 or more.
So the question is Can we build a dashboard Web Application for free?
Let’s see how we can do it.
Steps In Making A Data Science Dashboard For Free
Well, there are many ways of doing it, but the one we are discussing here is the most common way. Why stick to common ways? The answer is community support if you are following the way that everyone used to follow problems that you may encounter in the journey will be solved by someone already. If you face any problem while making the dashboard there are free open forums and communities to help you.
Steps Involved In Making Dashboard Using Dash
Just follow these 5 simple steps to make your own data science dashboard
1) Importing and Activating Dash and other dependencies
Install and import dash library to your project.
Use this code to install dash
pip install dash
Then import it into your project
Well, there are some other dependencies that you should import along with dash into your project. A detailed study should be made apart from this article. We wish to provide a basic understanding only.
After that, we need to activate dash using the following code
app = dash.Dash(__name__) server = app.server if __name__ == '__main__': app.run_server(debug=True)
After activating it if you open http://127.0.0.1:8050/ this in your web browser you can access the server that dash has made in your system.
2) Preparing the data
This is the most important step in the entire process, We need to collect and reframe data that has to be visualized. Advanced tools like pandas and NumPy are made use of here. For those who don’t know what is pandas and NumPy, both are python libraries that are widely used in data science along with sci-kit learn.
Data preparation has six essential steps, they are namely, accessing the data, ingesting, cleansing, formating combining, and finally analyzing the data. each of these steps has its own importance in the total throughput of the process.
3) Visualizing Charts
After that, we will create an app layout that will encapsulate HTML objects in the module. This will be your main access to layout the graphs and adjust the relative sizes to your view screen sizes. A module called
dcc , which is a core component of the dash that will handle the charts like a bar graph, line graph, and dropdown.
4) Dropdowns and Input Filter Selections
This is the time where you can specify your own filter to render your visualization component.
Use the following code
dcc.Dropdown( id='product-dropdown', options=dict_products, multi=True, value = [""] )
There are many components like in the given code, each handles specific tasks.
Id designates the function to be called.
options will insert the key-value pairs of all the available options.
multi an attribute will allow you to select more than 1 option.
value an attribute will store your dropdown values at the start of the server run.
5) Styling and Finishing
Styling in Dash is easy. By default, Dash already has a preconfigured setting to access the assets folder. This is where you could overwrite the CSS for styling and js for web behavior. You can insert the stylesheet.css to beautify your Dash Web Application. Specific room for improvements would be the margin among components and table borders.
Pros And Cons Of Custom Built Web-Based Dashboards
The Process of building a custom web-based dashboard is actually a cheap process but has many good sides and drawbacks. Let’s discuss some of them,
|We can have more control over the dashboard. you can give custom colors or shapes, can bring in data from any source.||The entire process is actually very time-consuming as we have to start everything from scratch.|
|It can provide better security and user access controls.||and initial upfront investment is required at the starting itself, in case if you hire someone for building a web-based dashboard for you.|
|It can be updated as per our needs.||If a wrong company or team is chosen for the purpose of developing a web-based dashboard it can lead to blown investment, responsive development. etc|
Pros And Cons Of Off The Shelf Web Dashboard Services Or Software
As we can see developing a custom web-based dashboard either requires a lot of technical knowledge or a large sum of initial upfront investment. Both of which are actually not suitable for small-scale business owners, in such cases we can make use of pre-build off-shelf software designed for this purpose.
There are many online companies that provide these services, it is not actually a good idea to list them here because almost all of them are sector-specific. You have to do your own research to find the best service that suits your business. Here let’s see the pros and cons of such services.
|A low-cost alternative for custom dashboards. Some of the services come in the form of subscriptions, which gives us the flexibility to unsubscribe from them in case if you don’t like their services or you don’t get the outcome you expect.||Gives us less control over the dashboard. As our business grows we will definitely need additional features in the software, if our needs are beyond the limits of the software our throughput may get reduced.|
|Since the service is pre-built there is no need for spending a lot of time on development. we can start using the dashboard right after installing the software or purchasing the subscription.||All the features that software offers may not be required for your business, but then also you right need to pay for those unused features unnecessarily.|
|No technical knowledge is required, anyone with no prior knowledge about python, or coding in general, could use the services.||Offers low security to data, as hackers can exploit vulnerabilities in publically accessible software and services.|
Here we have discussed how to make a dashboard for data analytics for free, the technical side is not explained in deep since that was not our intention. What we focused on was to introduce you to this amazing way to make your own data analytics dashboard and the 5 simple steps by which you can make your own dashboard. Knowledge from this article alone is not sufficient for practical purposes, we recommend you to do further research on this topic and learn adequate skills before you proceed.
All that we intend to do is to give you a strong basic understanding of the tools used for it and the steps involved.