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front end developers data visualization tools comparison contrast data capture tools

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front end developers data visualization tools comparison contrast data capture tools

What are the best data visualization tools?

Well, that’s a tricky question, because there are so many different types of data visualization tools. These tools meet different requirements and demand corresponding skills for users.

In this article, I reviewed what I consider to be the 6 mainstream types and 14 top data visualization tools. The comparison covers the use of these tools, their respective advantages, suitable crowd, and price. Hope can help you find the best data visualization tool for you.

1.Code tools

The code tools are characterized by more freedom of data parameters, increased data processing capacity, and more diverse data play.
Javascript, Python, and R are popular data visualization programming language nowadays, and they all have rich visualization library.

D3.js

D3.js is an open-source JavaScript library that’s used to create data visualizations with HTML, SVG, and CSS. D3 allows you to handle the Document Object Model (DOM) based on your data.

D3 is the best chart gallery, which also can be applied with Python or R.
I would recommend you use Javascript or R other than Python considering the Python-nvd3 library last updated in 2016, which is outdated compared to others. D3.js is highly flexible while hard for newbies.

Suitable crowd:front-end developers who are good at Javascript, SVG or DOM
Cost: Free

Plotly

Plotly is an open-source, interactive, and browser-based python graphing library. It enables creating complex interactive charts that can be smoothly applied to dashboards or websites. It is built on top of the d3.js visualization libraries. Therefore, Plotly is an advanced chart gallery.

Its distinct advantage is creating multi-chart visualizations when comparing datasets. Besides, you can set up Plotly to work in online or offline mode or jupyter notebooks.

Suitable crowd:front-end developers who are good at Python
Cost: Free with commercial plans

gglot2

ggplot2 is a data visualization package for the statistical programming language R. The idea of ggplot2 is to separate the drawing from the data. It is to make the drawing according to layers, which is conducive to architectural thinking.

For professionals who need making plots involving mountains of data, ggplot2 is the best choice. It is easy and quick to build plots in layers to display complex stories. You can define various underlying components and simple functions to achieve complex charts.

Suitable crowd: professionals with R knowledge
Cost: quote-based

2. Visual Reporting or BI

If you are going to use professional data visualization while having no programming background, you should try the following data visualization tools with drag-and-drop elements. In addition to visualization, such tools generally focus on database connection, data analysis, and data processing.

Beginners do not need to master too many such tools. Excel, FineReport, and Tableau are the first choice. Excel is widely used; FineReport is easy to create complex reports and dashboards, Tableau is the best for data analysis via visualization.

Excel

As a part of Microsoft’s business office suite, you must be familiar with Excel. Excel offers some standard charts, from unit heat maps to scatter plots. Although it’s an entry-level tool, it’s a great way to get started if you want to explore data.

Suitable crowd: Anyone
Price: Free with commercial plans

FineReport

FineReport is a reporting software while being distinct at data visualization, primarily visualizing your data via reports or dashboards with impressive HTML5 charts including 3d and dynamic effects.

What impressed me most is that it saved me much time to develop reports. Before using FineReport, we made 10 excel tables for ten stores, which were very troublesome. But with FineReport, we just need to use the parameter query in one template, and then export data in batches.

The other features worth mentioning is data integration and data entry in terms of datasets for data visualization.

Suitable crowd: for report developers and BI engineers
Price: Free for personal use, Quota-based for companies

Tableau

Tableau is a data analytics and visualization tool. Almost every data analyst will mention Tableau. It has standard built-in analysis charts and some data analysis models.

Unparalleled capacities of visualizing information are on top the list of Tableau software benefits. Its graphs and color schemes are v

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