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  5. Tableau vs ggplot2

Tableau vs ggplot2

OverviewDecisionsComparisonAlternatives

Overview

Tableau
Tableau
Stacks1.3K
Followers1.4K
Votes8
ggplot2
ggplot2
Stacks125
Followers70
Votes0
GitHub Stars6.8K
Forks2.1K

Tableau vs ggplot2: What are the differences?

Key Differences Between Tableau and ggplot2

Tableau and ggplot2 are both popular data visualization tools used for analyzing and presenting data. However, they differ in several ways. Here are the key differences between Tableau and ggplot2:

  1. User Interface: Tableau provides a user-friendly drag-and-drop interface that allows users to create visualizations without any coding. On the other hand, ggplot2 is a package in R that requires users to write code to create visualizations. This makes Tableau more accessible for non-programmers and beginners.

  2. Flexibility: ggplot2 offers more flexibility and customization options compared to Tableau. Users can leverage the full power of R programming to manipulate and transform data before creating visualizations. Tableau, on the other hand, has built-in data manipulation capabilities, but they are more limited compared to R.

  3. Integration: Tableau is a standalone software that provides a complete solution for data visualization and analytics. It allows users to connect to multiple data sources, perform complex calculations, and create interactive dashboards. ggplot2, on the other hand, is just a package in R and requires users to manually import and manipulate data using R functions before visualizing it.

  4. Learning Curve: Tableau has a relatively shorter learning curve compared to ggplot2. With its intuitive interface, beginners can quickly start creating visualizations without much prior knowledge. ggplot2, on the other hand, requires users to have a strong understanding of R programming and data manipulation concepts before they can effectively use it for visualization.

  5. Community Support: ggplot2 benefits from a large and active community of R users and developers. This means there are extensive online resources, tutorials, and forums available for users to seek help, learn new techniques, and troubleshoot issues. Tableau also has a strong community, but it may not be as extensive and specific to data visualization as the ggplot2 community.

  6. Cost: Tableau is a commercial software that comes with a cost. It offers different pricing tiers based on the features and capabilities required. ggplot2, on the other hand, is an open-source package in R, which means it is free to use for anyone with R installed. This makes ggplot2 a more cost-effective option for those on a tight budget or working with limited resources.

In summary, Tableau offers a user-friendly interface, while ggplot2 provides more flexibility and customization options. Tableau is a standalone software with built-in data manipulation capabilities, while ggplot2 is a package in R that requires users to write code for data manipulation. Tableau has a shorter learning curve but comes with a cost, whereas ggplot2 is free and benefits from a large community support.

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Advice on Tableau, ggplot2

Vojtech
Vojtech

Head of Data at Mews

Nov 24, 2019

Decided

Power BI is really easy to start with. If you have just several Excel sheets or CSV files, or you build your first automated pipeline, it is actually quite intuitive to build your first reports.

And as we have kept growing, all the additional features and tools were just there within the Azure platform and/or Office 365.

Since we started building Mews, we have already passed several milestones in becoming start up, later also a scale up company and now getting ready to grow even further, and during all these phases Power BI was just the right tool for us.

353k views353k
Comments
Wei
Wei

CTO at Flux Work

Jan 8, 2020

Decided

Very easy-to-use UI. Good way to make data available inside the company for analysis.

Has some built-in visualizations and can be easily integrated with other JS visualization libraries such as D3.

Can be embedded into product to provide reporting functions.

Support team are helpful.

The only complain I have is lack of API support. Hard to track changes as codes and automate report deployment.

230k views230k
Comments

Detailed Comparison

Tableau
Tableau
ggplot2
ggplot2

Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.

It is a general scheme for data visualization which breaks up graphs into semantic components such as scales and layers.

Connect to data on prem or in the cloud—whether it’s big data, a SQL database, a spreadsheet, or cloud apps like Google Analytics and Salesforce. Access and combine disparate data without writing code. Power users can pivot, split, and manage metadata to optimize data sources. Analysis begins with data. Get more from yours with Tableau.; Exceptional analytics demand more than a pretty dashboard. Quickly build powerful calculations from existing data, drag and drop reference lines and forecasts, and review statistical summaries. Make your point with trend analyses, regressions, and correlations for tried and true statistical understanding. Ask new questions, spot trends, identify opportunities, and make data-driven decisions with confidence.; Answer the “where” as well as the “why.” Create interactive maps automatically. Built-in postal codes mean lightning-fast mapping for more than 50 countries worldwide. Use custom geocodes and territories for personalized regions, like sales areas. We designed Tableau maps specifically to help your data stand out.; Ditch the static slides for live stories that others can explore. Create a compelling narrative that empowers everyone you work with to ask their own questions, analyzing interactive visualizations with fresh data. Be part of a culture of data collaboration, extending the impact of your insights.
Axis titles; Tickmarks; Margins and points in ggplot2 look cooler
Statistics
GitHub Stars
-
GitHub Stars
6.8K
GitHub Forks
-
GitHub Forks
2.1K
Stacks
1.3K
Stacks
125
Followers
1.4K
Followers
70
Votes
8
Votes
0
Pros & Cons
Pros
  • 6
    Capable of visualising billions of rows
  • 1
    Responsive
  • 1
    Intuitive and easy to learn
Cons
  • 3
    Very expensive for small companies
No community feedback yet
Integrations
No integrations available
MATLAB
MATLAB
React
React
Python
Python
SageMath
SageMath
Jupyter
Jupyter

What are some alternatives to Tableau, ggplot2?

D3.js

D3.js

It is a JavaScript library for manipulating documents based on data. Emphasises on web standards gives you the full capabilities of modern browsers without tying yourself to a proprietary framework.

Metabase

Metabase

It is an easy way to generate charts and dashboards, ask simple ad hoc queries without using SQL, and see detailed information about rows in your Database. You can set it up in under 5 minutes, and then give yourself and others a place to ask simple questions and understand the data your application is generating.

Highcharts

Highcharts

Highcharts currently supports line, spline, area, areaspline, column, bar, pie, scatter, angular gauges, arearange, areasplinerange, columnrange, bubble, box plot, error bars, funnel, waterfall and polar chart types.

Plotly.js

Plotly.js

It is a standalone Javascript data visualization library, and it also powers the Python and R modules named plotly in those respective ecosystems (referred to as Plotly.py and Plotly.R). It can be used to produce dozens of chart types and visualizations, including statistical charts, 3D graphs, scientific charts, SVG and tile maps, financial charts and more.

Superset

Superset

Superset's main goal is to make it easy to slice, dice and visualize data. It empowers users to perform analytics at the speed of thought.

Chart.js

Chart.js

Visualize your data in 6 different ways. Each of them animated, with a load of customisation options and interactivity extensions.

Recharts

Recharts

Quickly build your charts with decoupled, reusable React components. Built on top of SVG elements with a lightweight dependency on D3 submodules.

ECharts

ECharts

It is an open source visualization library implemented in JavaScript, runs smoothly on PCs and mobile devices, and is compatible with most current browsers.

Cube

Cube

Cube: the universal semantic layer that makes it easy to connect BI silos, embed analytics, and power your data apps and AI with context.

ZingChart

ZingChart

The most feature-rich, fully customizable JavaScript charting library available used by start-ups and the Fortune 100 alike.

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