pandas vs. Tableau Public

Pandas are great for quick and relatively simple analytics and visualizations

Pandas work well for exploratory ad-hoc analytic work

But , We had little success in implementing complicated predictive analytics. And large data sizes can be a problem.

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Tableau public is the best platform to build dashboards for your personal profile and share with recruiters. It's always good to keep ourselves updated on the latest features, create sample dashboards and save them to a personal profile. Tableau public is free and doesn't need any subscription. anyone can create an account and start building reports.

• It is easy to do statistical analysis
• It is easy to clean the data
• It is easy to produce graphs and charts to visualize

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• Data visualization: lots of different options, including bar, scatter, pie, waterfall charts to explore relationships between variables, and to present findings/trends to different teams
• Integrates readily with limited, though different data sources: TXT, CSV, TDE, Access
• Exports reports for review of different dashboards: client-ready/team-ready, with a clean and tidy presentation in PDF format (or hardcopy)

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• There are a lot of libraries and ways to do visualization. Sometimes it is very confusing.
• Error handling can be a challenge. Sometimes the error messages do not provide valuable clues for the debugging.
• In our case, there are a bunch of different frameworks and libraries working together. I would rather work with one framework, well tuned for my use case

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• Tableau Public (both Desktop and Server) like their "for a fee" counterparts offer very easy to learn and use tools to transform data into pictures and gain insights into your data. Most organizations report a reduction in development time of 10x vs. other similar tools, due to the intuitive user interface. That said, with Tableau Public, published workbooks are "disconnected" from the underlying data sources and require periodic updates when the data changes. Users are limited to 1 Gb of storage space per user ID and password as well.
• I would like to see better options for public sharing of visualizations and data from within the "for a fee" products as more and more organizations are moving in the direction of data sharing with partners and their communities.

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It's free, right? I'll keep using the free version. So the real question to ask is this? Will I pay $999 for the Personal version or $1,999 for the Professional? Yikes! That is a big stretch. I'm not sure about that. The product comparison chart is at: http://www.tableausoftware.com/public/comparison

Over the years, we tried a lot of different frameworks and tools, homegrown and commercial. Pandas provide the best results.

It is lightweight, flexible and easy to implement.

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Tableau public is a great training tool to understand the basics of Tableau before buying it. A great tool to extend Excel's visualization and to publish data for others. Not useful for anything you need secure. No ability to access databases. Static information only.

I have not yet required to contact support as the documentation and help i found online has always worked so far

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I found it sufficient, and fast. I could easily "kick the tires" with Tableau on my data so I got up and running fast.

Start at the end and work backward. Identify the business case / issue and questions the end users have, then identify the data needed, and where to get it.

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All these frameworks are great for gathering data and providing some initial analysis. But for real performance debugging work one needs more than tools provided by this tools. That's where the pandas excel.

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Google Charts/Drive is sufficient for simpler data sets, but it does not integrate with other web platforms and the visualization does not look as professional. I'm not aware of any other competitors that offer the same package as Microsoft.

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• Performance debugging was time consuming and mostly poorly automated exploratory process. Once we started use pandas for these tasks, it really moved the needle. Pandas are instrumental to provide actionable insights. As a result we were able to improve notably cloud software resource utilization and performance
• Analytics implemented with pandas allow us to detect and. address problems in our APIs before they are notable to our customers

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• Tableau Public visualizations have helped drive traffic to our content and sites
• The lack of cost means it's easy to demonstrate our experience to attract paying clients

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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info