Data Science Dojo delivers data science education, consulting, and technical services to harvest the power of data.

Trademarks: This software listing is packaged by Data Science Dojo. The respective trademarks mentioned in the offering are owned by the respective companies, and use of them does not imply any affiliation or endorsement.

Jupyter Hub for Data Visualization using Python gives you an effortless coding environment in the cloud and pre-installed data visualization python libraries, which reduces the burden of installation and maintenance of tasks. Data Visualization allows people or teams to understand better the nature of a dataset and the ability to convey the right message to an external audience. Through this offer, users can quickly identify errors, outliers, and inaccuracies in data. Also, the speed of decision-making can be improved with the help of visualization once the key trends are observed. Moreover, the responsiveness and processing speed improves as the computations are not performed locally but in the cloud.

• Students
• Data scientists
• Data Analysts
• Teams of developers
• Machine learning engineers
• And anyone else interested in data science or who wants to visualize their data interactively

• Pre-installed Python libraries and packages for Data visualization
• Ready to go notebooks which consist of example codes through which user can get guidance for working on Data analytics and visualization
• Code consoles to run code interactively, with full support for rich output
• Kernel-backed documents enable code in any text file (Markdown, Python, etc.) to be run interactively in Jupyter kernel
• Work with multiple notebooks at the same time

• Minimum recommended memory: 4 GB
• Minimum recommended vCPU: 2
• Operating System: Ubuntu 18.04
• Authoring Tools: Jupyter Hub, Jupyter Lab, and Terminal

Our instance supports following Python data visualization libraries:

• Numpy
• Matplotlib
• Pandas
• Seaborn
• Plotly
• Bokeh
• Plotnine
• Pygal
• Ggplot
• Missingno
• Leather
• Holoviews
• Chartify
• Cufflinks

Our offer provides repositries from following sources:

• Data Visualization with Python by Packt (From Book: "Interactive Data Visualization with Python")
• Data Visualization Recipes in Python by Packt (By Theodore Petrou)
• Python data-viz workshop by Stefanie Molin (Author of "Hands-On Data Analysis with Pandas")
• Data Visualization(Matplotlib) by Udacity

The default HTTP port JupyterHub listen to is 8000. You can access the web interface at http://yourip:8000

• Username: guest
• Password: guest@123