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.

About the offer:

Jupyter Hub for Data Wrangling using Python gives you an effortless coding environment in the cloud with pre-installed Data Wrangling python libraries, which reduces the burden of installation and maintenance of tasks. Data wrangling is important because it saves costs, improves data analysis, increases data usability and enhances business insights. Through our offer, users can work on various application domains of Data Wrangling such as Fraud Detection, Customer Behavior Analysis, and many more. Furthermore, users can combine data from multiple sources, identify and remove data gaps, and delete irrelevant data for better analysis. The heavy computations required for these applications are performed in the Azure cloud, which increases responsiveness and processing speed.

Who benefits from this offer:

Teams of developers
Data scientists
Machine learning engineers
Scientific researcher groups
And anyone else interested in data science tools

What is included in this offer:

Pre-installed Python libraries and packages for Data Wrangling.
Ready to go notebooks which consist of example codes through which user can get guidance for working on Data Wrangling applications.
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.

Technical Specifications:

Minimum Recommended memory: 4GB RAM
Minimum Recommended vCPU: 2 vCPUs
Operating System: Ubuntu 20.04

Following Authoring Tools are supported in this offer:

JupyterHub
Jupyter Lab
Terminal

Our instance supports following Python Data Wrangling libraries:

Numpy
Matplotlib
Pandas
Seaborn
Plotly
Plotnine
Bokeh
Ggplot
Datacleaner
Dora
Scipy
Statsmodels
xml-python
Arrow
Scrubadub
Tabulate
Modin
Dabl

Our offer provides repositories from following sources:

GitHub repository of book Data Wrangling with Python, by author Jacqueline Kazil, Katharine Jarmul.
GitHub repository of book The Data Wrangling Workshop, by author Brian Lipp, Shubhadeep Roychoudhury, and Tirthajyoti Sarkar.
GitHub repository of book Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython, by Wes McKinney.
GitHub repository of book Practical Data Wrangling, by Allan Visochek.

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

Use following credentials:

Username: guest
Password: guest@123

The Jupyter Trademark is registered with the U.S. Patent & Trademark Office.

Jupyter Hub for Data Wrangling using Python packaged by Data Science DojoData Science Dojo

Jupyter Hub for Data Wrangling using Python packaged by Data Science Dojo

Data Science Dojo

Jupyter Hub for Data Wrangling using Python packaged by Data Science Dojo

Data Science Dojo

Jupyter Hub for Data Wrangling using Python packaged by Data Science Dojo
Data Science Dojo