Data Analysis using Python - PivottableJS | Cloud Kitchen | Jupyter | Business Intelligence

Python is a powerful programming langauage which supports libraries which can be used for variety of tasks like APIs, data analysis, machine learning, etc. Anaconda is an open-source distribution of the Python and R programming languages for data science that aims to simplify package management and deployment. [1] The Jupyter Notebook is the original web application for creating and sharing computational documents. It offers a simple, streamlined, document-centric experience. [3] PivotTable.js is an open-source Javascript Pivot Table (aka Pivot Grid, Pivot Chart, Cross-Tab) implementation with drag'n'drop functionality written by Nicolas Kruchten. [4] In this video, we will be learning: • How to work with jupyter notebook • How to import libraries and run python scripts in jupyter notebook • Understand pivottableJS library and use pivot_ui for creating pivots, charts and visualization Timeline: • Introduction to Cloud Kitchen data - 1:10 • Questions - 2:42 • Data extracting - 3:03 • Installing PivottableJS - 5:04 • Question 1: Most popular item - 7:18 • Question 2: Which Partner had the most order? - 7:53 • Question 3: Which Brand is the most popular? - 8:08 • Question 4: Which kitchen take longest time and shortest time to prepare? - 9:05 • Question 5: Distribution of final bill by brand - 13:19 How can pivottableJS help you? • Data analysis • Data visualization • Creating pivotcharts, pivot tables * The information on the videos and the resources available for download/viewing through this YouTube Channel are for educational and informational purposes only.​ Source: 1. https://www.dominodatalab.com/data-science-dictionary/anaconda 2. https://www.python.org/doc/essays/blurb/ 3. https://jupyter.org/ 4. https://pivottable.js.org/examples/