This repository aims to provide tutorials for implementing various visualisations using Seaborn, Plotly, Bokeh, Networkx and even a sample report built using Tableau.

01 - Winter Olympics Analysis - Tableau.pdf : This file has a demo of the kind of plots you can make using Tableau. The data used for this tutorial is the Winter Olympics data.

02 - Introduction to Data Visualization with Seaborn.ipynb : Here, we can see how Seaborn can be used for exploratory data analysis. The dataset used for this visualisation can be found here https://think.cs.vt.edu/corgis/csv/graduates/graduates.html.

03 - Time-Series Visualization using bokeh.ipynb : This tutorial shows how Bokeh can be used to create interactive visuals. The dataset is the SF Property Crime data that is available here: https://data.sfgov.org/Public-Safety/Monthly-Property-Crime-2005-to-2015/k5vw-3yuz.

04 - Network Visualization using networkx.ipynb : In this tutorial, using dummy data, we can see how Networkx can be used to create graphs, which are visualised using Matplotlib and Plotly.

05 - Geographic Visualization using plotly and geoplotlib.ipynb : This tutorial shows the use of Plotly to create choropleth and symbol maps.

06 - Eigen Faces.ipynb : In this tutorial, we can see how image data can be preprocessed and how PCA analysis on the data can help us recontruct faces and see how similar they are to one another.

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Since some plots are interactive they can be best viewed here:

03 - Time-Series Visualization using bokeh.ipynb : https://nbviewer.jupyter.org/github/neerjad/DataVisualization/blob/master/03%20-%20Time-Series%20Visualization%20using%20bokeh.ipynb

05 - Geographic Visualization using plotly and geoplotlib.ipynb : https://nbviewer.jupyter.org/github/neerjad/DataVisualization/blob/master/05%20-%20Geographic%20Visualization%20using%20plotly%20and%20geoplotlib.ipynb