Data-Visualisation

Seaborn which is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics.Easiest way to install seaborn is to use pip.

Libraries used

The libraries used here are pandas, numpy, scipy, matplotlib, seaborn.To import random numbers and apply visulisation to them numpy.randm library is used it imports the random values, the number of values we need we have to state in advance.

Visualisation Techniques

The visualisation technique to be used depends upon the variables, number of variables, and information we want to extract from the raw data. Incase of single variable the techniques used are:-

1. Dotchart
2. Barplot
3. Histogram

The visualisation technique for multiple variables are:-

1. Heat map
2. Boxplot
3. Violin Plot
4. Regression
5. KDE

Data Set

There are 2 datasets which has been used one is flight.csv and the other diamond.csv both of them have been used from seaborn-data.The Diamond.csv has been ussed to plot regression plot,scatter plot, violin plot, whereas the flight.csv has been used to plot heat maps and cluster maps. All of these visualisation techniques are multiple variable tools or techniques, i.e. when there are more than 2 variables or columns in a data set and we want to find the inter relation betweeen them.