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Python Data Visualization

Box Plot: Box Plot is the visual representation of the depicting groups of numerical data through their quartiles. Boxplot is also used for detect the outlier in data set. It captures the summary of the data efficiently with a simple box and whiskers and allows us to compare easily across groups. Boxplot summarizes a sample data using 25th, 50th and 75th percentiles. These percentiles are also known as the lower quartile, median and upper quartile. A box plot consist of 5 things. Minimum First Quartile or 25% Median (Second Quartile) or 50% Third Quartile or 75% Maximum Histograms and Density Plots: Histograms and density plots show the frequency of a numeric variable aloing the y-axix, and the value along the x-axis. The sns.distplot() function plots a density curve. This plot is aesthetically better than vanilla matplotlib. In y-axis it plots the probability. Rug Plot: This plots the actual data points as small vertical bars. The rug plot is simply specifi

python

What is Python? python is a popular programming language. It was created by Guido van Rossum and released in 1991. It is used for: web development (server-side) software development mathematics system scripting What can python do? python can be used on a server to create web applications. python can be used alongside software to create workflows. python can connect to database systems. It can also read and modify files. Python can be used to handle big data and perform complex mathematics. python can be used for rapid prototyping or for production-ready software development. Why Python? Python works on different platforms (Windows, Mac, Linux, Raspberry Pi etc) Python has a simple syntax similar to the English language. Python has syntax that allows developers to write programs with fewer lines than some other programming languages. Python runs on an interpreter system, meaning that code can be executed as soon as it is written. thsi means that prototyp