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Swarm Plot in Seaborn is used to draw a categorical scatterplot with non-overlapping points. The seaborn.swarmplot() is used for this. Draw swarms of observations on top of a box plot using the seaborn.boxplot().Let’s say the following is our dataset in the form of a CSV file −Cricketers2.csvAt first, import the required libraries −import seaborn as sb import pandas as pd import numpy as np import matplotlib.pyplot as pltLoad data from a CSV file into a Pandas DataFrame −dataFrame = pd.read_csv("C:\Users\amit_\Desktop\Cricketers2.csv") Draw swarms of observations on top of a box plot −sb.boxplot(x = "Matches", y = "Role", data= dataFrame, whis=np.inf) sb.swarmplot(x ... Read More
Swarm Plot in Seaborn is used to draw a categorical scatterplot with non-overlapping points. The seaborn.swarmplot() is used for this. Control swarm order by passing an explicit order i.e. ordering on the basis of a specific column using the order parameter −Let’s say the following is our dataset in the form of a CSV file −Cricketers2.csvAt first, import the required libraries −import seaborn as sb import pandas as pd import matplotlib.pyplot as pltLoad data from a CSV file into a Pandas DataFrame −dataFrame = pd.read_csv("C:\Users\amit_\Desktop\Cricketers2.csv") Plotting swarm plot with Academy and Matches. Control swarm order by passing an explicit order ... Read More
Swarm Plot in Seaborn is used to draw a categorical scatterplot with non-overlapping points. The seaborn.swarmplot() is used for this. To group the swarms by two categorical variables, set those variables in the swarmplot() using the x, y or hue parameters.Let’s say the following is our dataset in the form of a CSV file: Cricketers2.csvAt first, import the required libraries −import seaborn as sb import pandas as pd import matplotlib.pyplot as pltLoad data from a CSV file into a Pandas DataFrame −dataFrame = pd.read_csv("C:\Users\amit_\Desktop\Cricketers2.csv") Group the swarms by two categorical variables −sb.swarmplot(x = "Role", y = "Matches", hue = "Academy", ... Read More
Violin Plot in Seaborn is used to draw a combination of boxplot and kernel density estimate. The seaborn.violinplot() is used for this. Set explicit order using the order parameter of the violinplot().Let’s say the following is our dataset in the form of a CSV file − Cricketers.csvAt first, import the required libraries −import seaborn as sb import pandas as pd import matplotlib.pyplot as pltLoad data from a CSV file into a Pandas DataFrame −dataFrame = pd.read_csv("C:\Users\amit_\Desktop\Cricketers.csv") Plotting violin plot with Role and Age. Control order by passing an explicit order i.e. ordering on the basis of "Role".sb.violinplot(x = 'Role', y ... Read More
To read all excel files in a directory, use the Glob module and the read_excel() method.Let’s say the following are our excel files in a directory −Sales1.xlsxSales2.xlsxAt first, set the path where all the excel files are located. Get the excel files and read them using glob −path = "C:\Users\amit_\Desktop\" filenames = glob.glob(path + "\*.xlsx") print('File names:', filenames)Next, use the for loop to iterate and read all the excels files in a specific directory. We are also using read_excel() −for file in filenames: print("Reading file = ", file) print(pd.read_excel(file))ExampleFollowing is the complete code ... Read More
To merge more than one CSV files into a single Pandas dataframe, use read_csv. At first, import the required Pandas library. Here. We have set pd as an alias −import pandas as pdNow, let’s say the following are our CSV Files −Sales1.csvSales2.csvWe have set the path as string. Both the files are on the Desktop −file1 = "C:\Users\amit_\Desktop\sales1.csv" file2 = "C:\Users\amit_\Desktop\sales2.csv"Next, merge the above two CSV files. The pd.concat() merge the CSV files together −dataFrame = pd.concat( map(pd.read_csv, [file1, file2]), ignore_index=True)ExampleFollowing is the code −import pandas as pd file1 = "C:\Users\amit_\Desktop\sales1.csv" file2 = "C:\Users\amit_\Desktop\sales2.csv" print("Merging ... Read More
In this article, you will learn how to create a globe using react-threefiber. We will first make a sphere and then map a whole Earth map on it. This is an interesting texture loader feature using which we canmake any image to wrap over a sphere as texture. So, let's get started!ExampleFirst, download important libraries −npm i --save @react-three/fiber threeThis library react-three/fiber will be used to add webGL renderer to the website and to connect threejs and React.Download an image of Earth map and place it in the “src” folder. We have named the image file as "world-map.gif".Add the following ... Read More
If you ever used C + +, then you must have heard about Palindrome numbers. So in this guide, we will explain everything about "Nth even-length Palindrome" using appropriate examples. Palindrome numbers are numbers that stay the same after reversing them. Not only numbers but a word whose spelling stays the same when its characters are reversed. For Example −Numbers = {1, 121, 131, 656, 1221, 1551}Words = {saas, malayalam, level, mom}It looks complicated but very easy to perform on any system. So let's discuss the palindrome in brief.Nth Even length Palindrome Number11, 22, 33, 44, 55, 66, 77, 88, ... Read More
In this article, we will learn volume testing, its objectives and characteristics, attributes of volume testing, how it differs from load testing, and the challenges in volume testing, some useful guidelines for volume testing, the benefits and disadvantages of volume testing and some tools for and real-life examples of volume testing.Volume TestingVolume Testing is a category of software testing, performed to test a software application with a huge volume of data. The volume of data used in volume testing varies from the size of a database to the size of an interface file.When a software application is being tested with ... Read More
Testing Maturity Model (TMM) is a framework to determine the maturity of the software testing process. The main reason of using a TMM is to determine maturity and provide targets or goals for improving the software testing process to obtain progress. It can be both used as a stand-alone model and complemented with a process improvement model.TMM was developed by Illinois Institute of Technology and is an extension of Capability Maturity Model (CMM). It is like a detailed model to improve the testing process. The two major parts of a TMM model are −A set of five levels defining the ... Read More