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We can create a Pivot Table with multiple columns. To create a Pivot Table, use the pandas.pivot_table to create a spreadsheet-style pivot table as a DataFrame.At first, import the required library −import pandas as pdCreate a DataFrame with Team records −dataFrame = pd.DataFrame({'Team ID': {0: 5, 1: 9, 2: 6, 3: 11, 4: 2, 5: 7 }, 'Team Name': {0: 'India', 1: 'Australia', 2: 'Bangladesh', 3: 'South Africa', 4: 'Sri Lanka', 5: 'England'}, 'Team Points': {0: 95, 1: 93, 2: 42, 3: 60, 4: 80, 5: 55}, 'Team Rank': {0: 'One', 1: 'Two', 2: 'Six', 3: 'Four', 4: 'Three', 5: ... Read More
Keyword-driven TestingKeyword-driven testing is a functional testing, also called table-driven testing or action-wordbased testing. In this testing, a table format is used, most likely a spreadsheet, to define keywords for a function to be executed.Basically, it is a scripting technique which uses data files to contain keywords that are related to the software under testing. These keywords represent a set of actions needed to execute a specific step. It includes high-level and low-level keywords, as well as keyword arguments, that is composed to define the action of a test case.The testing starts by identifying a set of keywords, then associating ... Read More
To get the minimum of column values, use the min() function. At first, import the required Pandas library −import pandas as pdNow, create a DataFrame with two columns −dataFrame1 = pd.DataFrame( { "Car": ['BMW', 'Lexus', 'Audi', 'Tesla', 'Bentley', 'Jaguar'], "Units": [100, 150, 110, 80, 110, 90] } )Finding the minimum value of a single column “Units” using min() −print"Minimum Units from DataFrame1 = ", dataFrame1['Units'].min() In the same way, we have calculated the minimum value from the 2nd DataFrame.ExampleFollowing is the complete code −import pandas as pd # Create DataFrame1 dataFrame1 = pd.DataFrame( { ... Read More
A common query that keeps running in the mind of every IT aspirant is: do software testers have to write or learn code? In this article, we will be discussing the solution to this question. Software testing can be done manually as well as through automation. We will be discussing what skills a good tester must possess, what all knowledge they must have, and how much coding knowledge a good tester must have.Before answering this question, we must understand various software testing roles. Quality assurance (QA) testing in software testing is primarily divided into two broad categories −Quality Analysts − ... Read More
The Basics of CookiesWe'll start by discussing what cookies are and how they operate. When you understand how cookies operate, it will be much easier for you to comprehend the test cases for testing cookies. How can cookies end up on your computer's hard drive? Also, how can we change our Cookie preferences?What Exactly Is a Cookie?A cookie is a little piece of data that a web server stores in a text file on the user are hard disc. The web browser then uses this information to obtain information from that machine.The cookie, in general, includes customized user data or information ... Read More
Backend TestingBacked testing is a method or technique that examines the server of database side of web applications or software. The primary motive of performing this test is to test the application layer or database layer to make the software defect-free, and prevent deadlock, data corruption, or data loss. For seamless and efficient working of a software, its GUI and database must interact with each other. Usually, databases are validated for: ACID functions, CRUD operations, Schema, Migration, business rule conformance, security purposes and performance.This testing is also referred to as "database testing". The data entered through the frontend is stored ... Read More
To create a 3D animation using matplotlib, we can take the following steps −Import the required packages. For 3D animation, you need to import Axes3D from mpl_toolkits.mplot3d and matplotlib.animation.Set the figure size and adjust the padding between and around the subplots.Create t, x, y and data points using numpy.Create a new figure or activate an existing figure.Get the instance of 3D axes.Turn off the axes.Plot the lines with data.Create an animation by repeatedly calling a function *animate*.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt import matplotlib.animation as animation from mpl_toolkits.mplot3d import Axes3D plt.rcParams["figure.figsize"] ... Read More
To create broken horizontal bar graphs in matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a figure and a set of subplots.Plot a horizontal sequence of rectangles.Scale X and Y axes limit.Configure the grid lines.Annotate the broken bars.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True fig, ax = plt.subplots() # Horizontal sequence of rectangles ax.broken_barh([(110, 30), (150, 10)], (10, 9), facecolors='tab:blue') ax.broken_barh([(10, 50), (100, 20), (130, 10)], (20, 9), facecolors=('tab:orange', 'tab:green', 'tab:red')) # Scale ... Read More
To modify a 2d scatterplot to display color based on a third array in a CSV file, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Read the CSV file with three headers.Create a new figure or activate an existing figure.Add an 'ax' to the figure as part of a subplot arrangement.Make a scatter plot with CSV file data points.To display the figure, use show() method.Exampleimport pandas as pd from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True columns = ["data1", "data2", "data3"] df = ... Read More
To make a multiline plot from .CSV file in matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a list of columns to fetch the data from a .CSV file. Make sure the names match with the column names used in the .CSV file.Read the data from the .CSV file.Plot the lines using df.plot() method.To display the figure, use show() method.Exampleimport pandas as pd from matplotlib import pyplot as plt # Set the figure size plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True # Make a list of ... Read More