Programming Articles - Page 1045 of 3363

Bar Plot in Seaborn is used to show point estimates and confidence intervals as rectangular bars. The seaborn.barplot() is used for this. Display Standard Deviation of Observations using confidence interval ci parameter value sd.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 bar plot with Academy and Matches. Display Standard Deviation of Observations using confidence interval parameter value "sd" −sb.barplot(x = "Academy", y = ... Read More

To select a subset of rows and columns, use the loc. Use the index operator i.e. the square bracket and set conditions in the loc.Let’s say the following are the contents of our CSV file opened in Microsoft Excel −At first, load data from a CSV file into a Pandas DataFrame −dataFrame = pd.read_csv("C:\Users\amit_\Desktop\SalesData.csv")Select a subset of rows and columns combined. Right column displays the column you want to display i.e. Cars column here −dataFrame.loc[dataFrame["Units"] > 100, "Car"]ExampleFollowing is the code −import pandas as pd # Load data from a CSV file into a Pandas DataFrame: dataFrame = pd.read_csv("C:\Users\amit_\Desktop\SalesData.csv") ... Read More

Point Plot in Seaborn is used to show point estimates and confidence intervals using scatter plot glyphs. The seaborn.pointplot() is used for this. For explicit order, use the order parameter of the pointplot() method.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 point plot with “Academy” and “Age”. Control order by passing an explicit order i.e. ordering on the basis of "Academy". Ordering using ... Read More

Point Plot in Seaborn is used to show point estimates and confidence intervals using scatter plot glyphs. The seaborn.pointplot() is used for this. To avoid drawing lines to connect points, simply set the “join” parameter of the pointplot() method to False.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")Now, plot the Horizontal point plot. The “join” parameter is set as False to avoid drawing ... Read More

To create a Time Series Plot with multiple columns using Line Plot, use the lineplot(). At first, import the required libraries −import seaborn as sb import pandas as pd import matplotlib.pyplot as pltCreate a DataFrame. We have multiple columns in our DataFrame −dataFrame = pd.DataFrame({'Date_of_Purchase': ['2018-07-25', '2018-10-25', '2019-01-25', '2019-05-25', '2019-08-25', '2020-09-25', '2021-03-25'], 'Units Sold': [98, 77, 51, 70, 70, 87, 76], 'Units Returned' : [60, 50, 40, 57, 62, 51, 60] })Plot time series plot for multiple columns −sb.lineplot(x="Date_of_Purchase", y="Units Sold", data=dataFrame) sb.lineplot(x="Date_of_Purchase", y="Units Returned", data=dataFrame)ExampleFollowing is the code −import seaborn as sb import pandas as pd import matplotlib.pyplot as ... Read More

The app.engine() method is used for registering the given template engine callback as "ext". The require() method needs the engine based on the function by default.Use the following methods for engines that do not provide the extensions (or want to map different extensions) or express out of the box.app.engine('html', require('ejs').renderFile)Syntaxapp.engine(ext, callback)Example 1Create a file with the name "appEngine.js" and copy the following code snippet. After creating the file, use the command "node appEngine.js" to run this code.// app.engine() Method Demo Example // Importing the express module const express = require('express'); // Initializing the express and port number var ... Read More

Horizontal point plots are a plotting based on the values of x and y i.e. the columns of the dataset you consider. Point Plot in Seaborn is used to show point estimates and confidence intervals using scatter plot glyphs. The seaborn.pointplot() is used for this.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")Now, use the pointplot() and set the x and y values −sb.pointplot(x ... Read More

The app.enable() function sets the Boolean setting ‘name’ to ‘true’, where name defines one of the properties from the app settings table. Using the app.set('foo', true) for a Boolean property is same as calling the app.enable('foo') function.Syntaxapp.enable(name)Example 1Create a file with the name "appEnable.js" and copy the following code snippet. After creating the file, use the command "node appEnable.js" to run this code.// app.enable() Method Demo Example // Importing the express module const express = require('express'); // Initializing the express and port number var app = express(); // Initializing the router from express var router = express.Router(); ... Read More

The app.disable() method disables the setting name passed in the function. This method sets the setting name to False. We can perform the same function by using the app.set() method too, by passing its value as False.Syntaxapp.disable(name)Example 1Create a file with the name "appDisable.js" and copy the following code snippet. After creating the file, use the command "node appDisable.js" to run this code.// app.disable() Method Demo Example // Importing the express module const express = require('express'); // Initializing the express and port number var app = express(); // Initializing the router from express var router = express.Router(); ... Read More

To apply the aggregation list, use the agg() method. At first, import the required library −import pandas as pdCreate a DataFrame with two columns −dataFrame = pd.DataFrame(    {       "Car": ['BMW', 'Lexus', 'Lexus', 'Mustang', 'Bentley', 'Mustang'], "Units": [100, 150, 110, 80, 110, 90] } )Specifying list as argument using agg() −dataFrame = dataFrame.groupby('Car').agg(list) ExampleFollowing is the complete code −import pandas as pd # Create DataFrame dataFrame = pd.DataFrame(    {       "Car": ['BMW', 'Lexus', 'Lexus', 'Mustang', 'Bentley', 'Mustang'], "Units": [100, 150, 110, 80, 110, 90] } ) ... Read More