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Python Articles
Page 787 of 855
How can decision tree be used to construct a classifier in Python?
Decision tree is the basic building block of the random forest algorithm. It is considered as one of the most popular algorithms in machine learning and is used for classification purposes. They are extremely popular because they are easy to understand.The decision given out by a decision tree can be used to explain why a certain prediction was made. This means the in and out of the process would be clear to the user.They are also a foundation for ensemble methods such as bagging, random forests, and gradient boosting. They are also known as CART, i.e. Classification And Regression Trees. ...
Read MoreHow to view the pixel values of an image using scikit-learn in Python?
Data pre-processing basically refers to the task of gathering all the data (which is collected from various resources or a single resource) into a common format or into uniform datasets (depending on the type of data).Since real-world data is never ideal, there is a possibility that the data would have missing cells, errors, outliers, discrepancies in columns, and much more.Sometimes, images may not be correctly aligned, or may not be clear or may have a very large size. The goal of pre-processing is to remove these discrepancies and errors.To get the pixels of an image, a built-in function named ‘flatten’ ...
Read MoreHow can scikit-learn library be used to get the resolution of an image in Python?
Data pre-processing basically refers to the task of gathering all the data (which is collected from various resources or a single resource) into a common format or into uniform datasets (depending on the type of data). Since real-world data is never ideal, there is a possibility that the data would have missing cells, errors, outliers, discrepancies in columns, and much more. Sometimes, images may not be correctly aligned, or may not be clear or may have a very large size. The goal of pre-processing is to remove these discrepancies and errors.To get the resolution of an image, a built-in function ...
Read MorePython - Join tuple elements in a list
In this article, we are going to learn how to join tuple elements in a list. It's a straightforward thing using join and map methods. Follow the below steps to complete the task.Initialize list with tuples that contain strings.Write a function called join_tuple_string that takes a tuple as arguments and return a string.Join the tuples in the list using map(join_tuple_string, list) method.Convert the result to list.Print the result.Example# initializing the list with tuples string_tuples = [('A', 'B', 'C'), ('Tutorialspoint', 'is a', 'popular', 'site', 'for tech learnings')] # function that converts tuple to string def join_tuple_string(strings_tuple) -> str: return ...
Read MoreLinear search on list or tuples in Python
In this article, we are going to learn how to apply a linear search on lists and tuples.A linear search starts searching from the first element and goes till the end of the list or tuple. It stops checking whenever it finds the required element.Linear Search - Lists & TuplesFollow the below steps to implement linear search on lists and tuples.Initialize the list or tuple and an element.Iterate over the list or tuple and check for the element.Break the loop whenever you find the element and mark a flag.Print element not found message based on the flag.ExampleLet's see the code.# ...
Read MorePython - Make pair from two list such that elements are not same in pairs
In this article, we are going to learn how to make pairs from two lists such that no similar elements make a pair. Follow the below steps to solve the problem.Initialize the lists with elements.Iterate over the lists and append the pair into a list if the corresponding elements from the lists are not same.Print the result.ExampleLet's see the code.# initializing the lists list_1 = [1, 2, 3, 4, 5] list_2 = [5, 8, 7, 1, 3, 6] # making pairs result = [(i, j) for i in list_1 for j in list_2 if i != j] # ...
Read MorePrefix matching in Python using pytrie module
In this article, we are going to learn about the pytrie module to prefix matching strings from a list of strings. Let's see an example to understand it clearly.Input: List: ['tutorialspoint', 'tutorials', 'tutorialspython', 'python'] Prefix: 'tutorials' Output: ['tutorialspoint', 'tutorials', 'tutorialspython']We can achieve it in different ways. In this tutorial, we are going to achieve it using the pytrie module.From pytrie module, we will use the pytrie.StringTrie data structure. We can perform create, insert, search, and delete operations.First, install the pytrie module with the following command.pip install pytrieLet's see steps to achieve the desired output.Import the pytrie module.Initialize the list, ...
Read MoreFetching text from Wikipedia's Infobox in Python
In this article, we are going to scrape the text from Wikipedia's Infobox using BeatifulSoup and requests in Python. We can do it in 10 mins. It's straightforward.We need to install bs4 and requests. Execute the below commands to install.pip install bs4 pip install requestsFollow the below steps to write the code to fetch the text that we want from the infobox.Import the bs4 and requests modules.Send an HTTP request to the page that you want to fetch data from using the requests.get() method.Parse the response text using bs4.BeautifulSoup class and store it in a variable.Go to the Wikipedia page ...
Read MoreHow to select multiple DataFrame columns using regexp and datatypes
DataFrame maybe compared to a data set held in a spreadsheet or a database with rows and columns. DataFrame is a 2D Object.Ok, confused with 1D and 2D terminology ?The major difference between 1D (Series) and 2D (DataFrame) is the number of points of information you need to inorer to arrive at any single data point. If you take an example of a Series, and wanted to extract a value, you only need one point of reference i.e. row index.In comparsion to a table (DataFrame), one point of reference is not sufficient to get to a data point, you need ...
Read MoreHow to find and filter Duplicate rows in Pandas ?
Sometimes during our data analysis, we need to look at the duplicate rows to understand more about our data rather than dropping them straight away.Luckily, in pandas we have few methods to play with the duplicates..duplciated()This method allows us to extract duplicate rows in a DataFrame. We will use a new dataset with duplicates. I have downloaded the Hr Dataset from link.import pandas as pd import numpy as np # Import HR Dataset with certain columns df = pd.read_csv("https://raw.githubusercontent.com/sasankac/TestDataSet/master/HRDataset.csv", usecols = ("Employee_Name""PerformanceScore", "Position", "CitizenDesc")) #Sort the values on employee name and make it permanent df.sort_values("Employee_Name"inplace = True) df.head(3)Employee_NamePositionCitizenDescPerformanceScore0AdinolfiProduction ...
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