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Technical articles with clear explanations and examples
Program to find number of ways we can arrange symbols to get target in Python?
Suppose we have a list of non-negative numbers called nums and also have an integer target. We have to find the number of ways to arrange + and - signs in front of nums such that the expression equals the target. So, if the input is like nums = [2, 3, 3, 3, 2] target = 9, then the output will be 2, as we can have −2 + 3 + 3 + 3 + 2 and 2 + 3 + 3 + 3 − 2. Algorithm Approach This problem can be transformed into a subset sum ...
Read MoreProgram to find number of arithmetic sequences from a list of numbers in Python?
Finding arithmetic sequences from a list of numbers is a common problem in programming. An arithmetic sequence is a sequence where the difference between consecutive numbers remains constant. We need to count all contiguous arithmetic subsequences of length ≥ 3. For example, in the list [6, 8, 10, 12, 13, 14], we have arithmetic sequences: [6, 8, 10], [8, 10, 12], [6, 8, 10, 12], and [12, 13, 14]. Algorithm Approach The key insight is to use a sliding window approach: Track consecutive elements that form arithmetic sequences When a sequence breaks, calculate how many ...
Read MoreHow to restrict argument values using choice options in Python?
When building command-line applications in Python, you often need to restrict user input to specific valid values. Python's argparse module provides the choices parameter to limit argument values to predefined options, preventing invalid input and improving data validation. Basic Argument Parser Without Restrictions Let's start with a simple tennis Grand Slam title tracker that accepts any integer value ? import argparse def get_args(): """Function to parse command line arguments""" parser = argparse.ArgumentParser( description='Tennis Grand Slam title tracker', ...
Read MoreHow to use one or more same positional arguments in Python?
Python's argparse module allows you to handle multiple positional arguments of the same type using the nargs parameter. This is particularly useful when you need exactly N arguments of the same data type, like performing arithmetic operations on numbers. Using nargs for Same Type Arguments The nargs parameter specifies how many command-line arguments should be consumed. When you set nargs=2, argparse expects exactly two values of the specified type. Example: Subtracting Two Numbers Let's create a program that subtracts two integers using positional arguments − import argparse def get_args(): ...
Read MoreHow to plot pie-chart with a single pie highlighted with Python Matplotlib?
Pie charts are one of the most popular visualization types for displaying percentages and proportions. In this tutorial, we'll learn how to create pie charts with highlighted segments using Python's Matplotlib library. Basic Pie Chart Setup First, let's install and import the required library − import matplotlib.pyplot as plt # Sample data: Tennis Grand Slam titles tennis_stats = (('Federer', 20), ('Nadal', 20), ('Djokovic', 17), ('Murray', 3)) # Extract titles and player names titles = [title for player, title in tennis_stats] players = [player for player, title in tennis_stats] print("Titles:", titles) print("Players:", players) ...
Read MoreHow to plot 4D scatter-plot with custom colours and cutom area size in Python Matplotlib?
A 4D scatter plot in Matplotlib allows you to visualize four dimensions of data simultaneously: X and Y coordinates, point size (area), and color. This is useful for analyzing relationships between multiple variables in a single visualization. Installing Matplotlib First, install matplotlib using pip ? pip install matplotlib Basic 2D Scatter Plot Let's start with a simple 2D scatter plot using tennis player statistics ? import matplotlib.pyplot as plt # Tennis player data (name, grand slam titles) tennis_stats = (('Federer', 20), ('Nadal', 20), ('Djokovic', 17), ('Sampras', 14), ...
Read MoreHow to extract required data from structured strings in Python?
When working with structured strings like log files or reports, you often need to extract specific data fields. Python provides several approaches to parse these strings efficiently when the format is known and consistent. Understanding Structured String Format Let's work with a structured report format: Report: - Time: - Player: - Titles: - Country: Here's our sample data: report = 'Report: Daily_Report - Time: 2020-10-10T12:30:59.000000 - Player: Federer - Titles: 20 - Country: Switzerland' print(report) Report: Daily_Report - Time: 2020-10-10T12:30:59.000000 - Player: Federer - ...
Read MoreHow to create Microsoft Word paragraphs and insert Images in Python?
Creating Microsoft Word documents programmatically in Python is essential for automating report generation. The python-docx library provides a simple interface to create paragraphs, add text formatting, and insert images into Word documents. Installing python-docx First, install the required library using pip ? pip install python-docx Creating Paragraphs and Adding Text Start by creating a new document and adding paragraphs with text ? import docx # Create a new document word_doc = docx.Document() # Add a paragraph paragraph = word_doc.add_paragraph('1. Hello World, Some Sample Text Here...') run = paragraph.add_run() ...
Read MoreHow to Add Legends to charts in Python?
Charts help visualize complex data effectively. When creating charts with multiple data series, legends are essential for identifying what each visual element represents. Python's matplotlib library provides flexible options for adding and customizing legends. Basic Legend Setup First, let's prepare sample data and create a basic bar chart with legends ? import matplotlib.pyplot as plt # Sample mobile sales data (in millions) mobile_brands = ['iPhone', 'Galaxy', 'Pixel'] units_sold = ( ('2016', 12, 8, 6), ('2017', 14, 10, 7), ('2018', 16, 12, 8), ...
Read MoreHow to Visualize API results with Python
One of the biggest advantages of writing an API is to extract current/live data. Even when data is rapidly changing, an API will always get up-to-date information. API programs use specific URLs to request certain data, like the top 100 most played songs of 2020 on Spotify or YouTube Music. The requested data is returned in easily processed formats like JSON or CSV. Python allows users to make API calls to almost any URL. In this tutorial, we'll extract API results from GitHub and visualize them using charts. Prerequisites First, install the required packages ? ...
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