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Articles on Trending Technologies
Technical articles with clear explanations and examples
Python Program to return the Length of the Longest Word from the List of Words
When it is required to return the length of the longest word from a list of words, a method is defined that takes a list as parameter. It iterates through each word to find the maximum length and returns it. Example Below is a demonstration of the same ? def find_longest_length(word_list): max_length = len(word_list[0]) temp = word_list[0] for element in word_list: if len(element) > max_length: ...
Read MorePython Program to Sort Matrix Rows by summation of consecutive difference of elements
This article demonstrates how to sort matrix rows by the summation of consecutive differences between adjacent elements. We calculate the absolute difference between consecutive elements in each row, sum them up, and use this sum as the sorting key. Understanding Consecutive Differences For a row like [97, 6, 47, 3], the consecutive differences are − |6 - 97| = 91 |47 - 6| = 41 |3 - 47| = 44 Sum = 91 + 41 + 44 = 176 Example Here's a complete program that sorts matrix rows by their consecutive difference summation ...
Read MorePython – Append given number with every element of the list
When you need to add a specific number to every element in a list, Python offers several approaches. The most common method uses list comprehension, which provides a concise and readable solution. Using List Comprehension List comprehension allows you to create a new list by applying an operation to each element ? numbers = [25, 36, 75, 36, 17, 7, 8, 0] print("Original list:") print(numbers) append_value = 6 result = [x + append_value for x in numbers] print("List after appending", append_value, "to each element:") print(result) Original list: [25, 36, 75, ...
Read MorePython – Cumulative Row Frequencies in a List
When you need to count how many times specific elements appear in each row of a nested list, you can use Python's Counter class from the collections module combined with list comprehension to calculate cumulative row frequencies. What are Cumulative Row Frequencies? Cumulative row frequencies refer to counting the total occurrences of specified elements within each row of a nested list. For example, if you want to find how many times elements [19, 2, 71] appear in each row, you sum their individual frequencies per row. Example Here's how to calculate cumulative row frequencies using Counter ...
Read MorePython Program To Get Minimum Element For String Construction
When you need to find the minimum number of strings required to construct a target string, you can use Python's combinations from itertools along with set operations. This approach finds the smallest subset of strings that contains all characters needed for the target string. Example Below is a demonstration of finding the minimum elements needed ? from itertools import combinations my_list = ["python", "is", "fun", "to", "learn"] print("The list is :") print(my_list) my_target_str = "onis" my_result = -1 my_set_string = set(my_target_str) complete_val = False for value in range(0, len(my_list) + 1): ...
Read MorePython - Filter Pandas DataFrame with numpy
The numpy.where() method can be used to filter Pandas DataFrame by returning indices that meet specified conditions. This approach is particularly useful when you need to apply multiple filtering conditions simultaneously. Setup First, let's import the required libraries and create a sample DataFrame ? import pandas as pd import numpy as np # Create a DataFrame with product records dataFrame = pd.DataFrame({ "Product": ["SmartTV", "ChromeCast", "Speaker", "Earphone"], "Opening_Stock": [300, 700, 1200, 1500], "Closing_Stock": [200, 500, 1000, 900] }) print("Original DataFrame:") print(dataFrame) ...
Read MorePython - Summing all the rows of a Pandas Dataframe
To sum all the rows of a DataFrame, use the sum() function with axis=1. Setting the axis parameter to 1 adds values across columns for each row, while axis=0 (default) would sum down columns. Creating a Sample DataFrame Let's start by creating a DataFrame with stock data ? import pandas as pd dataFrame = pd.DataFrame({ "Opening_Stock": [300, 700, 1200, 1500], "Closing_Stock": [200, 500, 1000, 900] }) print("DataFrame...") print(dataFrame) DataFrame... Opening_Stock Closing_Stock 0 ...
Read MorePython Pandas - How to append rows to a DataFrame
To append rows to a DataFrame, use the concat() method (recommended) or the deprecated append() method. Here, we will create two DataFrames and append one after the other. Using concat() Method (Recommended) The concat() method is the modern approach for appending DataFrames ? import pandas as pd # Create DataFrame1 dataFrame1 = pd.DataFrame({ "Car": ['BMW', 'Lexus', 'Audi', 'Jaguar'] }) print("DataFrame1 ...", dataFrame1) print("DataFrame1 length =", len(dataFrame1)) # Create DataFrame2 dataFrame2 = pd.DataFrame({ "Car": ['Mercedes', 'Tesla', 'Bentley', 'Mustang'] }) print("DataFrame2 ...", dataFrame2) print("DataFrame2 length =", ...
Read MorePython Pandas - Create a subset by choosing specific values from columns based on indexes
To create a subset by choosing specific values from columns based on indexes, use the iloc() method. The iloc() method allows you to select data by integer position, making it perfect for choosing specific rows and columns from a DataFrame. Creating a DataFrame Let us first create a sample DataFrame with product records ? import pandas as pd dataFrame = pd.DataFrame({ "Product": ["SmartTV", "ChromeCast", "Speaker", "Earphone"], "Opening_Stock": [300, 700, 1200, 1500], "Closing_Stock": [200, 500, 1000, 900] }) print("DataFrame...", dataFrame) ...
Read MorePython Pandas - Subset DataFrame by Column Name
To create a subset of DataFrame by column name, use the square brackets. Use the DataFrame with square brackets (indexing operator) and the specific column name like this ? dataFrame['column_name'] Syntax # Single column - returns a Series dataFrame['column_name'] # Multiple columns - returns a DataFrame dataFrame[['col1', 'col2']] Example - Single Column Subset Let us create a DataFrame and extract a single column ? import pandas as pd # Create a Pandas DataFrame with Product records dataFrame = pd.DataFrame({ "Product": ["SmartTV", "ChromeCast", "Speaker", ...
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