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Technical articles with clear explanations and examples
Python Program – Convert String to matrix having K characters per row
When it is required to convert a string into a matrix that has K characters per row, we can use string slicing and list comprehension. This technique is useful for formatting text data into fixed-width rows for display or processing. Method 1: Using String Slicing and List Comprehension This approach creates a matrix by slicing the string into chunks of K characters ? def convert_string_to_matrix(text, k): matrix = [] for i in range(0, len(text), k): row = list(text[i:i+k]) ...
Read MorePython – To convert a list of strings with a delimiter to a list of tuple
Converting a list of strings with delimiters to a list of tuples is a common task in Python. This can be achieved using list comprehension combined with the split() method to break strings at delimiter positions. Basic Example Here's how to convert delimiter-separated strings into tuples of integers ? data_list = ["33-22", "13-44-81-39", "42-10-42", "36-56-90", "34-77-91"] print("Original list:") print(data_list) delimiter = "-" result = [tuple(int(element) for element in item.split(delimiter)) for item in data_list] print("Converted to tuples:") print(result) Original list: ['33-22', '13-44-81-39', '42-10-42', '36-56-90', '34-77-91'] Converted to tuples: [(33, 22), ...
Read MorePython – Descending Order Sort grouped Pandas dataframe by group size?
Sorting grouped Pandas DataFrame by group size in descending order is useful for analyzing data distribution. We use groupby() to group data, size() to count group members, and sort_values(ascending=False) to sort in descending order. Creating a Sample DataFrame Let's start by creating a DataFrame with car information ? import pandas as pd # Create dataframe with Car and Registration Price columns dataFrame = pd.DataFrame({ "Car": ['BMW', 'Lexus', 'Audi', 'Mercedes', 'Jaguar', 'Bentley'], "Reg_Price": [1000, 1400, 1000, 900, 1700, 900] }) print("DataFrame:") print(dataFrame) DataFrame: ...
Read MorePython – Sort given list of strings by part the numeric part of string
When it is required to sort a given list of strings based on the numeric part of the string, we can use regular expressions with the sort() method's key parameter to extract and compare the numeric values. Example Below is a demonstration of sorting strings by their numeric parts ? import re def extract_numeric_part(string): return list(map(int, re.findall(r'\d+', string)))[0] strings = ["pyt23hon", "fu30n", "lea14rn", 'co00l', 'ob8uje3345t'] print("Original list:") print(strings) strings.sort(key=extract_numeric_part) print("Sorted list by numeric part:") print(strings) Original list: ['pyt23hon', 'fu30n', 'lea14rn', 'co00l', 'ob8uje3345t'] Sorted ...
Read MorePython – Substitute prefix part of List
When working with lists, you may need to substitute the prefix (beginning) part of one list with another list. Python provides a simple approach using list slicing with the : operator and the len() function. What is Prefix Substitution? Prefix substitution means replacing the first N elements of a list with elements from another list, where N is the length of the replacement list. Example Here's how to substitute the prefix part of a list ? # Define two lists original_list = [29, 77, 19, 44, 26, 18] replacement_list = [15, 44, 82] ...
Read MorePython - Merge DataFrames of different length
To merge DataFrames of different lengths, we use the merge() method with different join types. The left join keeps all rows from the left DataFrame and matches rows from the right DataFrame where possible. Creating DataFrames of Different Lengths Let's create two DataFrames with different lengths to demonstrate merging ? import pandas as pd # Create DataFrame1 with length 4 dataFrame1 = pd.DataFrame({ "Car": ['BMW', 'Lexus', 'Audi', 'Jaguar'], "Price": [50000, 45000, 48000, 60000] }) print("DataFrame1 ...", dataFrame1) print("DataFrame1 length =", len(dataFrame1)) DataFrame1 ... ...
Read MorePython – Cross mapping of Two dictionary value lists
When it is required to cross-map two dictionary valued lists, the setdefault and extend methods are used. This technique allows you to map values from one dictionary to another based on matching keys and indices. Understanding Cross Mapping Cross mapping involves using values from the first dictionary as keys to lookup corresponding values in the second dictionary. The result combines these lookups into a new dictionary structure. Example Below is a demonstration of cross mapping two dictionaries − my_dict_1 = {"Python" : [4, 7], "Fun" : [8, 6]} my_dict_2 = {6 : [5, 7], ...
Read MorePython – Check if elements index are equal for list elements
When it is required to check if the index of elements matches their values or compare elements at the same positions across lists, we can use simple iteration with the enumerate() function. Basic Example: Check if Index Equals Value Here's how to check if any element's index equals its value ? data = [0, 2, 1, 3, 5] print("The list is:") print(data) # Check if any element equals its index index_equals_value = [] for index, element in enumerate(data): if index == element: ...
Read MorePython – Convert List to Index and Value dictionary
When you need to convert a list into a dictionary containing separate index and value arrays, Python's enumerate() function provides an elegant solution. This approach creates a structured dictionary with index and values keys. Basic Example Here's how to convert a list to an index-value dictionary ? my_list = [32, 0, 11, 99, 223, 51, 67, 28, 12, 94, 89] print("The list is:") print(my_list) my_list.sort(reverse=True) print("The sorted list is:") print(my_list) index, value = "index", "values" my_result = {index : [], value : []} for id, vl in enumerate(my_list): my_result[index].append(id) ...
Read MorePython – Extend consecutive tuples
When working with tuples in Python, you may need to extend consecutive tuples by combining each tuple with the next one in the sequence. This creates a new list where each element is the concatenation of two adjacent tuples. Example Below is a demonstration of extending consecutive tuples ? my_list = [(13, 526, 73), (23, 67, 0, 72, 24, 13), (94, 42), (11, 62, 23, 12), (93, ), (83, 61)] print("The list is :") print(my_list) my_list.sort(reverse=True) print("The list after sorting in reverse is :") print(my_list) my_result = [] for index in range(len(my_list) - ...
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