HintlyDataAnalisys 0.2.1

Library for mathematical, financial and textual analysis

HintlyDataAnalysis – Mathematical, Financial, and Textual Analysis Library

Table of Contents

• Description
• Installation
• Usage
  • Math
  • Finance
  • Text
• API
  • Math
  • Finance
  • Text
• Authors
• License

Description

HintlyDataAnalysis is a Python library designed for performing a variety of mathematical, financial, and textual analyses. The library offers functions to calculate means, percentage differences, data normalization, number repetition, financial angles, word counting, and text normalization.

Installation

You can install the library using pip:

pip install HintlyDataAnalysis

Usage

After installation, import the library to access the functionalities.

Example Usage:

from HintlyDataAnalysis import Math, Finance, Text, FilterType, NormalizeType

Calculate mean

mean_value = Math.Mean([1, 2, 3, 4])

Calculate percentage difference

percent_diff = Math.Difference(100, 120)

Normalize data

normalized_data = Math.Normalize([10, 15, 20], 100)

Weighted average

weighted_avg = Math.WeightedAverage([10, 20, 30], [1, 2, 3])

Number repetition

num_repeats = Math.NumberRepeat([1, 2, 2, 3, 3, 3])

Financial angles

angles = Finance.FinancialAngle([100, 120, 80], 50)

Financial chance

chance = Finance.FinanceChance([1, 2, 2, 3, 3, 3])

Count interpunctions

interpunctions = Text.CountInterpunctions("This is a test, with punctuation!")

Count signs

signs = Text.CountSigns("This is a test", lowerSigns=True)

Count specific word

word_count = Text.CountWord("This is a test", "test")

Normalize text

normalized_text = Text.NormalizeText("This is a TEST!", NormalizeType.LowText)

print(mean_value, percent_diff, normalized_data, weighted_avg, num_repeats, angles, chance)

API

Math

Math.Mean(analisysData: list)

Calculates the arithmetic mean of a list of numbers.

• Parameters:
  analisysData (list): List of numbers to calculate the mean from.
• Returns:
  The mean value of the data.

Math.Difference(a: float, b: float)

Calculates the percentage difference between two numbers.

• Parameters:
  a (float): The base number.
  b (float): The second number.
• Returns:
  Percentage difference between a and b.

Math.Normalize(analisysData: list, normalizeNumber: int)

Normalizes a list of numbers relative to the largest value, scaling them to normalizeNumber.

• Parameters:
  analisysData (list): List of numbers to normalize.
  normalizeNumber (int): Value to normalize the data against.
• Returns:
  A list of normalized data.

Math.WeightedAverage(analisysData: list, weights: list)

Calculates the weighted average of the data using the given weights.

• Parameters:
  analisysData (list): List of numbers.
  weights (list): List of weights corresponding to each number.
• Returns:
  The weighted average of the data.

Math.NumberRepeat(numbers: list)

Counts the occurrences of each number in a list.

• Parameters:
  numbers (list): List of numbers to analyze.
• Returns:
  A dictionary where keys are numbers and values are the counts of their occurrences.

Finance

Finance.FinancialAngle(amounts: list, max_change: int)

Calculates the "financial angle" based on changes in the amounts over time.

• Parameters:
  amounts (list): List of financial amounts.
  max_change (int): The maximum possible change in value.
• Returns:
  A list of angles in degrees (0–180) representing changes between amounts.

Finance.FinanceChance(numbers: list)

Calculates the probability of each number occurring in the list.

• Parameters:
  numbers (list): List of numbers to analyze.
• Returns:
  A dictionary with each number's chance of occurring, expressed as a percentage.

Text

Text.CountInterpunctions(text: str)

Counts the occurrences of specific punctuation marks in the provided text.

• Parameters:
  text (str): The text to analyze.
• Returns:
  A dictionary where the keys are punctuation marks and the values are their occurrences in the text.

Text.CountSigns(text: str, lowerSigns: bool)

Counts each unique character (case-sensitive or insensitive) in the text.

• Parameters:
  text (str): The text to analyze.
  lowerSigns (bool): If True, characters will be counted case-insensitively.
• Returns:
  A dictionary of characters and their counts.

Text.CountWord(text: str, word: str)

Counts how many times a word appears in the text.

• Parameters:
  text (str): The text to search within.
  word (str): The word to count.
• Returns:
  The number of occurrences of the word.

Text.NormalizeText(text: str, normalizeType: NormalizeType)

Normalizes text based on the chosen normalization type (e.g., delete punctuation, convert to lowercase).

• Parameters:
  text (str): The text to normalize.
  normalizeType (NormalizeType): The type of normalization to apply.
• Returns:
  The normalized text.

Authors

Franciszek Chmielewski ([e-mail])

License

This project is licensed under the MIT License. More details can be found in the LICENSE file.

Version History

• 0.1 – Initial release.
• 0.2 – Added Text class with normalization functions.

Future Plans

• Add more advanced financial and mathematical analysis tools.
• Expand text analysis capabilities.