HintlyDataAnalisys 0.1

Biblioteka do analizy matematycznej i finansowej

HintlyDataAnalysis – Mathematical and Financial Library

Spis treści

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

Description

HintlyDataAnalysis is a Python library that provides tools for mathematical and financial analysis. It offers functions for calculating means, percentage differences, data normalization, weighted averages, number repetition, financial angles, and financial chances. Installation

You can install the library using pip:

pip install HintlyAnalisysData

Usage

After installation, you can import modules from the library and use the available functions. Example Usage

from HintlyAnalisysData.DataAnalisys import Math, Finance

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])

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 data.

Parameters: analisysData (list): List of numbers.

Returns:
    The mean value of the data.

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

Calculates the percentage difference between two numbers.

Parameters:
    a (float): Base number.
    b (float): Number to compare.
Returns:
    Percentage difference between a and b.

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

Normalizes the values in the list relative to the largest value, scaling them to normalizeNumber.

Parameters:
    analisysData (list): List of numbers to normalize.
    normalizeNumber (int): Target normalization value.
Returns:
    List of normalized data.

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

Calculates the weighted average of the data and corresponding weights.

Parameters:
    analisysData (list): List of numerical data.
    weights (list): List of weights assigned to the data.
Returns:
    The weighted average.

Math.NumberRepeat(numbers: list)

Returns a dictionary with the count of occurrences of each number in the list.

Parameters:
    numbers (list): List of numbers to analyze.
Returns:
    A dictionary with counts of occurrences for each number.

Finance

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

Calculates the financial angle (in degrees) based on changes in amounts.

Parameters:
    amounts (list): List of amounts.
    max_change (int): Maximum possible change in the data.
Returns:
    List of angles in degrees (0–180).

Finance.FinanceChance(numbers: list)

Calculates the chances (in percentage) of each number occurring in the list.

Parameters:
    numbers (list): List of numbers to analyze.
Returns:
    A dictionary with percentage chances for each number.

Authors

Franciszek Chmielewski ([e-mail])

License

The project is licensed under the MIT License. Details can be found in the LICENSE file.

Version History

0.1 – Initial release.

Future Plans

1. Add more advanced analytical tools.
2. Expand support for financial analysis.