nalyst 1.0.0

Packages for quantative analyst

1. INTRODUCTION

Nalyst is a powerful and user-friendly library designed for data analysts, professionals, and researchers in the field of Machine Learning and Data Science. It provides a comprehensive suite of tools for various tasks, such as Linear Regression, Logistic Regression, K-means Clustering, Principal Component Analysis (PCA), Decision Trees, Train Test Split, Min Max Scaling, MaxAbs Scaling, and Standard Scaling. With Nalyst, users can quickly and efficiently train, analyze, and evaluate their models, streamlining the entire data analysis process.

2. FEATURES

Linear Regression: a comprehensive set of tools for building and analyzing linear regression models.

Logistic Regression: a range of tools for building and analyzing logistic regression models.

K-means: a tool for clustering data into k clusters.

PCA: a tool for reducing the dimensionality of data while preserving its most important features.

Decision Tree: a tool for building and analyzing decision trees.

Train Test Split: a flexible and easy-to-use tool for splitting data into training and testing sets.

Min Max Scale: a tool for scaling data to a range of values between 0 and 1.

MaxAbs Scale: a tool for scaling data to the absolute maximum value of each feature.

Standard Scale: a tool for standardizing data to have a mean of 0 and a standard deviation of 1.

Quick model training: with this library, users can quickly and easily train machine learning models, saving time and effort.

3. INSTALLATION PACKAGE

To install the library, simply run the following command in your terminal:

pip install nalyst

pip install --upgrade nalyst

pip show nalyst

4. IMPORT DEPENDENCY

import numpy as np
import matplotlib.pyplot as plt
import yfinance as yf
import pyttsx3
import seaborn as sns
import yfinance as yf
import datetime

5. IMPORTING PACKAGES

from nalyst.LinearRegression import LinearRegression
from nalyst.DecisionTree import DecisionTree, Node
from nalyst.KMeans import KMeans
from nalyst.PCA import PCA
from nalyst.LogisticRegression import LogisticRegression, accuracy
from nalyst.MaxAbsScaler import MaxAbsScaler
from nalyst.MinMaxScaler import MinMaxScaler
from nalyst.StandardScaler import StandardScaler
from nalyst.TestTrainSplit import TrainTestSplit
from nalyst.MonteCarloSimulator import MonteCarloSimulator
from nalyst.BetaFive import calculate_beta_five
from nalyst.BetaMax import calculate_beta_max
from nalyst.ThresholdClassifier import ThresholdClassifier, ThresholdPlot
from nalyst.RegressionPlot import RegressionPlot
from nalyst.CorrelationAnalysis import LinearCorrelationVisualizer
from nalyst.TrendAnalyst import LinearRegressionVisualizer
from nalyst.StockVolatility import stock_volatility
from nalyst.StockAnalyzer import StockAnalyzer

6. SUPPORT

If you need help or have any questions, please feel free to reach out and text to Integrated audio architecture dosen't support google collab or cloud system.

7. COMMUNICATION

Github: https://github.com/harryworlds/nalyst