# Data Science Helper Library
## This library is designed to assist students in understanding key Data Science and Statistics concepts. It provides tools to analyze and validate statistical principles, including:
- Univariate & Bivariate Analysis
- Correlations
- Linear & Logistic Regression
- Predictive Modeling & Evaluation
## Additionally, it offers utility functions to simplify data analysis and explanations of popular Python libraries such as:
- pandas
- scikit-learn
- seaborn
### Whether you're exploring statistical relationships, building predictive models, or learning how different libraries work, this package will help make your Data Science journey smoother!
Raw data
{
"_id": null,
"home_page": null,
"name": "statshelp",
"maintainer": null,
"docs_url": null,
"requires_python": null,
"maintainer_email": null,
"keywords": "[stats, student, data science, analysis]",
"author": "Data Scientist",
"author_email": "datascientist@mateusalifontes.com",
"download_url": "https://files.pythonhosted.org/packages/2c/c7/f0d347bd2a67788f05f954c3cb11d03acceda57bf0fd0e6059d52d09d9dd/statshelp-0.0.2.tar.gz",
"platform": null,
"description": "# Data Science Helper Library\r\n## This library is designed to assist students in understanding key Data Science and Statistics concepts. It provides tools to analyze and validate statistical principles, including:\r\n\r\n - Univariate & Bivariate Analysis\r\n - Correlations\r\n - Linear & Logistic Regression\r\n - Predictive Modeling & Evaluation\r\n\r\n## Additionally, it offers utility functions to simplify data analysis and explanations of popular Python libraries such as:\r\n\r\n - pandas\r\n - scikit-learn\r\n - seaborn\r\n\r\n### Whether you're exploring statistical relationships, building predictive models, or learning how different libraries work, this package will help make your Data Science journey smoother! \r\n",
"bugtrack_url": null,
"license": "MIT License",
"summary": "Library to help Data Science students",
"version": "0.0.2",
"project_urls": null,
"split_keywords": [
"[stats",
" student",
" data science",
" analysis]"
],
"urls": [
{
"comment_text": null,
"digests": {
"blake2b_256": "2cc7f0d347bd2a67788f05f954c3cb11d03acceda57bf0fd0e6059d52d09d9dd",
"md5": "e72518f397e876b06c1c06195d5a0daf",
"sha256": "a95f073c3071152c5749c7268084259e84a927723ebb76ec040fe167d02fdaaf"
},
"downloads": -1,
"filename": "statshelp-0.0.2.tar.gz",
"has_sig": false,
"md5_digest": "e72518f397e876b06c1c06195d5a0daf",
"packagetype": "sdist",
"python_version": "source",
"requires_python": null,
"size": 5049,
"upload_time": "2025-02-21T07:56:08",
"upload_time_iso_8601": "2025-02-21T07:56:08.952535Z",
"url": "https://files.pythonhosted.org/packages/2c/c7/f0d347bd2a67788f05f954c3cb11d03acceda57bf0fd0e6059d52d09d9dd/statshelp-0.0.2.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2025-02-21 07:56:08",
"github": false,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"lcname": "statshelp"
}