{"id":19298403,"url":"https://github.com/mayankbohra/data-science-project","last_synced_at":"2025-07-19T05:09:06.479Z","repository":{"id":167205897,"uuid":"642697003","full_name":"mayankbohra/data-science-project","owner":"mayankbohra","description":"The objective of this report is to examine and analyze the recent growth of industries by considering various factors","archived":false,"fork":false,"pushed_at":"2023-05-20T13:05:11.000Z","size":3288,"stargazers_count":3,"open_issues_count":0,"forks_count":2,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-12T06:08:11.697Z","etag":null,"topics":["data-science","data-visualization","matplotlib","numpy","pandas","python"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/mayankbohra.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2023-05-19T06:36:16.000Z","updated_at":"2024-10-31T00:17:35.000Z","dependencies_parsed_at":"2023-05-23T11:00:12.110Z","dependency_job_id":null,"html_url":"https://github.com/mayankbohra/data-science-project","commit_stats":null,"previous_names":["mayankbohra/data-science-project"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/mayankbohra/data-science-project","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mayankbohra%2Fdata-science-project","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mayankbohra%2Fdata-science-project/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mayankbohra%2Fdata-science-project/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mayankbohra%2Fdata-science-project/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mayankbohra","download_url":"https://codeload.github.com/mayankbohra/data-science-project/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mayankbohra%2Fdata-science-project/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":265892345,"owners_count":23845014,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["data-science","data-visualization","matplotlib","numpy","pandas","python"],"created_at":"2024-11-09T23:07:55.469Z","updated_at":"2025-07-19T05:09:06.460Z","avatar_url":"https://github.com/mayankbohra.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003c!-- PROJECT TITLE --\u003e\n\u003cdiv align=\"center\"\u003e\n  \u003ch1 align=\"center\"\u003eData-Driven Analysis of SDG 9: Industry, Infrastructure \u0026 Innovation\u003c/h1\u003e\n  \n  \u003cp align=\"center\"\u003e\n    \u003ch3\u003eData Science Project\u003c/h3\u003e\n    \u003ca href=\"https://drive.google.com/file/d/1ENnvFl97JzeIMH4dSDsQIRPTuZvE-bk9/view?usp=sharing\"\u003e\u003cstrong\u003eProject Report\u003c/strong\u003e\u003c/a\u003e\n  \u003c/p\u003e  \n  \n\u003c/div\u003e\n\n\u003c!-- TABLE OF CONTENTS --\u003e\n\u003cdetails\u003e\n  \u003csummary\u003eTable of Contents\u003c/summary\u003e\n  \u003col\u003e\n    \u003cli\u003e\u003ca href=\"#introduction\"\u003eIntroduction\u003c/a\u003e\u003c/li\u003e\n    \u003cli\u003e\u003ca href=\"#objective\"\u003eObjective\u003c/a\u003e\u003c/li\u003e\n    \u003cli\u003e\u003ca href=\"#data-collection\"\u003eData Collection\u003c/a\u003e\u003c/li\u003e\n    \u003cli\u003e\u003ca href=\"#methodology\"\u003eMethodology\u003c/a\u003e\u003c/li\u003e\n    \u003cli\u003e\u003ca href=\"#analysis-and-result\"\u003eAnalysis and Result\u003c/a\u003e\u003c/li\u003e\n  \u003c/ol\u003e\n\u003c/details\u003e\n\n\u003c!-- INTRODUCTION --\u003e\n## Introduction\n\nThe Sustainable Development Goals (SDGs), established in 2015, provide a comprehensive framework for achieving a more sustainable and inclusive future globally. These 17 interlinked goals aim to address various challenges and promote long-term growth and development in all countries, including India.\n\nOur project focuses on SDG Goal 9, which centers around industry, infrastructure, and innovation. By conducting a thorough survey and analysis, we explore the current industrial landscape of India, considering factors that contribute to its growth, manufacturing, and financial status.\n\nThrough a deep statistical analysis, we evaluate India's investments in research and development, the progress made in different industries, and the financial standing of both large enterprises and small businesses (MSMEs). We also assess the overall power generation situation in India, which fuels these industries, and also identifying areas where improvements can be made.\n\nThis project aims to shed light on India's industrial development within the context of the SDGs, emphasizing the need for sustainable practices and suggesting areas for further enhancement.\n\n\n\u003c!-- OBJECTIVE --\u003e\n## Objective\n\nThe objective of this report is to examine and analyze the recent growth of industries by considering factors such as capital investment, the influence of MSMEs on the industrial sector, allocation of research and development funding across different industries, and the power generation attributed to these industries.\n\n\n\u003c!-- DATA COLLECTION --\u003e\n## Data Collection\n\nTo gather the necessary data for this study, we have utilized the Reserve Bank of India's (RBI) annual report, specifically the Handbook of Statistics on Indian States. This comprehensive resource provides valuable information and statistics on various states in India, enabling us to conduct a thorough analysis of industry growth. By leveraging this authoritative publication, we ensure the reliability and accuracy of our findings.\n\n\n\u003c!-- METHODOLOGY --\u003e\n## Methodology\n\nNow, let's delve into the methodology employed in this study to analyze the growth of industries. We utilized a combination of descriptive and inferential statistics, along with the power method, to gain valuable insights into the data.\n\n\u003cb\u003eDescriptive statistics\u003c/b\u003e involves calculating measures such as \u003cb\u003emean\u003c/b\u003e, \u003cb\u003estandard deviation\u003c/b\u003e, and \u003cb\u003evariance\u003c/b\u003e to summarize and describe the characteristics of a dataset. It provides a quantitative summary of the data, enabling insights into central tendencies, dispersion, and variability. This methodology helps in understanding the distribution and patterns within the dataset.\n\n\u003cb\u003eInferential statistics\u003c/b\u003e encompass a range of techniques used to draw conclusions or make inferences about a population based on sample data. \u003cb\u003eHypothesis testing\u003c/b\u003e allows researchers to assess the significance of observed differences or relationships, making informed decisions about the underlying population. \u003cb\u003eZ-test and T-test\u003c/b\u003e for two means are specifically employed to compare means between two groups or samples. \u003cb\u003eCorrelation\u003c/b\u003e measures the strength and direction of the linear relationship between two variables, while \u003cb\u003eregression\u003c/b\u003e helps model the relationship between a dependent variable and one or more independent variables.\n\nThese statistical approaches allowed us to summarize the characteristics of the dataset, make inferences about the population, and determine the appropriate sample size for our analyses.\n\n\n\u003c!-- ANALYSIS AND RESULT --\u003e\n## Analysis and Result\n\nThe comprehensive analysis of the data can be found in the detailed report of this project. In the report, we provide an in-depth examination of the findings obtained through the application of various statistical techniques, including descriptive statistics, inferential statistics, and the power method. The report offers a thorough exploration of the trends, correlations, and insights derived from the data, enabling a comprehensive understanding of the growth of industries based on parameters such as capital, the impact of MSMEs, distribution of R\u0026D finances, and power generation.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmayankbohra%2Fdata-science-project","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmayankbohra%2Fdata-science-project","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmayankbohra%2Fdata-science-project/lists"}