{"id":26902898,"url":"https://github.com/pedramjlo/car_sales_analysis","last_synced_at":"2025-04-01T09:54:04.695Z","repository":{"id":282320939,"uuid":"938392607","full_name":"pedramjlo/car_sales_analysis","owner":"pedramjlo","description":"Car sales analysis ","archived":false,"fork":false,"pushed_at":"2025-03-14T00:24:14.000Z","size":50517,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-14T00:26:45.106Z","etag":null,"topics":["data-analysis","jupyter-notebook","pandas","python"],"latest_commit_sha":null,"homepage":"https://www.kaggle.com/datasets/alikalwar/uae-used-car-prices-and-features-10k-listings","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/pedramjlo.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":"2025-02-24T22:09:33.000Z","updated_at":"2025-03-14T00:24:18.000Z","dependencies_parsed_at":"2025-03-14T00:36:51.732Z","dependency_job_id":null,"html_url":"https://github.com/pedramjlo/car_sales_analysis","commit_stats":null,"previous_names":["pedramjlo/car_sales_analysis"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pedramjlo%2Fcar_sales_analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pedramjlo%2Fcar_sales_analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pedramjlo%2Fcar_sales_analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pedramjlo%2Fcar_sales_analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/pedramjlo","download_url":"https://codeload.github.com/pedramjlo/car_sales_analysis/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246620271,"owners_count":20806722,"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-analysis","jupyter-notebook","pandas","python"],"created_at":"2025-04-01T09:54:04.103Z","updated_at":"2025-04-01T09:54:04.683Z","avatar_url":"https://github.com/pedramjlo.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Introduction\nThis is my personal data analysis project. I downloaded the dataset from \u003ca href='' \u003eKaggle\u003c/a\u003e. \nthis is not an offical real-world project, but solely for the purpose of self-teaching data analysis and practicing my Python skills.\n\n\n# Techonologies\n- Interactive Python Notebook (Jupyter Notebook)\n- Pandas\n- Plotly \n\n\n# The Pipeline\n\n## Data Cleaning (Pandas)\n- Imputed values of string (object in Pandas) type containing null values with the mode of the column\n- Imputed values of integer/float type containing null values with the mean of the column\n- Removed all duplicate rows\n- Applied camle-casing on some column header titles\n- Capitalised column header titles\n- Validated the data type of values column by column\n- Normalised Make titles, merged TK with the brands, also abbreviations to full brand names\n- Normalised state names and converted them from 2 lower case letter abbreviations to full state names\n- Ensured that the Transmission values are either 'Automatic', 'Manual', or 'unknown' (imputed for Nulls)\n- Similarly, Ensured that the Color values are either from a list of normal colors or 'unknown' (imputed for Nulls)\n- DataCleaner.save_changes() saves all the changes and created a new csv file in './dataset/cleaned/'\n\n\n## key Analysis Points\n- German brands have been doing tremendously. 5/10 selling cars are German:\n    1- BMW \n    2- Mercedes-Benz\n    3- Audi\n    4- Volkswagen\n    5- Porsche\n- 1990's were bad time in terms of sales, and majority of least profitable cars range from 1991-2004.\n- California account for an overwhelming amount of the revenue, $28.81M, followed by Florida, $4.88M, Pennsylvania, $4.81M, and Texas, $2.99M.\n- 18 out of 20 dealerships with highest generated are based in California as well as 6 of the least profitable ones.\n-  R Hollenshead Auto Sales Inc from Pennsylvania and TDAF Remarketing from FLorida are the only non-Californian sellers in the top-20 most profitable sellers.\n- A strong positive correlation between number of vehicles and the revenue of a brand. Quantity and consequently more options is a deciding factor.\n- Condition of the cars could quite effectively be a strong reason for customers to buy a car.\n- The number on odometer is often overlooked by customer and it doesn't influence the sales tremendously.\n- US. overseas terittories are amongst least profitable state, including Hawaii, Puerto Rico, and Alaska\n- Only 10 states have generated over $1M\n- Selling price plays a moderately weak role in the generation of revenue (0.3 coefficiency).\n- The Great Depression did not affect our sales significantly. Experiencing a 19.17% incraese in 2007-2008, and only 16.8% decrease in 2008-2009.\n- 2010-2011 witnessed a massive spike in revenue increase. Going from $3.06M to $6.6M (53.6%) followed by 26.6% in 2011-2012 ($6.6M to $9M).\n- Between 2012 and 2013, sales stalled, but a sharp increase in 2013-14.\n- in 2014, a rapid decrease resulted in sales dropping from $12.01M to $3.31M (72.43% decrease).\n  \n    \n## Visualisations (Plotly)\n\u003cimg src='./data-visuals/revenue_over_time.png' style='width: auto; height: 500px' /\u003e\n\n\u003cimg src='./data-visuals/top_20_selling_brands.png' style='width: auto; height: 500px' /\u003e\n\n\n\u003cimg src='./data-visuals/most_expensive_ccars.png' style='width: auto; height: 500px' /\u003e\n\n\u003cimg src='./data-visuals/least_profitable_cars.png' style='width: auto; height: 500px' /\u003e\n\n\u003cimg src='./data-visuals/transmission_sales.png' style='width: auto; height: 500px' /\u003e\n\n\u003cimg src='./data-visuals/top_20_sellers.png' style='width: auto; height: 500px' /\u003e\n\n\u003cimg src='./data-visuals/top_20_worst_sellers.png' style='width: auto; height: 500px' /\u003e\n\n\n\u003cimg src='./data-visuals/revenue_by_state.png' style='width: auto; height: 500px' /\u003e\n\n\u003cimg src='./data-visuals/least_revenue_by_state.png' style='width: auto; height: 500px' /\u003e\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpedramjlo%2Fcar_sales_analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpedramjlo%2Fcar_sales_analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpedramjlo%2Fcar_sales_analysis/lists"}