Apple Iphones sold in India

Price, Rating, and Reviews

By Tony Paul [source]

About this dataset

This dataset contains detailed information about Apple iPhones that have been sold in India. Each entry includes the product name, brand, sale price, maximum retail price (MRP), universal product code (UPC), number of reviews and ratings obtained from customers, discount percentage offered on various products, as well as the random access memory (RAM) size associated with each product. Dive into this comprehensive collection of Apple products for a better understanding of selling iPhone models in India and accurately capture insights about customer preferences and market trends!

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How to use the dataset

Here is how to use this dataset effectively: - Start by exploring the headers of each column to understand the data features available in the dataset; you should be able to identify which columns contain what kind of data. - To get an overview of your data, calculate summary statistics such as means and standard deviations for numerical columns (e.g., Sale Price, Mrp etc.). - Visualize your data using a variety of techniques like histograms, scatter plots and correlation matrices - this will help you look for possible relationships between different variables. You may also consider creating pair plots that allow you to compare and visualize pairs of variables against each other at a glance. - Finally, start building models or perform exploratory analysis such as hypothesis testing with the help of various statistical methods or machine learning algorithms for further insights into the Apple iPhone sales in India!

Research Ideas

• Developing an AI-based Product Recommender System using the attributes of Apple Iphones (e.g. price, discount percentage, ratings, reviews & RAM) for customers who are looking to purchase new Apple phone in India
• Creating a brand intelligence system that analyses the popularity of different Apple product models and rank them according to their performance over time
• Using Machine Learning to build a predictive model for forecasting sales patterns and predicting demand for future sales of Apple Iphones in India

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

Unknown License - Please check the dataset description for more information.

Columns

File: apple_products.csv | Column name | Description | |:------------------------|:--------------------------------------------------------------------------| | Product Name | The name of the Apple iPhone product. (String) | | Product URL | The URL of the product page. (String) | | Brand | The brand of the Apple iPhone product. (String) | | Sale Price | The price of the Apple iPhone product at the time of sale. (Numeric) | | Mrp | The maximum retail price of the Apple iPhone product. (Numeric) | | Discount Percentage | The percentage of discount offered on the Apple iPhone product. (Numeric) | | Number Of Ratings | The number of ratings given to the Apple iPhone product. (Numeric) | | Number Of Reviews | The number of reviews given to the Apple iPhone product. (Numeric) | | Upc | The universal product code of the Apple iPhone product. (String) | | Star Rating | The star rating of the Apple iPhone product. (Numeric) | | Ram | The Random Access Memory size of the Apple iPhone product. (Numeric) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit Tony Paul.

Amazon Brands and Exclusives

Dataset from "Amazon Puts Its Own 'Brands' First Above Better-Rated Products"

About this dataset

This dataset contains information on the quality and sales of products on Amazon, as well as on the percentage of time that Amazon's own products are featured in the Buy Box. It also includes data on the top searches and generic searches on Amazon, as well as on the percentage of panelists who ranked each trait as very important or somewhat important when choosing a product on Amazon

Research Ideas

• Determine which features are most important to customers when they are shopping on Amazon.
• Understand how Amazon's own products compare to other products in terms of quality and sales.
• Study how Amazon's marketing and ranking algorithms work, in order to optimize product listings on the site

Acknowledgements

Acknowledgements The datasets used in this article were provided by The Markup

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: combined_queries_with_source.csv | Column name | Description | |:----------------|:-----------------------------------------| | search_term | The search term used on Amazon. (String) | | source | The source of the search term. (String) |

File: quality_and_sales_comparisons.csv | Column name | Description | |:-------------------------------------|:----------------------------------------------------------------------------------------------| | search_term | The search term used on Amazon. (String) | | position_first_amazon | The position of the first Amazon product in the search results. (Integer) | | position_first_non_amazon | The position of the first non-Amazon product in the search results. (Integer) | | position_first_wholly_non_amazon | The position of the first wholly non-Amazon product in the search results. (Integer) | | amazon_stars | The average star rating for Amazon products in the search results. (Float) | | amazon_reviews | The average number of reviews for Amazon products in the search results. (Integer) | | non_amazon_stars | The average star rating for non-Amazon products in the search results. (Float) | | non_amazon_reviews | The average number of reviews for non-Amazon products in the search results. (Integer) | | wnon_amazon_stars | The average star rating for wholly non-Amazon products in the search results. (Float) | | wnon_amazon_reviews | The average number of reviews for wholly non-Amazon products in the search results. (Integer) |

File: amazon_trademarked_brands.csv | Column name | Description | |:-----------------------|:-------------------------------------------------------------| | Word Mark | The word mark of the product. (String) | | Goods and Services | The goods and services associated with the product. (String) | | Filing Date | The date on which the product was filed. (Date) |

File: fig2-scatter.csv | Column name | Description | |:-------------------|:----------------------------------------------------------------------------------------------------| | **** | | | Category | The category of the product. (String) | | Perc Products | The percentage of products in the category that are sponsored. (Float) | | Perc #1 spot | The percentage of products in the category that are in the #1 spot in the search results. (Float) | | Perc first row | The percentage of products in the category that are in the first row of the search results. (Float) |

File: fig3a-heatmap_amzn.csv | Column name | Description | |:-----...

Using the company’s descriptive language, details include the tests offered, species the test is used for, and what the test was advertised to include.