The number of Apple iPhone unit sales dramatically increased between 2007 and 2024. Indeed, in 2007, when the iPhone was first introduced, Apple shipped around **** million smartphones. By 2024, this number reached over ***** million units. The newest models and iPhone’s lasting popularity Apple has ventured into its 17th smartphone generation with its Phone ** lineup, which, released in September 2025, includes the **, ** Plus, ** Pro and Pro Max. Powered by the A19 bionic chip and running on iOS **, these models present improved displays, cameras, and functionalities. On the one hand, such features come, however, with hefty price tags, namely, an average of ***** U.S. dollars. On the other hand, they contribute to making Apple among the leading smartphone vendors worldwide, along with Samsung and Xiaomi. In the first quarter of 2024, Samsung shipped over ** million smartphones, while Apple recorded shipments of roughly ** million units. Success of Apple’s other products Apart from the iPhone, which is Apple’s most profitable product, Apple is also the inventor of other heavy-weight players in the consumer electronics market. The Mac computer and the iPad, like the iPhone, are both pioneers in their respective markets and have helped popularize the use of PCs and tablets. The iPad is especially successful, having remained as the largest vendor in the tablet market ever since its debut. The hottest new Apple gadget is undoubtedly the Apple Watch, which is a line of smartwatches that has fitness tracking capabilities and can be integrated via iOS with other Apple products and services. The Apple Watch has also been staying ahead of other smart watch vendors since its initial release and secures around ** percent of the market share as of the latest quarter.

Apple is one of the most influential and recognisable brands in the world, responsible for the rise of the smartphone with the iPhone. Valued at over $2 trillion in 2021, it is also the most valuable...

iPhone 14 📱 🐦 Tweets [11 July - Sept 9 2022 - 144k English] 📱 🐦

Updated on Sept 9th Includes sent tweets after launch

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Trying to do something useful and add a dataset here in Kaggle, and while there are over 90+ datasets for Elon, there's none yet for tweets about the upcoming iPhone 14. I'm interested in seeing what apple is up to this year, so I thought it could be interesting to deep dive into what people have been saying this month before the release, which was announced today by Apple. It will happen on September 7th.

The dataset has 144k tweets created between July 11th and Sept 9th. Tweets are in English. As the new iPhone was just announced, I plan on updating the dataset to include newer examples and maybe a few older ones to increase the number of samples in the dataset, at least until the first week of launch.

Columns Description

• [x] date_time - Date and Time tweet was sent
• [x] username - Username that sent the tweet
• [x] user_location - Location entered in the account location info on Twitter
• [x] user_description - Text added to "about" in account
• [x] verified - If the user has the "verified by Twitter" blue tick
• [x] followers_count - Number of Followers
• [x] following_count - Number of accounts followed by the person who sent the tweet
• [x] tweet_like_count - How many people liked the tweet
• [x] tweet_retweet_count - How many people retweeted the tweet
• [x] tweet_reply_count - How many people replied to that tweet
• [x] source - Where was the tweet sent from. The link has info if using iPhone, Android and others
• [x] tweet_text - Text sent in the tweet

Data and Utilization

Data was scrapped from Twitter and uploaded as is, no further process to data cleaning was performed, but the data from the tweets are in very good shape. I'd maybe recommend separating data and time and finding a way to change the source from links to the device name or website, depending on what you are interested in using the data for.

Usage suggestions - Data can be used to perform sentiment analysis, look at the geographical distribution, trends, spam x ham identification, and others.

In the fourth quarter of its 2025 fiscal year, Apple generated around ***billion U.S. dollars in revenue from the sales of iPhones. Apple iPhone revenue The Apple iPhone is one of the biggest success stories in the smartphone industry. Since its introduction to the market in 2007, Apple has sold more than *** billion units worldwide. As of the third quarter of 2024, the Apple iPhone’s market share of new smartphone sales was over ** percent. Much of its accomplishments can be attributed to Apple’s ability to keep the product competitive throughout the years, with new releases and updates. Apple iPhone growth The iPhone has shown to be a crucial product for Apple, considering that the iPhone’s share of the company’s total revenue has consistently grown over the years. In the first quarter of 2009, the iPhone sales were responsible for about ********* of Apple’s revenue. In the third quarter of FY 2024, this figure reached a high of roughly ** percent, equating to less than ** billion U.S. dollars in that quarter. In terms of units sold, Apple went from around **** million units in 2010 to about *** million in 2023, but registered a peak in the fourth quarter of 2020 with more than ** million iPhones sold worldwide.

This dataset contains reviews of the iPhone 14 from various customers. Each entry in the dataset includes information such as the title of the review, the rating given by the customer, the detailed review text, the name of the customer, the date when the review was posted, and the location of the customer. These reviews offer insights into customer opinions, satisfaction levels, and preferences regarding the iPhone 14.

Column Descriptions: 1. Title: Title or headline of the review provided by the customer. It summarizes the main point or sentiment expressed in the review. 2. Rating: Numerical rating given by the customer for the iPhone 14. Ratings typically range from 1 to 5, with 5 indicating the highest satisfaction level. 3. Review: Detailed text of the review where the customer shares their experiences, opinions, and feedback about the iPhone 14. 4. Customer Name: Name or identifier of the customer who wrote the review. It helps in tracking individual reviewers and analyzing their feedback. 5. Dates: Date when the review was posted by the customer. It provides temporal information for analyzing trends and changes in customer sentiment over time. 6. Customer Location: Location of the customer who wrote the review. It can be useful for demographic analysis, understanding regional preferences, and market segmentation.

This dataset can be used for sentiment analysis, feature analysis, trend analysis, customer profiling, and market research related to the iPhone 14.

iPhone Reviews from Amazon.com

30,000+ User-Submitted Reviews

By Crawl Feeds [source]

About this dataset

This 30,000+ reviews dataset for Apple iPhone from Amazon.com provides insights and comprehensive opinion data that can be used to understand current customer sentiment towards the product. With helpful_count as one of the columns, this dataset provides an opportunity to find out which reviews are most helpful for customers and highlights the key areas of improvement for other brands in a similar product range. Exceptional review ratings and detailed text reviews give readers an idea about why customers liked or disliked the product, providing valuable market feedback information such as what went wrong (or right). Alongside this, knowledge about where a review was made gives better context on whether comments should be taken lightly or with more pressing importance. An invaluable resource for industry stakeholders and researchers alike, use this dataset to gain a clearer picture of customer satisfaction surrounding Apple's latest release - The iPhone!

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How to use the dataset

This dataset contains over 30,000 reviews for the Apple iPhone from Amazon.com. It includes information such as the product name, helpful count, total comments, URL of the review, review country, date and time of the review, rating of the product given by reviewer, product company name and profile name. You can use this dataset to analyze customer feedback about the Apple iPhone from Amazon.

To get started with this dataset you should first read through each column and understand what it represents. Once you are familiar with each column then you can start exploring the data further by filtering out particular reviews or performing a sentiment analysis on particular reviews using tools such as Python's Natural Language Toolkit (NLTK). You could also look at analyzing trends in customer ratings over time or breaking down customer feedback into gender specific segments to gain more insights about user preferences.

You can also group reviews based on their geographical location and look at regional differences in user opinion towards a particular product feature or implementation style which may indicate alterations in usability/ technicalities that need to be addressed along with other factors such as cultural influence which may have an effect on user opinion towards a certain brand/product feature etc. This info could be used to inform your marketing strategies across different parts of your target market region thus providing more targeted results while creating ad campaigns aimed at driving sales for the aforementioned products/brands-helping improve ROI performance efficiently!

Lastly if you are looking for insights particularly regarding Apple’s competitors-it would be useful for you to analyze comparative feedback between customers regarding similar competitive brands/products allowing potential investments pivoting around stronger performers!

We hope this guide provides some useful insight into how to use this dataset effectively from Amazon mobile phones reviews set! Have fun exploring!!

Research Ideas

• To train a sentiment analysis model to better understand customers’ attitudes towards Apple's iPhone.
• To analyze the review comments and look for correlations between certain words and ratings, in order to gain insights on how customers perceive the phone based on their experiences with it.
• Create a combination of product reviews with video reviews from YouTube in order to provide potential buyers a more comprehensive overview of the features, performance and beauty of the iPhone before purchasing it

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_iphone_11_reviews.csv | Column name | Description | |:--------------------|:-------------------------------------------------------------| | product | The product being reviewed. (String) | | helpful_count | The number of people who found the review helpful. (Integer) | | total_comments | The total number of comments on the review. (Integer) | | url | The URL of the review post. (String) | | review_country | The country from which the review was posted. (Strin...

Percentage of smartphone users by selected smartphone use habits in a typical day.

This dataset provides a comprehensive collection of information about all the latest smartphones available in the market as of the current time.

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The dataset was created by web scraping reputable online sources to gather accurate and up-to-date information about various smartphone models, their specifications, features, and pricing.

Our organization provides technology websites with content about the current value of used smartphones and the value per dollar of phones in the market to help people buy and sell smartphones. A model that could predict the real value of phones based on several factors would be helpful.

Attributes of the dataset include:

• PhoneID The identification number of a phone in this dataset.
• Brand The smartphone manufacturer (e.g., Apple, Google, Samsung, etc.)
• Model The smartphone model (e.g., iPhone 13, Galaxy S21, etc.)
• Release Year The year the smartphone model was released.
• Screen Size (inches) The model's screen size is in inches.
• RAM (GB) The model's RAM in GB (2, 4, 6, 8, 12, 16)
• Storage (GB) The internal storage of the smartphone in GB (32, 64, 128, 256, 512)
• Battery Capacity (mAh) The battery life is measured in milliampere-hours. The abbreviation mAh stands for milliampere-hour, a unit of electrical charge that measures a battery's capacity. It indicates how much current a battery can supply over time. A higher mAh rating means the battery can store more energy and power a device for longer.
• Camera (MP) is the smartphone's camera's megapixel rating. The higher the number of MP, the better the camera's resolution.
• 5G Support If the smartphone supports 5G connectivity, Yes. Otherwise, No.
• Operating System One of two, Android or iOS.
• Price (USD) is the current market price of the smartphone in US Dollars.

Infant Crying smartphone speech dataset, collected by Android smartphone and iPhone, covering infant crying. Our dataset was collected from extensive and diversify speakers(201 people in total, with balanced gender distribution), geographicly speaking, enhancing model performance in real and complex tasks. Quality tested by various AI companies. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.

The global number of smartphone users in was forecast to continuously increase between 2024 and 2029 by in total *** billion users (+***** percent). After the fifteenth consecutive increasing year, the smartphone user base is estimated to reach *** billion users and therefore a new peak in 2029. Notably, the number of smartphone users of was continuously increasing over the past years.Smartphone users here are limited to internet users of any age using a smartphone. The shown figures have been derived from survey data that has been processed to estimate missing demographics.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to *** countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of smartphone users in countries like the Americas and Asia.

Apple is one of the leaders in smartphone design and innovation. So naturally, people want to buy Apple devices. Various factors have been deemed to affect the purchase decision of buyers in the past, and present time isn't any different either. This dataset will try to predict this exact behavior from over 400 samples taken online.

There are a total of 17 questions in the survey, addressing the following categories:Internet useMobile phone use (smartphones & basic voice/SMS phones)Awareness and use of WikipediaGeneral demographicsThe survey collected 2500 total responses, representing populations in 5 geographical regions served by 3 mobile Iraqi operators. 3 language choices (Arabic, English, Kurdish) were provided.Here are the main questions this survey was designed to answer. However, analyzing the full data set allows you to conduct more in-depth data explorations and gain meaningful insights beyond the points presented here.What is the actual number of people who use the internet?(Real-world behavior makes this difficult to measure from industry reports, since people might have access to the internet through school, friends, internet cafés, public Wifi, etc.)For internet users: What do people mostly use the internet for?For non-internet users: Why not use the internet?How many people use smartphones?Do people with smartphones use the internet from just Wifi? Or just cellular service?How many people think that they don’t use the internet, but still use Facebook or WhatsApp?How many people have heard of Wikipedia? What do they use it for? How often?If they have heard of Wikipedia, but aren’t using it, why not?Compared to previous phone surveys in other countries, the 2017 Iraq phone survey presented new questions.What are people’s awareness of other major internet brands in comparison to Wikipedia?Can people find online content in their preferred language?How does data cost impact internet use?

The release of the first iPhone was On June 29, 2007 so this dataset provide the historical data of APPl stock

This dataset contains historical data for appl stock. The dataset provides information for each trading day, including the date, price, open, high, low, volume, and percentage change.

Here is a description of the columns in the dataset :

1) Date: (datetime64) This column represents the date of the trading day. It indicates when the data was recorded.

2) Price: (float64) The price column represents the index's closing price on each trading day. It shows the value at which the index concluded its trading session.

3) Open: (float64) This column denotes the opening price of the index on each trading day. It represents the value at which the index began trading at the start of the session.

4) High: (float64) The high column indicates the highest price reached by the index during the trading day. It represents the peak value recorded for the index's price.

5) Low: (float64) The low column represents the lowest price reached by the index during the trading day. It indicates the minimum value recorded for the index's price.

6) Vol.: (object) The volume column denotes the trading volume, usually measured in millions, for each trading day. It represents the total number of shares or contracts traded during the session.

7) Change %: (float64) This column provides the percentage change in the index's price from the previous trading day. It indicates the daily price movement of the index.

The dataset contains 4034 rows, including the header row that describes the columns. The actual data starts from the second row and provides information for each trading day in descending order, with the most recent date appearing first.

This database automatically captures metadata, the source of which is the GOVERNMENT OF THE REPUBLIC OF SLOVENIA STATISTICAL USE OF THE REPUBLIC OF SLOVENIA and corresponding to the source database entitled “Number of individuals in terms of security when using a smartphone in the last 3 months for private purposes, by activity status, Slovenia, 2020”.

Actual data are available in Px-Axis format (.px). With additional links, you can access the source portal page for viewing and selecting data, as well as the PX-Win program, which can be downloaded free of charge. Both allow you to select data for display, change the format of the printout, and store it in different formats, as well as view and print tables of unlimited size, as well as some basic statistical analyses and graphics.

The number of smartphone users in France was forecast to continuously increase between 2024 and 2029 by in total 3.2 million users (+5.96 percent). After the fifteenth consecutive increasing year, the smartphone user base is estimated to reach 56.89 million users and therefore a new peak in 2029. Notably, the number of smartphone users of was continuously increasing over the past years.Smartphone users here are limited to internet users of any age using a smartphone. The shown figures have been derived from survey data that has been processed to estimate missing demographics.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of smartphone users in countries like Belgium and Luxembourg.

The number of smartphone users in the United Kingdom was forecast to continuously increase between 2024 and 2029 by in total *** million users (+**** percent). After the ninth consecutive increasing year, the smartphone user base is estimated to reach ***** million users and therefore a new peak in 2029. Notably, the number of smartphone users of was continuously increasing over the past years.Smartphone users here are limited to internet users of any age using a smartphone. The shown figures have been derived from survey data that has been processed to estimate missing demographics.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to *** countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more information concerning Denmark and Latvia.

Hypothesis 1: learners using SETs in physics laboratories (as an experimental group) would report high flow experience. Hypothesis 2: Using SETs in physics laboratories would reduce learners’ intrinsic and extraneous cognitive load but enhance their germane cognitive load. Hypothesis 3: Flow experience was negatively correlated with the intrinsic and extraneous cognitive load while remarkably positively related with the germane cognitive load.

The data set includes all participants in the research. You can see students' basic information, like gender and research group, and their flow experience and cognitive load through this set. Using all these data, you can explore the difference in flow and cognitive load between the two groups. Besides, the correlation between flow and cognitive load would be further detected. The results indicated that students learning with smartphones reported higher flow experience and germane cognitive load but a lower extraneous and intrinsic cognitive load than those learning with traditional tools. Moreover, the flow was positively correlated with the germane cognitive load but negatively related to extraneous and intrinsic cognitive load in this study.

The number of smartphone users in the Philippines was forecast to increase between 2024 and 2029 by in total 5.6 million users (+7.29 percent). This overall increase does not happen continuously, notably not in 2026, 2027, 2028 and 2029. The smartphone user base is estimated to amount to 82.33 million users in 2029. Notably, the number of smartphone users of was continuously increasing over the past years.Smartphone users here are limited to internet users of any age using a smartphone. The shown figures have been derived from survey data that has been processed to estimate missing demographics.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

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Hey there, phone fans! This dataset dives into the hottest-selling mobile phones, giving you the lowdown on the Top 120 models that ruled the market. We've got data on:

Manufacturer: The big names behind the phones, like Apple, Samsung, and whoever else is cooking up the latest tech (you know, these Tony Starks). Model: The specific phone name, because let's face it, not all iPhones are created equal (looking at you, iPhone 3G). Form Factor: We're talking about the phone's overall shape and style, whether it's a classic Bar, a sleek Touchscreen, or Keyboard bar phone. Year: The year these phones hit the shelves, so you can see how trends changed over time. Units Sold (Million): This is the big one - how many millions of people actually bought these phones?

So, if you're curious about the cell phone hall of fame, or just want to see how phone technology has evolved over the years, this dataset is your one-stop shop.