A. SUMMARY San Francisco International Airport Report on Monthly Passenger Traffic Statistics by Airline. B. HOW THE DATASET IS CREATED Data is self-reported by airlines and is only available at a monthly level C. UPDATE PROCESS Data updated quarterly D. HOW TO USE THIS DATASET Airport data is seasonal in nature, therefore any comparative analyses should be done on a period-over-period basis (i.e. January 2010 vs. January 2009) as opposed to period-to-period (i.e. January 2010 vs. February 2010). It is also important to note that fact and attribute field relationships are not always 1-to-1. For example, Passenger Counts belonging to United Airlines will appear in multiple attribute fields and are additive, which provides flexibility for the user to derive categorical Passenger Counts as desired.

This dataset provides valuable insights into the aviation industry's trends and growth patterns, making it a valuable resource for analysts, researchers, and aviation enthusiasts.

1.**Country:** This column represents the name of the country where the airline is based. It provides valuable geographical context to the dataset, allowing users to explore passenger trends on a country-by-country basis.

2.**Airline Passengers Carried:** This column contains the number of passengers carried by each airline. It is a critical metric for evaluating an airline's performance and market share.

3.**Year:** The year column indicates the year to which the data corresponds. It allows users to track changes in passenger numbers over time and observe trends and fluctuations in the airline industry.

This dataset, enables data scientists, analysts, and researchers to conduct a wide range of analyses and create data-driven visualizations to answer various questions related to air travel, such as:

• Which countries have the highest and lowest airline passenger numbers?
• How has the global airline industry evolved over the years in terms of passenger volume?
• Are there any seasonal patterns or trends in airline passenger data?
• What are the top airlines in terms of passenger volume for a specific year or country?
• How does economic or political stability in a country correlate with airline passenger numbers?

By making this dataset available on Kaggle, we aim to foster collaboration and innovation within the data science community, allowing users to extract valuable insights from the world of aviation and contribute to a better understanding of global travel patterns. Researchers, analysts, and data enthusiasts can leverage this dataset to gain a deeper understanding of the dynamics of the airline industry and make informed decisions based on the trends observed in the data.

In 2023, the estimated number of scheduled passengers boarded by the global airline industry amounted to approximately *** billion people. This represents a significant increase compared to the previous year since the pandemic started and the positive trend was forecast to continue in 2024, with the scheduled passenger volume reaching just below **** billion travelers. Airline passenger traffic The number of scheduled passengers handled by the global airline industry has increased in all but one of the last decade. Scheduled passengers refer to the number of passengers who have booked a flight with a commercial airline. Excluded are passengers on charter flights, whereby an entire plane is booked by a private group. In 2023, the Asia Pacific region had the highest share of airline passenger traffic, accounting for ********* of the global total.

In 2024, around **** percent of airline passenger traffic was operated by airline companies in the Asia-Pacific region. Meanwhile, Europe accounted for the second largest passenger traffic share, with **** percent.

Airline passenger data from 2000-2023 data collected from the United States Bureau of Transportation Statistics (bts.gov). This dataset includes the following columns: airline carrier code, airline name, total number of passengers and year.

When it comes to share of Americans who flew with American Airlines in the past 12 months, ** percent of 18 - 29 year olds do so in the U.S. This is according to exclusive insights from the Consumer Insights Global survey which shows that ** percent of 30 - 49 year old consumers also fall into this category.Statista Consumer Insights offer you all results of our exclusive Statista surveys, based on more than ********* interviews.

Dataset + pivot tables for Aviation.

Graph and download economic data for Enplanements for U.S. Air Carrier Domestic, Scheduled Passenger Flights (ENPLANEDD11) from Jan 2000 to Jul 2025 about flight, passenger, air travel, travel, domestic, and USA.

Airlines Traffic Passenger Statistics

A New Look at an Old Problem

About this dataset

This dataset contains information on air traffic passenger statistics by the airline. It includes information on the airlines, airports, and regions that the flights departed from and arrived at. It also includes information on the type of activity, price category, terminal, boarding area, and number of passengers

How to use the dataset

Air traffic passenger statistics can be a useful tool for understanding the airline industry and for making travel plans. This dataset from Open Flights contains information on air traffic passenger statistics by airline for 2017. The data includes the number of passengers, the operating airline, the published airline, the geographic region, the activity type code, the price category code, the terminal, the boarding area, and the year and month of the flight

Research Ideas

• Air traffic passenger statistics could be used to predict future trends in air travel.
• The data could be used to generate heat maps of airline traffic patterns.
• The data could be used to study the effects of different factors on air traffic passenger numbers, such as the time of year or day, the price of airfare, or the number of flights offered by an airline

License

License: Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) - You are free to: - Share - copy and redistribute the material in any medium or format for non-commercial purposes only. - Adapt - remix, transform, and build upon the material for non-commercial purposes only. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - You may not: - Use the material for commercial purposes.

Columns

File: Air_Traffic_Passenger_Statistics.csv | Column name | Description | |:--------------------------------|:------------------------------------------------------------------------------| | Activity Period | The date of the activity. (Date) | | Operating Airline | The airline that operated the flight. (String) | | Operating Airline IATA Code | The IATA code of the airline that operated the flight. (String) | | Published Airline | The airline that published the fare for the flight. (String) | | Published Airline IATA Code | The IATA code of the airline that published the fare for the flight. (String) | | GEO Summary | A summary of the geographic region. (String) | | GEO Region | The geographic region. (String) | | Activity Type Code | The type of activity. (String) | | Price Category Code | The price category of the fare. (String) | | Terminal | The terminal of the flight. (String) | | Boarding Area | The boarding area of the flight. (String) | | Passenger Count | The number of passengers on the flight. (Integer) | | Adjusted Activity Type Code | The type of activity, adjusted for missing data. (String) | | Adjusted Passenger Count | The number of passengers on the flight, adjusted for missing data. (Integer) | | Year | The year of the activity. (Integer) | | Month | The month of the activity. (Integer) |

San Francisco International Airport Report on Monthly Passenger Traffic Statistics by Airline. Airport data is seasonal in nature, therefore any comparative analyses should be done on a period-over-period basis (i.e. January 2010 vs. January 2009) as opposed to period-to-period (i.e. January 2010 vs. February 2010). It is also important to note that fact and attribute field relationships are not always 1-to-1. For example, Passenger Counts belonging to United Airlines will appear in multiple attribute fields and are additive, which provides flexibility for the user to derive categorical Passenger Counts as desired.

In 2024, U.S. airlines recorded ****** million passengers on domestic and international flights. The previous year, the number of passengers at U.S. airports officially surpassed the pre-pandemic peak of ***** million passengers recorded in 2019.

This Dataset contains year-wise cumulative city pair-wise passenger, freight and mail traffic statistics

Passengers enplaned and deplaned at Canadian airports, annual.

Airline Passenger Satisfaction – EDA Report

This project analyzes the Airline Passenger Satisfaction Dataset, containing 103,904 rows and 25 columns describing passenger demographics, flight information, and service ratings.The goal is to understand which factors influence satisfaction, identify important service features,and compare satisfaction between different traveler types and flight classes.

  Dataset Overview

The dataset includes:

Passenger demographics (age… See the full description on the dataset page: https://huggingface.co/datasets/drukeroni/airline-satisfaction-analysis.

Air passenger origin and destination data (passenger numbers, city rank), for transborder journeys, by total outbound and inbound passengers exceeding 4000, by city-pair, annual.

The Air transport domain contains national and international intra and extra-EU data. This provides air transport data for passengers (in number of passengers) and for freight and mail (in 1 000 tonnes) as well as air traffic data by airports, airlines and aircraft. Data are transmitted to Eurostat by EU Member States, EFTA countries and some other reporting countries. Data are compiled following the provisions of the Regulation (EC) N°1358/2003, implementing Regulation N°437/2003 of the European Parliament and of the Council on statistical returns in respect of the carriage of passengers, freight and mail by air. The air transport data are collected at airport level. As from 2003 reference year the data are provided according to the legal act (some countries were given derogation until 2005). Until 2002 partial information (passenger transport only) are available for some countries and airports.

Airports handling less than 15 000 passenger units annually are excluded from the scope of the Regulation. Datasets A1 and B1 are provided on monthly basis, while dataset C1 can be provided either on monthly or annual basis. For some countries optional variable - total number of transfer passengers - is provided as well.

The data are disseminated by Eurostat in on-line database in four sub-domains:

• Air Transport measurement - Passengers
• Air Transport measurement - Freight and mail
• Air Transport measurement - Traffic data by airports, aircraft and airlines
• Air Transport measurement - Data aggregated at standard regional levels (NUTS).

The two first domains contain several data collections:

• Overview of the air transport by country and airport,
• National air transport by country and airport,
• International intra-EU air transport by country and airport,
• International extra-EU air transport by country and airport,
• Detailed air transport by reporting country and routes.

In the tables of the sub-domain "Transport measurement - Passengers", data are broken down by passengers on board (arrivals, departures and total), passengers carried (arrivals, departures and total) and passenger commercial air flights (arrival, departures and total). Additionally, the tables of collection "Detailed air transport by reporting country and routes" provide data on seats available (arrival, departures and total). The data is presented at monthly, quarterly and annual level.

In the tables of the sub-domain "Transport measurement - Freight and mail", data are broken down by freight and mail on board (arrival, departures and total), freight and mail loaded/unloaded (loaded, unloaded and total) and all-freight and mail commercial air flights (arrival, departures and total). The data is presented at monthly, quarterly and annual level.

In the tables of the sub-domain "Transport measurement - Traffic by airports, aircraft and airlines":

• Data by type of aircraft are broken down by total passengers on board, total freight and mail on board in tonnes, total passengers seats available, total commercial air flights (passengers + all-freight and mail), passenger commercial air flights, all-freight and mail commercial air flights. The data is presented at annual level since 2003.
• Data by type of airline are broken down by total passengers on board, total passengers carried, total freight and mail on board, total freight and mail loaded/unloaded, total passengers seats available, total commercial air flights (passengers + all-freight and mail), passenger commercial air flights, all-freight and mail commercial air flights. The data is presented at annual level since 2003.
• Data by airport are broken down by total passengers carried, total transit passengers, total transfer passengers, total freight and mail loaded/unloaded, total commercial aircraft movements, total aircrafts movements. The data is presented at monthly, quarterly and annual level.

The sub-domain "Transport measurement - Data aggregated at standard regional levels (NUTS)", contains two tables:

• Air transport of passengers at regional level
• Air transport of freight at regional level

The tables present the evolution of the number of passengers carried (if not available passengers on board) and the volume of freight and mail loaded or unloaded (if not available freight and mail on board) to/from the NUTS regions (level 2, 1 and 0) since 1999. The data is presented at annual level. The air transport regional data have been calculated using data collected at the airport level in the frame of the regulatory data collection on air transport.

For more details on datasets, data validation and dissemination refer also to Reference Manual on Air Transport Statistics available in the Annex part of the metadata.

Graph and download economic data for Revenue Passenger Miles for U.S. Air Carrier Domestic and International, Scheduled Passenger Flights (RPM) from Jan 2000 to Jul 2025 about flight, miles, passenger, air travel, travel, revenue, domestic, and USA.

Graph and download economic data for Air Revenue Passenger Miles (AIRRPMTSID11) from Jan 2000 to Aug 2025 about miles, passenger, air travel, travel, revenue, and USA.

Canada Canadian Airlines: Passenger Load Factor data was reported at 84.000 % in Feb 2025. This records an increase from the previous number of 81.000 % for Jan 2025. Canada Canadian Airlines: Passenger Load Factor data is updated monthly, averaging 82.350 % from Jan 2015 (Median) to Feb 2025, with 122 observations. The data reached an all-time high of 89.800 % in Aug 2023 and a record low of 26.000 % in Apr 2020. Canada Canadian Airlines: Passenger Load Factor data remains active status in CEIC and is reported by Statistics Canada. The data is categorized under Global Database’s Canada – Table CA.TA015: Canadian Airlines Statistics. [COVID-19-IMPACT]