European Union Imports from United States was US$355.76 Billion during 2024, according to the United Nations COMTRADE database on international trade. European Union Imports from United States - data, historical chart and statistics - was last updated on August of 2025.

European Union Exports to United States was US$571.11 Billion during 2024, according to the United Nations COMTRADE database on international trade. European Union Exports to United States - data, historical chart and statistics - was last updated on August of 2025.

The United States' total Imports in 2024 were valued at US$3.36 Trillion, according to the United Nations COMTRADE database on international trade. The United States' main import partners were: Mexico, China and Canada. The top three import commodities were: Machinery, nuclear reactors, boilers; Electrical, electronic equipment and Vehicles other than railway, tramway. Total Exports were valued at US$2.06 Trillion. In 2024, The United States had a trade deficit of US$1.29 Trillion.

The European Union's total Imports in 2024 were valued at US$2.64 Trillion, according to the United Nations COMTRADE database on international trade. The European Union's main import partners were: China, the United States and the United Kingdom. The top three import commodities were: Mineral fuels, oils, distillation products; Electrical, electronic equipment and Machinery, nuclear reactors, boilers. Total Exports were valued at US$2.80 Trillion. In 2024, The European Union had a trade surplus of US$159.68 Billion.

Large go-around, also referred to as missed approach, data set. The data set is in support of the paper presented at the OpenSky Symposium on November the 10th.

If you use this data for a scientific publication, please consider citing our paper.

The data set contains landings from 176 (mostly) large airports from 44 different countries. The landings are labelled as performing a go-around (GA) or not. In total, the data set contains almost 9 million landings with more than 33000 GAs. The data was collected from OpenSky Network's historical data base for the year 2019. The published data set contains multiple files:

go_arounds_minimal.csv.gz

Compressed CSV containing the minimal data set. It contains a row for each landing and a minimal amount of information about the landing, and if it was a GA. The data is structured in the following way:

    Column name
    Type
    Description




    time
    date time
    UTC time of landing or first GA attempt


    icao24
    string
    Unique 24-bit (hexadecimal number) ICAO identifier of the aircraft concerned


    callsign
    string
    Aircraft identifier in air-ground communications


    airport
    string
    ICAO airport code where the aircraft is landing


    runway
    string
    Runway designator on which the aircraft landed


    has_ga
    string
    "True" if at least one GA was performed, otherwise "False"


    n_approaches
    integer
    Number of approaches identified for this flight


    n_rwy_approached
    integer
    Number of unique runways approached by this flight

The last two columns, n_approaches and n_rwy_approached, are useful to filter out training and calibration flight. These have usually a large number of n_approaches, so an easy way to exclude them is to filter by n_approaches > 2.

go_arounds_augmented.csv.gz

Compressed CSV containing the augmented data set. It contains a row for each landing and additional information about the landing, and if it was a GA. The data is structured in the following way:

    Column name
    Type
    Description




    time
    date time
    UTC time of landing or first GA attempt


    icao24
    string
    Unique 24-bit (hexadecimal number) ICAO identifier of the aircraft concerned


    callsign
    string
    Aircraft identifier in air-ground communications


    airport
    string
    ICAO airport code where the aircraft is landing


    runway
    string
    Runway designator on which the aircraft landed


    has_ga
    string
    "True" if at least one GA was performed, otherwise "False"


    n_approaches
    integer
    Number of approaches identified for this flight


    n_rwy_approached
    integer
    Number of unique runways approached by this flight


    registration
    string
    Aircraft registration


    typecode
    string
    Aircraft ICAO typecode


    icaoaircrafttype
    string
    ICAO aircraft type


    wtc
    string
    ICAO wake turbulence category


    glide_slope_angle
    float
    Angle of the ILS glide slope in degrees


    has_intersection

string

    Boolean that is true if the runway has an other runway intersecting it, otherwise false


    rwy_length
    float
    Length of the runway in kilometre


    airport_country
    string
    ISO Alpha-3 country code of the airport


    airport_region
    string
    Geographical region of the airport (either Europe, North America, South America, Asia, Africa, or Oceania)


    operator_country
    string
    ISO Alpha-3 country code of the operator


    operator_region
    string
    Geographical region of the operator of the aircraft (either Europe, North America, South America, Asia, Africa, or Oceania)


    wind_speed_knts
    integer
    METAR, surface wind speed in knots


    wind_dir_deg
    integer
    METAR, surface wind direction in degrees


    wind_gust_knts
    integer
    METAR, surface wind gust speed in knots


    visibility_m
    float
    METAR, visibility in m


    temperature_deg
    integer
    METAR, temperature in degrees Celsius


    press_sea_level_p
    float
    METAR, sea level pressure in hPa


    press_p
    float
    METAR, QNH in hPA


    weather_intensity
    list
    METAR, list of present weather codes: qualifier - intensity


    weather_precipitation
    list
    METAR, list of present weather codes: weather phenomena - precipitation


    weather_desc
    list
    METAR, list of present weather codes: qualifier - descriptor


    weather_obscuration
    list
    METAR, list of present weather codes: weather phenomena - obscuration


    weather_other
    list
    METAR, list of present weather codes: weather phenomena - other

This data set is augmented with data from various public data sources. Aircraft related data is mostly from the OpenSky Network's aircraft data base, the METAR information is from the Iowa State University, and the rest is mostly scraped from different web sites. If you need help with the METAR information, you can consult the WMO's Aerodrom Reports and Forecasts handbook.

go_arounds_agg.csv.gz

Compressed CSV containing the aggregated data set. It contains a row for each airport-runway, i.e. every runway at every airport for which data is available. The data is structured in the following way:

    Column name
    Type
    Description




    airport
    string
    ICAO airport code where the aircraft is landing


    runway
    string
    Runway designator on which the aircraft landed


    n_landings
    integer
    Total number of landings observed on this runway in 2019


    ga_rate
    float
    Go-around rate, per 1000 landings


    glide_slope_angle
    float
    Angle of the ILS glide slope in degrees


    has_intersection
    string
    Boolean that is true if the runway has an other runway intersecting it, otherwise false


    rwy_length
    float
    Length of the runway in kilometres


    airport_country
    string
    ISO Alpha-3 country code of the airport


    airport_region
    string
    Geographical region of the airport (either Europe, North America, South America, Asia, Africa, or Oceania)

This aggregated data set is used in the paper for the generalized linear regression model.

Downloading the trajectories

Users of this data set with access to OpenSky Network's Impala shell can download the historical trajectories from the historical data base with a few lines of Python code. For example, you want to get all the go-arounds of the 4th of January 2019 at London City Airport (EGLC). You can use the Traffic library for easy access to the database:

import datetime from tqdm.auto import tqdm import pandas as pd from traffic.data import opensky from traffic.core import Traffic

load minimum data set

df = pd.read_csv("go_arounds_minimal.csv.gz", low_memory=False) df["time"] = pd.to_datetime(df["time"])

select London City Airport, go-arounds, and 2019-01-04

airport = "EGLC" start = datetime.datetime(year=2019, month=1, day=4).replace( tzinfo=datetime.timezone.utc ) stop = datetime.datetime(year=2019, month=1, day=5).replace( tzinfo=datetime.timezone.utc )

df_selection = df.query("airport==@airport & has_ga & (@start <= time <= @stop)")

iterate over flights and pull the data from OpenSky Network

flights = [] delta_time = pd.Timedelta(minutes=10) for _, row in tqdm(df_selection.iterrows(), total=df_selection.shape[0]): # take at most 10 minutes before and 10 minutes after the landing or go-around start_time = row["time"] - delta_time stop_time = row["time"] + delta_time

# fetch the data from OpenSky Network
flights.append(
  opensky.history(
    start=start_time.strftime("%Y-%m-%d %H:%M:%S"),
    stop=stop_time.strftime("%Y-%m-%d %H:%M:%S"),
    callsign=row["callsign"],
    return_flight=True,
  )
)

The flights can be converted into a Traffic object

Traffic.from_flights(flights)

Additional files

Additional files are available to check the quality of the classification into GA/not GA and the selection of the landing runway. These are:

validation_table.xlsx: This Excel sheet was manually completed during the review of the samples for each runway in the data set. It provides an estimate of the false positive and false negative rate of the go-around classification. It also provides an estimate of the runway misclassification rate when the airport has two or more parallel runways. The columns with the headers highlighted in red were filled in manually, the rest is generated automatically.

validation_sample.zip: For each runway, 8 batches of 500 randomly selected trajectories (or as many as available, if fewer than 4000) classified as not having a GA and up to 8 batches of 10 random landings, classified as GA, are plotted. This allows the interested user to visually inspect a random sample of the landings and go-arounds easily.

European Union Imports from China was US$560.36 Billion during 2024, according to the United Nations COMTRADE database on international trade. European Union Imports from China - data, historical chart and statistics - was last updated on August of 2025.

European Union Imports from India was US$77.06 Billion during 2024, according to the United Nations COMTRADE database on international trade. European Union Imports from India - data, historical chart and statistics - was last updated on August of 2025.

The United States' total Exports in 2024 were valued at US$2.06 Trillion, according to the United Nations COMTRADE database on international trade. The United States' main export partners were: Canada, Mexico and China. The top three export commodities were: Mineral fuels, oils, distillation products; Machinery, nuclear reactors, boilers and Electrical, electronic equipment. Total Imports were valued at US$3.36 Trillion. In 2024, The United States had a trade deficit of US$1.29 Trillion.

European Union Imports from Kenya was US$1.52 Billion during 2024, according to the United Nations COMTRADE database on international trade. European Union Imports from Kenya - data, historical chart and statistics - was last updated on August of 2025.

European Union Exports to China was US$227.17 Billion during 2024, according to the United Nations COMTRADE database on international trade. European Union Exports to China - data, historical chart and statistics - was last updated on August of 2025.

European Union Imports from Israel was US$17 Billion during 2024, according to the United Nations COMTRADE database on international trade. European Union Imports from Israel - data, historical chart and statistics - was last updated on August of 2025.

European Union Imports from South Africa was US$21.72 Billion during 2024, according to the United Nations COMTRADE database on international trade. European Union Imports from South Africa - data, historical chart and statistics - was last updated on August of 2025.

European Union Imports of electrical, electronic equipment from China was US$173.71 Billion during 2024, according to the United Nations COMTRADE database on international trade. European Union Imports of electrical, electronic equipment from China - data, historical chart and statistics - was last updated on August of 2025.

China's total Exports in 2024 were valued at US$3.58 Trillion, according to the United Nations COMTRADE database on international trade. China's main export partners were: the United States, Hong Kong and Vietnam. The top three export commodities were: Electrical, electronic equipment; Machinery, nuclear reactors, boilers and Vehicles other than railway, tramway. Total Imports were valued at US$2.59 Trillion. In 2024, China had a trade surplus of US$991.41 Billion.

European Union Imports from Sri Lanka was US$2.91 Billion during 2024, according to the United Nations COMTRADE database on international trade. European Union Imports from Sri Lanka - data, historical chart and statistics - was last updated on August of 2025.