traffic.core.sv

class traffic.core.sv.StateVectors(data)

Bases: GeographyMixin

Plots the state vectors returned by OpenSky REST API.

agg_xy(resolution, projection=None, **kwargs)

Aggregates values of a traffic over a grid of x/y, with x and y computed by compute_xy().

Parameters:

resolution (None | dict[str, float]) – The resolution of the grid is passed as a dictionary parameter. By default, the grid is made by rounding x and y to the lower ten kilometer values. dict(x=5000, y=3000) will take 1 value per 5000 meters for x (10000, 15000, 20000, …) and 1 value per 3000 meters for y (9000, 12000, 15000, 18000, 20000, …).
projection (None | pyproj.Proj | ‘crs.Projection) – is used to compute the x and y values.

The kwargs specifies how to aggregate values:

altitude="mean" would average all values in the given cell;
timestamp="count" would return the number of samples per cell;
icao24="nunique" would return the number of different aircraft int the given cell.

Return type:: pd.DataFrame
Returns:: a DataFrame indexed over x and y values. It is conveniently chainable with the .to_xarray() method in order to plot density heatmaps.

Example usage:

belevingsvlucht.agg_xy(
    resolution=dict(x=3e3, y=3e3),
    vertical_rate="mean",
    timestamp="count"
)

assign(*args, **kwargs)

Applies the Pandas assign() method to the underlying pandas DataFrame and get the result back in the same structure.

Return type:: TypeVar(T, bound= DataFrameMixin)

compute_latlon_from_xy(projection): Enrich a DataFrame with new longitude and latitude columns computed from x and y columns. :rtype: TypeVar(T, bound= DataFrameMixin)

Warning

Make sure to use as source projection the one used to compute 'x' and 'y' columns in the first place.

compute_xy(projection=None)

Enrich the structure with new x and y columns computed through a projection of the latitude and longitude columns.

The source projection is WGS84 (EPSG 4326). The default destination projection is a Lambert Conformal Conical projection centred on the data inside the dataframe.

Other valid projections are available: :rtype: T

as pyproj.Proj objects;
as cartopy.crs.Projection objects.

convert_dtypes(*args, **kwargs)

Applies the Pandas convert_dtypes() method to the underlying pandas DataFrame and get the result back in the same structure.

Return type:: TypeVar(T, bound= DataFrameMixin)

drop(*args, **kwargs)

Applies the Pandas drop() method to the underlying pandas DataFrame and get the result back in the same structure.

Return type:: TypeVar(T, bound= DataFrameMixin)

drop_duplicates(*args, **kwargs)

Applies the Pandas drop_duplicates() method to the underlying pandas DataFrame and get the result back in the same structure.

Return type:: TypeVar(T, bound= DataFrameMixin)

fillna(*args, **kwargs)

Applies the Pandas fillna() method to the underlying pandas DataFrame and get the result back in the same structure.

Return type:: TypeVar(T, bound= DataFrameMixin)

classmethod from_file(filename, **kwargs)

Read data from various formats.

This class method dispatches the loading of data in various format to the proper pandas.read_* method based on the extension of the filename. Potential compression of the file is inferred by pandas itself based on the extension. :rtype: Optional[TypeVar(T, bound= DataFrameMixin)]

.pkl.* or .parquet.* dispatch to pandas.read_pickle();
.parquet.* dispatch to pandas.read_parquet();
.feather.* dispatch to pandas.read_feather();
.json.* dispatch to pandas.read_json();
.jsonl dispatch to a specific function (output of jet1090);
.csv.* dispatch to pandas.read_csv();
.h5.* dispatch to pandas.read_hdf().

Other extensions return None. Specific arguments may be passed to the underlying pandas.read_* method with the kwargs argument.

Example usage:

>>> from traffic.core import Traffic
>>> t = Traffic.from_file(filename)

geoencode(**kwargs)

Returns an altair encoding of the shape to be composed in an interactive visualization. Specific plot features, such as line widths, can be passed with the kwargs argument. See documentation.

Return type:: Chart

groupby(*args, **kwargs)

Applies the Pandas groupby() method to the underlying pandas DataFrame.

Return type:: DataFrameGroupBy

leaflet(**kwargs)

Returns a Leaflet layer to be directly added to a Map.

The elements passed as kwargs as passed as is to the Marker constructor.

Return type:: MarkerCluster

merge(*args, **kwargs)

Applies the Pandas merge() method to the underlying pandas DataFrame and get the result back in the same structure.

Return type:: TypeVar(T, bound= DataFrameMixin)

plot(ax, s=10, **kwargs)

Plotting function. All arguments are passed to ax.scatter

Return type:: Artist

query(query_str, *args, **kwargs)

Applies the Pandas query() method to the underlying pandas DataFrame and get the result back in the same structure.

Return type:: Optional[TypeVar(T, bound= DataFrameMixin)]

rename(*args, **kwargs)

Applies the Pandas rename() method to the underlying pandas DataFrame and get the result back in the same structure.

Return type:: TypeVar(T, bound= DataFrameMixin)

replace(*args, **kwargs)

Applies the Pandas replace() method to the underlying pandas DataFrame and get the result back in the same structure.

Return type:: TypeVar(T, bound= DataFrameMixin)

reset_index(*args, **kwargs)

Applies the Pandas reset_index() method to the underlying pandas DataFrame and get the result back in the same structure.

Return type:: TypeVar(T, bound= DataFrameMixin)

sort_values(by, **kwargs)

Applies the Pandas sort_values() method to the underlying pandas DataFrame and get the result back in the same structure.

Return type:: TypeVar(T, bound= DataFrameMixin)

to_csv(filename, *args, **kwargs)

Exports to CSV format.

Options can be passed to pandas.DataFrame.to_csv() as args and kwargs arguments.

Return type:: None

to_excel(filename, *args, **kwargs)

Exports to Excel format.

Options can be passed to pandas.DataFrame.to_excel() as args and kwargs arguments.

Return type:: None

to_feather(filename, *args, **kwargs)

Exports to feather format.

Options can be passed to pandas.DataFrame.to_feather() as args and kwargs arguments.

Return type:: None

to_hdf(filename, *args, **kwargs)

Exports to HDF format.

Options can be passed to pandas.DataFrame.to_hdf() as args and kwargs arguments.

Return type:: None

to_json(filename, *args, **kwargs)

Exports to JSON format.

Options can be passed to pandas.DataFrame.to_json() as args and kwargs arguments.

Return type:: None

to_parquet(filename, *args, **kwargs)

Exports to parquet format.

Options can be passed to pandas.DataFrame.to_parquet() as args and kwargs arguments.

Return type:: None

to_pickle(filename, *args, **kwargs)

Exports to pickle format.

Options can be passed to pandas.DataFrame.to_pickle() as args and kwargs arguments.

Return type:: None