Input/Output

We primarily support two types of data ingestion:

• From CSV files.
• From PostGIS databases.

CSV File Import

trackintel.io.file.read_positionfixes_csv(*args, **kwargs)

Wraps the pandas read_csv function, extracts longitude and latitude and builds a geopandas GeoDataFrame. This also validates that the ingested data conforms to the trackintel understanding of positionfixes. See Model.

Returns:

GeoDataFrame

A GeoDataFrame containing the positionfixes.

PostGIS Import

trackintel.io.postgis.read_positionfixes_postgis(conn_string, table_name, *args, **kwargs)

Reads positionfixes from a PostGIS database.

Parameters:

conn_string : str

A connection string to connect to a database, e.g., postgresql://username:password@host:socket/database.

table_name : str

The table to read the positionfixes from.

Returns:

GeoDataFrame

A GeoDataFrame containing the positionfixes.

trackintel.io.postgis.write_positionfixes_postgis(positionfixes, conn_string, table_name)

Stores positionfixes to PostGIS. Usually, this is directly called on a positionfixes dataframe (see example below).

Attention! This replaces the table if it already exists!

Parameters:

positionfixes : GeoDataFrame

The positionfixes to store to the database.

conn_string : str

A connection string to connect to a database, e.g., postgresql://username:password@host:socket/database.

table_name : str

The name of the table to write to.

Examples

>>> df.as_positionfixes.to_postgis(conn_string, table_name)