mtdata.datasets package

Submodules

mtdata.datasets.air_quality module

class mtdata.datasets.air_quality.AirQuality

Bases: Dataset

Air quality data for Montana.

property dedup_facets: Iterable[str]

Fields used to determine which rows should be compared for de-duplication.

For example, if the data are sensor readings for various locations, the field that indicates the location would be listed here. That way, we don’t drop a new reading from a different location just because it occurred at the same time as a reading from a different location.

Uses the transformed version of the field names.

property dedup_fields: Iterable[str]

Fields used to compare rows for de-duplication. This is likely to be some kind of timestamp, but that depends on the kind of data.

For example, if the data are sensor readings and each row is timestamped based on when the reading occurred, then that field will be listed here because two or more fetches might retrieve the same reading instance.

Uses the transformed version of the field names.

fetch() FetchResult

Fetch new data from the source (generally the web).

static name() str

The dataset name, which is used in the UI and for things like file and table names.

property transformer: Transformer

The transformer to be applied to each row that is fetched from the data source before it is stored.

mtdata.datasets.missoula_911 module

class mtdata.datasets.missoula_911.Missoula911

Bases: Dataset

Record of 911 events for Missoula city and county in Montana.

property dedup_facets: Iterable[str]

Fields used to determine which rows should be compared for de-duplication.

For example, if the data are sensor readings for various locations, the field that indicates the location would be listed here. That way, we don’t drop a new reading from a different location just because it occurred at the same time as a reading from a different location.

Uses the transformed version of the field names.

property dedup_fields: Iterable[str]

Fields used to compare rows for de-duplication. This is likely to be some kind of timestamp, but that depends on the kind of data.

For example, if the data are sensor readings and each row is timestamped based on when the reading occurred, then that field will be listed here because two or more fetches might retrieve the same reading instance.

Uses the transformed version of the field names.

fetch() FetchResult

Fetch new data from the source (generally the web).

static name() str

The dataset name, which is used in the UI and for things like file and table names.

property transformer: Transformer

The transformer to be applied to each row that is fetched from the data source before it is stored.

mtdata.datasets.mt_covid_counts module

class mtdata.datasets.mt_covid_counts.CovidCounts

Bases: Dataset

Covid-19 case data for Montana.

Source front-end display: https://www.arcgis.com/apps/MapSeries/index.html?appid=7c34f3412536439491adcc2103421d4b

property dedup_facets: Iterable[str]

Fields used to determine which rows should be compared for de-duplication.

For example, if the data are sensor readings for various locations, the field that indicates the location would be listed here. That way, we don’t drop a new reading from a different location just because it occurred at the same time as a reading from a different location.

Uses the transformed version of the field names.

property dedup_fields: Iterable[str]

Fields used to compare rows for de-duplication. This is likely to be some kind of timestamp, but that depends on the kind of data.

For example, if the data are sensor readings and each row is timestamped based on when the reading occurred, then that field will be listed here because two or more fetches might retrieve the same reading instance.

Uses the transformed version of the field names.

fetch() FetchResult

Fetch new data from the source (generally the web).

static name() str

The dataset name, which is used in the UI and for things like file and table names.

property transformer: Transformer

The transformer to be applied to each row that is fetched from the data source before it is stored.

Module contents

datasets - a collection of curated, built-in datasets