Datasets API Reference¶

Built-in datasets for ggplotly, mirroring those available in ggplot2.

Loading Datasets¶

`ggplotly.datasets.data(name=None)` ¶

List available datasets or load a dataset by name.

Parameters:

Name	Type	Description	Default
`name`	`str \| None`	The name of the dataset to load (without .csv extension). If None, returns list of available datasets. Special case: 'us_flights' returns an igraph Graph object.	`None`

Returns:

Name	Type	Description
		If name is None: list of available dataset names.
		If name is 'us_flights': igraph.Graph object.
`Otherwise`		pandas.DataFrame containing the dataset.

Raises:

Type	Description
`ValueError`	If the dataset name is not found.

Examples:

>>> from ggplotly.datasets import data
>>> data()  # Returns list of available datasets
['diamonds', 'economics', 'iris', 'mpg', 'us_flights', ...]
>>> df = data('mpg')  # Load a specific dataset
>>> g = data('us_flights')  # Load as igraph Graph

Map Data¶

`ggplotly.map_data.map_data(map_name='state')` ¶

Get map region data for use with geom_map.

Similar to ggplot2's map_data() function, but returns region identifiers that work with Plotly's built-in geographic support.

Parameters:

Name	Type	Description	Default
`map_name`	`str`	The map to retrieve. Options: - 'state': US state abbreviations - 'usa': Alias for 'state' - 'world': ISO-3 country codes - 'county': US county FIPS codes (placeholder)	`'state'`

Returns:

Type	Description
	pandas.DataFrame: A dataframe with region identifiers

Examples:

>>> from ggplotly import map_data
>>> states = map_data('state')
>>> countries = map_data('world')

Available Datasets¶

The following datasets are included with ggplotly:

Dataset	Description
`mpg`	Fuel economy data for 234 cars (1999-2008)
`diamonds`	Prices and attributes of ~54,000 diamonds
`iris`	Classic Fisher's iris flower measurements
`mtcars`	Motor Trend car road tests (1974)
`economics`	US economic time series data
`economics_long`	Long format US economic time series
`midwest`	Midwest demographics data
`txhousing`	Texas housing market data
`faithfuld`	Old Faithful geyser eruption data (2D density)
`msleep`	Mammalian sleep data
`presidential`	US presidential terms
`seals`	Location data for seal movements
`commodity_prices`	Historical commodity price data
`luv_colours`	Color data in LUV color space
`us_flights`	US flight network (returns igraph Graph)

Example Usage¶

from ggplotly import data

# List all available datasets
data()

# Load a specific dataset
mpg = data('mpg')
diamonds = data('diamonds')

# Load network data (requires igraph)
flights = data('us_flights')