plotly.data package

Built-in datasets for demonstration, educational and test purposes.

plotly.data.carshare()

Each row represents the availability of car-sharing services near the centroid of a zone in Montreal over a month-long period.

Returns

['centroid_lat', 'centroid_lon', 'car_hours', 'peak_hour'].

Return type

A pandas.DataFrame with 249 rows and the following columns

plotly.data.election()

Each row represents voting results for an electoral district in the 2013 Montreal mayoral election.

Returns

['district', 'Coderre', 'Bergeron', 'Joly', 'total', 'winner', 'result', 'district_id'].

Return type

A pandas.DataFrame with 58 rows and the following columns

plotly.data.election_geojson()

Each feature represents an electoral district in the 2013 Montreal mayoral election.

Returns

A GeoJSON-formatted dict with 58 polygon or multi-polygon features whose id is an electoral district numerical ID and whose district property is the ID and district name.

plotly.data.experiment(indexed=False)

Each row in this wide dataset represents the results of 100 simulated participants on three hypothetical experiments, along with their gender and control/treatment group.

Returns

['experiment_1', 'experiment_2', 'experiment_3', 'gender', 'group']. If indexed is True, the data frame index is named “participant”

Return type

A pandas.DataFrame with 100 rows and the following columns

plotly.data.gapminder(datetimes=False, centroids=False, year=None, pretty_names=False)

Each row represents a country on a given year.

https://www.gapminder.org/data/

Returns

['country', 'continent', 'year', 'lifeExp', 'pop', 'gdpPercap', 'iso_alpha', 'iso_num']. If datetimes is True, the ‘year’ column will be a datetime column If centroids is True, two new columns are added: [‘centroid_lat’, ‘centroid_lon’] If year is an integer, the dataset will be filtered for that year

Return type

A pandas.DataFrame with 1704 rows and the following columns

plotly.data.iris()

Each row represents a flower.

https://en.wikipedia.org/wiki/Iris_flower_data_set

Returns

['sepal_length', 'sepal_width', 'petal_length', 'petal_width', 'species', 'species_id'].

Return type

A pandas.DataFrame with 150 rows and the following columns

plotly.data.medals_long(indexed=False)

This dataset represents the medal table for Olympic Short Track Speed Skating for the top three nations as of 2020.

Returns

['nation', 'medal', 'count']. If indexed is True, the ‘nation’ column is used as the index.

Return type

A pandas.DataFrame with 9 rows and the following columns

plotly.data.medals_wide(indexed=False)

This dataset represents the medal table for Olympic Short Track Speed Skating for the top three nations as of 2020.

Returns

['nation', 'gold', 'silver', 'bronze']. If indexed is True, the ‘nation’ column is used as the index and the column index is named ‘medal’

Return type

A pandas.DataFrame with 3 rows and the following columns

plotly.data.stocks(indexed=False, datetimes=False)

Each row in this wide dataset represents closing prices from 6 tech stocks in 2018/2019.

Returns

['date', 'GOOG', 'AAPL', 'AMZN', 'FB', 'NFLX', 'MSFT']. If indexed is True, the ‘date’ column is used as the index and the column index If datetimes is True, the ‘date’ column will be a datetime column is named ‘company’

Return type

A pandas.DataFrame with 100 rows and the following columns

plotly.data.tips(pretty_names=False)

Each row represents a restaurant bill.

https://vincentarelbundock.github.io/Rdatasets/doc/reshape2/tips.html

Returns

['total_bill', 'tip', 'sex', 'smoker', 'day', 'time', 'size'].

Return type

A pandas.DataFrame with 244 rows and the following columns

plotly.data.wind()

Each row represents a level of wind intensity in a cardinal direction, and its frequency.

Returns

['direction', 'strength', 'frequency'].

Return type

A pandas.DataFrame with 128 rows and the following columns