kedro.extras.datasets.plotly.PlotlyDataSet

class kedro.extras.datasets.plotly.PlotlyDataSet(filepath, plotly_args, load_args=None, save_args=None, version=None, credentials=None, fs_args=None)[source]

PlotlyDataSet generates a plot from a pandas DataFrame and saves it to a JSON file using an underlying filesystem (e.g.: local, S3, GCS). It loads the JSON into a plotly figure.

PlotlyDataSet is a convenience wrapper for plotly.JSONDataSet. It generates the JSON file directly from a pandas DataFrame through plotly_args.

Example usage for the YAML API:

bar_plot:
  type: plotly.PlotlyDataSet
  filepath: data/08_reporting/bar_plot.json
  plotly_args:
    type: bar
    fig:
      x: features
      y: importance
      orientation: h
    layout:
      xaxis_title: x
      yaxis_title: y
      title: Title

Example usage for the Python API:

from kedro.extras.datasets.plotly import PlotlyDataSet
import plotly.express as px
import pandas as pd

df_data = pd.DataFrame([[0, 1], [1, 0]], columns=('x1', 'x2'))

data_set = PlotlyDataSet(
    filepath='scatter_plot.json',
    plotly_args={
        'type': 'scatter',
        'fig': {'x': 'x1', 'y': 'x2'},
    }
)
data_set.save(df_data)
reloaded = data_set.load()
assert px.scatter(df_data, x='x1', y='x2') == reloaded

Attributes

DEFAULT_LOAD_ARGS

DEFAULT_SAVE_ARGS

Methods

exists()

Checks whether a data set's output already exists by calling the provided _exists() method.

from_config(name, config[, load_version, ...])

Create a data set instance using the configuration provided.

load()

Loads data by delegation to the provided load method.

release()

Release any cached data.

resolve_load_version()

Compute the version the dataset should be loaded with.

resolve_save_version()

Compute the version the dataset should be saved with.

save(data)

Saves data by delegation to the provided save method.
DEFAULT_LOAD_ARGS: Dict[str, Any] = {}
DEFAULT_SAVE_ARGS: Dict[str, Any] = {}
__init__(filepath, plotly_args, load_args=None, save_args=None, version=None, credentials=None, fs_args=None)[source]

Creates a new instance of PlotlyDataSet pointing to a concrete JSON file on a specific filesystem.

Parameters:

  • filepath (str) – Filepath in POSIX format to a JSON file prefixed with a protocol like s3://. If prefix is not provided file protocol (local filesystem) will be used. The prefix should be any protocol supported by fsspec. Note: http(s) doesn’t support versioning.

  • plotly_args (Dict[str, Any]) – Plotly configuration for generating a plotly figure from the dataframe. Keys are type (plotly express function, e.g. bar, line, scatter), fig (kwargs passed to the plotting function), theme (defaults to plotly), layout.

  • load_args (Optional[Dict[str, Any]]) – Plotly options for loading JSON files. Here you can find all available arguments: https://plotly.com/python-api-reference/generated/plotly.io.from_json.html#plotly.io.from_json All defaults are preserved.

  • save_args (Optional[Dict[str, Any]]) – Plotly options for saving JSON files. Here you can find all available arguments: https://plotly.com/python-api-reference/generated/plotly.io.write_json.html All defaults are preserved.

  • version (Optional[Version]) – If specified, should be an instance of kedro.io.core.Version. If its load attribute is None, the latest version will be loaded. If its save attribute is None, save version will be autogenerated.

  • credentials (Optional[Dict[str, Any]]) – Credentials required to get access to the underlying filesystem. E.g. for GCSFileSystem it should look like {‘token’: None}.

  • fs_args (Optional[Dict[str, Any]]) – Extra arguments to pass into underlying filesystem class constructor (e.g. {“project”: “my-project”} for GCSFileSystem), as well as to pass to the filesystem’s open method through nested keys open_args_load and open_args_save. Here you can find all available arguments for open: https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.open All defaults are preserved, except mode, which is set to w when saving.

exists()

Checks whether a data set’s output already exists by calling the provided _exists() method.

Return type:

bool

Returns:

Flag indicating whether the output already exists.

Raises:

DatasetError – when underlying exists method raises error.

classmethod from_config(name, config, load_version=None, save_version=None)

Create a data set instance using the configuration provided.

Parameters:

  • name – Data set name.

  • config – Data set config dictionary.

  • load_version – Version string to be used for load operation if the data set is versioned. Has no effect on the data set if versioning was not enabled.

  • save_version – Version string to be used for save operation if the data set is versioned. Has no effect on the data set if versioning was not enabled.

Returns:

An instance of an AbstractDataset subclass.

Raises:

DatasetError – When the function fails to create the data set from its config.

load()

Loads data by delegation to the provided load method.

Return type:

TypeVar(_DO)

Returns:

Data returned by the provided load method.

Raises:

DatasetError – When underlying load method raises error.

release()

Release any cached data.

Raises:

DatasetError – when underlying release method raises error.

Return type:

None

resolve_load_version()

Compute the version the dataset should be loaded with.

Return type:

str | None

resolve_save_version()

Compute the version the dataset should be saved with.

Return type:

str | None

save(data)

Saves data by delegation to the provided save method.

Parameters:

data (TypeVar(_DI)) – the value to be saved by provided save method.

Raises:

  • DatasetError – when underlying save method raises error.

  • FileNotFoundError – when save method got file instead of dir, on Windows.

  • NotADirectoryError – when save method got file instead of dir, on Unix.

Return type:

None