GnnForPrivacyScan/data/purposeSplit/visualize/visualize_3_1.py

def scatterplot(
    df: pd.DataFrame,
    col: str,
    color: str = None,
    hover_name: str = None,
    hover_data: list = None,
    title="",
    return_figure=False,
):
    """
    Show scatterplot of DataFrame column using python plotly scatter.

    Plot the values in column col. For example, if every cell in df[col]
    is a list of three values (e.g. from doing PCA with 3 components),
    a 3D-Plot is created and every cell entry [x, y, z] is visualized
    as the point (x, y, z).

    Parameters
    ----------
    df: DataFrame with a column to be visualized.

    col: str
        The name of the column of the DataFrame to use for x and y (and z)
        axis.

    color: str, optional, default=None
        Name of the column to use for coloring (rows with same value get same
        color).

    hover_name: str, optional, default=None
        Name of the column to supply title of hover data when hovering over a
        point.

    hover_data: List[str], optional, default=[]
        List of column names to supply data when hovering over a point.

    title: str, default to "".
        Title of the plot.

    return_figure: bool, optional, default=False
        Function returns the figure instead of showing it if set to True.

    Examples
    --------
    >>> import texthero as hero
    >>> import pandas as pd
    >>> df = pd.DataFrame(["Football, Sports, Soccer",
    ...                    "music, violin, orchestra", "football, fun, sports",
    ...                    "music, fun, guitar"], columns=["texts"])
    >>> df["texts"] = hero.clean(df["texts"]).pipe(hero.tokenize)
    >>> df["pca"] = (
    ...             hero.tfidf(df["texts"])
    ...                 .pipe(hero.pca, n_components=3)
    ... )
    >>> df["topics"] = (
    ...                hero.tfidf(df["texts"])
    ...                    .pipe(hero.kmeans, n_clusters=2)
    ... )
    >>> hero.scatterplot(df, col="pca", color="topics",
    ...                  hover_data=["texts"]) # doctest: +SKIP
    """

    plot_values = np.stack(df[col], axis=1)
    dimension = len(plot_values)

    if dimension < 2 or dimension > 3:
        raise ValueError(
            "The column you want to visualize has dimension < 2 or dimension > 3."
            " The function can only visualize 2- and 3-dimensional data."
        )

    if dimension == 2:
        x, y = plot_values[0], plot_values[1]

        fig = px.scatter(
            df,
            x=x,
            y=y,
            color=color,
            hover_data=hover_data,
            title=title,
            hover_name=hover_name,
        )

    else:
        x, y, z = plot_values[0], plot_values[1], plot_values[2]

        fig = px.scatter_3d(
            df,
            x=x,
            y=y,
            z=z,
            color=color,
            hover_data=hover_data,
            title=title,
            hover_name=hover_name,
        )

    if return_figure:
        return fig
    else:
        fig.show()