from bokeh import models as bm, plotting as bp
from bokeh.transform import factor_cmap
from pandas import DataFrame

from data_utils import get_categorical_stats

gender_colormap = factor_cmap("Sukupuoli", ["#4834d4", "#eb4d4b"], ["mies", "nainen"])


def get_df_hover_tool(df: DataFrame):
    return bm.HoverTool(tooltips=[(c, f"@{{{c}}}") for c in df.columns])


def set_yaxis_cash(plot):
    plot.yaxis.axis_label = "Vuositulot"
    plot.yaxis[0].formatter = bm.NumeralTickFormatter(format="€0")


def get_categorical_stats_plot(df, *, category):
    df = get_categorical_stats(df, category, "Vuositulot")
    df.reset_index(inplace=True)
    df[category] = df[category].astype("category")
    plot = bp.figure(
        title=f"{category}/tulot", x_range=list(df[category].cat.categories)
    )
    set_yaxis_cash(plot)
    plot.vbar(df[category], 0.4, df["max"], df["min"], color="#a4b0be")
    plot.line(
        df[category], df["median"], legend_label="median", color="#1289A7", line_width=4
    )
    plot.line(
        df[category], df["mean"], legend_label="mean", color="#B53471", line_width=4
    )
    return plot