# tutorial
import matplotlib.pyplot as plt
import pandas as pd

color_dict = {
    (2022, "Norway"): "#9194A3",
    (2004, "Norway"): "#2B314D",
    (2022, "Denmark"): "#E2AFA5",
    (2004, "Denmark"): "#A54836",
    (2022, "Sweden"): "#C4D6F8",
    (2004, "Sweden"): "#5375D4",
}

xy_ticklabel_color, xlabel_color, grand_totals_color, grid_color, datalabels_color = (
    "#7E8293",
    "#7C8091",
    "#101628",
    "#B5B7C1",
    "#2B314D",
)

data = {
    "year": [2004, 2022, 2004, 2022, 2004, 2022],
    "countries": ["Denmark", "Denmark", "Norway", "Norway", "Sweden", "Sweden"],
    "sites": [4, 10, 5, 8, 13, 15],
}
df = pd.DataFrame(data)
df["year_lbl"] = "'" + df["year"].astype(str).str[-2:].astype(str)
df["sub_total"] = df.groupby("countries")["sites"].transform("sum")

# custom sort
sort_order_dict = {"Denmark": 1, "Sweden": 3, "Norway": 2, 2004: 5, 2022: 4}
df = df.sort_values(
    by=[
        "year",
        "countries",
    ],
    key=lambda x: x.map(sort_order_dict),
)
# Add the color based on the color dictionary
df["color"] = df.set_index(["year", "countries"]).index.map(color_dict.get)

df

fig, ax = plt.subplots(figsize=(5, 5), facecolor="#FFFFFF")
fig.tight_layout(pad=3.0)

for year, group in groups:
    ax.bar(
        group.countries, 
        group.sites, 
        width=0.5
        )

for bar, row in zip(ax.patches, df.itertuples()):

    bar.set_facecolor(row.color)
    ax.text(
        bar.get_x() + bar.get_width() / 2,
        bar.get_height() - 0.2 + bar.get_y(),  # height
        row.year_lbl,
        ha="center",
        va="top",
        color="w",
        weight="light",
    )

fig

ax.axhline(
    y = 0, 
    xmin = 0, 
    xmax = 1, 
    color = xy_ticklabel_color
    )

common_tick_params = {
    "which": "major",
    "labelsize": 11,
    "colors": xy_ticklabel_color,
    "pad": 15
}

# hide ticks
ax.tick_params(axis = "x", length = 0, **common_tick_params)

ax.tick_params(axis = "y", **common_tick_params)


ax.set_ylim(0, 16)
ax.set_axisbelow(True)  # set the grid lines in the BACK
ax.set_frame_on(False)

fig