偏离

import matplotlib.pyplot as plt
import numpy as np
import polars as pl
from plotnine import *

Diverging Bar

mtcars = pl.read_csv("data/mtcars.csv")
mtcars.head()

shape: (5, 13)

mpg	cyl	disp	hp	drat	wt	qsec	vs	am	gear	carb	fast	cars
f64	i64	f64	i64	f64	f64	f64	i64	i64	i64	i64	i64	str
4.582576	6	160.0	110	3.9	2.62	16.46	0	1	4	4	1	"Mazda RX4"
4.582576	6	160.0	110	3.9	2.875	17.02	0	1	4	4	1	"Mazda RX4 Wag"
4.774935	4	108.0	93	3.85	2.32	18.61	1	1	4	1	1	"Datsun 710"
4.626013	6	258.0	110	3.08	3.215	19.44	1	0	3	1	1	"Hornet 4 Drive"
4.32435	8	360.0	175	3.15	3.44	17.02	0	0	3	2	1	"Hornet Sportabout"

mtcars = mtcars.with_columns(
    mpg_z=(pl.col("mpg") - pl.col("mpg").mean()) / pl.col("mpg").std()
)
mtcars_sorted = (
    mtcars.with_columns(
        types=pl.col("mpg_z").map_batches(
            lambda x: np.where(x < 0, "red", "green"), return_dtype=pl.String
        )
    )
    .sort(by="mpg_z")
    .with_row_index()
)
mtcars_sorted.head()

shape: (5, 16)

index	mpg	cyl	disp	hp	drat	wt	qsec	vs	am	gear	carb	fast	cars	mpg_z	types
u32	f64	i64	f64	i64	f64	f64	f64	i64	i64	i64	i64	i64	str	f64	str
0	3.224903	8	472.0	205	2.93	5.25	17.98	0	0	3	4	0	"Cadillac Fleetwood"	-1.829979	"red"
1	3.224903	8	460.0	215	3.0	5.424	17.82	0	0	3	4	0	"Lincoln Continental"	-1.829979	"red"
2	3.646917	8	350.0	245	3.73	3.84	15.41	0	0	3	4	0	"Camaro Z28"	-1.191664	"red"
3	3.781534	8	360.0	245	3.21	3.57	15.84	0	0	3	4	0	"Duster 360"	-0.988049	"red"
4	3.834058	8	440.0	230	3.23	5.345	17.42	0	0	3	4	0	"Chrysler Imperial"	-0.908604	"red"

_, ax = plt.subplots(figsize=(10, 6))

bar = ax.barh(
    y=mtcars_sorted["index"],
    width=mtcars_sorted["mpg_z"],
    color=mtcars_sorted["types"],
    alpha=0.4,
    lw=5,
)

ax.bar_label(container=bar, fmt="%0.2g", label_type="edge", padding=3)

ax.set(
    xlabel="Mileage",
    ylabel="Model",
    yticks=mtcars_sorted["index"],
    yticklabels=mtcars_sorted["cars"],
    title="Diverging Bars of Car Mileage",
)
ax.tick_params(axis="both", labelsize="medium")
ax.grid(linestyle="--", alpha=0.5)

ggplot2 version

g = ggplot(mtcars_sorted, aes(x="cars", y="mpg_z", label="mpg_z"))

(
    g
    + geom_bar(aes(fill="types"), stat="identity", width=0.5)
    + scale_fill_manual(
        name="Mileage",
        labels=["Above Average", "Below Average"],
        values={"green": "#00ba38", "red": "#f8766d"},
    )
    + scale_x_discrete(limits=mtcars_sorted["cars"])
    + labs(title="Diverging Bars of Car Mileage", x="Model", y="Mileage")
    + theme(plot_title=element_text(hjust=0.5))
    + coord_flip()
)

Diverging Lollipop

_, ax = plt.subplots(figsize=(10, 6))

ax.scatter(
    mtcars_sorted["mpg_z"],
    mtcars_sorted["index"],
    color=mtcars_sorted["types"],
    s=200,
    alpha=0.6,
)

ax.barh(
    y=mtcars_sorted["index"],
    width=mtcars_sorted["mpg_z"],
    color=mtcars_sorted["types"],
    alpha=0.4,
    height=0.1,
)

ax.annotate(
    "Mercedes Models",
    xy=(0.0, 11.0),
    xytext=(1.0, 11),
    xycoords="data",
    fontsize="medium",
    ha="center",
    va="center",
    color="white",
    bbox={"boxstyle": "square", "fc": "firebrick"},
    arrowprops={
        "arrowstyle": "-[, widthB=2.0, lengthB=1.5",
        "lw": 2.0,
        "color": "steelblue",
    },
)

ax.set(
    xlabel="Mileage",
    ylabel="Model",
    yticks=mtcars.with_row_index()["index"],
    yticklabels=mtcars["cars"],
    title="Diverging Bars of Car Mileage",
)
ax.tick_params(axis="both", labelsize="medium")
ax.grid(linestyle="--", alpha=0.5)

ggplot2 version

(
    g
    + geom_point(aes(fill="types"), stat="identity", size=8)
    + scale_fill_manual(
        name="Mileage",
        labels=["Above Average", "Below Average"],
        values={"green": "#00ba38", "red": "#f8766d"},
    )
    + geom_segment(aes(y=0, x="cars", yend="mpg_z", xend="cars", color="types"))
    + scale_color_manual(
        name="Mileage",
        labels=["Above Average", "Below Average"],
        values={"green": "#00ba38", "red": "#f8766d"},
    )
    + scale_x_discrete(limits=mtcars_sorted["cars"])
    + labs(
        title="Diverging Lollipop Chart",
        subtitle="Normalized mileage from 'mtcars': Lollipop",
        x="Model",
        y="Mileage",
    )
    + ylim(-2.5, 2.5)
    + coord_flip()
)

Diverging Dot

_, ax = plt.subplots(figsize=(10, 6))

scat = ax.scatter(
    mtcars_sorted["mpg_z"],
    mtcars_sorted["index"],
    s=450,
    alpha=0.6,
    color=mtcars_sorted["types"],
)

for x, y, text in zip(
    mtcars_sorted["mpg_z"], mtcars_sorted["index"], mtcars_sorted["mpg_z"]
):
    ax.text(
        x,
        y,
        round(text, 1),
        horizontalalignment="center",
        verticalalignment="center",
        fontdict={"color": "white"},
    )

ax.spines[["top", "right"]].set_visible(False)
ax.set(
    xlabel="Mileage",
    ylabel="Model",
    yticks=mtcars_sorted["index"],
    yticklabels=mtcars_sorted["cars"],
    title="Diverging Dotplot of Car Mileage",
)
ax.tick_params(axis="both", labelsize="medium")
ax.grid(linestyle="--", alpha=0.5)

(
    g
    + geom_point(aes(fill="types"), stat="identity", size=8)
    + scale_fill_manual(
        name="Mileage",
        labels=["Above Average", "Below Average"],
        values={"green": "#00ba38", "red": "#f8766d"},
    )
    + geom_text(color="white", size=6, format_string="{:.2f}")
    + labs(title="Diverging Dotplot of Car Mileage", x="Model", y="Mileage")
    + theme(plot_title=element_text(hjust=0.5))
    + scale_x_discrete(limits=mtcars_sorted["cars"])
    + ylim(-2.5, 2.5)
    + coord_flip()
)