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python - 向多水平条形图添加垂直线

问题描述

我正在生成一个多条形图作为水平条形图，我现在需要做的是在每个 y 的特定位置（基于 x 轴值）的每个水平条中注释（基本上创建一条垂直线） -axis，其中 y 轴是分类（名称），x 轴是数字（整数）s。

我看过axis.vlines但无法正常工作。

import seaborn as sns
import matplotlib.pyplot as plt
crashes = sns.load_dataset("car_crashes").sort_values("total", ascending=False)
crashes['max_range'] = crashes['total'] * 0.85
sns.set_color_codes("muted")
sns.set(style="whitegrid")
sns.barplot(x="total", y="abbrev", data=crashes, label="", color="r")
sns.barplot(x="max_range", y="abbrev", data=crashes, label="", color="y")
sns.barplot(x="alcohol", y="abbrev", data=crashes,label="normal range", color="g")

#dummy data for the "vertical lines" i want to plot
crashes['actual'] = crashes['alcohol'] * 1.85

上面的代码创建了一个像这样的图：

https://seaborn.pydata.org/examples/horizo​​ntal_barplot.html

现在我基本上想从底层数据框的另一列中的每一行添加一条垂直线（因此对于图中的每个条）。

标签： pythonpandasseaborn

解决方案

axis.vlines足以胜任这项工作。为此，我首先提取条形图标签的 y 点。比我为这些点制作一个 x 值的字典。比我用来axis.vlines在条上画一条红线。

import seaborn as sns
import matplotlib.pyplot as plt

crashes = sns.load_dataset("car_crashes").sort_values("total", ascending=False)
crashes['max_range'] = crashes['total'] * 0.85
sns.set_color_codes("muted")
sns.set(style="whitegrid")
# Store the returned axes in a variable
ax = sns.barplot(x="total", y="abbrev", data=crashes, label="", color="r")
ax = sns.barplot(x="max_range", y="abbrev", data=crashes, label="", color="y")
ax = sns.barplot(x="alcohol", y="abbrev", data=crashes,label="normal range", color="g")

#dummy data for the "vertical lines" i want to plot
crashes['actual'] = crashes['alcohol'] * 1.85


#### MY ADDITIONS ####

# Form dictionary of bar chart keys (i.e. Y axis data, here it is "abbrev") to
# corresponding y and x points
y_labs = list(ax.get_yticklabels())
y_tic_pos = list(ax.get_yticks())
y_tick_vals = {}
for i in range(len(y_tic_pos)):
    y_tick_vals[y_labs[i].get_text()] = y_tic_pos[i]
x_points = {lab:crashes[crashes["abbrev"] == lab]["actual"].values[0] for lab in y_tick_vals}

# for each of the relevant y axis, draw a vertical line
for key in y_tick_vals:
    c_y = y_tick_vals[key]
    c_x = x_points[key]
    # I just did some trial and error to find out that each bar is 0.5 wide;
    # this may not be the case for other plots.
    c_ymin = c_y - 0.25
    c_ymax = c_y + 0.25

    ax.vlines(c_x, c_ymin, c_ymax, colors="r")

plt.show()

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