这里有一个方法来做到这一点。

import matplotlib.pyplot as plt
import pandas as pd
import numpy as np

df = pd.read_excel("path_to_data")

labels = df['ORDER'].unique()
aa_values = df.loc[df['TYPE'] == 'AA']['CURRENT_PRICE']
bb_values = df.loc[df['TYPE'] == 'BB']['CURRENT_PRICE']

x = np.arange(len(labels))  # the label locations
width = 0.35  # the width of the bars

fig, ax = plt.subplots()
rects1 = ax.bar(x - width/2, aa_values, width, label='AA')
rects2 = ax.bar(x + width/2, bb_values, width, label='BB')

# Add min_max lines
for label, x_ in zip(labels, x):
    # Add for AA
    aa_min, aa_max = df.loc[(df.ORDER == label) & (df.TYPE == 'AA')][['MIN_PRICE', 'MAX_PRICE']].values[0]
    bb_min, bb_max = df.loc[(df.ORDER == label) & (df.TYPE == 'BB')][['MIN_PRICE', 'MAX_PRICE']].values[0]

    ax.vlines(x_ - width / 2, aa_min, aa_max, color="black", lw=3)
    ax.vlines(x_ + width / 2, bb_min, bb_max, color="black", lw=3)

# Add some text for labels, title and custom x-axis tick labels, etc.
ax.set_ylabel('Price')
ax.set_xticks(x)
ax.set_xticklabels(labels)
ax.legend()

ax.bar_label(rects1, padding=3)
ax.bar_label(rects2, padding=3)

fig.tight_layout()