添加表格

import matplotlib.pyplot as plt
# 解决plt中文显示问题
plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False

x = ('A', 'B', 'C', 'D', 'E')
y = [1, 2, 3, 4, 5]
y2 = [2, 4, 6, 8, 10]
plt.bar(x, y)
plt.xticks([])  # 去x坐标刻度
plt.title('结果')


# 表格
columns = x
rows = ['美', '丽']
d = np.array([ y, y2])
table = plt.table(cellText=d,
                  rowLabels=rows,
                  colLabels=columns,
                  cellLoc='center',
                  loc="bottom",
                  bbox=[0.02, -0.25, 0.96, 0.24])
# 调整表格的大小
table.auto_set_font_size(False)
table.set_fontsize(12)

plt.show()

import matplotlib.pyplot as plt
import numpy as np

data = [[ 66386, 174296,  75131, 577908,  32015],
        [ 58230, 381139,  78045,  99308, 160454],
        [ 89135,  80552, 152558, 497981, 603535],
        [ 78415,  81858, 150656, 193263,  69638],
        [139361, 331509, 343164, 781380,  52269]]

columns = ('Freeze', 'Wind', 'Flood', 'Quake', 'Hail')
rows = ['%d year' % x for x in (100, 50, 20, 10, 5)]

values = np.arange(0, 2500, 500)
value_increment = 1000

# Get some pastel shades for the colors
colors = plt.cm.BuPu(np.linspace(0, 0.5, len(rows)))
n_rows = len(data)

index = np.arange(len(columns)) + 0.3
bar_width = 0.4

# Initialize the vertical-offset for the stacked bar chart.
y_offset = np.zeros(len(columns))

# Plot bars and create text labels for the table
cell_text = []
for row in range(n_rows):
    plt.bar(index, data[row], bar_width, bottom=y_offset, color=colors[row])
    y_offset = y_offset + data[row]
    cell_text.append(['%1.1f' % (x / 1000.0) for x in y_offset])
# Reverse colors and text labels to display the last value at the top.
colors = colors[::-1]
cell_text.reverse()

# Add a table at the bottom of the axes
the_table = plt.table(cellText=cell_text,
                      rowLabels=rows,
                      rowColours=colors,
                      colLabels=columns,
                      loc='bottom')

# Adjust layout to make room for the table:
plt.subplots_adjust(left=0.2, bottom=0.2)

plt.ylabel(f"Loss in ${value_increment}'s")
plt.yticks(values * value_increment, ['%d' % val for val in values])
plt.xticks([])
plt.title('Loss by Disaster')

plt.show()