具有双标题的Matplotlib表 [英] Matplotlib table with double headers

问题描述

可以使matplotlib表具有这样的双头" (注意虚线)

Hi is possible to make a matplotlib table to have a "double header" like this (mind the dashed line)

          ----------------------------------------
          |  Feb Total     |     YTD Total        |
          ----------------------------------------
          |  2014|2015     | 2014/2015| 2015/2016 |
--------------------------------------------------
|VVI-ID   | 12  | 20       | 188      | 169       |
--------------------------------------------------
|TDI-ID   | 34  | 45       | 556      | 456       |

推荐答案

您可以通过使用没有数据的其他表作为标题来做到这一点.也就是说，您创建了空表，其表的列标签将成为表的标题.让我们考虑此演示示例.首先，添加表header_0和header_1.第二，更正标题和表的参数bbox以正确放置所有表.由于这些表是重叠的，因此包含数据的表应该是最后一个.

You can do this by using another tables with no data as headers. That is, you create empty tables, whose column labels will be the headers for your table. Let's consider this demo example. At first, add tables header_0 and header_1. At second, correct headers' and table's argument bbox to position all tables correctly. Since the tables are overlapped, the table with data should be the last one.

import numpy as np
import matplotlib.pyplot as plt


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.array([0.0] * 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 headers and a table at the bottom of the axes
header_0 = plt.table(cellText=[['']*2],
                     colLabels=['Extra header 1', 'Extra header 2'],
                     loc='bottom',
                     bbox=[0, -0.1, 0.8, 0.1]
                     )

header_1 = plt.table(cellText=[['']],
                     colLabels=['Just Hail'],
                     loc='bottom',
                     bbox=[0.8, -0.1, 0.2, 0.1]
                     )

the_table = plt.table(cellText=cell_text,
                      rowLabels=rows,
                      rowColours=colors,
                      colLabels=columns,
                      loc='bottom',
                      bbox=[0, -0.35, 1.0, 0.3]
                      )

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

plt.ylabel("Loss in ${0}'s".format(value_increment))
plt.yticks(values * value_increment, ['%d' % val for val in values])
plt.xticks([])
plt.title('Loss by Disaster')

plt.show()

如果额外的标头是对称的或组合了相同数量的正常"标头，则您需要做的就是添加一个额外的标头表并像这样纠正数据表的bbox(与删除列的示例相同):

If extra header is symmetric or combine equal quantity of "normal" header, all you need to do is to add an extra header table and correct bbox of data table like this (the same example with deleted column):

header = plt.table(cellText=[['']*2],
                      colLabels=['Extra header 1', 'Extra header 2'],
                      loc='bottom'
                      )

the_table = plt.table(cellText=cell_text,
                      rowLabels=rows,
                      rowColours=colors,
                      colLabels=columns,
                      loc='bottom',
                      bbox=[0, -0.35, 1.0, 0.3]
                      )

这篇关于具有双标题的Matplotlib表的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！