python - Matplotlib 表中的双 header

Question

我需要在 matplotlib 中绘制一个表格。问题是有些列有一级标题，有些列有双层标题。

这是我需要的:

这是一级标题的简单示例:

df = pd.DataFrame()
df['Animal'] = ['Cow', 'Bear']
df['Weight'] = [250, 450]
df['Favorite'] = ['Grass', 'Honey']
df['Least Favorite'] = ['Meat', 'Leaves']
df

fig = plt.figure(figsize=(9,2))
ax=plt.subplot(111)
ax.axis('off') 
table = ax.table(cellText=df.values, colColours=['grey']*df.shape[1], bbox=[0, 0, 1, 1], colLabels=df.columns)
plt.savefig('Table.jpg')

最后一段代码生成下一张图片:

我需要做哪些更改才能拥有我需要的表格？

Answer 1

单元格合并解决方案

您可以合并 ax.table 生成的单元格，这是 Excel 电子表格中的单元格合并功能。这允许一个完全自动化的解决方案，您不需要摆弄任何坐标(保存要合并的单元格的索引):

import matplotlib.pyplot as plt
import pandas as pd

df = pd.DataFrame()
df['Animal'] = ['Cow', 'Bear']
df['Weight'] = [250, 450]
df['Favorite'] = ['Grass', 'Honey']
df['Least Favorite'] = ['Meat', 'Leaves']

fig = plt.figure(figsize=(9,2))
ax=fig.gca()
ax.axis('off')
r,c = df.shape

# ensure consistent background color
ax.table(cellColours=[['lightgray']] + [['none']], bbox=[0,0,1,1])

# plot the real table
table = ax.table(cellText=np.vstack([['', '', 'Food', ''], df.columns, df.values]), 
                 cellColours=[['none']*c]*(2 + r), bbox=[0, 0, 1, 1])

# need to draw here so the text positions are calculated
fig.canvas.draw()

# do the 3 cell merges needed
mergecells(table, (1,0), (0,0))
mergecells(table, (1,1), (0,1))
mergecells(table, (0,2), (0,3))

输出:

下面是上面使用的 mergecells 函数的代码:

import matplotlib as mpl

def mergecells(table, ix0, ix1):
    ix0,ix1 = np.asarray(ix0), np.asarray(ix1)
    d = ix1 - ix0
    if not (0 in d and 1 in np.abs(d)):
        raise ValueError("ix0 and ix1 should be the indices of adjacent cells. ix0: %s, ix1: %s" % (ix0, ix1))

    if d[0]==-1:
        edges = ('BRL', 'TRL')
    elif d[0]==1:
        edges = ('TRL', 'BRL')
    elif d[1]==-1:
        edges = ('BTR', 'BTL')
    else:
        edges = ('BTL', 'BTR')

    # hide the merged edges
    for ix,e in zip((ix0, ix1), edges):
        table[ix[0], ix[1]].visible_edges = e

    txts = [table[ix[0], ix[1]].get_text() for ix in (ix0, ix1)]
    tpos = [np.array(t.get_position()) for t in txts]

    # center the text of the 0th cell between the two merged cells
    trans = (tpos[1] - tpos[0])/2
    if trans[0] > 0 and txts[0].get_ha() == 'right':
        # reduce the transform distance in order to center the text
        trans[0] /= 2
    elif trans[0] < 0 and txts[0].get_ha() == 'right':
        # increase the transform distance...
        trans[0] *= 2

    txts[0].set_transform(mpl.transforms.Affine2D().translate(*trans))

    # hide the text in the 1st cell
    txts[1].set_visible(False)