如何用Matplotlib为表格添加基于数值的背景渐变着色？

我需要将DataFrame导出为带单元格数值背景着色的图片，已经通过dataframe_image实现了该效果，现在要基于已有的Matplotlib表格渲染代码，实现同样的渐变背景着色功能。现有代码如下：

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

df = pd.DataFrame({'Name': ['One','Two','Three','Four', 'Five', 'Six', 'Seven', 'Eight', 'Nine', 'Ten','Eleven'],
                         '1Param': [255,191,1200,130,474,22,1203,1618,959,45,6097],
                         '2Param': [21,27,173,16,43,0,181,151,107,7,726],
                         '3Param': [2022,1794,9045,1054,3642,152,8431,12411,6630,325,45506],
                         '4Param': [470,486,2230,252,1092,18,2008,2748,1364,86,10754],
                             })
    

def render_mpl_table(data, col_width=3.0, row_height=0.625, font_size=14,
                     header_color='#40466e', row_colors=['#f1f1f2', 'w'], edge_color='w',
                     bbox=[0, 0, 1, 1], header_columns=0,
                     ax=None, **kwargs):
    if ax is None:
        size = (np.array(data.shape[::-1]) + np.array([0, 1])) * np.array([col_width, row_height])
        fig, ax = plt.subplots(figsize=size)
        ax.axis('off')

    mpl_table = ax.table(cellText=data.values, bbox=bbox, colLabels=data.columns, **kwargs)
    
    mpl_table.auto_set_font_size(False)
    mpl_table.set_fontsize(font_size)
    mpl_table.auto_set_column_width(col=list(range(len(data.columns))))  
    
    for k, cell in six.iteritems(mpl_table._cells):
        cell.set_edgecolor(edge_color)
        if k[0] == 0 or k[1] < header_columns:
            cell.set_text_props(weight='bold', color='w')
            cell.set_facecolor(header_color)
        # else:
        #     cell.set_facecolor(row_colors[k[0]%len(row_colors)])      

    return ax

render_mpl_table(df, header_columns=0)
plt.show()

实现方案 #

要实现基于数值的渐变背景色，需借助Matplotlib的颜色映射和归一化工具，将单元格数值映射为对应颜色。具体修改如下：

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import six
from matplotlib import cm
from matplotlib.colors import Normalize

df = pd.DataFrame({'Name': ['One','Two','Three','Four', 'Five', 'Six', 'Seven', 'Eight', 'Nine', 'Ten','Eleven'],
                         '1Param': [255,191,1200,130,474,22,1203,1618,959,45,6097],
                         '2Param': [21,27,173,16,43,0,181,151,107,7,726],
                         '3Param': [2022,1794,9045,1054,3642,152,8431,12411,6630,325,45506],
                         '4Param': [470,486,2230,252,1092,18,2008,2748,1364,86,10754],
                             })
    

def render_mpl_table(data, col_width=3.0, row_height=0.625, font_size=14,
                     header_color='#40466e', cmap='Blues', edge_color='w',
                     bbox=[0, 0, 1, 1], header_columns=0,
                     ax=None, **kwargs):
    if ax is None:
        size = (np.array(data.shape[::-1]) + np.array([0, 1])) * np.array([col_width, row_height])
        fig, ax = plt.subplots(figsize=size)
        ax.axis('off')

    mpl_table = ax.table(cellText=data.values, bbox=bbox, colLabels=data.columns, **kwargs)
    
    mpl_table.auto_set_font_size(False)
    mpl_table.set_fontsize(font_size)
    mpl_table.auto_set_column_width(col=list(range(len(data.columns))))  

    # 为每个数值列创建归一化规则
    norm_dict = {}
    for col_idx in range(1, data.shape[1]):  # 跳过Name列（第0列）
        col_data = data.iloc[:, col_idx].values
        norm = Normalize(vmin=col_data.min(), vmax=col_data.max())
        norm_dict[col_idx] = norm

    color_map = cm.get_cmap(cmap)
    
    for k, cell in six.iteritems(mpl_table._cells):
        cell.set_edgecolor(edge_color)
        if k[0] == 0 or k[1] < header_columns:
            # 表头样式设置
            cell.set_text_props(weight='bold', color='w')
            cell.set_facecolor(header_color)
        else:
            col_idx = k[1]
            if col_idx >= 1:
                # 获取单元格数值并映射为颜色
                val = data.iloc[k[0]-1, col_idx]
                norm = norm_dict[col_idx]
                rgba_color = color_map(norm(val))
                cell.set_facecolor(rgba_color)
                # 根据背景亮度自动调整文本颜色，保证可读性
                luminance = 0.299 * rgba_color[0] + 0.587 * rgba_color[1] + 0.114 * rgba_color[2]
                cell.set_text_props(color='w' if luminance < 0.5 else 'k')

    return ax

render_mpl_table(df, header_columns=0)
plt.show()

关键说明 #

• 列内归一化：每个数值列单独做范围归一化，确保颜色渐变是基于列内数值差异，避免因列间数值量级差距过大导致颜色失效。
• 颜色映射可选：示例用Blues色系，可替换为Greens、Reds等Matplotlib内置colormap，或自定义色系。
• 文本自适应：通过计算背景色亮度，自动切换文本为白色/黑色，保证深浅背景下都清晰可读。

内容的提问来源于stack exchange，提问作者ararat