如何实现Pandas DataFrame多行共用同一索引并垂直显示，生成类Excel格式表格

Hey there! Let's fix up your table to meet your requirements—vertical index display and every 3 consecutive rows sharing the same index. Here's a step-by-step solution with modified code:

Step 1: Key Adjustments Needed #

Your original code generates a basic table, but we need two critical tweaks:

• Add the index as a dedicated column with vertically aligned text
• Merge cells in the index column for every 3 rows to create the shared-index effect

Step 2: Modified Code Implementation #

We'll update the render_mpl_table function to handle vertical text and cell merging, then create a DataFrame with grouped indices.

import os
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import math
from IPython.core.interactiveshell import InteractiveShell
InteractiveShell.ast_node_interactivity = "all"

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, index_vertical=True, group_rows=3, **kwargs):
    if ax is None:
        # Account for the extra index column in figure size
        size = (np.array(data.shape[::-1]) + np.array([1, 1])) * np.array([col_width, row_height])
        fig, ax = plt.subplots(figsize=size)
        ax.axis('off')
    
    # Prepare table data including the index as the first column
    cell_text = []
    for idx, row in data.iterrows():
        cell_text.append([str(idx)] + list(row.values))
    
    # Column labels: add "Index" for the first column
    col_labels = ['Index'] + list(data.columns)
    
    # Create the table
    mpl_table = ax.table(cellText=cell_text, bbox=bbox, colLabels=col_labels, **kwargs)
    mpl_table.auto_set_font_size(False)
    mpl_table.set_fontsize(font_size)
    
    # Style cells
    for k, cell in mpl_table._cells.items():
        cell.set_edgecolor(edge_color)
        # Style header row
        if k[0] == 0:
            cell.set_text_props(weight='bold', color='w')
            cell.set_facecolor(header_color)
        else:
            # Alternate row background colors
            cell.set_facecolor(row_colors[(k[0]-1)%len(row_colors)])
            
            # Set vertical text for index column
            if index_vertical and k[1] == 0:
                cell.set_text_props(rotation=90, ha='center', va='center')
    
    # Merge index cells for every `group_rows` rows
    if group_rows > 1:
        total_rows = len(data)
        num_groups = total_rows // group_rows
        for group_idx in range(num_groups):
            start_row = group_idx * group_rows + 1  # Header is row 0, data starts at row 1
            end_row = start_row + group_rows - 1
            # Set height of the first cell in the group to cover all 3 rows
            mpl_table[start_row, 0].set_height(group_rows * row_height)
            # Hide the subsequent cells in the same index group
            for row in range(start_row + 1, end_row + 1):
                mpl_table[row, 0].set_visible(False)
    
    return ax.get_figure(), ax

# Create a DataFrame with grouped indices (every 3 rows share the same index)
df = pd.DataFrame({
    'Planet': ['Earth','Mercury', 'Jupiter', 'Mars', 'Venus', 'Saturn'],
    'time': [2200, 2100, 1500, 2000, 1900, 1600],
    'distance': [8, 7.5, 8.2, 9, 7.8, 8.5],
    'Bz': [9,8, 10, 7, 6, 11]
}, index=[0,0,0,1,1,1])

# Generate the table
fig, ax = render_mpl_table(df, header_columns=0, col_width=2.0, group_rows=3)
plt.show()

Key Changes Breakdown #

• Index as a Dedicated Column: We added the DataFrame's index as the first table column, making it easy to style and merge independently.
• Vertical Index Text: Using rotation=90 on the index column cells ensures text displays vertically, with center alignment for readability.
• Shared Index Merging: For each group of 3 rows, we set the first index cell's height to cover all 3 rows, then hide the other two index cells in the group—this creates the seamless shared-index look you want.
• Scalable: To add more rows, just extend the index list in the DataFrame (e.g., [0,0,0,1,1,1,2,2,2] for 9 rows across 3 groups).

内容的提问来源于stack exchange，提问作者user11607936