如何移除Matplotlib中x轴的空坐标 解决重复名称绘图异常问题

修正后可运行代码 #

import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
import matplotlib.ticker as ticker

data = {'Name': ['Status', 'Status', 'HMI', 'Allst', 'Drvr', 'CurrTUBand', 'RUSource', 'RUReqstrPriority', 'RUReqstrSystem', 'RUResReqstStat', 'CurrTUBand', 'DSP', 'SetDSP', 'SetDSP', 'DSP', 'RUSource', 'RUReqstrPriority', 'RUReqstrSystem', 'RUResReqstStat', 'Status', 'Delay', 'Status', 'Delay', 'HMI', 'Status', 'Status', 'HMI', 'DSP'],
        'Value': [4, 4, 2, 1, 1, 1, 0, 7, 0, 4, 1, 1, 3, 0, 3, 0, 7, 0, 4, 1, 0, 1, 0, 1, 4, 4, 2, 3],
        'Id_Par': [0, 0, 0, 0, 0, 0, 10, 10, 10, 10, 10, 0, 0, 22, 22, 28, 28, 28, 28, 0, 0, 38, 38, 0, 0, 0, 0, 0]
}

signals_df = pd.DataFrame(data)


def plot_signals(signals_df):
    # Count signals by parallel
    signals_df['Count'] = signals_df.groupby('Id_Par').cumcount().add(1).mask(signals_df['Id_Par'].eq(0), 0)
    # Subtract Parallel values from the index column
    signals_df['Sub'] = signals_df.index - signals_df['Count']
    id_par_prev = signals_df['Id_Par'].unique()
    id_par = np.delete(id_par_prev, 0)
    signals_df['Prev'] = [1 if x in id_par else 0 for x in signals_df['Id_Par']]
    signals_df['Final'] = signals_df['Prev'] + signals_df['Sub']
    # 按计算后的Final索引排序后重置连续索引作为绘图x轴位置
    signals_df.sort_values('Final', inplace=True)
    signals_df.reset_index(drop=True, inplace=True)
    # 记录原始Final索引作为x轴刻度标签
    x_labels = signals_df['Final'].values.tolist()
    # 识别需要加黄色阴影的跳过区间
    skip_intervals = []
    current_par = None
    start_idx = None
    for idx, row in signals_df.iterrows():
        if row['Id_Par'] != 0:
            if current_par is None:
                current_par = row['Id_Par']
                start_idx = idx
        else:
            if current_par is not None:
                skip_intervals.append((start_idx-0.5, idx-0.5))
                current_par = None
    if current_par is not None:
        skip_intervals.append((start_idx-0.5, len(signals_df)-0.5))

    # Get individual names and variables for the chart
    names_list = [name for name in signals_df['Name'].unique()]
    num_names_list = len(names_list)

    # Creation Graphics
    fig, ax = plt.subplots(nrows=num_names_list, figsize=(10, 10), sharex=True)
    plt.xticks(color='SteelBlue', fontweight='bold')

    # 用连续数值作为x轴位置，手动设置刻度标签避免分类轴乱序问题
    x_pos = np.arange(len(signals_df))
    plt.xticks(x_pos, labels=[str(i) for i in x_labels])

    for pos, (a_, name) in enumerate(zip(ax, names_list)):
        # 绘制跳过区域黄色阴影
        for (start, end) in skip_intervals:
            a_.axvspan(start, end, color='yellow', alpha=0.3)
        # Get data
        data = signals_df[signals_df["Name"] == name]["Value"]
        # Get values axis-x and axis-y
        x_ = np.hstack([-1, data.index.values, len(signals_df)])
        y_ = np.hstack([0, data.values, data.iloc[-1]])
        # 直接用数值x轴绘图
        a_.plot(x_, y_, drawstyle='steps-post', marker='*', markersize=8, color='k', linewidth=2)
        a_.set_ylabel(name, fontsize=8, fontweight='bold', color='SteelBlue', rotation=30, labelpad=35)
        a_.yaxis.set_major_formatter(ticker.FormatStrFormatter('%0.1f'))
        a_.yaxis.set_tick_params(labelsize=6)
        a_.grid(alpha=0.4, color='SteelBlue')
        # 标注数值
        for i in range(len(y_)-1):
            xy = [x_[i], y_[i]]
            a_.text(x=xy[0], y=xy[1], s=str(xy[1]), color='k', fontweight='bold', fontsize=12)
    plt.xlim(-0.5, len(signals_df)-0.5)
    plt.tight_layout()
    plt.show()


plot_signals(signals_df)

核心改动说明 #

• 修复了原代码未定义变量all_names_list的语法错误
• 放弃将x值转为字符串的分类轴方案，改用连续数值作为x轴位置，手动映射原始Final索引作为刻度标签，彻底避免x轴值重复导致的顺序错乱
• 新增了跳过区间的黄色阴影绘制逻辑，自动识别Id_Par非0的并行区间添加半透明黄色背景
• 调整了x轴范围和文本标注逻辑，避免标注错位
• 对dataframe按Final索引排序后重置了连续数值索引，避免绘图时索引跳跃导致的图形异常

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