【问题标题】:how to highlight weekends in matplotlib plots?如何在 matplotlib 图中突出显示周末?
【发布时间】:2020-07-31 20:45:17
【问题描述】:

对于一个简单的时间序列:

import pandas as pd
df = pd.DataFrame({'dt':['2020-01-01', '2020-01-02', '2020-01-04', '2020-01-05', '2020-01-06'], 'foo':[1,2, 4,5,6]})
df['dt'] = pd.to_datetime(df.dt)
df['dt_label']= df['dt'].dt.strftime('%Y-%m-%d %a')
df = df.set_index('dt')
#display(df)
df['foo'].plot()
x =plt.xticks(ticks=df.reset_index().dt.values, labels=df.dt_label, rotation=90, horizontalalignment='right')

如何突出显示周末的 x 轴标签?

编辑

Pandas Plots: Separate color for weekends, pretty printing times on x axis

建议:

def highlight_weekends(ax, timeseries):
    d = timeseries.dt
    ranges = timeseries[d.dayofweek >= 5].groupby(d.year * 100 + d.weekofyear).agg(['min', 'max'])
    for i, tmin, tmax in ranges.itertuples():
        ax.axvspan(tmin, tmax, facecolor='orange', edgecolor='none', alpha=0.1)

但应用它与

highlight_weekends(ax, df.reset_index().dt)

不会改变剧情

【问题讨论】:

    标签: python matplotlib time-series weekend


    【解决方案1】:

    我已经稍微扩展了您的示例数据,以便我们可以确保我们可以突出显示多个周末实例。

    在这个解决方案中,我创建了一个列'weekend',它是一列布尔值,指示相应的日期是否在周末。

    然后我们遍历这些值并调用ax.axvspan

    import pandas as pd
    import matplotlib.pyplot as plt
    
    # Add a couple of extra dates to sample data
    df = pd.DataFrame({'dt': ['2020-01-01',
                              '2020-01-02',
                              '2020-01-04',
                              '2020-01-05',
                              '2020-01-06',
                              '2020-01-07',
                              '2020-01-09',
                              '2020-01-10',
                              '2020-01-11',
                              '2020-01-12']})
    # Fill in corresponding observations
    df['foo'] = range(df.shape[0])
    
    df['dt'] = pd.to_datetime(df.dt)
    
    df['dt_label']= df['dt'].dt.strftime('%Y-%m-%d %a')
    
    df = df.set_index('dt')
    
    ax = df['foo'].plot()
    plt.xticks(ticks=df.reset_index().dt.values, 
               labels=df.dt_label,
               rotation=90,
               horizontalalignment='right')
    
    # Create an extra column which highlights whether or not a date occurs at the weekend
    df['weekend'] = df['dt_label'].apply(lambda x: x.endswith(('Sat', 'Sun')))
    
    # Loop over weekend pairs (Saturdays and Sundays), and highlight
    for i in range(df['weekend'].sum() // 2):
        ax.axvspan(df[df['weekend']].index[2*i],
                   df[df['weekend']].index[2*i+1],
                   alpha=0.5)
    

    【讨论】:

      【解决方案2】:

      这是一个使用 fill_between 绘图函数和 x 轴单位的解决方案,以便可以独立于 DatetimeIndex 和数据频率突出显示周末。

      x 轴范围用于以天为单位计算绘图所涵盖的时间范围,这是matplotlib dates 使用的单位。然后计算weekends 掩码并将其传递给fill_between 函数的where 参数。掩码作为右排他处理,因此在这种情况下,它们必须包含星期一,以便在星期一 00:00 之前绘制亮点。由于绘制这些高光可能会在周末发生在边界附近时改变 x 轴范围,因此绘制后 x 轴范围将设置回原始值。

      请注意,与axvspan 不同,fill_between 函数需要y1y2 参数。出于某种原因,使用默认的 y 轴限制会在图框与周末亮点的顶部和底部之间留下一个小间隙。这个问题可以通过在创建绘图后运行ax.set_ylim(*ax.get_ylim()) 来解决。

      这是一个基于提供的示例代码并使用类似于 jwalton 提供的答案的扩展数据集的完整示例:

      import numpy as np                   # v 1.19.2
      import pandas as pd                  # v 1.1.3
      import matplotlib.pyplot as plt      # v 3.3.2
      import matplotlib.dates as mdates
      
      # Create sample dataset
      dt = pd.to_datetime(['2020-01-01', '2020-01-02', '2020-01-04', '2020-01-05',
                           '2020-01-06', '2020-01-07', '2020-01-09', '2020-01-10',
                           '2020-01-11', '2020-01-14'])
      df = pd.DataFrame(dict(foo=range(len(dt))), index=dt)
      
      # Draw pandas plot: setting x_compat=True converts the pandas x-axis units to
      # matplotlib date units. This is not necessary for this particular example but
      # it is necessary for all cases where the dataframe contains a continuous
      # DatetimeIndex (for example ones created with pd.date_range) that uses a
      # frequency other than daily
      ax = df['foo'].plot(x_compat=True, figsize=(6,4), ylabel='foo')
      ax.set_ylim(*ax.get_ylim()) # reset y limits to display highlights without gaps
      
      # Highlight weekends based on the x-axis units
      xmin, xmax = ax.get_xlim()
      days = np.arange(np.floor(xmin), np.ceil(xmax)+2) # range of days in date units
      weekends = [(dt.weekday()>=5)|(dt.weekday()==0) for dt in mdates.num2date(days)]
      ax.fill_between(days, *ax.get_ylim(), where=weekends, facecolor='k', alpha=.1)
      ax.set_xlim(xmin, xmax) # set limits back to default values
      
      # Create and format x tick for each data point
      plt.xticks(df.index.values, df.index.strftime('%d\n%a'), rotation=0, ha='center')
      
      plt.title('Weekends are highlighted from SAT 00:00 to MON 00:00', pad=15, size=12);
      



      您可以在我发布的herehere 的答案中找到此解决方案的更多示例。

      【讨论】:

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