使用Python绘制空气质量日历图

def calendar_heatmap(df, title):
    # 定义颜色
    color_list = ['#009966', '#FFDE33', '#FF9A32', '#CC0033', '#660099']
    levels = [0, 50, 100, 150, 200, 300]
    cmap = colors.ListedColormap(color_list)
    norm = colors.BoundaryNorm(levels, cmap_aqi.N)
    # 绘图
    fig, ax = plt.subplots(figsize=(18, 9))
    calmap.yearplot(
        df,
        vmin=0,
        vmax=300,
        cmap=cmap,
        norm=norm,
        how=None,
        year=2020,
    )
    cbar_ax  = fig.add_axes([0.94, 0.4, 0.015, 0.2])
    cb  = mpl.colorbar.ColorbarBase(
        cbar_ax,
        cmap=cmap,
        ticks=levels,
        norm=norm,
        orientation='vertical',
        extend='neither',
        extendrect=True,
        extendfrac=0.15
    )
    # 色标
    cb.set_ticks([0, 50, 100, 150, 200, 300])
    cb.ax.yaxis.set_tick_params(length=0.01)
    ax.set_ylabel('2020', fontdict=dict(fontsize=25, color='grey'))
    # 标题
    ax.set_title(f'AQI of {title}', fontweight = 'bold', fontsize = 25)
    plt.savefig(f'{title}_calendar_heatmap.png')

cp = df.resample('1d').mean().round(2)['昌平']
calendar_heatmap(cp, 'Changping')

dx = df.resample('1d').mean().round(2)['大兴']
calendar_heatmap(dx, 'DaXing')

cp_bin = pd.cut(
    cp,
    bins=[0, 50, 100, 150, 200, 300],
    right=False
).value_counts()

dx_bin = pd.cut(
dx,
bins=[0, 50, 100, 150, 200, 300],
right=False
).value_counts()