MatPlotlib Seaborn多个打印格式

Question

我正在将一组R可视化转换为Python。我有以下目标R多重曲线直方图：

使用Matplotlib和Seaborn的组合，在一个StackOverflow成员的帮助下（参见链接：Python Seaborn Distplot Y value corresponding to a given X value），我能够创建以下Python图：

我对它的外观很满意，除了，我不知道如何将标题信息放入绘图中。下面是我创建Python图表的Python代码

""" Program to draw the sampling histogram distributions """
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
import seaborn as sns

def main():
    """ Main routine for the sampling histogram program """
    sns.set_style('whitegrid')
    markers_list = ["s", "o", "*", "^", "+"]
    # create the data dataframe as df_orig
    df_orig = pd.read_csv('lab_samples.csv')
    df_orig = df_orig.loc[df_orig.hra != -9999]
    hra_list_unique = df_orig.hra.unique().tolist()
    # create and subset df_hra_colors to match the actual hra colors in df_orig
    df_hra_colors = pd.read_csv('hra_lookup.csv')
    df_hra_colors['hex'] = np.vectorize(rgb_to_hex)(df_hra_colors['red'], df_hra_colors['green'], df_hra_colors['blue'])
    df_hra_colors.drop(labels=['red', 'green', 'blue'], axis=1, inplace=True)
    df_hra_colors = df_hra_colors.loc[df_hra_colors['hra'].isin(hra_list_unique)]

    # hard coding the current_component to pc1 here, we will extend it by looping
    # through the list of components
    current_component = 'pc1'
    num_tests = 5
    df_columns = df_orig.columns.tolist()
    start_index = 5
    for test in range(num_tests):
        current_tests_list = df_columns[start_index:(start_index + num_tests)]
        # now create the sns distplots for each HRA color and overlay the tests
        i = 1
        for _, row in df_hra_colors.iterrows():
            plt.subplot(3, 3, i)
            select_columns = ['hra', current_component] + current_tests_list
            df_current_color = df_orig.loc[df_orig['hra'] == row['hra'], select_columns]
            y_data = df_current_color.loc[df_current_color[current_component] != -9999, current_component]
            axs = sns.distplot(y_data, color=row['hex'],
                               hist_kws={"ec":"k"},
                               kde_kws={"color": "k", "lw": 0.5})
            data_x, data_y = axs.lines[0].get_data()
            axs.text(0.0, 1.0, row['hra'], horizontalalignment="left", fontsize='x-small',
                     verticalalignment="top", transform=axs.transAxes)
            for current_test_index, current_test in enumerate(current_tests_list):
                # this_x defines the series of current_component(pc1,pc2,rhob) for this test
                # indicated by 1, corresponding R program calls this test_vector
                x_series = df_current_color.loc[df_current_color[current_test] == 1, current_component].tolist()
                for this_x in x_series:
                    this_y = np.interp(this_x, data_x, data_y)
                    axs.plot([this_x], [this_y - current_test_index * 0.05],
                             markers_list[current_test_index], markersize = 3, color='black')
            axs.xaxis.label.set_visible(False)
            axs.xaxis.set_tick_params(labelsize=4)
            axs.yaxis.set_tick_params(labelsize=4)
            i = i + 1
        start_index = start_index + num_tests
    # plt.show()
    pp = PdfPages('plots.pdf')
    pp.savefig()
    pp.close()

def rgb_to_hex(red, green, blue):
    """Return color as #rrggbb for the given color values."""
    return '#%02x%02x%02x' % (red, green, blue)

if __name__ == "__main__":
    main()

熊猫守则运作良好，它正在做它应该做的。我缺乏在Matplotlib中使用“PdfPages”的知识和经验，这是我的瓶颈。如何在Python/Matplotlib/Seaborn中显示可以在相应的R visalization中显示的头信息。标题信息，我指的是R可视化在柱状图之前的顶部，即‘pc1’、MRP、XRD等等，。。。。在

我可以很容易地从我的程序中得到它们的值，例如，当前的嫘u组件是'pc1'等，但我不知道如何用标题格式化绘图。有人能提供一些指导吗？在

Answer 1

您可能正在查找图形标题或超级标题，^{}：

fig.suptitle('this is the figure title', fontsize=12)

在您的例子中，您可以很容易地用plt.gcf()得到这个数字，所以请尝试一下

^{pr2}$

头中的其余信息称为legend。 下面让我们假设所有子图都有相同的标记。然后为其中一个子批次创建一个图例就足够了。 要创建图例标签，可以将label参数放入绘图，即

axs.plot( ... , label="MRP")

稍后调用axs.legend()时，将自动生成带有相应标签的图例。图例的定位方法详见this answer。
在这里，您可能需要根据图形坐标来放置图例，即

ax.legend(loc="lower center",bbox_to_anchor=(0.5,0.8),bbox_transform=plt.gcf().transFigure)