result[file_name] = averaged.iloc[0]是什么意思

这行代码是将一个 Pandas DataFrame 数据框的第一行数据取平均值后，将结果赋值给一个字典中的某个键（key）。具体来说，假设 averaged 是一个 Pandas DataFrame 数据框，其中有多行数据，则 averaged.iloc[0] 表示取 averaged 数据框的第一行数据。将该行数据取平均值后，将结果赋值给字典 result 的 file_name 键对应的值。其中，file_name 是一个字符串类型的键。这行代码的作用是将多个数据框的第一行数据取平均值后，以键值对的形式存储在字典 result 中。

相关问题

result[file_name] = averaged.iloc[0]是什么意识

这段代码是将一个DataFrame对象averaged的第一行转换为一个Series对象，然后将该Series对象赋值给字典result中的一个键file_name的值。具体来说，averaged.iloc[0]会返回DataFrame对象averaged的第一行，而该行的每一列会被转换为一个Series对象。然后，result[file_name]将返回字典result中键为file_name的值，该值被赋值为averaged的第一行转换而来的Series对象。

def draw_stats(self, vals, vals1, vals2, vals3, vals4, vals5, vals6): self.ax1 = plt.subplot(self.gs[0, 0]) self.ax1.plot(vals) self.ax1.set_xlim(self.xlim) locs = self.ax1.get_xticks() locs[0] = self.xlim[0] locs[-1] = self.xlim[1] self.ax1.set_xticks(locs) self.ax1.use_sticky_edges = False self.ax1.set_title(f'Connected Clients Ratio') self.ax2 = plt.subplot(self.gs[1, 0]) self.ax2.plot(vals1) self.ax2.set_xlim(self.xlim) self.ax2.set_xticks(locs) self.ax2.yaxis.set_major_formatter(FuncFormatter(format_bps)) self.ax2.use_sticky_edges = False self.ax2.set_title('Total Bandwidth Usage') self.ax3 = plt.subplot(self.gs[2, 0]) self.ax3.plot(vals2) self.ax3.set_xlim(self.xlim) self.ax3.set_xticks(locs) self.ax3.use_sticky_edges = False self.ax3.set_title('Bandwidth Usage Ratio in Slices (Averaged)') self.ax4 = plt.subplot(self.gs[3, 0]) self.ax4.plot(vals3) self.ax4.set_xlim(self.xlim) self.ax4.set_xticks(locs) self.ax4.use_sticky_edges = False self.ax4.set_title('Client Count Ratio per Slice') self.ax5 = plt.subplot(self.gs[0, 1]) self.ax5.plot(vals4) self.ax5.set_xlim(self.xlim) self.ax5.set_xticks(locs) self.ax5.use_sticky_edges = False self.ax5.set_title('Coverage Ratio') self.ax6 = plt.subplot(self.gs[1, 1]) self.ax6.plot(vals5) self.ax6.set_xlim(self.xlim) self.ax6.set_xticks(locs) self.ax6.yaxis.set_major_formatter(FormatStrFormatter('%.3f')) self.ax6.use_sticky_edges = False self.ax6.set_title('Block ratio') self.ax7 = plt.subplot(self.gs[2, 1]) self.ax7.plot(vals6) self.ax7.set_xlim(self.xlim) self.ax7.set_xticks(locs) self.ax7.yaxis.set_major_formatter(FormatStrFormatter('%.3f')) self.ax7.use_sticky_edges = False self.ax7.set_title('Handover ratio')修改为一张张输出图片

好的，你可以将这段代码修改为：

def draw_stats(self, vals, vals1, vals2, vals3, vals4, vals5, vals6, save_path):
        fig, axs = plt.subplots(4, 2, figsize=(16, 16))
        axs[0, 0].plot(vals)
        axs[0, 0].set_xlim(self.xlim)
        locs = axs[0, 0].get_xticks()
        locs[0] = self.xlim[0]
        locs[-1] = self.xlim[1]
        axs[0, 0].set_xticks(locs)
        axs[0, 0].use_sticky_edges = False
        axs[0, 0].set_title(f'Connected Clients Ratio')

        axs[1, 0].plot(vals1)
        axs[1, 0].set_xlim(self.xlim)
        axs[1, 0].set_xticks(locs)
        axs[1, 0].yaxis.set_major_formatter(FuncFormatter(format_bps))
        axs[1, 0].use_sticky_edges = False
        axs[1, 0].set_title('Total Bandwidth Usage')

        axs[2, 0].plot(vals2)
        axs[2, 0].set_xlim(self.xlim)
        axs[2, 0].set_xticks(locs)
        axs[2, 0].use_sticky_edges = False
        axs[2, 0].set_title('Bandwidth Usage Ratio in Slices (Averaged)')

        axs[3, 0].plot(vals3)
        axs[3, 0].set_xlim(self.xlim)
        axs[3, 0].set_xticks(locs)
        axs[3, 0].use_sticky_edges = False
        axs[3, 0].set_title('Client Count Ratio per Slice')

        axs[0, 1].plot(vals4)
        axs[0, 1].set_xlim(self.xlim)
        axs[0, 1].set_xticks(locs)
        axs[0, 1].use_sticky_edges = False
        axs[0, 1].set_title('Coverage Ratio')

        axs[1, 1].plot(vals5)
        axs[1, 1].set_xlim(self.xlim)
        axs[1, 1].set_xticks(locs)
        axs[1, 1].yaxis.set_major_formatter(FormatStrFormatter('%.3f'))
        axs[1, 1].use_sticky_edges = False
        axs[1, 1].set_title('Block ratio')

        axs[2, 1].plot(vals6)
        axs[2, 1].set_xlim(self.xlim)
        axs[2, 1].set_xticks(locs)
        axs[2, 1].yaxis.set_major_formatter(FormatStrFormatter('%.3f'))
        axs[2, 1].use_sticky_edges = False
        axs[2, 1].set_title('Handover ratio')

        plt.tight_layout()
        plt.savefig(save_path)
        plt.show()

这样就可以一张张输出图片了，你只需要传入一个保存路径参数 `save_path` 即可。