多个箱线图，其中包含 for 循环保存输出中文件的数据？

我正在使用保存在要绘制箱线图的文件中的一些数据。

每个文件（第 3 行）中有 27 个值，每个文件我希望成为沿 x 轴 5 ' 的单独箱线图

然后，我还希望将每个文件作为单个箱线图进行概述，因为我有 10 个“对象”（使用所有 5 个文件 27 个值（135 个值）作为单个箱线图）

我已经开始在代码上，但目前我只给出了一个箱线图，因为我认为它没有正确保存数据以便能够绘制多个箱线图，到目前为止我还没有开始组合整个图形的数​​据。|| |任何帮助将不胜感激。

` import numpy as np 从 numpy 导入 genfromtxt 将 matplotlib.pyplot 导入为 plt import pandas as pd

`

dataset = pd.read_excel("ObjectData.xlsx") #Where the names of the Objects are kept
data = []

#Iterations for objects and runs
for object in range(0, 10, 1):
    for run in range(0, 5, 1):

        #Access data from files
        recordname1 = str(dataset.iloc[object, 1]) + " run:" + str(run) #Object and run name
        path1 = recordname1 + "clonemin.csv"
        my_plot_data = genfromtxt(path1, delimiter=',') #Get individual file (eg 1of10,1of5)
        data = [data, np.append(my_plot_data,([3, :]))] #Get individual line from file R=3, C=all

        #Save individual boxplots for plotting
        fig = plt.figure(figsize=(10,7))
        ax = fig.add_axes([0,0,1,1])
        bp = ax.boxplot(data)
        plt.show()

    #Save object boxplots (1x5) iteratedx10
    path2 = str(dataset.iloc[object, 1]) + "Boxplot.png" 
    plt.savefig(path2)
    plt.clf()

path3 = "Final_Boxplot.png" #Save overall boxplots (1x10)
plt.savefig(path3)
plt.clf()

结果应该是：对于每个对象 (10)，应该有一个由 5 个箱线图组成的图形，以及一个沿 x 轴显示 10 个对象箱线图的整体图形。总共 11 张图片。

Result should be: For each object (10) there should be a graphic made up of 5 boxplots, and one overall graphic showing the 10 objects boxplots along the x-axis. So 11 Images overall.

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

dataset = pd.read_excel("ObjectData.xlsx")
# Create a figure to store all object boxplots
fig_all_objects = plt.figure(figsize=(10, 7))

for object in range(0, 10, 1):
    data_object = []  # Store data for all runs of current object
    for run in range(0, 5, 1):
        recordname1 = str(dataset.iloc[object, 1]) + " run:" + str(run)
        path1 = recordname1 + "clonemin.csv"
        my_plot_data = genfromtxt(path1, delimiter=',')
        data_object.append(my_plot_data) 

    # Create a figure for each object
    fig_object = plt.figure(figsize=(10, 7))
    ax_object = fig_object.add_axes([0, 0, 1, 1])
    # Boxplot for all runs of current object
    bp = ax_object.boxplot(data_object)
    ax_object.set_xticklabels([f"Run {i+1}" for i in range(5)])
    ax_object.set_title(f"Object {dataset.iloc[object, 1]}")
    plt.savefig(f"{dataset.iloc[object, 1]}_Boxplot.png") 
    plt.close(fig_object) 

    # Add data to the overall figure
    ax_all_objects = fig_all_objects.add_axes([0, 0, 1, 1])
    bp_all = ax_all_objects.boxplot(data_object, positions=[object * 5 + i for i in range(5)])

# Customize and save the overall boxplot
ax_all_objects.set_xticks([i * 5 + 2 for i in range(10)])
ax_all_objects.set_xticklabels([dataset.iloc[i, 1] for i in range(10)])
plt.savefig("Final_Boxplot.png")
plt.close(fig_all_objects)

Here's how this code works:

1. Data Loading & Initialization:
2. Reads object names from "ObjectData.xlsx."

3. Initializes lists to store data for plotting.

4. Iterating Through Objects and Runs:

5. Loops through each object and its corresponding runs.
6. Constructs file names for each run's data.

7. Reads data from each file using genfromtxt .

8. Creating and Saving Individual Object Boxplots:

9. For each object, creates a new figure ( plt.figure ).
10. Appends the data for all 5 runs of the object to data_object .
11. Generates a boxplot ( ax.boxplot ) using the collected data.
12. Sets labels for the x-axis ticks (Run 1 to Run 5).
13. Sets the title of the plot with the object's name.
14. Saves the figure as a PNG file named "{Object Name}_Boxplot.png".

15. Clears the figure to prepare for the next object's plot.

16. Creating and Saving the Overall Boxplot:

17. Creates a new figure ( plt.figure ) for the overall boxplot.
18. Iterates through the data of each object and its runs.
19. For each object, adds its data to the overall boxplot ( ax.boxplot ) at specific positions along the x-axis to avoid overlap.
20. Sets custom x-axis ticks and labels to represent each object.

21. Saves the final overall boxplot as "Final_Boxplot.png".

22. Output:

23. The code generates 11 images in total:
    • 10 images named "{Object Name}_Boxplot.png" each showing boxplots for the 5 runs of a specific object.
    • 1 image named "Final_Boxplot.png" showing an overall boxplot combining the data of all 10 objects.