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% 数据加载

data = readtable('附件1.csv', 'Encoding', 'UTF-8');

% 转换日期格式

data.x____ = datetime(data.x____, 'InputFormat', 'yyyy/MM/dd');

% 按分拣中心分组

g = findgroups(data.x_______);

% 计算分拣中心的数量

total_centers = max(g);

num_plots = ceil(total_centers / 3); % 每个图三个分拣中心

% 对每组三个分拣中心生成一个图

for plot_index = 0:num_plots-1

figure;

centers = unique(data.x_______);

centers = centers(1 + plot_index * 3:min(end, 3 + plot_index * 3));

for i = 1:length(centers)

center = centers(i);

idx = ismember(data.x_______, center);

series = data.x_____1(idx);

% Q-Q图

subplot(3, 3, 3 * (i - 1) + 1);

qqplot(series);

title(['Q-Q plot for ', center]);

% 箱型图

subplot(3, 3, 3 * (i - 1) + 2);

boxplot(series, 'Orientation', 'horizontal');

title(['Box plot for ', center]);

% 3σ原则

subplot(3, 3, 3 * (i - 1) + 3);

histogram(series, 30, 'Normalization', 'probability');

meanVal = mean(series);

stdVal = std(series);

xline(meanVal - 3 * stdVal, 'r--', 'Label', 'Lower 3σ');

xline(meanVal + 3 * stdVal, 'r--', 'Label', 'Upper 3σ');

title(['3σ Rule for ', center]);

end

end

% 按分拣中心分组

[g, centers] = findgroups(data.x_______);

% 初始化结果表格

ks_results = table('Size', [0 3], 'VariableTypes', {'string', 'double', 'double'}, ...

'VariableNames', {'分拣中心', '统计量', 'p值'});

% 遍历每个分拣中心，执行K-S检验

for i = 1:max(g)

series = data.x_____1(g == i);

% 计算正态分布的参数

[mu, sigma] = normfit(series);

% 执行K-S检验

[statistic, p_value] = kstest(series, 'CDF', [series, normcdf(series, mu, sigma)]);

% 保存结果

ks_results = [ks_results; {centers(i), statistic, p_value}];

end

% 保存到Excel文件

writetable(ks_results, 'K-S检验结果.xlsx');

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import scipy.stats as stats

# 数据加载
data_path = '附件1.csv'
data = pd.read_csv(data_path, encoding='GBK')

# 按分拣中心分组
grouped = data.groupby('分拣中心')

# 选择前三个分拣中心
selected_centers = list(grouped.groups.keys())[:3]

# 设置matplotlib的布局
fig, axs = plt.subplots(3, 3, figsize=(18, 12))  # 3行3列
fig.subplots_adjust(hspace=0.4, wspace=0.4)

for i, center in enumerate(selected_centers):
    series = grouped.get_group(center)['货量']

    # Q-Q图
    stats.probplot(series, dist="norm", plot=axs[0, i])
    axs[0, i].set_title(f'Q-Q plot for {center}')

    # 箱型图
    axs[1, i].boxplot(series, vert=False)
    axs[1, i].set_title(f'Box plot for {center}')

    # 3σ原则
    mean = series.mean()
    std = series.std()
    lower_bound = mean - 3 * std
    upper_bound = mean + 3 * std

    axs[2, i].hist(series, bins=30, alpha=0.7, label='Data Distribution')
    axs[2, i].axvline(lower_bound, color='red', linestyle='dashed', linewidth=1, label='Lower 3σ')
    axs[2, i].axvline(upper_bound, color='red', linestyle='dashed', linewidth=1, label='Upper 3σ')
    axs[2, i].set_title(f'3σ Rule for {center}')
    axs[2, i].legend()

plt.show()