import gradio as gr import pandas as pd import matplotlib.pyplot as plt import tempfile import warnings warnings.filterwarnings(action='ignore', category=UserWarning) # 设置中文字体和编码 plt.rcParams['font.sans-serif'] = ['SimHei'] # 选择合适的中文字体,这里使用黑体 plt.rcParams['axes.unicode_minus'] = False # 设置正常显示字符 def process_file(file): # 读取CSV或Excel文件并创建DataFrame if file.name.endswith('.csv'): df = pd.read_csv(file.name) elif file.name.endswith('.xlsx') or file.name.endswith('.xls'): df = pd.read_excel(file.name) else: return "不支持的数据文件格式。" columns = df.columns.tolist() feature_columns = columns[:-1] last_column = [columns[-1]] # 返回前5行数据,更新下拉列表选项,并使其他控件可见 return (gr.update(choices=feature_columns, value=feature_columns[0], visible=True), gr.update(choices=last_column, value=last_column[-1], visible=True), gr.update(visible=True), gr.update(visible=True), df.head() ) def update_slider(choice): # 更新数轴控件的可见性 return gr.update(visible=choice == "是") def generate_output(file, column1, column2, choice, bins): df = pd.read_csv(file.name) data_x = df[column1] data_y = df[column2] # 自动判断column1的数据类型 if choice == "是": # 如果是连续值,则进行分组 data_x = pd.qcut(data_x, q=bins, duplicates='drop') else: # 如果是离散值,则直接使用 pass # 统计每个身高分段中不同心血管疾病类别的数量 counts = pd.crosstab(data_x, data_y) # 绘制分段柱形图 counts.plot(kind='bar') # 设置画布大小 plt.figure(figsize=(bins*2, 6)) # 设置 x 轴刻度标签横向显示 plt.xticks(rotation=0) plt.xlabel(column1, fontsize=12) plt.ylabel(column2, fontsize=12) # plt.legend(['不患病', '患病']) plt.title(f'{column1}与{column2}的关系', fontsize=14) # plt.show() image_path = 'output.png' plt.savefig(image_path) # plt.close() return df.head(), gr.update(visible=True), image_path, gr.update(visible=True), gr.update(visible=True) with gr.Blocks() as demo: with gr.Row(): with gr.Column(): file_input = gr.File(label="上传表格文件(支持CSV、XLS、XLSX等格式", file_types=["csv", "xls", "xlsx"]) col1_dropdown = gr.Dropdown(label="请选择特征列", visible=False) col2_dropdown = gr.Dropdown(label="选择标签列", visible=False) choice_radio = gr.Radio(["是", "否"], label="特征列是否为连续值", value="否", visible=False) slider = gr.Slider(minimum=3, maximum=7, step=1, label="选择将特征列分组的分组数", visible=False, value=4) submit_button = gr.Button("查看结果", visible=False) with gr.Column(): df_display = gr.Dataframe(visible=False) output_image = gr.Image(visible=False) # 文件上传后调用 process_file 函数 file_input.upload(process_file, inputs=file_input, outputs=[col1_dropdown, col2_dropdown, choice_radio, df_display, df_display]) # 选择框值改变时调用 update_slider 函数 choice_radio.change(update_slider, inputs=choice_radio, outputs=slider) # 点击提交按钮时调用 generate_output 函数 submit_button.click(generate_output, inputs=[file_input, col1_dropdown, col2_dropdown, choice_radio, slider], outputs=[df_display, df_display, output_image, output_image, submit_button]) demo.launch(share=True)