from pyecharts import options as opts from pyecharts.charts import Bar,Page,Line,Timeline from pyecharts.commons.utils import JsCode from pyecharts.globals import ThemeType from pyecharts.charts import Pie import sql from pyecharts.faker import Faker # from main import book_list_data from collections import Counter class Book: def __init__(self, name, url, star, star_people, author, translater, publisher, pub_year, price, comment): self.name = name self.url = url self.star = star self.star_people = star_people self.author = author self.translater = translater self.publisher = publisher self.pub_year = pub_year self.price = price self.comment = comment # db = sql.BookDatabase(host='localhost', user='root', password='123456', database='xiaosuo', table_name='books') # db.initialize_table() def show(): db = sql.BookDatabase(host='localhost', user='root', password='123456', database='xiaosuo', table_name='books') db.initialize_table() data = db.get_book_list() book_list_data = [] for book in data: book_list_data.append( Book(book["name"], book["url"], book["star"], book["star_people"], book["author"], book["translater"], book["publisher"], book["pub_year"], book["price"], book["comment"])) book_list_data_sortBystart = sorted(book_list_data, key=lambda x: (x.star, x.star_people), reverse=True) book_list_data_sortBystart = book_list_data_sortBystart[:10] book_list_data_sortBystart = book_list_data_sortBystart[::-1] # 从book_list_data中提取书籍名称和评分数据 book_names = [book.name for book in book_list_data_sortBystart] book_stars = [book.star for book in book_list_data_sortBystart] x_data = list(range(1, len(book_names) + 1)) # 创建柱状图 bar = ( Bar(init_opts=opts.InitOpts(theme="shine", width="850px", height='400px')) .add_xaxis(book_names) .add_yaxis("评分", book_stars, color="red") .reversal_axis() # 实现旋转 .set_global_opts( title_opts=opts.TitleOpts(title="评分前10榜", pos_bottom="bottom", pos_left="center"), xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=0)), yaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=-45)) ) # .render("bar_datazoom_slider.html") ) publisher_list = [book.publisher for book in book_list_data] # 使用Counter来计算每个出版商的数量 publisher_counter = Counter(publisher_list) publisher_names = list(publisher_counter.keys()) publisher_counts = list(publisher_counter.values()) colors = [ "#5470c6", "#91cc75", "#fac858", "#ee6666", "#73c0de", "#3ba272", "#fc8452", "#9a60b4", "#ea7ccc", "#bb60b4", "#8B008B", "#FF1493", "#1E90FF", "#20B2AA", "#2E8B57", "#B22222", "#FF4500", "#4682B4", "#DAA520", "#32CD32" ] # 使用Pyecharts创建饼图 pie = ( Pie() .add("", [list(z) for z in zip(publisher_names, publisher_counts)]) .set_colors(colors) # 设置颜色 .set_global_opts(title_opts=opts.TitleOpts(title="出版商分布饼图", pos_left="center", pos_bottom="bottom")) .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}")) ) prices = [float(book.price) for book in book_list_data] print(prices) # 将价格分组到不同的区间 price_intervals = [0, 50, 100, 150, 200, 250, 300, 350, 400, 450, 500, float('inf')] # 设置价格区间 price_counts = [0] * (len(price_intervals) - 1) # 初始化每个区间的计数为0 prices_intervalsStr = ["0-50", "50-100", "100-150", "150-200", "200-250", "250-300", "300-350", "350-400", "400-450", "450-500", "500以上"] # 统计每个价格区间的数量 for price in prices: for i in range(len(price_intervals) - 1): if price >= 500: price_counts[len(price_intervals) - 1] += 1 break if price_intervals[i] <= price and price < price_intervals[i + 1]: price_counts[i] += 1 break # print(price_counts) # 生成价格区间与书籍数量折线图 line = ( Line() .add_xaxis([str(interval) for interval in prices_intervalsStr[:-1]]) # X轴标签为价格区间 .add_yaxis("书籍数量", price_counts, symbol="circle", is_smooth=True, markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(type_="max")])) .set_global_opts( title_opts=opts.TitleOpts(title="价格区间与书籍数量折线图", pos_left="center", pos_bottom="bottom"), xaxis_opts=opts.AxisOpts(name="价格区间"), yaxis_opts=opts.AxisOpts(name="书籍数量"), datazoom_opts=opts.DataZoomOpts(range_start=0, range_end=100), ) ) # 生成时间与书籍数量折线图# 假设您的书籍数据保存在book_list_data中 # 提取每本书的出版年份 publish_dates = [int(book.pub_year.replace('-', '.').split('.')[0]) for book in book_list_data] print(publish_dates) # 使用Counter来计算每年出版的书的数量 publish_year_counter = Counter(publish_dates) print(publish_year_counter) # 确保结果包含连续的年份范围，并且将缺失的年份对应的数量设为 0 full_year_range = range(min(publish_dates), max(publish_dates) + 1) print(full_year_range) pub_year_counts = [(year, publish_year_counter[year]) for year in full_year_range] # 提取年份和对应的书籍数量 years = [str(year) for year, count in pub_year_counts] counts = [count for year, count in pub_year_counts] print(pub_year_counts) line_year_count = ( Line() .add_xaxis(years) .add_yaxis( series_name="出版书籍数量", y_axis=counts, markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(type_="max", name="最大值"), opts.MarkPointItem(type_="min", name="最小值")]), markline_opts=opts.MarkLineOpts(data=[opts.MarkLineItem(type_="average", name="平均值")]), ) .set_global_opts(title_opts=opts.TitleOpts(title="年份与出版书籍数量变化"), xaxis_opts=opts.AxisOpts(name="年份"), yaxis_opts=opts.AxisOpts(name="书籍数量"), ) ) # 创建一个页面 page = Page() # 将柱状图和饼图添加到页面中 page.add(line_year_count) page.add(bar) page.add(pie) page.add(line) # 生成HTML文件 page.render("book_analysis.html")