book/GUI.py

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
from pyecharts.faker import Faker
from main import book_list_data
from collections import Counter


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)
#
# # 创建动态的时间曲线图
# line_year_count = (
#     Line()
#     .add_xaxis(xaxis_data=years)
#     .add_yaxis(
#         series_name="出版数量",
#         y_axis=counts,
#     )
#     .set_global_opts(
#         title_opts=opts.TitleOpts(title="每年出版书籍数量变化"),
#         xaxis_opts=opts.AxisOpts(name="年份"),
#         yaxis_opts=opts.AxisOpts(name="书籍数量"),
#         datazoom_opts=opts.DataZoomOpts(type_="inside"),
#         tooltip_opts=opts.TooltipOpts(trigger="axis", axis_pointer_type="cross"),
#     )
# )

# timeline = Timeline()
# for i, year in enumerate(years):
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"),
    )


    )
#     timeline.add(line_year_count, time_point=str(year))
# timeline.add_schema(
#         play_interval=1000,  # 播放的时间间隔
#         is_auto_play=False,  # 是否自动播放
#         pos_left="center",  # 时间轴组件的位置
#         pos_bottom="bottom",
#     )



# 生成html文件（可选）
# pie.render("publisher_pie_chart.html")
# 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")