import pandas as pd
import matplotlib.pyplot as plt
from pyecharts.charts import Bar,Scatter,Pie
from pyecharts import options as opts
from pyecharts.charts import Scatter3D

from pyecharts.charts import WordCloud
from pyecharts.globals import SymbolType
from pyecharts.charts import Timeline

df =pd.read_csv('flaskProject/data/export.csv')
def tubiao_country_bar():
    country_counts = df['country'].value_counts().head(10)
    bar=(
        Bar()
        .add_xaxis(country_counts.index.tolist())
        .add_yaxis("电影数量",country_counts.tolist())
        .set_global_opts(title_opts=opts.TitleOpts("按国家分组统计电影数量 Top 10"))
    )
    bar.render('country_movie_count.html')

def tubiao_top10_reviews():
    top10_reviews=df.nlargest(10,'num_reviews')
    bar=(
        Bar()
        .add_xaxis(top10_reviews['title'].tolist())
        .add_yaxis("评价人数",top10_reviews['num_reviews'].tolist())
        .set_global_opts(title_opts=opts.TitleOpts(title="评价人数 Top 10"))
    )
    bar.render('top10reviews.html')

    scatter=(
        Scatter()
        .add_xaxis(df['ranking'].tolist())
        .add_yaxis('电影评分',df['rating'].tolist())
        .set_global_opts(
            title_opts=opts.TitleOpts(title="高分电影评分-排名散点分布图"),
            xaxis_opts=opts.AxisOpts(type_='value',name="电影排名"),
            yaxis_opts=opts.AxisOpts(type_='value', name="电影评分")
        )
    )
    scatter.render("rating_ranting_scatter.html")




tubiao_country_bar()
tubiao_top10_reviews()