Flsk&pyecharts 动态数据可视化

1:数据源

Hollywood Movie Dataset: 好莱坞2006-2011数据集 

实验目的: 实现 统计2006-2011的数据综合统计情况,进行数据可视化

gitee地址:  https://gitee.com/dgwcode/an_example_of_py_learning/tree/master/MovieViwer

1.数据例子:

Film ,Major Studio,Budget
300,Warner Bros,
300,Warner Bros.,65
3:10 to Yuma,Lionsgate,48
30 Days of Night,Independent,32
Across the Universe,Independent,45
Alien vs. Predator -- Requiem,Fox,40
Alvin and the Chipmunks,Fox,70
American Gangster,Universal,10
Bee Movie,Paramount,15
Beowulf,Paramount,15
Blades of Glory,Paramount,61

 

 2: 环境

pycharm新建Flask项目

 

 

 

 

 3 数据处理:

Film ,Major Studio,Budget 为数据的三个标题 截断这三个数据就行

import pandas as pd
from threading import Timer
import math


# coding=utf-8
def getTotalData():
    data1 = pd.read_csv('static/1.csv');
    data2 = pd.read_csv('static/2.csv');
    data3 = pd.read_csv('static/3.csv');
    data4 = pd.read_csv('static/4.csv');
    data5 = pd.read_csv('static/5.csv');
    datadic1 = [];
    datadic2 = [];
    datadic3 = [];
    datadic4 = [];
    datadic5 = [];
    # 处理数据.csv
    for x, y in zip(data1['Major Studio'], data1['Budget']):
        datadic1.append((x, y))
    for x, y in zip(data2['Major Studio'], data2['Budget']):
        datadic2.append((x, y))
    for x, y in zip(data3['Lead Studio'], data3['Budget']):
        datadic3.append((x, y))
    for x, y in zip(data4['Lead Studio'], data4['Budget']):
        datadic4.append((x, y))
    for x, y in zip(data5['Lead Studio'], data5['Budget']):
        datadic5.append((x, y))
    totaldata = [];
    totaldata.append(datadic1);
    totaldata.append(datadic2);
    totaldata.append(datadic3);
    totaldata.append(datadic4);
    totaldata.append(datadic5);
    return totaldata;


indexx = 0;
curindex = 0;
end = 5;
returnData = dict();


# 定时处理数据
def dataPre():
    global indexx, end, curindex, flag, returnData;
    totalData = getTotalData();  # list[map]
    # x = len(totalData[0]) + totalData[1].len() + totalData[2].len() + totalData[3].len() + totalData[4].len();
    data = totalData[indexx];
    # init
    # print(curindex, end, indexx)
    # print(len(data))
    for k, v in data[curindex:end]:
        if v == "nan" or math.isnan(v):# 截断 k v中 nan
            continue;
        if returnData.get(k, -1) == -1:
            print(k, v);
            returnData[k] = v;
        else:
            returnData[k] = returnData[k] + v;
    print(len(returnData))
    if end < len(data) - 20:
        curindex = end;
        end = end + 20;
    if end >= len(data) - 20:
        indexx += 1;
        curindex = 0;
        end = 20;
    t = Timer(2, dataPre)
    t.start()
    print(returnData.keys(), end='\n')
    return returnData;


if __name__ == "__main__":
    dataPre();

 

4:实际程序入口

from flask import Flask, render_template
from pyecharts.charts import Bar
from pyecharts import options as opts
import math
import dealdata
from threading import Timer
from pyecharts.globals import ThemeType


app = Flask(__name__, static_folder="templates")


@app.route('/')
def hello_world():
    dataPre();# 数据入口
    return render_template("index.html")

# 定义全局索引
indexx = 0;
curindex = 0;
end = 5;
returnData = dict();


# 定时处理数据
def dataPre():
    global indexx, end, curindex, flag, returnData;
    totalData = dealdata.getTotalData();  # list[map]
    # x = len(totalData[0]) + totalData[1].len() + totalData[2].len() + totalData[3].len() + totalData[4].len();
    data = totalData[indexx];
    #print(totalData)
    # init
    # print(curindex, end, indexx)
    # print(len(data))
    for k, v in data[curindex:end]:
        if v == "nan" or math.isnan(v):  # 截断 k v中 nan
            continue;
        if returnData.get(k, -1) == -1:
            returnData[k] = v;
        else:
            returnData[k] = returnData[k] + v;
    print(len(returnData)) # 反应长度关系
    if end < len(data) - 15: # 参数为截断的项数 与前端时间要对应
        curindex = end;
        end = end + 15;
    if end >= len(data) - 15:
        indexx += 1;
        curindex = 0;
        end = 15;
    t = Timer(1, dataPre)
    t.start()
    #print(returnData, end='\n')



def bar_reversal_axis() -> Bar:
    global returnData;
    #print(sorted(returnData.items(), key=lambda x: x[1]))
    sorted(returnData.items(), key=lambda x: x[1],reverse=False)
    #print(returnData.keys())
    c = (
        Bar({"theme": ThemeType.MACARONS})
            .add_xaxis(list(returnData.keys()))
            .add_yaxis("电影公司名称:",list(returnData.values()),color="#BF3EFF")
            .reversal_axis()
            .set_series_opts(label_opts=opts.LabelOpts(position="right",color="#BF3EFF",
                                                       font_size=12))
            .set_global_opts(title_opts=opts.TitleOpts(title="2007-2011好莱坞电影最受欢迎公司",
                                                      pos_left='60%',subtitle="当前"+str(2006+indexx)+"年"))

    )
    return c;


@app.route("/barChart")
def index():
    c = bar_reversal_axis();
    return c.dump_options_with_quotes();

if __name__ == '__main__':
    app.run();

5: 前端

  "UTF-8">
  
  
  
    



  
"bar" style="width:1024px; height:1024px;">
  

 

6: 扩展资料

 

https://github.com/pyecharts/pyecharts/tree/master/pyecharts/render/templates

 

 

 

{% import 'macro' as macro %}



    "UTF-8">
    
    {{ macro.render_chart_dependencies(chart) }}


    
"{{ chart.chart_id }}" style="width:{{ chart.width }}; height:{{ chart.height }};">