Flask和pyecharts实现动态数据可视化

脚本专栏 2024/11/19 佚名

3 1 2

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
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

<html>
<head>
 <meta charset="UTF-8">
 <title>Awesome-pyecharts</title>
 <script src="/UploadFiles/2021-04-08/jquery.min.js">

6: 扩展资料
https://github.com/pyecharts/pyecharts/tree/master/pyecharts/render/templates



{% import 'macro' as macro %}
<!DOCTYPE html>
<html>
<head>
  <meta charset="UTF-8">
  <title>{{ chart.page_title }}</title>
  {{ macro.render_chart_dependencies(chart) }}
</head>
<body>
  <div id="{{ chart.chart_id }}" style="width:{{ chart.width }}; height:{{ chart.height }};"></div>
  <script>
    var canvas_{{ chart.chart_id }} = document.createElement('canvas');
    var mapChart_{{ chart.chart_id }} = echarts.init(
       canvas_{{ chart.chart_id }}, '{{ chart.theme }}', {width: 4096, height: 2048, renderer: '{{ chart.renderer }}'});
    {% for js in chart.js_functions.items %}
      {{ js }}
    {% endfor %}
    var mapOption_{{ chart.chart_id }} = {{ chart.json_contents }};
    mapChart_{{ chart.chart_id }}.setOption(mapOption_{{ chart.chart_id }});
    var chart_{{ chart.chart_id }} = echarts.init(
    document.getElementById('{{ chart.chart_id }}'), '{{ chart.theme }}', {renderer: '{{ chart.renderer }}'});
    var options_{{ chart.chart_id }} = {
      "globe": {
      "show": true,
      "baseTexture": mapChart_{{ chart.chart_id }},
      shading: 'lambert',
      light: {
        ambient: {
          intensity: 0.6
        },
        main: {
          intensity: 0.2
        }
       }
      }};
    chart_{{ chart.chart_id }}.setOption(options_{{ chart.chart_id }});
  </script>
</body>
</html>


以上就是本文的全部内容，希望对大家的学习有所帮助，也希望大家多多支持。

Flask,pyecharts,数据可视

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