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In fact, it's very simple. It teaches you to easily realize the cool data visualization big screen

2022-07-07 09:29:00 【Python data mining】

Hello everyone , Today I'd like to share a Python Visual large screen project ,GitHub Address ：https://github.com/TurboWay/big_screen,

The project is simple in structure and easy to use , Data visualization can be realized by directly transmitting data . Like to remember to collect 、 Focus on 、 give the thumbs-up .

notes : Technical exchange is provided at the end of the article 、 Source code acquisition method

install

The project relies on third-party modules flask, Therefore, we need to install dependencies first , Installation command ：pip install -i https://pypi.tuna.tsinghua.edu.cn/simple flask.

Share some source code

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# @Author : way
# @Site : 
# @Describe:

import json

class SourceDataDemo:

    def __init__(self):
        self.title = ' General template for big data visualization display board '
        self.counter = {
    'name': '2018 Total annual income ', 'value': 12581189}
        self.counter2 = {
    'name': '2018 Total annual expenditure ', 'value': 3912410}
        self.echart1_data = {
    
            'title': ' Industry distribution ',
            'data': [
                {
    "name": " Supermarket stores ", "value": 47},
                {
    "name": " Education and training ", "value": 52},
                {
    "name": " The real estate ", "value": 90},
                {
    "name": " Life service ", "value": 84},
                {
    "name": " Car sales ", "value": 99},
                {
    "name": " Tourist Hotel ", "value": 37},
                {
    "name": " Hardware and building materials ", "value": 2},
            ]
        }
        self.echart2_data = {
    
            'title': ' Province Distribution ',
            'data': [
                {
    "name": " Zhejiang ", "value": 47},
                {
    "name": " Shanghai ", "value": 52},
                {
    "name": " jiangsu ", "value": 90},
                {
    "name": " guangdong ", "value": 84},
                {
    "name": " Beijing ", "value": 99},
                {
    "name": " Shenzhen ", "value": 37},
                {
    "name": " anhui ", "value": 150},
            ]
        }
        self.echarts3_1_data = {
    
            'title': ' Age distribution ',
            'data': [
                {
    "name": "0 Under the age of ", "value": 47},
                {
    "name": "20-29 year ", "value": 52},
                {
    "name": "30-39 year ", "value": 90},
                {
    "name": "40-49 year ", "value": 84},
                {
    "name": "50 Years of age or older ", "value": 99},
            ]
        }
        self.echarts3_2_data = {
    
            'title': ' Career distribution ',
            'data': [
                {
    "name": " Electronic Commerce ", "value": 10},
                {
    "name": " education ", "value": 20},
                {
    "name": "IT/ Internet ", "value": 20},
                {
    "name": " Finance ", "value": 30},
                {
    "name": " Student ", "value": 40},
                {
    "name": " other ", "value": 50},
            ]
        }
        self.echarts3_3_data = {
    
            'title': ' Interest distribution ',
            'data': [
                {
    "name": " automobile ", "value": 4},
                {
    "name": " tourism ", "value": 5},
                {
    "name": " Finance and economics, ", "value": 9},
                {
    "name": " education ", "value": 8},
                {
    "name": " Software ", "value": 9},
                {
    "name": " other ", "value": 9},
            ]
        }
        self.echart4_data = {
    
            'title': ' Time trend ',
            'data': [
                {
    "name": " Android ", "value": [3, 4, 3, 4, 3, 4, 3, 6, 2, 4, 2, 4, 3, 4, 3, 4, 3, 4, 3, 6, 2, 4, 4]},
                {
    "name": "IOS", "value": [5, 3, 5, 6, 1, 5, 3, 5, 6, 4, 6, 4, 8, 3, 5, 6, 1, 5, 3, 7, 2, 5, 8]},
            ],
            'xAxis': ['01', '02', '03', '04', '05', '06', '07', '08', '09', '11', '12', '13', '14', '15', '16', '17',
                      '18', '19', '20', '21', '22', '23', '24'],
        }
        self.echart5_data = {
    
            'title': ' Province TOP',
            'data': [
                {
    "name": " Zhejiang ", "value": 2},
                {
    "name": " Shanghai ", "value": 3},
                {
    "name": " jiangsu ", "value": 3},
                {
    "name": " guangdong ", "value": 9},
                {
    "name": " Beijing ", "value": 15},
                {
    "name": " Shenzhen ", "value": 18},
                {
    "name": " anhui ", "value": 20},
                {
    "name": " sichuan ", "value": 13},
            ]
        }
        self.echart6_data = {
    
            'title': ' First tier cities ',
            'data': [
                {
    "name": " Zhejiang ", "value": 80, "value2": 20, "color": "01", "radius": ['59%', '70%']},
                {
    "name": " Shanghai ", "value": 70, "value2": 30, "color": "02", "radius": ['49%', '60%']},
                {
    "name": " guangdong ", "value": 65, "value2": 35, "color": "03", "radius": ['39%', '50%']},
                {
    "name": " Beijing ", "value": 60, "value2": 40, "color": "04", "radius": ['29%', '40%']},
                {
    "name": " Shenzhen ", "value": 50, "value2": 50, "color": "05", "radius": ['20%', '30%']},
            ]
        }
        self.map_1_data = {
    
            'symbolSize': 100,
            'data': [
                {
    'name': ' Haimen ', 'value': 239},
                {
    'name': ' ordos ', 'value': 231},
                {
    'name': ' Zhaoyuan ', 'value': 203},
            ]
        }

    @property
    def echart1(self):
        data = self.echart1_data
        echart = {
    
            'title': data.get('title'),
            'xAxis': [i.get("name") for i in data.get('data')],
            'series': [i.get("value") for i in data.get('data')]
        }
        return echart

    @property
    def echart2(self):
        data = self.echart2_data
        echart = {
    
            'title': data.get('title'),
            'xAxis': [i.get("name") for i in data.get('data')],
            'series': [i.get("value") for i in data.get('data')]
        }
        return echart

    @property
    def echarts3_1(self):
        data = self.echarts3_1_data
        echart = {
    
            'title': data.get('title'),
            'xAxis': [i.get("name") for i in data.get('data')],
            'data': data.get('data'),
        }
        return echart

    @property
    def echarts3_2(self):
        data = self.echarts3_2_data
        echart = {
    
            'title': data.get('title'),
            'xAxis': [i.get("name") for i in data.get('data')],
            'data': data.get('data'),
        }
        return echart

    @property
    def echarts3_3(self):
        data = self.echarts3_3_data
        echart = {
    
            'title': data.get('title'),
            'xAxis': [i.get("name") for i in data.get('data')],
            'data': data.get('data'),
        }
        return echart

    @property
    def echart4(self):
        data = self.echart4_data
        echart = {
    
            'title': data.get('title'),
            'names': [i.get("name") for i in data.get('data')],
            'xAxis': data.get('xAxis'),
            'data': data.get('data'),
        }
        return echart

    @property
    def echart5(self):
        data = self.echart5_data
        echart = {
    
            'title': data.get('title'),
            'xAxis': [i.get("name") for i in data.get('data')],
            'series': [i.get("value") for i in data.get('data')],
            'data': data.get('data'),
        }
        return echart

    @property
    def echart6(self):
        data = self.echart6_data
        echart = {
    
            'title': data.get('title'),
            'xAxis': [i.get("name") for i in data.get('data')],
            'data': data.get('data'),
        }
        return echart

    @property
    def map_1(self):
        data = self.map_1_data
        echart = {
    
            'symbolSize': data.get('symbolSize'),
            'data': data.get('data'),
        }
        return echart


class SourceData(SourceDataDemo):

    def __init__(self):
        """  according to  SourceDataDemo  Just overwrite the data in the format of  """
        super().__init__()
        self.title = ' General template for big data visualization display board '

class CorpData(SourceDataDemo):

    def __init__(self):
        """  according to  SourceDataDemo  Just overwrite the data in the format of  """
        super().__init__()
        with open('corp.json', 'r', encoding='utf-8') as f:
            data = json.loads(f.read())
        self.title = data.get('title')
        self.counter = data.get('counter')
        self.counter2 = data.get('counter2')
        self.echart1_data = data.get('echart1_data')
        self.echart2_data = data.get('echart2_data')
        self.echarts3_1_data = data.get('echarts3_1_data')
        self.echarts3_2_data = data.get('echarts3_2_data')
        self.echarts3_3_data = data.get('echarts3_3_data')
        self.echart4_data = data.get('echart4_data')
        self.echart5_data = data.get('echart5_data')
        self.echart6_data = data.get('echart6_data')
        self.map_1_data = data.get('map_1_data')

class JobData(SourceDataDemo):

    def __init__(self):
        """  according to  SourceDataDemo  Just overwrite the data in the format of  """
        super().__init__()
        with open('job.json', 'r', encoding='utf-8') as f:
            data = json.loads(f.read())
        self.title = data.get('title')
        self.counter = data.get('counter')
        self.counter2 = data.get('counter2')
        self.echart1_data = data.get('echart1_data')
        self.echart2_data = data.get('echart2_data')
        self.echarts3_1_data = data.get('echarts3_1_data')
        self.echarts3_2_data = data.get('echarts3_2_data')
        self.echarts3_3_data = data.get('echarts3_3_data')
        self.echart4_data = data.get('echart4_data')
        self.echart5_data = data.get('echart5_data')
        self.echart6_data = data.get('echart6_data')
        self.map_1_data = data.get('map_1_data')

function

First , We from GitHub Download the project locally , Of course, it can also be on the official account Python waiter The background to reply big_screen Direct access to .

After the project is downloaded , We enter the project root path , As shown below ：

then , Hold down Shift spot Right mouse button , Then choose Open command window here (W), After the command window opens, enter the command ：python app.py Start project .

After the project starts , We can directly enter the address in the browser to access , Here's an example .

General template for big data visualization display board ：http://127.0.0.1:5000, As shown below ：

4600 Large screen visualization of enterprise data ：http://127.0.0.1:5000/corp, As shown below ：

Xiamen 10 10000 recruitment data (2020-09) Large screen visualization ：http://127.0.0.1:5000/job, As shown below ：

Use

edit data.py Medium SourceData class ( Or add a new class , If it is added, it needs to be edited app.py Add route , Please refer to CorpData/JobData)
Read your data from anywhere , according to SourceDataDemo Data format , Fill in SourceData class
function python app.py Check the effect of data changes

Contact information

At present, a technical exchange group has been opened , Group friends have exceeded 3000 people , The best way to add notes is ： source + Interest direction , Easy to find like-minded friends , Data acquisition can also be added

The way 1、 Add microsignals ：dkl88191, remarks ： come from CSDN
The way 2、 WeChat search official account ：Python Learning and data mining , The background to reply ： Add group
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