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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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