current position：Home>Visualization of epidemic data (entries in 2020)
Visualization of epidemic data (entries in 2020)
2021-08-27 00:12:40 【HH13】
Large screen of epidemic situation analysis in time and space
Temporal and spatial situation analysis of epidemic situation 、 Monitor the development trend of the epidemic 、 Assessment of epidemic prevention and control measures
Introduction to the work
The theme of the work is ： Temporal and spatial situation analysis of epidemic situation ： Using visual analysis technology , Analyze the temporal and spatial distribution pattern of epidemic situation 、 Monitor the development trend of the epidemic 、 Assessment of epidemic prevention and control measures .
The idea of this topic starts with the growth trend of the cumulative number of confirmed cases in each province over time and the growth trend of spatial distribution over time , Using the collected data, the temporal and spatial distribution of the cumulative number of confirmed cases in each province is mapped 、 Broken line diagram 、 In the form of stacked bars , Make a general analysis from the overall situation , Then, by displaying the detailed information related to the epidemic situation in different provinces at different granularity , To find out the reasons that affect the change of situation in different time periods （ Import from abroad 、 Promulgation of relevant policies, etc ）. At the same time, the epidemic situation will be confirmed 、 Death and other data are different from those of the provinces GDP、 Education level 、 Urbanization rate 、 Medical and health level , In order to find its relationship with GDP、 Education level 、 Whether there is a relationship between urbanization rate . Its target users are the government and other prevention and control organs , Through this system, the temporal and spatial distribution pattern of epidemic situation can be analyzed 、 Monitor the development trend of the epidemic 、 Assessment of epidemic prevention and control measures .
Through Tianxing data api Got 2 Species data （ The data comes from crawling the epidemic related data released by the National Health Commission ）
（1）weibo.json Before Sina Weibo real-time hot search 50 The data of
|hotword||string||The missing girl was confirmed to have appeared in Zhangzhou||Hot search topic|
|hotwordnum||string||129940||Hot search index|
（2）ProvinceData.json Details of epidemic situation in provinces and cities
|cityName||string||wuhan||The city name|
|confirmedCount||int||495||Number of confirmed cases|
From the National Bureau of statistics of China （2018 China Statistical Yearbook ） The data of
cityPopulation.json The population of each city
|Name||string||Chengdu||The city name|
|Value||int||1633||population size （ ten thousand people ）|
cityRate.json The urbanization rate of each province
|Name||string||Beijing||Name of province|
|Value||int||86.5||Urbanization rate （%）|
educationRate.json The penetration rate of higher education in each province （ Sampling data , The sampling ratio is 0.82‰, The total proportion of graduate students and undergraduate students ）
|Name||string||sichuan||Name of province|
|Value||int||0.056785446||Higher education rate|
doctor.json The number of health technicians per 10000 people in each province
|Name||string||sichuan||Name of province|
|Value||int||67||The number of health technicians per 10000 people|
2020-01-10 to 2020-02-06 Data from countries , The provinces , Wuhan Health Commission's epidemic situation announcement ,2020-02-07 The post data is collected from today's headlines interface
|Field explain ****||Field name ****||Field explanation ****|
|String||province||Province （ Foreign is empty ）|
|String||city||The city （ Foreign is empty ）|
|Integer||confirmed||Cumulative number of confirmed cases|
|Integer||suspected||Number of suspects|
|Integer||cured||The number of people cured|
|Integer||dead||Cumulative death toll|
DXYArea.csv The data source is dingxiangyuan
|Field name||type||Field explanation|
|continentName||string||Chinese name of the continent|
|continentEnglishName||string||English name of the continent|
|countryEnglishName||string||English name of the country|
|provinceName||string||Name of province|
|provinceEnglishName||string||English name of province|
|province_confirmedCount||int||Cumulative number of confirmed cases|
|province_suspectedCount||int||Cumulative number of suspected patients|
datas.json Overseas input data （ Manually collect from online news ）
|Date||date||2 month 2 Japan||Time|
|provinceName||string||liaoning||Enter the province|
|countryName||string||Japan||Country of origin|
|Count||int||2||Enter the quantity of the day|
|Total||int||10||Cumulative input quantity|
Overall process of analysis task and visual analysis
Analysis task ： Analyze the temporal and spatial distribution pattern of epidemic situation 、 Monitor the development trend of the epidemic 、 Assessment of epidemic prevention and control measures .
Visual analysis of the overall process ：
- Observe the change curve of the number of epidemic cases in China 、 Map , Overall perception of the temporal and spatial distribution of the epidemic situation .
By observing the change curve of national epidemic situation and the spatial distribution pattern of national cumulative diagnosis map over time , Find out some fluctuation nodes of curve changes and abnormal color parts of the map , Then click the corresponding province on the map to view its details .
- Click the urbanization rate and the number of confirmed cases , In the pop-up panel , Check the relationship between various factors and the number of confirmed epidemic cases in detail , You can view the urbanization rate of each province 、GDP、 Some potential relationships between education level and the number of confirmed cases .
3. Click provinces on the map , View the province details in the corresponding linkage panel , To further analyze the causes of different patterns at different granularity , For example, click Hubei Province , The linkage panel will display the details of Hubei .
Data processing and algorithm model
about Wuhan-2019-nCoV.csv Data files , Because the data comes from the National Health Commission , The Health Commission publishes data in the form of documents , Therefore, when crawling, there will be some deviations due to the change of document form , So for the vacant data , Will manually compare the data of the National Health Commission to complete .
about DXYArea.csv Data files , Among them, the time interval of data crawling , As a result, there may be multiple pieces of data every day , So as to generate a large number of redundant and repeated data , We go through pandas We're going to process it , For data from the same province or country every day , We only take the latest one released on that day , Take this as the data of the current day .
4 month 17 The National Health Commission revised the data of cumulative diagnosis in Hubei on June , So the data is 4 month 17 There will be small fluctuations on the day .
Visualization and interaction design
main interface ：
（1） The system is divided into hot search word cloud module 、 The proportion of confirmed cases in each province 、 New people （ Native land / Import from abroad ） Distribution 、 Map 、 The number of epidemic cases is displayed 、 The relationship between urbanization rate and the number of confirmed cases 、 Import from abroad top10 Province 、 Distribution of epidemic cases in provinces （ mortality 、 The proportion of infected people ） modular .
（2） Scroll down the slider and there are two more modules , They are the change curves of the number of epidemic cases in provinces 、 National epidemic population change curve （ A stacked bar chart of the number of new people in the country ） modular .
Among them, the number of newly added people （ Native land / Import from abroad ） Distribution 、 Distribution of epidemic cases in provinces （ mortality 、 The proportion of infected people ）、 The three modules of the change curve of the number of epidemic cases in provinces are linked with the map , Click on the provinces on the map , These three panels are updated to click the details of provinces .
（3） The map module can display the national cumulative diagnosis distribution at different times according to the dragging time axis
（4） Click the overseas input distribution button , The pop-up panel displays the overseas input propagation diagram , You can also drag the timeline to view the cumulative overseas input data at different times
（5） Click on the map , The corresponding linkage panel will display the detailed information of the corresponding province , For example, click Heilongjiang , The linkage panel displays the information as shown in the figure
（6） Click the relationship between urbanization rate and number of confirmed cases , Different factors can be viewed in the pop-up panel （ Such as GDP、 Higher education 、 Urbanization rate ） Potential link with the number of confirmed cases
experiment \ Case study \ Scene analysis
By observing the change of epidemic distribution over time on the map , We found the spatial distribution pattern of the epidemic with time in space , The specific mode is as follows ：
At the beginning of January, only Hubei was the infected area .
January 20 After the th, it began to spread out , Almost all of Hubei's neighboring provinces have confirmed patients .
from 1 month 24 The epidemic distribution map of No. 1 can be seen except Qinghai 、 Almost all the other provinces in Tibet have confirmed patients . from 2 month 10 It can be seen that confirmed cases have appeared in all provinces of the country , The number of confirmed cases in the provinces close to Hubei is significantly higher than that in other provinces .
from 5 month 13 According to the epidemic distribution map of the day , The overall distribution trend is ： The areas with a large number of infected people are almost in the Hu Huanyong line （ Heihe - tengchong ） The southeast plate , Hu Huanyong line plays an extremely important role in geography , It's about agriculture 、 Population 、GDP, So we click on the relationship between urbanization rate and the number of confirmed cases , View details in “ The provinces GDP Scatter diagram of the relationship with the number of confirmed patients ”（ chart 6-2）. It is found that GDP Almost all provinces with high level of diagnosis are far more than other provinces , because GDP High represents large population mobility 、 High population density , More conducive to the spread of the virus . Therefore, in cities with high population density, we should strictly control all kinds of epidemic prevention Links , Prevent local rebound , Regular sampling for nucleic acid detection .
At the same time, from figure 6-1 It can also be seen that there is an anomaly in the map distribution , Heilongjiang, far from Hubei, is very dark , It represents a large number of confirmed patients . This is inconsistent with the previously found law that there are more infected people in neighboring Hubei . Then we analyze it through the national stacked bar chart , Due to the new in Hubei 、 The cumulative number of confirmed cases is much higher than that in other provinces , When we check, we block Hubei first （ The red value is Hubei ）, Because of Taiwan 、 Hong Kong 、 The data of Macao is not perfect, so we also block Hong Kong 、 Macau 、 Taiwan .
You can find 3 Month to 4 Mid month , Small scale growth in some provinces , Among them, Heilongjiang 、 Inner Mongolia 、 Shanghai accounts for the largest proportion of growth , So we click on these three provinces to see their detailed growth personnel distribution .
By increasing the number of people （ Native land / overseas ） Distribution , Can see in 4 The increase in the number of abnormal diagnoses in these three provinces in June was due to a large number of overseas imports , Click overseas to enter the diagnosis distribution , View overseas input details .
Can see that recently , A large number of patients imported from abroad have poured into China , The country of origin is Britain 、 The United States 、 Russia 、 Brazil 、 Most of Spain , These countries are also one of the most serious epidemic areas in the world . therefore , A key point of prevention and control is to strictly prevent overseas import , Strict immigration procedures , Strictly control the number of people entering the country , When entering the country, it must be tested for nucleic acid , Forced isolation 14 God .
Discussion and summary
Through analysis , We extracted the temporal and spatial distribution of the epidemic situation , As follows ：
Time distribution situation ：2019 year 12 month 1 Japan -2020 year 1 month 20, Hubei has seen small-scale growth , There are no confirmed patients in other provinces
2020 year 1 month 20 Japan -2020 year 2 month 12 Japan , A large-scale outbreak occurred across the country , The number of confirmed cases has risen sharply ,2 month 12 There is an inflection point on the th .
2020 year 2 month 13 There is an inflection point on the th , The number of people growing in a single day has decreased .
2020 year 2 month 13 Japan -3 month 1 Japan , The number of people growing in a single day is decreasing .
2020 year 3 month 1 After the day, the provinces outside the north of the lake are basically cleared .
2020 year 3 month 10-2020 year 4 month 15 Japan , A few provinces outside Hubei have seen small-scale growth , It is mainly imported from abroad and asymptomatic infected people .
Spatial distribution situation ： Similar to the time distribution
2019 year 12 month 1 Japan -2020 year 1 month 20, Hubei has a confirmed patient , There are no confirmed patients in other provinces .
2020 year 1 month 21 Japan -2020 year 1 month 29 Japan , There have been confirmed patients all over the country .
2020 year 1 month 30 Japan -2020 year 3 month 1 Japan , There was a large-scale outbreak of confirmed patients near Hubei .
2020 year 3 month 2 Japan - at present , A few provinces , Such as Heilongjiang 、 guangdong 、 Beijing 、 Small scale outbreak in Inner Mongolia .
The overall situation of spatial distribution is ： Areas with a large number of confirmed cases are mostly distributed in the southeast of Hu Huanyong line , This is related to population density 、 Population mobility has a great relationship .
Key points of prevention and control ：
The prevention and control in the post epidemic era should mainly focus on the prevention and control of overseas imports and asymptomatic infections .
For overseas input ：
Strictly control the entry procedures and the number of people , For entry personnel, their case history must be strictly examined 、 Contact history （ Whether it comes from countries with serious epidemic ）, For entry personnel, it is necessary to 100% Detect whether the nucleic acid is positive . Strict isolation is required during testing . At the same time, it focuses on the four aviation hub areas （ Beijing 、 Shanghai 、 Guangzhou 、 Chengdu ）, This kind of aviation hub is the top priority of prevention and control , Because the daily traffic is huge , There is a large flow of people from abroad . At the same time, we should also pay attention to China's border provinces , Such as Inner Mongolia 、 heilongjiang 、 Tibet 、 xinjiang , Many areas along the border are sparsely populated , It is prone to illegal immigrants , At the same time, the medical level in many border areas is limited , Unable to detect and treat in time .
For asymptomatic infections ： At present, there is little information about asymptomatic infection , Generally, only the number of people is published , I hope to further publish its relatively detailed information later , Such as activity track, etc . At the same time, scientific and effective sampling nucleic acid detection should be carried out at regular intervals according to the standards in the medical field , To understand the situation of asymptomatic infected people in the area .
author[HH13],Please bring the original link to reprint, thank you.
The sidebar is recommended
- Crazy blessing! Tencent boss's "million JVM learning notes", real topic of Huawei Java interview 2020-2021
- How to implement injection in vuex source code?
- JQuery operation select (value, setting, selected)
- An article disassembles the pyramid architecture behind the gamefi outbreak
- BEM - a front-end CSS naming methodology
- [vue3] encapsulate custom global plug-ins
- Error using swiper plug-in in Vue
- Another ruthless character fell by 40000, which was "more beautiful" than Passat and maiteng, and didn't lose BMW
guess what you like
Huang Lei basks in Zhang Yixing's album, and the relationship between teachers and apprentices is no less than that in the past. Netizens envy Huang Lei
He was cheated by Wang Xiaofei and Li Chengxuan successively. Is an Yixuan a blessed daughter and not a blessed home?
Zhou Shen sang the theme song of the film "summer friends and sunny days" in mainland China. Netizen: endless aftertaste
Pink is Wangyuan online! Back to the peak! The new hairstyle is creamy and sassy
Front end interview daily 3 + 1 - day 858
Spring Webflux tutorial: how to build reactive web applications
[golang] walk into go language lesson 24 TCP high-level operation
August 23, 2021 Daily: less than three years after its establishment, Google dissolved the health department
The female doctor of Southeast University is no less beautiful than the female star. She has been married four times, and her personal experience has been controversial
There are many potential safety hazards in Chinese restaurant. The top of the program recording shed collapses, and the artist will fall down if he is careless
- Anti Mafia storm: He Yun's helpless son, Sun Xing, is destined to be caught by his dry son
- Introduction to flex flexible layout in CSS -- learning notes
- CSS learning notes - Flex layout (Ruan Yifeng tutorial summary)
- Today, let's talk about the arrow function of ES6
- Some thoughts on small program development
- Talk about mobile terminal adaptation
- Unwilling to cooperate with Wang Yibo again, Zhao Liying's fans went on a collective strike and made a public apology in less than a day
- JS function scope, closure, let, const
- Zheng Shuang's 30th birthday is deserted. Chen Jia has been sending blessings for ten years. Is it really just forgetting to make friends?
- Unveil the mystery of ascension
- Asynchronous solution async await
- Analysis and expansion of Vue infinite scroll source code
- Compression webpack plugin first screen loading optimization
- Specific usage of vue3 video play plug-in
- "The story of huiyeji" -- people are always greedy, and fairies should be spotless!
- Installing Vue devtool for chrome and Firefox
- Basic usage of JS object
- Two easy-to-use animation JS that make the page move
- Front end Engineering - scaffold
- Java SQL Server intelligent fixed asset management, back end + front end + mobile end
- Array de duplication problem solution - Nan recognition problem
- New choice for app development: building mobile applications using Vue native
- New gs8 Chengdu auto show announces interior Toyota technology blessing
- Vieira officially terminated his contract and left the team. The national security club sent blessings to him
- Less than 200000 to buy a Ford RV? 2.0T gasoline / diesel power, horizontal bed / longitudinal bed layout can be selected
- How does "heart 4" come to an end? Pinhole was boycotted by the brand, Ma Dong deleted the bad comments, and no one blessed him
- We are fearless in epidemic prevention and control -- pay tribute to the front-line workers of epidemic prevention!
- Front end, netty framework tutorial
- Xiaomi 11 | miui12.5 | android11 solves the problem that the httpcanary certificate cannot be installed
- The wireless charging of SAIC Roewe rx5 plus is so easy to use!
-  typescript
- CSS transform Complete Guide (Second Edition) flight.archives 007
- Ajax foundation - HTTP foundation of interview essential knowledge
- Cloud lesson | explain in detail how Huawei cloud exclusive load balancing charges
- [JS] 10. Closure application (loop processing)
- Left hand IRR, right hand NPV, master the password of getting rich