Covid19, Analysis, Visualization, Prediction

Covid19, Analysis, Visualization, Prediction

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Author: ZhuoFei, Zhou

Date: 2020/10/5

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Introduction

Covid-19

Novel Coronavirus 2019, on 12 January 2020, WHO officially named it 2019-NCOV. Coronaviruses are a large family of viruses known to cause colds and more serious illnesses such as Middle East Respiratory syndrome (MERS) and severe acute respiratory syndrome (SARS). Novel Coronavirus is a novel coronavirus strain that has never been found in humans before. More information is available.百度百科

data

Data from COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University.link

• time series covid19 confirmed global.csv.(github link).

• time series covid19 deaths global.csv.(github link)

• time serise covid19 recoverd global.csv(github link)

• cases contry.csv.(github link)

• cases time.csv. (github link)

download here:

• “time_series_covid19_confirmed_global.csv”
• “time_series_covid19_deaths_global.csv”
• “time_series_covid19_recovered_global.csv”
• “cases_country.csv”
• “cases_time.csv”

import some julia packages.

using DataFrames
using CSV
using DelimitedFiles
using BenchmarkTools
using Queryverse
using Dates
using Plots
pgfplotsx()

using Flux
using Flux: @epochs
using IterTools: ncycle 
using Parameters: @with_kw

Analysis

read Global data, and Data-operate

#read data:
dt, Header = readdlm("time_series_covid19_confirmed_global.csv", ',', header=true)
dt_deaths, Header_deaths = readdlm("time_series_covid19_deaths_global.csv", ',', header=true)
dt_recover,Header_recov = readdlm("time_series_covid19_recovered_global.csv",',',header=true)

creat a new dataframe to store data

confirmed_num = []
deaths_num = []
recovered_num = []
for i in 5:259
	push!(confirmed_num, sum(dt[:, i]))
	push!(deaths_num, sum(dt_deaths[:, i]))
	push!(recovered_num, sum(dt_recover[:,i]))
end
dates = Date(2020, 1, 22):Day(1):Date(2020, 10, 2)
Global