Exploring data on COVID-19¶

In this post, We will cover the basic syntax of julia language, and explore the data related on COVID-19. This is the summary of lecture "Introduction to Computational Thinking with Julia, with applications to modeling the COVID-19 Pandemic" from MIT.

toc: true
badges: true
comments: true
author: Chanseok Kang
categories: [Julia, MIT]
image: images/US_data.png

Why Julia?¶

Julia: Developed at MIT by Prof. Alan Edelman's group
Released in 2012.
Current release: 1.4
Free, open source software
developed by world-wide community on Github
Over 3000 registered packages in wide range of domains

Julia¶

Modern, powerful language
Interactive but high performance (fast) - previously mutually exclusive
Syntax: similar to Python / Matlab / R
But carefully designed for high-performance computational science & engineering applications
Design means that most of Julia is written in Julia itself
Hence much easier to examine and modify algorithms

us_data

In [1]:

url = "https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv"

Out[1]:

"https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv"

In [2]:

url

Out[2]:

"https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv"

In [3]:

typeof(url)

Out[3]:

String

In [4]:

Out[4]:

* (generic function with 357 methods)

In [5]:

(1 + 2im) * (3 + im)

Out[5]:

1 + 7im

In [6]:

@which (1+ 2im) * (3 + im)

Out[6]:

*(z::Complex, w::Complex) in Base at complex.jl:277

Grab the data¶

In [7]:

download(url, "covid_data.csv")

Out[7]:

"covid_data.csv"

In [8]:

readdir

Out[8]:

readdir (generic function with 2 methods)

In [9]:

readdir()

Out[9]:

234-element Array{String,1}:
 ".ipynb_checkpoints"
 "2020-05-21-Software-Engineering-Practices-Pt-1.ipynb"
 "2020-05-22-01-Decorator.ipynb"
 "2020-05-22-02-More-On-Decorators.ipynb"
 "2020-05-23-01-Read-clean-and-validate.ipynb"
 "2020-05-23-02-Distributions.ipynb"
 "2020-05-24-01-Relationships.ipynb"
 "2020-05-24-02-Multivariate-Thinking.ipynb"
 "2020-05-25-01-Preparing-the-data-for-analysis.ipynb"
 "2020-05-25-02-Exploring-the-relationship-between-gender-and-policing.ipynb"
 "2020-05-25-03-Visual-exploratory-data-analysis.ipynb"
 "2020-05-25-04-Software-Engineering-Practices-Pt-2.ipynb"
 "2020-05-26-01-Analyzing-the-effect-of-weather-on-policing.ipynb"
 ⋮
 "2020-12-28-01-Exploring-data-on-COVID-19.ipynb"
 "README.md"
 "checkpoints"
 "covid_data.csv"
 "dataset"
 "html"
 "image"
 "models"
 "my_icons"
 "spark-warehouse"
 "utils"
 "video"

Install Package¶

In [10]:

using Pkg   # built-in package manager in Julia: Pkg
Pkg.add("CSV")   # calls the `add` function from the module Pkg.  This installs a package

   Updating registry at `C:\Users\kcsgo\.julia\registries\General`

   Updating git-repo `https://github.com/JuliaRegistries/General.git`

  Resolving package versions...
   Updating `C:\Users\kcsgo\.julia\environments\v1.4\Project.toml`
 [no changes]
   Updating `C:\Users\kcsgo\.julia\environments\v1.4\Manifest.toml`
 [no changes]

In [11]:

Pkg.add("DataFrames")

  Resolving package versions...
   Updating `C:\Users\kcsgo\.julia\environments\v1.4\Project.toml`
 [no changes]
   Updating `C:\Users\kcsgo\.julia\environments\v1.4\Manifest.toml`
 [no changes]

Load a package¶

Load a package every time we run a Julia session:

In [12]:

using CSV, DataFrames

In [13]:

CSV.read("./covid_data.csv", DataFrame)

Out[13]:

271 rows × 347 columns (omitted printing of 342 columns)

	Province/State	Country/Region	Lat	Long	1/22/20
	String?	String	Float64?	Float64?	Int64
1	missing	Afghanistan	33.9391	67.71	0
2	missing	Albania	41.1533	20.1683	0
3	missing	Algeria	28.0339	1.6596	0
4	missing	Andorra	42.5063	1.5218	0
5	missing	Angola	-11.2027	17.8739	0
6	missing	Antigua and Barbuda	17.0608	-61.7964	0
7	missing	Argentina	-38.4161	-63.6167	0
8	missing	Armenia	40.0691	45.0382	0
9	Australian Capital Territory	Australia	-35.4735	149.012	0
10	New South Wales	Australia	-33.8688	151.209	0
11	Northern Territory	Australia	-12.4634	130.846	0
12	Queensland	Australia	-27.4698	153.025	0
13	South Australia	Australia	-34.9285	138.601	0
14	Tasmania	Australia	-42.8821	147.327	0
15	Victoria	Australia	-37.8136	144.963	0
16	Western Australia	Australia	-31.9505	115.861	0
17	missing	Austria	47.5162	14.5501	0
18	missing	Azerbaijan	40.1431	47.5769	0
19	missing	Bahamas	25.0259	-78.0359	0
20	missing	Bahrain	26.0275	50.55	0
21	missing	Bangladesh	23.685	90.3563	0
22	missing	Barbados	13.1939	-59.5432	0
23	missing	Belarus	53.7098	27.9534	0
24	missing	Belgium	50.8333	4.46994	0
25	missing	Belize	17.1899	-88.4976	0
26	missing	Benin	9.3077	2.3158	0
27	missing	Bhutan	27.5142	90.4336	0
28	missing	Bolivia	-16.2902	-63.5887	0
29	missing	Bosnia and Herzegovina	43.9159	17.6791	0
30	missing	Botswana	-22.3285	24.6849	0
⋮	⋮	⋮	⋮	⋮	⋮

In [14]:

data = CSV.read("covid_data.csv", DataFrame)
data

Out[14]:

271 rows × 347 columns (omitted printing of 342 columns)

	Province/State	Country/Region	Lat	Long	1/22/20
	String?	String	Float64?	Float64?	Int64
1	missing	Afghanistan	33.9391	67.71	0
2	missing	Albania	41.1533	20.1683	0
3	missing	Algeria	28.0339	1.6596	0
4	missing	Andorra	42.5063	1.5218	0
5	missing	Angola	-11.2027	17.8739	0
6	missing	Antigua and Barbuda	17.0608	-61.7964	0
7	missing	Argentina	-38.4161	-63.6167	0
8	missing	Armenia	40.0691	45.0382	0
9	Australian Capital Territory	Australia	-35.4735	149.012	0
10	New South Wales	Australia	-33.8688	151.209	0
11	Northern Territory	Australia	-12.4634	130.846	0
12	Queensland	Australia	-27.4698	153.025	0
13	South Australia	Australia	-34.9285	138.601	0
14	Tasmania	Australia	-42.8821	147.327	0
15	Victoria	Australia	-37.8136	144.963	0
16	Western Australia	Australia	-31.9505	115.861	0
17	missing	Austria	47.5162	14.5501	0
18	missing	Azerbaijan	40.1431	47.5769	0
19	missing	Bahamas	25.0259	-78.0359	0
20	missing	Bahrain	26.0275	50.55	0
21	missing	Bangladesh	23.685	90.3563	0
22	missing	Barbados	13.1939	-59.5432	0
23	missing	Belarus	53.7098	27.9534	0
24	missing	Belgium	50.8333	4.46994	0
25	missing	Belize	17.1899	-88.4976	0
26	missing	Benin	9.3077	2.3158	0
27	missing	Bhutan	27.5142	90.4336	0
28	missing	Bolivia	-16.2902	-63.5887	0
29	missing	Bosnia and Herzegovina	43.9159	17.6791	0
30	missing	Botswana	-22.3285	24.6849	0
⋮	⋮	⋮	⋮	⋮	⋮

In [15]:

typeof(data)

Out[15]:

DataFrame

We can rename each column name.

In [16]:

data_2 = rename(data, 1 => "province", 2 => "country")
data_2

Out[16]:

271 rows × 347 columns (omitted printing of 342 columns)

	province	country	Lat	Long	1/22/20
	String?	String	Float64?	Float64?	Int64
1	missing	Afghanistan	33.9391	67.71	0
2	missing	Albania	41.1533	20.1683	0
3	missing	Algeria	28.0339	1.6596	0
4	missing	Andorra	42.5063	1.5218	0
5	missing	Angola	-11.2027	17.8739	0
6	missing	Antigua and Barbuda	17.0608	-61.7964	0
7	missing	Argentina	-38.4161	-63.6167	0
8	missing	Armenia	40.0691	45.0382	0
9	Australian Capital Territory	Australia	-35.4735	149.012	0
10	New South Wales	Australia	-33.8688	151.209	0
11	Northern Territory	Australia	-12.4634	130.846	0
12	Queensland	Australia	-27.4698	153.025	0
13	South Australia	Australia	-34.9285	138.601	0
14	Tasmania	Australia	-42.8821	147.327	0
15	Victoria	Australia	-37.8136	144.963	0
16	Western Australia	Australia	-31.9505	115.861	0
17	missing	Austria	47.5162	14.5501	0
18	missing	Azerbaijan	40.1431	47.5769	0
19	missing	Bahamas	25.0259	-78.0359	0
20	missing	Bahrain	26.0275	50.55	0
21	missing	Bangladesh	23.685	90.3563	0
22	missing	Barbados	13.1939	-59.5432	0
23	missing	Belarus	53.7098	27.9534	0
24	missing	Belgium	50.8333	4.46994	0
25	missing	Belize	17.1899	-88.4976	0
26	missing	Benin	9.3077	2.3158	0
27	missing	Bhutan	27.5142	90.4336	0
28	missing	Bolivia	-16.2902	-63.5887	0
29	missing	Bosnia and Herzegovina	43.9159	17.6791	0
30	missing	Botswana	-22.3285	24.6849	0
⋮	⋮	⋮	⋮	⋮	⋮

In [17]:

# ! is convention: function *modifies* its argument in place
rename!(data, 1 => "province", 2 => "country")

Out[17]:

271 rows × 347 columns (omitted printing of 342 columns)

	province	country	Lat	Long	1/22/20
	String?	String	Float64?	Float64?	Int64
1	missing	Afghanistan	33.9391	67.71	0
2	missing	Albania	41.1533	20.1683	0
3	missing	Algeria	28.0339	1.6596	0
4	missing	Andorra	42.5063	1.5218	0
5	missing	Angola	-11.2027	17.8739	0
6	missing	Antigua and Barbuda	17.0608	-61.7964	0
7	missing	Argentina	-38.4161	-63.6167	0
8	missing	Armenia	40.0691	45.0382	0
9	Australian Capital Territory	Australia	-35.4735	149.012	0
10	New South Wales	Australia	-33.8688	151.209	0
11	Northern Territory	Australia	-12.4634	130.846	0
12	Queensland	Australia	-27.4698	153.025	0
13	South Australia	Australia	-34.9285	138.601	0
14	Tasmania	Australia	-42.8821	147.327	0
15	Victoria	Australia	-37.8136	144.963	0
16	Western Australia	Australia	-31.9505	115.861	0
17	missing	Austria	47.5162	14.5501	0
18	missing	Azerbaijan	40.1431	47.5769	0
19	missing	Bahamas	25.0259	-78.0359	0
20	missing	Bahrain	26.0275	50.55	0
21	missing	Bangladesh	23.685	90.3563	0
22	missing	Barbados	13.1939	-59.5432	0
23	missing	Belarus	53.7098	27.9534	0
24	missing	Belgium	50.8333	4.46994	0
25	missing	Belize	17.1899	-88.4976	0
26	missing	Benin	9.3077	2.3158	0
27	missing	Bhutan	27.5142	90.4336	0
28	missing	Bolivia	-16.2902	-63.5887	0
29	missing	Bosnia and Herzegovina	43.9159	17.6791	0
30	missing	Botswana	-22.3285	24.6849	0
⋮	⋮	⋮	⋮	⋮	⋮

In [18]:

data

Out[18]:

271 rows × 347 columns (omitted printing of 342 columns)

	province	country	Lat	Long	1/22/20
	String?	String	Float64?	Float64?	Int64
1	missing	Afghanistan	33.9391	67.71	0
2	missing	Albania	41.1533	20.1683	0
3	missing	Algeria	28.0339	1.6596	0
4	missing	Andorra	42.5063	1.5218	0
5	missing	Angola	-11.2027	17.8739	0
6	missing	Antigua and Barbuda	17.0608	-61.7964	0
7	missing	Argentina	-38.4161	-63.6167	0
8	missing	Armenia	40.0691	45.0382	0
9	Australian Capital Territory	Australia	-35.4735	149.012	0
10	New South Wales	Australia	-33.8688	151.209	0
11	Northern Territory	Australia	-12.4634	130.846	0
12	Queensland	Australia	-27.4698	153.025	0
13	South Australia	Australia	-34.9285	138.601	0
14	Tasmania	Australia	-42.8821	147.327	0
15	Victoria	Australia	-37.8136	144.963	0
16	Western Australia	Australia	-31.9505	115.861	0
17	missing	Austria	47.5162	14.5501	0
18	missing	Azerbaijan	40.1431	47.5769	0
19	missing	Bahamas	25.0259	-78.0359	0
20	missing	Bahrain	26.0275	50.55	0
21	missing	Bangladesh	23.685	90.3563	0
22	missing	Barbados	13.1939	-59.5432	0
23	missing	Belarus	53.7098	27.9534	0
24	missing	Belgium	50.8333	4.46994	0
25	missing	Belize	17.1899	-88.4976	0
26	missing	Benin	9.3077	2.3158	0
27	missing	Bhutan	27.5142	90.4336	0
28	missing	Bolivia	-16.2902	-63.5887	0
29	missing	Bosnia and Herzegovina	43.9159	17.6791	0
30	missing	Botswana	-22.3285	24.6849	0
⋮	⋮	⋮	⋮	⋮	⋮

In [19]:

?rename

search: rename rename! propertynames

Out[19]:

rename(df::AbstractDataFrame, vals::AbstractVector{Symbol};
       makeunique::Bool=false)
rename(df::AbstractDataFrame, vals::AbstractVector{<:AbstractString};
       makeunique::Bool=false)
rename(df::AbstractDataFrame, (from => to)::Pair...)
rename(df::AbstractDataFrame, d::AbstractDict)
rename(df::AbstractDataFrame, d::AbstractVector{<:Pair})
rename(f::Function, df::AbstractDataFrame)

Create a new data frame that is a copy of df with changed column names. Each name is changed at most once. Permutation of names is allowed.

Arguments¶

df : the AbstractDataFrame; if it is a SubDataFrame then renaming is only allowed if it was created using : as a column selector.
d : an AbstractDict or an AbstractVector of Pairs that maps the original names or column numbers to new names
f : a function which for each column takes the old name as a String and returns the new name that gets converted to a Symbol
vals : new column names as a vector of Symbols or AbstractStrings of the same length as the number of columns in df
makeunique : if false (the default), an error will be raised if duplicate names are found; if true, duplicate names will be suffixed with _i (i starting at 1 for the first duplicate).

If pairs are passed to rename (as positional arguments or in a dictionary or a vector) then:

from value can be a Symbol, an AbstractString or an Integer;
to value can be a Symbol or an AbstractString.

Mixing symbols and strings in to and from is not allowed.

Examples¶

julia> df = DataFrame(i = 1, x = 2, y = 3)
1×3 DataFrame
 Row │ i      x      y
     │ Int64  Int64  Int64
─────┼─────────────────────
   1 │     1      2      3

julia> rename(df, :i => :A, :x => :X)
1×3 DataFrame
 Row │ A      X      y
     │ Int64  Int64  Int64
─────┼─────────────────────
   1 │     1      2      3

julia> rename(df, :x => :y, :y => :x)
1×3 DataFrame
 Row │ i      y      x
     │ Int64  Int64  Int64
─────┼─────────────────────
   1 │     1      2      3

julia> rename(df, [1 => :A, 2 => :X])
1×3 DataFrame
 Row │ A      X      y
     │ Int64  Int64  Int64
─────┼─────────────────────
   1 │     1      2      3

julia> rename(df, Dict("i" => "A", "x" => "X"))
1×3 DataFrame
 Row │ A      X      y
     │ Int64  Int64  Int64
─────┼─────────────────────
   1 │     1      2      3

julia> rename(uppercase, df)
1×3 DataFrame
 Row │ I      X      Y
     │ Int64  Int64  Int64
─────┼─────────────────────
   1 │     1      2      3

Interact.jl: Simple interactive visualizations¶

In [20]:

Pkg.add("Interact")

  Resolving package versions...
   Updating `C:\Users\kcsgo\.julia\environments\v1.4\Project.toml`
 [no changes]
   Updating `C:\Users\kcsgo\.julia\environments\v1.4\Manifest.toml`
 [no changes]

In [21]:

using Interact

Unable to load WebIO. Please make sure WebIO works for your Jupyter client. For troubleshooting, please see the WebIO/IJulia documentation.

In [22]:

for i in 1:10
    @show i
end

i = 1
i = 2
i = 3
i = 4
i = 5
i = 6
i = 7
i = 8
i = 9
i = 10

In [23]:

typeof(1:10)

Out[23]:

UnitRange{Int64}

In [24]:

collect(1:10)

Out[24]:

10-element Array{Int64,1}:
  1
  2
  3
  4
  5
  6
  7
  8
  9
 10

In [25]:

for i in 1:10
    println("i = ", i)
end

i = 1
i = 2
i = 3
i = 4
i = 5
i = 6
i = 7
i = 8
i = 9
i = 10

In [31]:

countries = data[2:5, 2]

Out[31]:

4-element Array{String,1}:
 "Albania"
 "Algeria"
 "Andorra"
 "Angola"

In [32]:

countries = data[1:end, 2]

Out[32]:

271-element Array{String,1}:
 "Afghanistan"
 "Albania"
 "Algeria"
 "Andorra"
 "Angola"
 "Antigua and Barbuda"
 "Argentina"
 "Armenia"
 "Australia"
 "Australia"
 "Australia"
 "Australia"
 "Australia"
 ⋮
 "United Kingdom"
 "United Kingdom"
 "United Kingdom"
 "Uruguay"
 "Uzbekistan"
 "Vanuatu"
 "Venezuela"
 "Vietnam"
 "West Bank and Gaza"
 "Yemen"
 "Zambia"
 "Zimbabwe"

In [33]:

countries = collect(data[:, 2])

Out[33]:

271-element Array{String,1}:
 "Afghanistan"
 "Albania"
 "Algeria"
 "Andorra"
 "Angola"
 "Antigua and Barbuda"
 "Argentina"
 "Armenia"
 "Australia"
 "Australia"
 "Australia"
 "Australia"
 "Australia"
 ⋮
 "United Kingdom"
 "United Kingdom"
 "United Kingdom"
 "Uruguay"
 "Uzbekistan"
 "Vanuatu"
 "Venezuela"
 "Vietnam"
 "West Bank and Gaza"
 "Yemen"
 "Zambia"
 "Zimbabwe"

In [34]:

unique_countries = unique(countries)

Out[34]:

191-element Array{String,1}:
 "Afghanistan"
 "Albania"
 "Algeria"
 "Andorra"
 "Angola"
 "Antigua and Barbuda"
 "Argentina"
 "Armenia"
 "Australia"
 "Austria"
 "Azerbaijan"
 "Bahamas"
 "Bahrain"
 ⋮
 "Ukraine"
 "United Arab Emirates"
 "United Kingdom"
 "Uruguay"
 "Uzbekistan"
 "Vanuatu"
 "Venezuela"
 "Vietnam"
 "West Bank and Gaza"
 "Yemen"
 "Zambia"
 "Zimbabwe"

Note: Julia has 1-based indexing: indices of vectors start at 1, not 0

Extract data and plot¶

In [36]:

startswith("United", "U")

Out[36]:

true

In [37]:

startswith("David", "U")

Out[37]:

false

Array comprehension:

In [38]:

U_countries = [startswith(country, "U") for country in countries]

Out[38]:

271-element Array{Bool,1}:
 0
 0
 0
 0
 0
 0
 0
 0
 0
 0
 0
 0
 0
 ⋮
 1
 1
 1
 1
 1
 0
 0
 0
 0
 0
 0
 0

In [40]:

data[U_countries, :]

Out[40]:

17 rows × 347 columns (omitted printing of 342 columns)

	province	country	Lat	Long	1/22/20
	String?	String	Float64?	Float64?	Int64
1	missing	US	40.0	-100.0	1
2	missing	Uganda	1.37333	32.2903	0
3	missing	Ukraine	48.3794	31.1656	0
4	missing	United Arab Emirates	23.4241	53.8478	0
5	Anguilla	United Kingdom	18.2206	-63.0686	0
6	Bermuda	United Kingdom	32.3078	-64.7505	0
7	British Virgin Islands	United Kingdom	18.4207	-64.64	0
8	Cayman Islands	United Kingdom	19.3133	-81.2546	0
9	Channel Islands	United Kingdom	49.3723	-2.3644	0
10	Falkland Islands (Malvinas)	United Kingdom	-51.7963	-59.5236	0
11	Gibraltar	United Kingdom	36.1408	-5.3536	0
12	Isle of Man	United Kingdom	54.2361	-4.5481	0
13	Montserrat	United Kingdom	16.7425	-62.1874	0
14	Turks and Caicos Islands	United Kingdom	21.694	-71.7979	0
15	missing	United Kingdom	55.3781	-3.436	0
16	missing	Uruguay	-32.5228	-55.7658	0
17	missing	Uzbekistan	41.3775	64.5853	0

In [41]:

# . is "broadcasting": apply operation to each element of a vector
countries .== "US"

Out[41]:

271-element BitArray{1}:
 0
 0
 0
 0
 0
 0
 0
 0
 0
 0
 0
 0
 0
 ⋮
 0
 0
 0
 0
 0
 0
 0
 0
 0
 0
 0
 0

In [42]:

US_row = findfirst(countries .== "US")

Out[42]:

In [43]:

data[US_row, :]

Out[43]:

DataFrameRow (347 columns)

	province	country	Lat	Long	1/22/20	1/23/20	1/24/20	1/25/20	1/26/20
	String?	String	Float64?	Float64?	Int64	Int64	Int64	Int64	Int64
248	missing	US	40.0	-100.0	1	1	2	2	5

In [46]:

UC_data_row = data[US_row, :]

Out[46]:

DataFrameRow (347 columns)

	province	country	Lat	Long	1/22/20	1/23/20	1/24/20	1/25/20	1/26/20
	String?	String	Float64?	Float64?	Int64	Int64	Int64	Int64	Int64
248	missing	US	40.0	-100.0	1	1	2	2	5

In [47]:

US_data = convert(Vector, UC_data_row[5:end])

Out[47]:

343-element Array{Int64,1}:
        1
        1
        2
        2
        5
        5
        5
        6
        6
        8
        8
        8
       11
        ⋮
 17468841
 17665284
 17853731
 18045048
 18239758
 18466484
 18665343
 18765529
 18992126
 19142603
 19309281
 19510836

In [49]:

Pkg.add("Plots")

  Resolving package versions...
  Installed libfdk_aac_jll ── v0.1.6+4
  Installed EarCut_jll ────── v2.1.5+1
  Installed x265_jll ──────── v3.0.0+3
  Installed Showoff ───────── v0.3.2
  Installed RecipesPipeline ─ v0.1.13
  Installed Contour ───────── v0.5.7
  Installed StaticArrays ──── v1.0.1
  Installed Plots ─────────── v1.6.12
  Installed FreeType2_jll ─── v2.10.1+5
  Installed Bzip2_jll ─────── v1.0.6+5
  Installed LAME_jll ──────── v3.100.0+3
  Installed OpenSSL_jll ───── v1.1.1+6
  Installed Grisu ─────────── v1.0.0
  Installed libass_jll ────── v0.14.0+4
  Installed libvorbis_jll ─── v1.3.6+6
  Installed LaTeXStrings ──── v1.2.0
  Installed IterTools ─────── v1.3.0
  Installed Opus_jll ──────── v1.3.1+3
  Installed Adapt ─────────── v2.3.0
  Installed LibVPX_jll ────── v1.9.0+1
  Installed GeometryTypes ─── v0.8.4
  Installed FFMPEG_jll ────── v4.3.1+4
  Installed PlotUtils ─────── v1.0.8
  Installed FFMPEG ────────── v0.4.0
  Installed Ogg_jll ───────── v1.3.4+2
  Installed RecipesBase ───── v1.1.1
  Installed Zlib_jll ──────── v1.2.11+18
  Installed GR ────────────── v0.49.1
  Installed Latexify ──────── v0.14.7
  Installed GeometryBasics ── v0.3.5
  Installed StatsBase ─────── v0.33.2
  Installed NaNMath ───────── v0.3.5
  Installed x264_jll ──────── v2020.7.14+2
  Installed FriBidi_jll ───── v1.0.5+6
  Installed PlotThemes ────── v2.0.0
  Installed StructArrays ──── v0.4.4
  Installed ColorSchemes ──── v3.10.2
   Updating `C:\Users\kcsgo\.julia\environments\v1.4\Project.toml`
  [91a5bcdd] + Plots v1.6.12
   Updating `C:\Users\kcsgo\.julia\environments\v1.4\Manifest.toml`
  [79e6a3ab] + Adapt v2.3.0
  [6e34b625] + Bzip2_jll v1.0.6+5
  [35d6a980] + ColorSchemes v3.10.2
  [d38c429a] + Contour v0.5.7
  [5ae413db] + EarCut_jll v2.1.5+1
  [c87230d0] + FFMPEG v0.4.0
  [b22a6f82] + FFMPEG_jll v4.3.1+4
  [d7e528f0] + FreeType2_jll v2.10.1+5
  [559328eb] + FriBidi_jll v1.0.5+6
  [28b8d3ca] + GR v0.49.1
  [5c1252a2] + GeometryBasics v0.3.5
  [4d00f742] + GeometryTypes v0.8.4
  [42e2da0e] + Grisu v1.0.0
  [c8e1da08] + IterTools v1.3.0
  [c1c5ebd0] + LAME_jll v3.100.0+3
  [b964fa9f] + LaTeXStrings v1.2.0
  [23fbe1c1] + Latexify v0.14.7
  [dd192d2f] + LibVPX_jll v1.9.0+1
  [77ba4419] + NaNMath v0.3.5
  [e7412a2a] + Ogg_jll v1.3.4+2
  [458c3c95] + OpenSSL_jll v1.1.1+6
  [91d4177d] + Opus_jll v1.3.1+3
  [ccf2f8ad] + PlotThemes v2.0.0
  [995b91a9] + PlotUtils v1.0.8
  [91a5bcdd] + Plots v1.6.12
  [3cdcf5f2] + RecipesBase v1.1.1
  [01d81517] + RecipesPipeline v0.1.13
  [992d4aef] + Showoff v0.3.2
  [90137ffa] + StaticArrays v1.0.1
  [2913bbd2] + StatsBase v0.33.2
  [09ab397b] + StructArrays v0.4.4
  [83775a58] + Zlib_jll v1.2.11+18
  [0ac62f75] + libass_jll v0.14.0+4
  [f638f0a6] + libfdk_aac_jll v0.1.6+4
  [f27f6e37] + libvorbis_jll v1.3.6+6
  [1270edf5] + x264_jll v2020.7.14+2
  [dfaa095f] + x265_jll v3.0.0+3
   Building GR → `C:\Users\kcsgo\.julia\packages\GR\cRdXQ\deps\build.log`

In [50]:

using Plots

┌ Info: Precompiling Plots [91a5bcdd-55d7-5caf-9e0b-520d859cae80]
└ @ Base loading.jl:1260

In [51]:

plot(US_data)

Out[51]:

In [52]:

col_names = names(data)

Out[52]:

347-element Array{String,1}:
 "province"
 "country"
 "Lat"
 "Long"
 "1/22/20"
 "1/23/20"
 "1/24/20"
 "1/25/20"
 "1/26/20"
 "1/27/20"
 "1/28/20"
 "1/29/20"
 "1/30/20"
 ⋮
 "12/18/20"
 "12/19/20"
 "12/20/20"
 "12/21/20"
 "12/22/20"
 "12/23/20"
 "12/24/20"
 "12/25/20"
 "12/26/20"
 "12/27/20"
 "12/28/20"
 "12/29/20"

In [58]:

date_strings = String.(names(data))[5:end]

Out[58]:

343-element Array{String,1}:
 "1/22/20"
 "1/23/20"
 "1/24/20"
 "1/25/20"
 "1/26/20"
 "1/27/20"
 "1/28/20"
 "1/29/20"
 "1/30/20"
 "1/31/20"
 "2/1/20"
 "2/2/20"
 "2/3/20"
 ⋮
 "12/18/20"
 "12/19/20"
 "12/20/20"
 "12/21/20"
 "12/22/20"
 "12/23/20"
 "12/24/20"
 "12/25/20"
 "12/26/20"
 "12/27/20"
 "12/28/20"
 "12/29/20"

Parse: convert string representation into a Julia object

In [59]:

date_strings[1]

Out[59]:

"1/22/20"

In [56]:

using Dates

In [57]:

format = Dates.DateFormat("d/m/Y")

Out[57]:

dateformat"d/m/Y"

In [60]:

parse(Date, date_strings[1], format)

ArgumentError: Month: 22 out of range (1:12)

Stacktrace:
 [1] Date(::Int64, ::Int64, ::Int64) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Dates\src\types.jl:223
 [2] parse(::Type{Date}, ::String, ::DateFormat{Symbol("d/m/Y"),Tuple{Dates.DatePart{'d'},Dates.Delim{Char,1},Dates.DatePart{'m'},Dates.Delim{Char,1},Dates.DatePart{'Y'}}}) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.4\Dates\src\parse.jl:285
 [3] top-level scope at In[60]:1

In [62]:

format = Dates.DateFormat("m/d/Y")
parse(Date, date_strings[1], format) + Year(2000)

Out[62]:

2020-01-22

In [63]:

dates = parse.(Date, date_strings, format) + Year(2000)

Out[63]:

343-element Array{Date,1}:
 2020-01-22
 2020-01-23
 2020-01-24
 2020-01-25
 2020-01-26
 2020-01-27
 2020-01-28
 2020-01-29
 2020-01-30
 2020-01-31
 2020-02-01
 2020-02-02
 2020-02-03
 ⋮
 2020-12-18
 2020-12-19
 2020-12-20
 2020-12-21
 2020-12-22
 2020-12-23
 2020-12-24
 2020-12-25
 2020-12-26
 2020-12-27
 2020-12-28
 2020-12-29

In [67]:

plot(dates, US_data, xticks=dates[1:5:end], xrotation=45, leg=:topleft, 
    label="US data", m=:o)

xlabel!("date")
ylabel!("confirmed cases in US")
title!("US confirmed COVID-19 cases")

Out[67]:

In [68]:

plot(dates, US_data, xticks=dates[1:5:end], xrotation=45, leg=:topleft, 
    label="US data", m=:o,
    yscale=:log10)

xlabel!("date")
ylabel!("confirmed cases in US")
title!("US confirmed COVID-19 cases")

Out[68]: