Total electricity generation”

Author

math4mad

info

ref:Total electricity generation

load pacakge

Code

using CairoMakie,CSV,DataFrames,Pipe,Tidier,HypertextLiteral
using MakieThemes
using StatsBase
using AlgebraOfGraphics
Makie.set_theme!(ggthemr(:dust))

2. load data->dataframe

Code

df=@pipe CSV.File("./data/electricity-generation.csv")|>DataFrame|>rename(_,"Electricity generation - TWh"=>:EGtwh)|>coalesce.(_, 0.0)

show(levels(df.Entity))
first(df,5)

["ASEAN (Ember)", "Afghanistan", "Africa", "Africa (EI)", "Africa (Ember)", "Albania", "Algeria", "American Samoa", "Angola", "Antigua and Barbuda", "Argentina", "Armenia", "Aruba", "Asia", "Asia (Ember)", "Asia Pacific (EI)", "Australia", "Austria", "Azerbaijan", "Bahamas", "Bahrain", "Bangladesh", "Barbados", "Belarus", "Belgium", "Belize", "Benin", "Bermuda", "Bhutan", "Bolivia", "Bosnia and Herzegovina", "Botswana", "Brazil", "British Virgin Islands", "Brunei", "Bulgaria", "Burkina Faso", "Burundi", "CIS (EI)", "Cambodia", "Cameroon", "Canada", "Cape Verde", "Cayman Islands", "Central African Republic", "Central America (EI)", "Chad", "Chile", "China", "Colombia", "Comoros", "Congo", "Cook Islands", "Costa Rica", "Cote d'Ivoire", "Croatia", "Cuba", "Cyprus", "Czechia", "Democratic Republic of Congo", "Denmark", "Djibouti", "Dominica", "Dominican Republic", "East Timor", "Eastern Africa (EI)", "Ecuador", "Egypt", "El Salvador", "Equatorial Guinea", "Eritrea", "Estonia", "Eswatini", "Ethiopia", "Europe", "Europe (EI)", "Europe (Ember)", "European Union (27)", "Falkland Islands", "Faroe Islands", "Fiji", "Finland", "France", "French Guiana", "French Polynesia", "G20 (Ember)", "G7 (Ember)", "Gabon", "Gambia", "Georgia", "Germany", "Ghana", "Gibraltar", "Greece", "Greenland", "Grenada", "Guadeloupe", "Guam", "Guatemala", "Guinea", "Guinea-Bissau", "Guyana", "Haiti", "High-income countries", "Honduras", "Hong Kong", "Hungary", "Iceland", "India", "Indonesia", "Iran", "Iraq", "Ireland", "Israel", "Italy", "Jamaica", "Japan", "Jordan", "Kazakhstan", "Kenya", "Kiribati", "Kosovo", "Kuwait", "Kyrgyzstan", "Laos", "Latin America and Caribbean (Ember)", "Latvia", "Lebanon", "Lesotho", "Liberia", "Libya", "Lithuania", "Low-income countries", "Lower-middle-income countries", "Luxembourg", "Macao", "Madagascar", "Malawi", "Malaysia", "Maldives", "Mali", "Malta", "Martinique", "Mauritania", "Mauritius", "Mexico", "Middle Africa (EI)", "Middle East (EI)", "Middle East (Ember)", "Moldova", "Mongolia", "Montenegro", "Montserrat", "Morocco", "Mozambique", "Myanmar", "Namibia", "Nauru", "Nepal", "Netherlands", "New Caledonia", "New Zealand", "Nicaragua", "Niger", "Nigeria", "Niue", "Non-OECD (EI)", "North America", "North America (EI)", "North America (Ember)", "North Korea", "North Macedonia", "Norway", "OECD (EI)", "OECD (Ember)", "Oceania", "Oceania (Ember)", "Oman", "Pakistan", "Palestine", "Panama", "Papua New Guinea", "Paraguay", "Peru", "Philippines", "Poland", "Portugal", "Puerto Rico", "Qatar", "Reunion", "Romania", "Russia", "Rwanda", "Saint Helena", "Saint Kitts and Nevis", "Saint Lucia", "Saint Pierre and Miquelon", "Saint Vincent and the Grenadines", "Samoa", "Sao Tome and Principe", "Saudi Arabia", "Senegal", "Serbia", "Seychelles", "Sierra Leone", "Singapore", "Slovakia", "Slovenia", "Solomon Islands", "Somalia", "South Africa", "South America", "South Korea", "South Sudan", "South and Central America (EI)", "Spain", "Sri Lanka", "Sudan", "Suriname", "Sweden", "Switzerland", "Syria", "Taiwan", "Tajikistan", "Tanzania", "Thailand", "Togo", "Tonga", "Trinidad and Tobago", "Tunisia", "Turkey", "Turkmenistan", "Turks and Caicos Islands", "Uganda", "Ukraine", "United Arab Emirates", "United Kingdom", "United States", "United States Virgin Islands", "Upper-middle-income countries", "Uruguay", "Uzbekistan", "Vanuatu", "Venezuela", "Vietnam", "Western Africa (EI)", "Western Sahara", "World", "Yemen", "Zambia", "Zimbabwe"]

5×4 DataFrame

Row	Entity	Code	Year	EGtwh
	String	Any	Int64	Float64
1	ASEAN (Ember)	0.0	2000	368.08
2	ASEAN (Ember)	0.0	2001	396.6
3	ASEAN (Ember)	0.0	2002	423.11
4	ASEAN (Ember)	0.0	2003	447.7
5	ASEAN (Ember)	0.0	2004	485.55

Code

list=("United States","United Kingdom","France","India","Sweden")
@eval(Main, myvars =list )
df2=@chain df begin
    @filter(Entity in !!myvars)
end

190×4 DataFrame

165 rows omitted

Row	Entity	Code	Year	EGtwh
	String	Any	Int64	Float64
1	France	FRA	1985	344.465
2	France	FRA	1986	362.995
3	France	FRA	1987	378.486
4	France	FRA	1988	392.087
5	France	FRA	1989	404.85
6	France	FRA	1990	417.2
7	France	FRA	1991	451.62
8	France	FRA	1992	460.02
9	France	FRA	1993	469.66
10	France	FRA	1994	474.6
11	France	FRA	1995	491.2
12	France	FRA	1996	509.16
13	France	FRA	1997	500.96
⋮	⋮	⋮	⋮	⋮
179	United States	USA	2011	4088.87
180	United States	USA	2012	4040.67
181	United States	USA	2013	4055.61
182	United States	USA	2014	4096.01
183	United States	USA	2015	4083.99
184	United States	USA	2016	4087.56
185	United States	USA	2017	4052.31
186	United States	USA	2018	4201.55
187	United States	USA	2019	4158.38
188	United States	USA	2020	4043.18
189	United States	USA	2021	4153.62
190	United States	USA	2022	4286.91

## 3. plot

Code

axis = (width = 1000, height =500,xticklabelrotation = pi/8,title="Electricity generation",subtitle="Measured in terawatt-hours.")
data_layer = data(df2)
mapping_layer=mapping(:Year,:EGtwh,color=:Entity)
visual_layer = visual(ScatterLines;stroke=1,strokecolor=(:red,0.8),markersize=4,linewidth=5)
draw(data_layer * mapping_layer * visual_layer,axis=axis)

┌ Warning: Keyword argument `bgcolor` is deprecated, use `backgroundcolor` instead.
└ @ Makie ~/.julia/packages/Makie/RgxaV/src/makielayout/blocks/legend.jl:23