2  Analysis of French PhD theses in Julia

2.1 Load packages

using CSV
using DataFrames
using Dates
using Plots
using StatsPlots

2.2 English prevalence in French PhD theses since 1985

df = CSV.read("../tmp/english_prevalence.csv", DataFrame)

38×4 DataFrame

13 rows omitted

Row	year	english	french	missing
	Int64	Int64	Int64	Int64
1	1985	1	1138	0
2	1986	5	3408	0
3	1987	4	4573	0
4	1988	4	6297	0
5	1989	2	6262	0
6	1990	7	6326	0
7	1991	1	6645	0
8	1992	7	7431	1
9	1993	10	7892	1
10	1994	15	8097	0
11	1995	14	6349	0
12	1996	16	6883	0
13	1997	20	7126	2
⋮	⋮	⋮	⋮	⋮
27	2011	1418	9042	0
28	2012	1890	9592	0
29	2013	2356	9560	0
30	2014	1877	7360	0
31	2015	1507	5777	0
32	2016	1422	5357	0
33	2017	1474	4929	0
34	2018	1371	3949	0
35	2019	1585	3398	0
36	2020	1526	2922	0
37	2021	1841	2940	0
38	2022	745	865	0

# Get the english / (french + english) ratio on a new column
df.ratio = df.english ./ (df.french + df.english)

38-element Vector{Float64}:
 0.000877963125548727
 0.001464986815118664
 0.0008739348918505571
 0.0006348198698619266
 0.00031928480204342275
 0.0011053213327017212
 0.0001504664459825459
 0.0009411132024737832
 0.0012655024044545685
 0.0018491124260355029
 0.0022002200220022
 0.0023191766922742428
 0.00279876854184159
 ⋮
 0.1355640535372849
 0.16460546943041282
 0.19771735481705272
 0.20320450362671863
 0.206891817682592
 0.20976545213158282
 0.23020459159768858
 0.2577067669172932
 0.3180814770218744
 0.3430755395683453
 0.3850658857979502
 0.46273291925465837

Plot:

plot(df.year, df.ratio, label="ratio", legend=:topleft, xlabel="Year", ylabel="English", title="English in French PhD theses since 1985", ylim=(0, 1))

Rate of French PhD theses in English since 1985

Save:

savefig("../media/plots/english_prevalence.png")

"/home/sortion/Documents/Projects/bio/bioinfo-fr/bioinfo-theses-analyses/media/plots/english_prevalence.png"