using CSV, DataFrames, StatsPlotsfifa_filepath = "data//archive//fifa.csv""data//archive//fifa.csv"
fifa_data = CSV.read(fifa_filepath, DataFrame)| Date | ARG | BRA | ESP | FRA | GER | ITA | |
|---|---|---|---|---|---|---|---|
| 1 | 1993-08-08 | 5.0 | 8.0 | 13.0 | 12.0 | 1.0 | 2.0 |
| 2 | 1993-09-23 | 12.0 | 1.0 | 14.0 | 7.0 | 5.0 | 2.0 |
| 3 | 1993-10-22 | 9.0 | 1.0 | 7.0 | 14.0 | 4.0 | 3.0 |
| 4 | 1993-11-19 | 9.0 | 4.0 | 7.0 | 15.0 | 3.0 | 1.0 |
| 5 | 1993-12-23 | 8.0 | 3.0 | 5.0 | 15.0 | 1.0 | 2.0 |
| 6 | 1994-02-15 | 9.0 | 2.0 | 6.0 | 14.0 | 1.0 | 7.0 |
| 7 | 1994-03-15 | 8.0 | 2.0 | 6.0 | 15.0 | 1.0 | 11.0 |
| 8 | 1994-04-19 | 10.0 | 1.0 | 7.0 | 15.0 | 2.0 | 13.0 |
| 9 | 1994-05-17 | 6.0 | 1.0 | 9.0 | 17.0 | 2.0 | 16.0 |
| 10 | 1994-06-14 | 8.0 | 3.0 | 5.0 | 13.0 | 1.0 | 4.0 |
| ... | |||||||
| 286 | 2018-06-07 | 5.0 | 2.0 | 10.0 | 7.0 | 1.0 | 19.0 |
#gr(size=(1000,600))@df fifa_data plot(fifa_data.Date, cols(2:7), xlabel="Date")
Built with Julia 1.9.1 and
CSV 0.10.9DataFrames 1.5.0
StatsPlots 0.15.4
To run this tutorial locally, download [this file](/tutorials/fifa03x01.jl) and open it with Pluto.jl._