Martin Alfaro

These are datasets I assembled or cleaned for their use.

Press on the title to download the dataset, and on Details for further information. If you want to open and close all the details simultaneously, press Ctrl + 🠙 and Ctrl + 🠛 respectively.

World Coordinates for Heatmaps

Details

For a full description of the dataset, see HERE. The estimates are in CSV format and can be downloaded HERE. The description of variables is provided in this README.txt.The information covers the years 2012-2019.

Julia

using CSV, Downloads, DataFrames

worldcoordinates = "https://alfaromartino.github.io/data/countries_mapCoordinates.csv" |>
                    x -> DataFrame(CSV.File(Downloads.download(x)))

worldcoordinates <- read.csv("https://alfaromartino.github.io/data/countries_mapCoordinates.csv")

Python

import pandas as pd

worldcoordinates = pd.read_csv("https://alfaromartino.github.io/data/countries_mapCoordinates.csv")

Revenue Estimates for European Countries at 4-digit level (NACE Rev 2)
Details

For a full description of the dataset, see HERE. The estimates are in CSV format and can be downloaded HERE, whereas the description of variables is in this README.txt. The information covers European countries for the years 2012-2019. You can also access the data directly by executing the following commands in your preferred language.
Julia

using CSV, Downloads, DataFrames dataset = "https://alfaromartino.github.io/data/RevenueManufacture_NACE4.csv" |> x -> DataFrame(CSV.File(Downloads.download(x)))
R

dataset <- read.csv("https://alfaromartino.github.io/data/RevenueManufacture_NACE4.csv")
Python

import pandas as pd dataset = pd.read_csv("https://alfaromartino.github.io/data/RevenueManufacture_NACE4.csv")