Birds Dataset Description

Code

library(tidyverse)
library(readr)
knitr::opts_chunk$set(echo = TRUE)

Code

birds <- read_csv('_data/birds.csv', show_col_types = FALSE)

Code

head(birds)

# A tibble: 6 × 14
  Domai…¹ Domain Area …² Area  Eleme…³ Element Item …⁴ Item  Year …⁵  Year Unit 
  <chr>   <chr>    <dbl> <chr>   <dbl> <chr>     <dbl> <chr>   <dbl> <dbl> <chr>
1 QA      Live …       2 Afgh…    5112 Stocks     1057 Chic…    1961  1961 1000…
2 QA      Live …       2 Afgh…    5112 Stocks     1057 Chic…    1962  1962 1000…
3 QA      Live …       2 Afgh…    5112 Stocks     1057 Chic…    1963  1963 1000…
4 QA      Live …       2 Afgh…    5112 Stocks     1057 Chic…    1964  1964 1000…
5 QA      Live …       2 Afgh…    5112 Stocks     1057 Chic…    1965  1965 1000…
6 QA      Live …       2 Afgh…    5112 Stocks     1057 Chic…    1966  1966 1000…
# … with 3 more variables: Value <dbl>, Flag <chr>, `Flag Description` <chr>,
#   and abbreviated variable names ¹​`Domain Code`, ²​`Area Code`,
#   ³​`Element Code`, ⁴​`Item Code`, ⁵​`Year Code`

There are 14 columns or variables in this dataset Domain Code, Domain, Area Code, Area, Element Code, Element, Item Code, Item, Year Code, Year, Unit, Value, Flag, Flag Description and some of the columns especially the ones with codes are redundant as the succeeding columns provides the same info and can be used for grouping

Code

unique(birds$Domain)

[1] "Live Animals"

Code

length(unique(birds$Area))

[1] 248

Code

length(unique(birds$Item))

[1] 5

Code

length(unique(birds$Element))

[1] 1

Code

length(unique(birds$Year))

[1] 58

Code

length(unique(birds$Flag))

[1] 6

Code

unique(birds$Item)

[1] "Chickens"               "Ducks"                  "Geese and guinea fowls"
[4] "Turkeys"                "Pigeons, other birds"  

Code

unique(birds$Year)

 [1] 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975
[16] 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990
[31] 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
[46] 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

This dataset contains Food and Agriculture Data of five Live Animals which are ‘Chickens’, ‘Ducks’, ‘Geese and guinea fowls’, ‘Turkeys’ and ‘Pigeons, other birds’ that are collected from across 248 Areas. There is only one domain in the dataset which is ‘Live Animals’. The Data is collected across years from 1961-2018 every year