Load the global food prices dataset for the porject 2.

setwd("C:/Users/dkim174/Documents/Classes/Data 110/Week11_project2")
globalfoodprices <-read.csv("global_food_prices.csv")

Understand the structure of the global food prices data.

View its class.

class(globalfoodprices)
## [1] "data.frame"

View its dimensions.

dim(globalfoodprices) # the dataset contains 2,050,638 rows and 18 columns.
## [1] 2050638      18

Look at the column names and structures.

names(globalfoodprices)
##  [1] "adm0_id"            "adm0_name"          "adm1_id"           
##  [4] "adm1_name"          "mkt_id"             "mkt_name"          
##  [7] "cm_id"              "cm_name"            "cur_id"            
## [10] "cur_name"           "pt_id"              "pt_name"           
## [13] "um_id"              "um_name"            "mp_month"          
## [16] "mp_year"            "mp_price"           "mp_commoditysource"
str(globalfoodprices)
## 'data.frame':    2050638 obs. of  18 variables:
##  $ adm0_id           : num  1 1 1 1 1 1 1 1 1 1 ...
##  $ adm0_name         : chr  "Afghanistan" "Afghanistan" "Afghanistan" "Afghanistan" ...
##  $ adm1_id           : int  272 272 272 272 272 272 272 272 272 272 ...
##  $ adm1_name         : chr  "Badakhshan" "Badakhshan" "Badakhshan" "Badakhshan" ...
##  $ mkt_id            : int  266 266 266 266 266 266 266 266 266 266 ...
##  $ mkt_name          : chr  "Fayzabad" "Fayzabad" "Fayzabad" "Fayzabad" ...
##  $ cm_id             : int  55 55 55 55 55 55 55 55 55 55 ...
##  $ cm_name           : chr  "Bread - Retail" "Bread - Retail" "Bread - Retail" "Bread - Retail" ...
##  $ cur_id            : num  0 0 0 0 0 0 0 0 0 0 ...
##  $ cur_name          : chr  "AFN" "AFN" "AFN" "AFN" ...
##  $ pt_id             : int  15 15 15 15 15 15 15 15 15 15 ...
##  $ pt_name           : chr  "Retail" "Retail" "Retail" "Retail" ...
##  $ um_id             : int  5 5 5 5 5 5 5 5 5 5 ...
##  $ um_name           : chr  "KG" "KG" "KG" "KG" ...
##  $ mp_month          : int  1 2 3 4 5 6 7 8 9 10 ...
##  $ mp_year           : int  2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 ...
##  $ mp_price          : num  50 50 50 50 50 50 50 50 50 50 ...
##  $ mp_commoditysource: logi  NA NA NA NA NA NA ...

Clean the dataset

head(globalfoodprices)
##   adm0_id   adm0_name adm1_id  adm1_name mkt_id mkt_name cm_id        cm_name
## 1       1 Afghanistan     272 Badakhshan    266 Fayzabad    55 Bread - Retail
## 2       1 Afghanistan     272 Badakhshan    266 Fayzabad    55 Bread - Retail
## 3       1 Afghanistan     272 Badakhshan    266 Fayzabad    55 Bread - Retail
## 4       1 Afghanistan     272 Badakhshan    266 Fayzabad    55 Bread - Retail
## 5       1 Afghanistan     272 Badakhshan    266 Fayzabad    55 Bread - Retail
## 6       1 Afghanistan     272 Badakhshan    266 Fayzabad    55 Bread - Retail
##   cur_id cur_name pt_id pt_name um_id um_name mp_month mp_year mp_price
## 1      0      AFN    15  Retail     5      KG        1    2014       50
## 2      0      AFN    15  Retail     5      KG        2    2014       50
## 3      0      AFN    15  Retail     5      KG        3    2014       50
## 4      0      AFN    15  Retail     5      KG        4    2014       50
## 5      0      AFN    15  Retail     5      KG        5    2014       50
## 6      0      AFN    15  Retail     5      KG        6    2014       50
##   mp_commoditysource
## 1                 NA
## 2                 NA
## 3                 NA
## 4                 NA
## 5                 NA
## 6                 NA
tail(globalfoodprices)
##         adm0_id adm0_name adm1_id adm1_name mkt_id   mkt_name cm_id
## 2050633     271  Zimbabwe    3444  Midlands   5594 Mbilashaba   185
## 2050634     271  Zimbabwe    3444  Midlands   5594 Mbilashaba   432
## 2050635     271  Zimbabwe    3444  Midlands   5594 Mbilashaba   539
## 2050636     271  Zimbabwe    3444  Midlands   5594 Mbilashaba   540
## 2050637     271  Zimbabwe    3444  Midlands   5594 Mbilashaba   541
## 2050638     271  Zimbabwe    3444  Midlands   5594 Mbilashaba   887
##                         cm_name cur_id cur_name pt_id pt_name um_id um_name
## 2050633           Salt - Retail      0      ZWL    15  Retail     5      KG
## 2050634  Beans (sugar) - Retail      0      ZWL    15  Retail     5      KG
## 2050635     Toothpaste - Retail      0      ZWL    15  Retail   116  100 ML
## 2050636   Laundry soap - Retail      0      ZWL    15  Retail     5      KG
## 2050637  Handwash soap - Retail      0      ZWL    15  Retail    66   250 G
## 2050638 Fish (kapenta) - Retail      0      ZWL    15  Retail     5      KG
##         mp_month mp_year  mp_price mp_commoditysource
## 2050633        6    2021   71.0000                 NA
## 2050634        6    2021  233.3333                 NA
## 2050635        6    2021  112.5000                 NA
## 2050636        6    2021  114.0000                 NA
## 2050637        6    2021   59.5000                 NA
## 2050638        6    2021 1200.0000                 NA