|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
|
- library(readr)
- library(dplyr)
- library(tidyr)
- library(WriteXLS)
- # Read all raw datasets from UN into one dataframe ---------
- df <- list.files(path='data/raw/UN Data/', full.names = TRUE) %>%
- lapply(read_delim, delim = ',', skip = 1) %>%
- bind_rows
- # Keep the variables required to create the data dictionary
- df %>%
- select(Series, Year, Source) -> df
- # Keep only latest data for each variable
- df %>%
- group_by(Series) %>%
- filter(Year == max(Year)) %>%
- ungroup() -> df
- # Variables are repeated for they occur for every country. Let's remove the
- # duplicates.
- df %>%
- distinct(Series, .keep_all = TRUE) -> df
- # Fix names according to preprocessed dataset
- df %>%
- # Make them all lowercase
- mutate(Series = tolower(Series)) %>%
- # Replace special chars
- mutate(Series = gsub(' ', '_', Series)) %>%
- mutate(Series = gsub('-', '_', Series)) %>%
- mutate(Series = gsub('_+', '_', Series)) %>%
- mutate(Series = gsub(',', '', Series)) -> df
- # Add _year to the end of variable name, just like in the preprocessed file
- df %>%
- unite("Series", Series:Year, remove=FALSE) -> df
- # Add engineering UN variables
- df <- rbind(df, c('whos_major_trade_partner_exp_1', 2018,
- paste0('United Nations Statistics Division, New York, ',
- 'Commodity Trade Statistics Database (UN COMTRADE), ',
- 'last accessed May 2019.')))
- # Add COVID-19 and engineering columns
- df <- rbind(df,
- c('country_code', '2020', paste0('European Centre for Disease ',
- 'Prevention and Control. Last ',
- 'accessed 28 April, 2020.')),
- c('country_name', '2020', paste0('European Centre for Disease ',
- 'Prevention and Control. Last ',
- 'accessed 28 April, 2020.')),
- c('date', '2020', paste0('European Centre for Disease ',
- 'Prevention and Control. Last ',
- 'accessed 28 April, 2020.')),
- c('new_cases', '2020', paste0('European Centre for Disease ',
- 'Prevention and Control. Last ',
- 'accessed 28 April, 2020.')),
- c('new_deaths', '2020', paste0('European Centre for Disease ',
- 'Prevention and Control. Last ',
- 'accessed 28 April, 2020.')),
- c('pop_data_2018', '2018', paste0('European Centre for Disease ',
- 'Prevention and Control ',
- 'collected from World Bank. ',
- 'Last accessed 28 April, 2020.')),
- c('acc_cases', '2020', paste0('Engineered based on data from ',
- 'European Centre for Disease ',
- 'Prevention and Control. Last ',
- 'accessed 28 April, 2020.')),
- c('acc_deaths', '2020', paste0('Engineered based on data from ',
- 'European Centre for Disease ',
- 'Prevention and Control. Last ',
- 'accessed 28 April, 2020.')),
- c('lethality_rate_percent', '2020', paste0('Engineered based on data from ',
- 'European Centre for Disease ',
- 'Prevention and Control. Last ',
- 'accessed April, 2020.')),
- c('retail_recreation', '2020', paste0('Google Community Mobility ',
- 'Report. Last accessed 28 ',
- 'April, 2020')),
- c('grocery_pharmacy', '2020', paste0('Google Community Mobility ',
- 'Report. Last accessed 28 ',
- 'April, 2020')),
- c('parks', '2020', paste0('Google Community Mobility ',
- 'Report. Last accessed 28 ',
- 'April, 2020')),
- c('transit_stations', '2020', paste0('Google Community Mobility ',
- 'Report. Last accessed 28 ',
- 'April, 2020')),
- c('workplaces', '2020', paste0('Google Community Mobility ',
- 'Report. Last accessed 28 ',
- 'April, 2020')),
- c('residential', '2020', paste0('Google Community Mobility ',
- 'Report. Last accessed 28 ',
- 'April, 2020')),
- c('first_case_date', '2020',
- paste0('https://en.wikipedia.org/w/index.php?title=2019%E2%80%93',
- '20_coronavirus_pandemic_by_country_and_territory&oldid=9',
- '53662872 Last accessed April 28, 2020')),
- c('n_days_since_1st_case', '2020',
- paste0('Engineering from ECDC and https://en.wikipedia.org/w/index.php?title=2019%E2%80%93',
- '20_coronavirus_pandemic_by_country_and_territory&oldid=9',
- '53662872 Last accessed April 28, 2020')),
- c('first_death_date', '2020', paste0('Engineering based on ',
- 'data from ECDC ',
- 'counting the first death ',
- 'after February, 15th.')),
- c('n_days_since_1st_death', '2020', paste0('Engineering based on ',
- 'data from ECDC ',
- 'counting the first death ',
- 'after February, 15th.'))
- )
- colnames(df) <- c('Variable name', 'Year', 'Source')
- # Add description for some variables
- df$Description <- NULL
- WriteXLS(x = df, ExcelFileName = 'data_dictionary.xls',
- SheetNames = 'Data Dictionary')
|
Models
Annotations
Connect to our Discord channel