Summary Codebook

Source: vignettes/codebook.Rmd 
library(covdata)
#> 
#> Attaching package: 'covdata'
#> The following object is masked from 'package:datasets':
#> 
#>     uspop

Overview of Included Tables

This vignette provides an overview of the contents of each table of data in the package. For further details on the variables, consult each table’s help page. Note that many of these data tables are provisional, or are estimates subject to significant interpretive limits. Read the supplied documentation carefully before working with any of the tables.

National-level case and mortality data from the European Centers for Disease Control

Daily case and mortality data runs until December 14th 2020 and was subsequently discontinued. 

covnat_daily %>%
  dplyr::ungroup() %>%
  skimr::skim()
Data summary
Name Piped data
Number of rows 61836
Number of columns 8
_______________________
Column type frequency:
character 2
Date 1
numeric 5
________________________
Group variables None

Variable type: character

skim_variable n_missing complete_rate min max empty n_unique whitespace
cname 0 1 4 42 0 213 0
iso3 0 1 3 3 0 213 0

Variable type: Date

skim_variable n_missing complete_rate min max median n_unique
date 0 1 2019-12-31 2020-12-14 2020-07-21 350

Variable type: numeric

skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist
cases 0 1 1156.33 6782.63 -8261 0 15 275.00 234633 ▇▁▁▁▁
deaths 0 1 26.08 131.29 -1918 0 0 4.00 4928 ▁▇▁▁▁
pop 59 1 40987698.23 153129379.34 815 1293120 7169456 28515829.00 1433783692 ▇▁▁▁▁
cu_cases 0 1 100686.99 607743.06 0 129 2055 24650.00 16256754 ▇▁▁▁▁
cu_deaths 0 1 3104.89 15545.84 0 1 42 464.25 299177 ▇▁▁▁▁

Weekly case and mortality data 

covnat_weekly %>%
  dplyr::ungroup() %>%
  skimr::skim()
Data summary
Name Piped data
Number of rows 4966
Number of columns 11
_______________________
Column type frequency:
character 3
Date 1
numeric 7
________________________
Group variables None

Variable type: character

skim_variable n_missing complete_rate min max empty n_unique whitespace
year_week 0 1.00 7 7 0 159 0
cname 0 1.00 5 14 0 31 0
iso3 196 0.96 3 3 0 30 0

Variable type: Date

skim_variable n_missing complete_rate min max median n_unique
date 0 1 2019-12-30 2023-01-09 2021-07-05 159

Variable type: numeric

skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist
pop 0 1.00 31613614.13 85253844.55 39055 2108977.00 6916548.00 17475415.00 453006705.00 ▇▁▁▁▁
cases 222 0.96 77511.62 374657.80 0 1127.00 5487.00 28342.00 9023067.00 ▇▁▁▁▁
deaths 279 0.94 514.14 2005.64 0 8.00 46.00 250.50 28380.00 ▇▁▁▁▁
cu_cases 222 0.96 4188407.63 16969793.99 0 43400.25 485047.50 2117551.00 183857564.00 ▇▁▁▁▁
cu_deaths 279 0.94 44362.78 142967.65 0 651.00 6268.00 28807.00 1204878.00 ▇▁▁▁▁
r14_cases 263 0.95 557.34 1044.46 0 51.61 216.74 576.99 13728.65 ▇▁▁▁▁
r14_deaths 321 0.94 34.08 50.74 0 3.81 14.21 42.57 435.28 ▇▁▁▁▁

State-level case and mortality data for the United States from the COVID Tracking Project

Cumulative testing, deaths, and hospitalization data over time 

skimr::skim(covus)
Data summary
Name covus
Number of rows 664960
Number of columns 7
_______________________
Column type frequency:
character 4
Date 1
logical 1
numeric 1
________________________
Group variables None

Variable type: character

skim_variable n_missing complete_rate min max empty n_unique whitespace
state 0 1 2 2 0 56 0
fips 0 1 2 2 0 56 0
measure 0 1 5 30 0 31 0
measure_label 0 1 6 54 0 32 0

Variable type: Date

skim_variable n_missing complete_rate min max median n_unique
date 0 1 2020-01-13 2021-03-07 2020-09-03 420

Variable type: logical

skim_variable n_missing complete_rate mean count
data_quality_grade 664960 0 NaN :

Variable type: numeric

skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist
count 434365 0.35 387436.8 1638507 0 498 7782 134223 49646014 ▇▁▁▁▁

Total case and death counts by race and ethnicity 

skimr::skim(covus_race)
Data summary
Name covus_race
Number of rows 47880
Number of columns 7
_______________________
Column type frequency:
character 2
Date 1
numeric 4
________________________
Group variables None

Variable type: character

skim_variable n_missing complete_rate min max empty n_unique whitespace
state 0 1 2 2 0 56 0
group 0 1 5 11 0 9 0

Variable type: Date

skim_variable n_missing complete_rate min max median n_unique
date 0 1 2020-04-12 2021-03-07 2020-09-23 95

Variable type: numeric

skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist
cases 15684 0.67 30240.68 103176.64 0 568 3661 21026 2619476 ▇▁▁▁▁
deaths 17686 0.63 708.93 1836.84 -1 12 68 440 24402 ▇▁▁▁▁
hosp 37253 0.22 2077.78 4654.37 0 67 345 1716 41099 ▇▁▁▁▁
tests 43549 0.09 349773.42 1269936.08 0 6298 36108 199214 18567612 ▇▁▁▁▁ 
skimr::skim(covus_ethnicity)
Data summary
Name covus_ethnicity
Number of rows 15960
Number of columns 7
_______________________
Column type frequency:
character 2
Date 1
numeric 4
________________________
Group variables None

Variable type: character

skim_variable n_missing complete_rate min max empty n_unique whitespace
state 0 1 2 2 0 56 0
group 0 1 7 12 0 3 0

Variable type: Date

skim_variable n_missing complete_rate min max median n_unique
date 0 1 2020-04-12 2021-03-07 2020-09-23 95

Variable type: numeric

skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist
cases 3080 0.81 73357.18 166184.31 0 5529 21920.5 70265.5 2619476 ▇▁▁▁▁
deaths 3144 0.80 1645.64 3463.93 -1 63 291.5 1401.0 32664 ▇▁▁▁▁
hosp 11662 0.27 5079.37 8831.52 0 556 1556.0 4959.5 56406 ▇▁▁▁▁
tests 14271 0.11 892566.44 2376098.22 0 58933 224156.0 537668.0 21633943 ▇▁▁▁▁

State-level and county-level case and mortality data for the United States from the New York Times 

skimr::skim(nytcovcounty)
Data summary
Name nytcovcounty
Number of rows 2502832
Number of columns 6
_______________________
Column type frequency:
character 3
Date 1
numeric 2
________________________
Group variables None

Variable type: character

skim_variable n_missing complete_rate min max empty n_unique whitespace
county 0 1.00 3 35 0 1932 0
state 0 1.00 4 24 0 56 0
fips 23678 0.99 5 5 0 3220 0

Variable type: Date

skim_variable n_missing complete_rate min max median n_unique
date 0 1 2020-01-21 2022-05-13 2021-04-23 844

Variable type: numeric

skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist
cases 0 1.00 10033.80 47525.22 0 382 1773 5884 2908425 ▇▁▁▁▁
deaths 57605 0.98 161.61 820.33 0 6 33 101 40267 ▇▁▁▁▁ 
skimr::skim(nytcovstate)
Data summary
Name nytcovstate
Number of rows 58526
Number of columns 5
_______________________
Column type frequency:
character 2
Date 1
numeric 2
________________________
Group variables None

Variable type: character

skim_variable n_missing complete_rate min max empty n_unique whitespace
state 0 1 4 24 0 56 0
fips 0 1 2 2 0 56 0

Variable type: Date

skim_variable n_missing complete_rate min max median n_unique
date 0 1 2020-01-21 2023-01-21 2021-08-16 1097

Variable type: numeric

skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist
cases 0 1 834511.91 1394631.70 1 64160 324958 985279.8 11955605 ▇▁▁▁▁
deaths 0 1 11294.84 16797.98 0 1080 4790 14373.0 101982 ▇▁▁▁▁ 
skimr::skim(nytcovus)
Data summary
Name nytcovus
Number of rows 1097
Number of columns 3
_______________________
Column type frequency:
Date 1
numeric 2
________________________
Group variables None

Variable type: Date

skim_variable n_missing complete_rate min max median n_unique
date 0 1 2020-01-21 2023-01-21 2021-07-22 1097

Variable type: numeric

skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist
cases 0 1 44522009.0 35239239.4 1 8404635 34364829 80836264 101726588 ▇▆▃▂▆
deaths 0 1 602590.7 370532.5 0 222195 609870 989584 1111011 ▆▂▅▃▇

Data from the CDC’s COVID-NET

CDC Catchment Areas_ 

skimr::skim(cdc_catchments)
Data summary
Name cdc_catchments
Number of rows 17
Number of columns 2
_______________________
Column type frequency:
character 2
________________________
Group variables None

Variable type: character

skim_variable n_missing complete_rate min max empty n_unique whitespace
name 0 1 3 9 0 3 0
area 0 1 4 14 0 15 0

Deaths by Age 

skimr::skim(cdc_deaths_by_age)
Data summary
Name cdc_deaths_by_age
Number of rows 12
Number of columns 10
_______________________
Column type frequency:
character 1
Date 3
numeric 6
________________________
Group variables None

Variable type: character

skim_variable n_missing complete_rate min max empty n_unique whitespace
age_group 0 1 5 10 0 12 0

Variable type: Date

skim_variable n_missing complete_rate min max median n_unique
data_as_of 0 1 2020-04-30 2020-04-30 2020-04-30 1
start_week 0 1 2020-02-01 2020-02-01 2020-02-01 1
end_week 0 1 2020-04-25 2020-04-25 2020-04-25 1

Variable type: numeric

skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist
covid_deaths 0 1 5753.50 9877.31 2.00 30.25 1211.50 7918.25 34521.00 ▇▃▁▁▁
total_deaths 0 1 118897.67 202377.07 712.00 5675.25 28460.00 149341.50 713386.00 ▇▂▁▁▁
percent_expected_deaths 0 1 0.97 0.00 0.97 0.97 0.97 0.97 0.97 ▁▁▇▁▁
pneumonia_deaths 0 1 10454.17 18036.25 33.00 109.00 1799.50 14114.25 62725.00 ▇▃▁▁▁
pneumonia_and_covid_deaths 0 1 2550.17 4387.93 0.00 12.50 491.50 3515.75 15301.00 ▇▃▁▁▁
all_influenza_deaths_j09_j11 0 1 970.17 1618.90 11.00 40.75 358.50 1222.75 5821.00 ▇▃▁▁▁

Deaths by Sex 

skimr::skim(cdc_deaths_by_sex)
Data summary
Name cdc_deaths_by_sex
Number of rows 3
Number of columns 10
_______________________
Column type frequency:
character 1
Date 3
numeric 6
________________________
Group variables None

Variable type: character

skim_variable n_missing complete_rate min max empty n_unique whitespace
sex 0 1 4 7 0 3 0

Variable type: Date

skim_variable n_missing complete_rate min max median n_unique
data_as_of 0 1 2020-04-30 2020-04-30 2020-04-30 1
start_week 0 1 2020-02-01 2020-02-01 2020-02-01 1
end_week 0 1 2020-04-25 2020-04-25 2020-04-25 1

Variable type: numeric

skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist
covid_deaths 0 1 11507.33 10231.40 1.00 7470.50 14940.00 17260.50 19581.00 ▇▁▁▇▇
total_deaths 0 1 237795.00 206241.06 25.00 172555.00 345085.00 356680.00 368275.00 ▃▁▁▁▇
percent_expected_deaths 0 1 0.97 0.00 0.97 0.97 0.97 0.97 0.97 ▁▁▇▁▁
pneumonia_deaths 0 1 20908.33 18248.40 1.00 14545.00 29089.00 31362.00 33635.00 ▃▁▁▁▇
pneumonia_and_covid_deaths 0 1 5100.33 4559.67 1.00 3258.00 6515.00 7650.00 8785.00 ▇▁▁▇▇
all_influenza_deaths_j09_j11 0 1 1940.33 1682.21 0.00 1416.00 2832.00 2910.50 2989.00 ▃▁▁▁▇

Deaths by State 

skimr::skim(cdc_deaths_by_state)
Data summary
Name cdc_deaths_by_state
Number of rows 53
Number of columns 10
_______________________
Column type frequency:
character 1
Date 3
numeric 6
________________________
Group variables None

Variable type: character

skim_variable n_missing complete_rate min max empty n_unique whitespace
state 0 1 4 20 0 53 0

Variable type: Date

skim_variable n_missing complete_rate min max median n_unique
data_as_of 0 1 2020-04-30 2020-04-30 2020-04-30 1
start_week 0 1 2020-02-01 2020-02-01 2020-02-01 1
end_week 0 1 2020-04-25 2020-04-25 2020-04-25 1

Variable type: numeric

skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist
covid_deaths 6 0.89 735.02 1801.11 0 54.50 153.00 519.00 10978.00 ▇▁▁▁▁
total_deaths 0 1.00 13557.43 13996.83 856 3813.00 10721.00 17624.00 69341.00 ▇▂▁▁▁
percent_expected_deaths 0 1.00 0.93 0.27 0 0.86 0.95 0.99 2.19 ▁▂▇▁▁
pneumonia_deaths 0 1.00 1197.26 1453.17 41 277.00 769.00 1306.00 6076.00 ▇▁▁▁▁
pneumonia_and_covid_deaths 10 0.81 355.81 759.51 0 30.50 65.00 296.00 4019.00 ▇▁▁▁▁
all_influenza_deaths_j09_j11 3 0.94 116.58 142.24 14 30.50 87.50 125.50 850.00 ▇▁▁▁▁

Deaths by Week 

skimr::skim(cdc_deaths_by_week)
Data summary
Name cdc_deaths_by_week
Number of rows 13
Number of columns 10
_______________________
Column type frequency:
Date 3
numeric 7
________________________
Group variables None

Variable type: Date

skim_variable n_missing complete_rate min max median n_unique
data_as_of 0 1 2020-04-30 2020-04-30 2020-04-30 1
start_week 0 1 2020-02-01 2020-04-25 2020-03-14 13
end_week 0 1 2020-02-01 2020-04-25 2020-03-14 13

Variable type: numeric

skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist
covid_deaths 0 1 2655.46 4194.37 0.00 0.00 49.00 2659.00 11864.00 ▇▁▁▂▁
total_deaths 0 1 54875.85 9864.46 24387.00 53940.00 56831.00 57299.00 65676.00 ▁▁▁▇▂
percent_expected_deaths 0 1 0.97 0.17 0.45 0.97 0.97 0.99 1.19 ▁▁▁▇▂
pneumonia_deaths 0 1 4825.00 2217.19 2219.00 3671.00 3692.00 5598.00 9580.00 ▇▃▁▁▂
pneumonia_and_covid_deaths 0 1 1177.00 1863.76 0.00 0.00 25.00 1220.00 5281.00 ▇▁▁▂▁
all_influenza_deaths_j09_j11 0 1 447.77 156.19 58.00 427.00 494.00 536.00 619.00 ▁▁▁▇▇
pneumonia_influenza_and_covid_19_deaths 0 1 6690.23 4292.62 3553.00 4165.00 4275.00 7397.00 16272.00 ▇▁▁▂▁

National ER Visits 

skimr::skim(nssp_covid_er_nat)
Data summary
Name nssp_covid_er_nat
Number of rows 54
Number of columns 9
_______________________
Column type frequency:
character 4
numeric 5
________________________
Group variables None

Variable type: character

skim_variable n_missing complete_rate min max empty n_unique whitespace
total_ed_visits 0 1 7 7 0 27 0
visit_type 0 1 3 3 0 2 0
region 0 1 8 8 0 1 0
source 0 1 21 21 0 1 0

Variable type: numeric

skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist
week 0 1 26.04 19.81 1.00 7.25 14.00 45.75 52.00 ▇▂▁▂▇
num_fac 0 1 3346.89 48.97 3249.00 3329.50 3352.00 3389.50 3406.00 ▃▁▆▃▇
visits 0 1 41521.67 16344.25 17639.00 31216.00 39183.50 50532.00 86088.00 ▅▇▃▂▁
pct_visits 0 1 0.02 0.01 0.01 0.01 0.02 0.02 0.05 ▇▆▂▁▂
year 0 1 2019.52 0.50 2019.00 2019.00 2020.00 2020.00 2020.00 ▇▁▁▁▇

Regional ER Visits 

skimr::skim(nssp_covid_er_reg)
Data summary
Name nssp_covid_er_reg
Number of rows 538
Number of columns 9
_______________________
Column type frequency:
character 4
numeric 5
________________________
Group variables None

Variable type: character

skim_variable n_missing complete_rate min max empty n_unique whitespace
total_ed_visits 0 1 5 6 0 269 0
visit_type 0 1 3 3 0 2 0
region 0 1 8 9 0 10 0
source 0 1 21 21 0 1 0

Variable type: numeric

skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist
week 0 1 25.99 19.66 1 7.00 14.00 46.00 52.00 ▇▂▁▂▇
num_fac 0 1 335.18 234.58 135 190.00 222.00 343.00 884.00 ▇▃▁▂▂
visits 0 1 4164.87 4028.53 279 1596.00 2780.00 4723.75 23345.00 ▇▂▁▁▁
pct_visits 0 1 0.02 0.01 0 0.01 0.02 0.02 0.11 ▇▂▁▁▁
year 0 1 2019.52 0.50 2019 2019.00 2020.00 2020.00 2020.00 ▇▁▁▁▇

Data from the U.S. National Center for Health Statistics

Provisional COVID-19 Death Counts by Sex, Age, and State 

skimr::skim(nchs_sas)
Data summary
Name nchs_sas
Number of rows 115668
Number of columns 15
_______________________
Column type frequency:
character 6
Date 1
numeric 8
________________________
Group variables None

Variable type: character

skim_variable n_missing complete_rate min max empty n_unique whitespace
start_date 0 1 10 10 0 37 0
end_date 0 1 10 10 0 37 0
group 0 1 7 8 0 3 0
state 0 1 4 20 0 54 0
sex 0 1 4 9 0 3 0
age_group 0 1 8 17 0 17 0

Variable type: Date

skim_variable n_missing complete_rate min max median n_unique
data_as_of 0 1 2023-01-18 2023-01-18 2023-01-18 1

Variable type: numeric

skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist
year 2754 0.98 2021.10 0.91 2020 2020 2021 2022 2023 ▇▇▁▇▁
month 13770 0.88 6.35 3.52 1 3 6 9 12 ▇▅▅▅▇
covid_19_deaths 31823 0.72 351.76 6263.51 0 0 10 60 1094723 ▇▁▁▁▁
total_deaths 17146 0.85 2812.18 52269.95 0 41 148 648 10144808 ▇▁▁▁▁
pneumonia_deaths 36293 0.69 349.71 6016.66 0 0 17 76 1030983 ▇▁▁▁▁
pneumonia_and_covid_19_deaths 30476 0.74 174.88 3162.39 0 0 0 26 550128 ▇▁▁▁▁
influenza_deaths 22407 0.81 4.94 103.26 0 0 0 0 18477 ▇▁▁▁▁
pneumonia_influenza_or_covid_19_deaths 35678 0.69 535.21 9239.91 0 0 25 112 1591892 ▇▁▁▁▁

Estimated distributions of US COVID-19 deaths and population size by race and Hispanic origin, by State 

skimr::skim(nchs_wss)
Data summary
Name nchs_wss
Number of rows 15582
Number of columns 12
_______________________
Column type frequency:
character 6
Date 1
numeric 5
________________________
Group variables None

Variable type: character

skim_variable n_missing complete_rate min max empty n_unique whitespace
start_date 0 1 10 10 0 37 0
end_date 0 1 10 10 0 37 0
year 0 1 4 9 0 5 0
obs_unit 0 1 7 8 0 3 0
state 0 1 4 20 0 53 0
race_ethnicity 0 1 18 54 0 7 0

Variable type: Date

skim_variable n_missing complete_rate min max median n_unique
data_as_of 0 1 2023-01-18 2023-01-18 2023-01-18 1

Variable type: numeric

skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist
month 1855 0.88 6.35 3.52 1 3.0 6.0 9.0 12.0 ▇▅▅▅▇
deaths 4625 0.70 596.40 8680.87 0 0.0 14.0 100.0 718968.0 ▇▁▁▁▁
dist_pct 4625 0.70 17.59 29.22 0 0.0 1.1 19.7 100.0 ▇▁▁▁▁
uw_dist_pop_pct 0 1.00 14.28 23.57 0 0.9 3.1 12.7 92.7 ▇▁▁▁▁
wt_dist_pop_pct 0 1.00 13.68 21.60 0 0.5 3.2 14.4 93.6 ▇▁▁▁▁

Cross-national short-term mortality fluctuations data from the Human Mortality Database 

skimr::skim(stmf)
Data summary
Name stmf
Number of rows 580395
Number of columns 17
_______________________
Column type frequency:
character 7
Date 1
numeric 9
________________________
Group variables None

Variable type: character

skim_variable n_missing complete_rate min max empty n_unique whitespace
country_code 0 1.00 3 7 0 38 0
cname 0 1.00 5 25 0 38 0
iso2 34380 0.94 2 2 0 35 0
continent 35850 0.94 4 13 0 5 0
iso3 34380 0.94 3 3 0 35 0
sex 0 1.00 1 1 0 3 0
age_group 0 1.00 3 5 0 5 0

Variable type: Date

skim_variable n_missing complete_rate min max median n_unique
approx_date 0 1 1990-01-07 2023-01-01 2012-10-07 1722

Variable type: numeric

skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist
year 0 1 2011.58 6.88 1990 2006.00 2012.00 2017.00 2022.00 ▁▂▆▆▇
week 0 1 26.50 15.03 1 13.00 26.00 39.00 53.00 ▇▇▇▇▇
split 0 1 0.12 0.32 0 0.00 0.00 0.00 1.00 ▇▁▁▁▁
split_sex 0 1 0.00 0.07 0 0.00 0.00 0.00 1.00 ▇▁▁▁▁
forecast 0 1 0.10 0.30 0 0.00 0.00 0.00 1.00 ▇▁▁▁▁
death_count 0 1 617.60 1585.49 0 39.00 162.00 449.75 26362.00 ▇▁▁▁▁
death_rate 0 1 0.05 0.07 0 0.00 0.02 0.07 0.57 ▇▂▁▁▁
deaths_total 0 1 3088.00 6498.29 2 472.00 998.00 2543.00 87413.00 ▇▁▁▁▁
rate_total 0 1 0.01 0.00 0 0.01 0.01 0.01 0.04 ▅▇▁▁▁

National-level all-cause and excess mortality estimates from the New York Times 

skimr::skim(nytexcess)
Data summary
Name nytexcess
Number of rows 7258
Number of columns 12
_______________________
Column type frequency:
character 5
Date 2
numeric 5
________________________
Group variables None

Variable type: character

skim_variable n_missing complete_rate min max empty n_unique whitespace
country 0 1.00 4 14 0 35 0
placename 6883 0.05 6 8 0 4 0
frequency 0 1.00 6 7 0 2 0
year 0 1.00 4 17 0 15 0
baseline 5990 0.17 20 25 0 7 0

Variable type: Date

skim_variable n_missing complete_rate min max median n_unique
start_date 768 0.89 2010-01-09 2020-12-23 2018-02-05 1267
end_date 768 0.89 2010-01-15 2020-12-29 2018-02-11 1267

Variable type: numeric

skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist
month 0 1.00 6.60 3.36 1 4.00 7.0 9.0 12 ▇▆▆▆▇
week 666 0.91 26.77 14.58 2 14.00 27.0 39.0 52 ▇▇▇▇▇
deaths 0 1.00 7968.24 14334.14 455 1460.00 2395.5 10486.0 141292 ▇▁▁▁▁
expected_deaths 5990 0.17 9237.09 15850.00 548 1443.00 2423.0 10771.5 139343 ▇▁▁▁▁
excess_deaths 5990 0.17 1195.43 3242.72 -6721 -42.25 76.5 926.0 30400 ▇▂▁▁▁

Mobility Data from Apple 

skimr::skim(apple_mobility)
Data summary
Name apple_mobility
Number of rows 2254515
Number of columns 7
_______________________
Column type frequency:
character 5
Date 1
numeric 1
________________________
Group variables None

Variable type: character

skim_variable n_missing complete_rate min max empty n_unique whitespace
country 0 1 5 20 0 63 0
sub_region 0 1 4 46 0 606 0
subregion_and_city 0 1 4 46 0 853 0
geo_type 0 1 4 14 0 3 0
transportation_type 0 1 7 7 0 3 0

Variable type: Date

skim_variable n_missing complete_rate min max median n_unique
date 0 1 2020-01-13 2022-04-12 2021-02-26 819

Variable type: numeric

skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist
score 608041 0.73 122.59 66.81 2.43 83.79 113.72 148.8 2228.83 ▇▁▁▁▁

Other Tables

Country Codes 

countries %>%
  dplyr::ungroup() %>%
  skimr::skim()
Data summary
Name Piped data
Number of rows 213
Number of columns 4
_______________________
Column type frequency:
character 4
________________________
Group variables None

Variable type: character

skim_variable n_missing complete_rate min max empty n_unique whitespace
cname 0 1.00 4 42 0 213 0
iso3 0 1.00 3 3 0 213 0
iso2 2 0.99 2 2 0 211 0
continent 0 1.00 4 13 0 6 0

U.S. Census Population Estimates 

skimr::skim(uspop)
Data summary
Name uspop
Number of rows 459
Number of columns 17
_______________________
Column type frequency:
character 10
numeric 7
________________________
Group variables None

Variable type: character

skim_variable n_missing complete_rate min max empty n_unique whitespace
state 0 1.00 4 20 0 51 0
state_abbr 9 0.98 2 2 0 50 0
statefips 0 1.00 2 2 0 51 0
region_name 9 0.98 4 9 0 4 0
division_name 9 0.98 7 18 0 9 0
sex_id 0 1.00 4 6 0 3 0
sex 0 1.00 4 10 0 3 0
hisp_id 0 1.00 4 7 0 3 0
hisp_label 0 1.00 5 12 0 3 0
fips 0 1.00 11 11 0 51 0

Variable type: numeric

skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist
pop 0 1 2851132.32 4198641.26 6154 386961.5 1349442 3558480.0 39557045 ▇▁▁▁▁
white 0 1 2179861.40 3116129.25 5120 296294.0 1088503 2759335.5 28531740 ▇▁▁▁▁
black 0 1 381736.98 644380.66 260 11907.0 80714 486281.5 3673855 ▇▁▁▁▁
amind 0 1 36143.97 65036.83 161 6103.5 15273 35770.5 651076 ▇▁▁▁▁
asian 0 1 168458.39 515557.14 79 5045.5 26484 140424.5 6063600 ▇▁▁▁▁
nhopi 0 1 6966.61 18657.18 23 669.0 2029 5063.5 199872 ▇▁▁▁▁
tom 0 1 77964.97 131251.16 455 12091.0 33757 98669.5 1554757 ▇▁▁▁▁