R/cleaning_scripts/Run_this_first_18.R
In gabrielburcea/cvindia: Analysis of symptoms
# library(tidyverse)
# library(naniar)
# library(forcats)
# data_rec <-
# read_csv("/Users/gabrielburcea/Rprojects/data/csvdata.csv")
# nrow(distinct(data_rec))
# data_rename <- data_rec %>%
# dplyr::rename(
# id = ID,
# age = Age,
# gender = Gender,
# location = Location,
# country = Country,
# chills = Chills,
# cough = Cough,
# diarrhoea = Diarrhoea,
# fatigue = Fatigue,
# headache = Headcahe,
# pregnant = Pregnant,
# sputum = Sputum,
# temperature = Temperature,
# sneezing = Sneezing,
# loss_of_smell_and_taste = "Loss of smell and taste",
# muscle_ache = 'Muscle Ache',
# nasal_congestion = "Nasal Congestion",
# nausea_vomiting = "Nausea and Vomiting",
# self_diagnosis = "Self Diagnosis",
# shortness_breath = "Shortness of Breath",
# sore_throat = "Sore Throat",
# loss_appetite = "Loss of Appetite",
# chest_pain = "Chest Pain",
# itchy_eyes = "Itchy Eyes",
# joint_pain = "Joint Pain",
# care_home_worker = 'Care Home Worker',
# health_care_worker = "Healthcare Worker",
# date_completed = 'Date Completed',
# how_unwell = "How Unwell",
# number_days_symptom_showing = "Number Of Days Symptoms Showing",
# reason_for_help = "Reason For Helping",
# language = Language,
# health_condition = "Long Standing Health Issues"
# ) %>%
# dplyr::mutate(id = str_sub(id, -10))
# data_com <- data_rename %>%
# rowwise() %>%
# mutate(health_condition =
# str_extract_all(health_condition,
# pattern = "None|Diabetes Type 2|Asthma \\(managed with an inhaler\\)|Obesity|High Blood Pressure \\(hypertension\\)|Long-Standing Lung Condition|Long-Standing Liver Disease|Long-Standing Heart Disease|Long-Standing Kidney Disease|Diabetes Type 1 \\(controlled by insulin\\)"),
# health_condition = paste(health_condition, collapse = ","))
# data_com$health_condition <- sub("^$", "None", data_com$health_condition)
# reason_for_help_levels <-
# c(
# "negative" = "Curious",
# "negative" = "Curious,Self-Isolating With No Symptoms" ,
# "negative" = "Live With Someone With Coronavirus",
# "negative" = "Live With Someone With Coronavirus,Curious" ,
# "negative" = "Live With Someone With Coronavirus,Curious,Self-Isolating With No Symptoms",
# "negative" = "Live With Someone With Coronavirus,Self-Isolating With No Symptoms",
# "negative" = "Muscle Ache",
# "negative" = "No",
# "negative" = "None",
# "negative" = "Reason For Helping",
# "showing symptoms" = "Recovered But Have New Symptoms",
# "showing symptoms" = "Recovered But Have New Symptoms,Curious",
# "showing symptoms" = "Recovered But Have New Symptoms,Curious,Self-Isolating With No Symptoms",
# "showing symptoms" = "Recovered But Have New Symptoms,Self-Isolating With No Symptoms",
# "negative" = "Self-Isolating With No Symptoms",
# "showing symptoms" = "Showing Symptoms But Not Tested",
# "showing symptoms" = "Showing Symptoms But Not Tested,Curious",
# "showing symptoms" = "Showing Symptoms But Not Tested,Curious,Self-Isolating With No Symptoms",
# "showing symptoms" = "Showing Symptoms But Not Tested,Live With Someone With Coronavirus",
# "showing symptoms" = "Showing Symptoms But Not Tested,Live With Someone With Coronavirus,Curious",
# "showing symptoms" = "Showing Symptoms But Not Tested,Live With Someone With Coronavirus,Recovered But Have New Symptoms",
# "showing symptoms" = "Showing Symptoms But Not Tested,Recovered But Have New Symptoms",
# "showing symptoms" = "Showing Symptoms But Not Tested,Recovered But Have New Symptoms,Curious",
# "showing symptoms" = "Showing Symptoms But Not Tested,Self-Isolating With No Symptoms",
# "showing symptoms" = "Tested Negative But Have Symptoms",
# "showing symptoms" = "Tested Negative But Have Symptoms,Curious",
# "showing symptoms" = "Tested Negative But Have Symptoms,Curious,Self-Isolating With No Symptoms",
# "showing symptoms" = "Tested Negative But Have Symptoms,Live With Someone With Coronavirus",
# "showing symptoms" = "Tested Negative But Have Symptoms,Live With Someone With Coronavirus,Recovered But Have New Symptoms",
# "showing symptoms" = "Tested Negative But Have Symptoms,Self-Isolating With No Symptoms",
# "showing symptoms" = "Tested Negative But Have Symptoms,Showing Symptoms But Not Tested",
# "showing symptoms" = "Tested Negative But Have Symptoms,Showing Symptoms But Not Tested,Curious",
# "showing symptoms" = "Tested Negative But Have Symptoms,Showing Symptoms But Not Tested,Recovered But Have New Symptoms,Curious,Self-Isolating With No Symptoms",
# "positive" = "Tested Positive",
# "positive" = "Tested Positive,Curious",
# "positive" = "Tested Positive,Live With Someone With Coronavirus",
# "positive" = "Tested Positive,Recovered But Have New Symptoms",
# "positive" = "Tested Positive,Recovered But Have New Symptoms,Curious",
# "positive" = "Tested Positive,Self-Isolating With No Symptom",
# "positive" = "Tested Positive,Showing Symptoms But Not Tested",
# "positive" = "Tested Positive,Tested Negative But Have Symptoms",
# "positive" = "Tested Positive,Tested Negative But Have Symptoms,Recovered But Have New Symptoms",
# "positive" = "Tested Positive,Tested Negative But Have Symptoms,Showing Symptoms But Not Tested",
# "positive" = "Tested Positive,Tested Negative But Have Symptoms,Showing Symptoms But Not Tested,Curious",
# "positive" = "Tested Positive,Tested Negative But Have Symptoms,Showing Symptoms But Not Tested,Live With Someone With Coronavirus,Recovered But Have New Symptoms,Curious,Self-Isolating With No Symptoms",
# "positive" = "Tested Positive,Tested Negative But Have Symptoms,Showing Symptoms But Not Tested,Recovered But Have New Symptoms,Curious,Self-Isolating With No Symptom)",
# "positive" = "Tested Positive,Tested Negative But Have Symptoms,Showing Symptoms But Not Tested,Recovered But Have New Symptoms,Curious,Self-Isolating With No Symptoms",
# "positive" = "Tested Positive,Self-Isolating With No Symptoms"
# )
# data_comorb <- data_com %>%
# tidyr::separate(
# health_condition,
# c(
# 'Comorbidity_one',
# 'Comorbidity_two',
# 'Comorbidity_three',
# 'Comorbidity_four',
# 'Comorbidity_five',
# 'Comorbidity_six',
# 'Comorbidity_seven',
# 'Comorbidity_eight',
# 'Comorbidity_nine'
# ),
# sep = ","
# )
# data_comorb %>% distinct(Comorbidity_one)
# data_comorb %>% distinct(Comorbidity_two)
# data_comorb %>% distinct(Comorbidity_three)
# data_comorb %>% distinct(Comorbidity_four)
# data_comorb %>% distinct(Comorbidity_five)
# data_comorb %>% distinct(Comorbidity_six)
# data_comorb %>% distinct(Comorbidity_seven)
# data_comorb %>% distinct(Comorbidity_eight)
# data_comorb %>% distinct(Comorbidity_nine)
# data_long_wid <- data_comorb %>%
# tidyr::pivot_longer(cols = starts_with('Comorbidity'),
# names_to = 'Comorbidity_count',
# values_to = 'Comorbidity') %>%
# naniar::replace_with_na(replace = list(Comorbidity = "None")) %>%
# distinct() %>%
# dplyr::group_by(id) %>%
# dplyr::mutate(number_morbidities = sum(!is.na(Comorbidity))) %>%
# tidyr::drop_na('Comorbidity') %>%
# dplyr::select(-Comorbidity_count) %>%
# dplyr::distinct() %>%
# dplyr::mutate(Condition = 'Yes') %>%
# tidyr::pivot_wider(names_from = Comorbidity, values_from = Condition, values_fill = list(Condition = 'No'))
#
# df_comorbidity_unique <- distinct(data_comorb, id, .keep_all = TRUE)
# ###########################################################
# ### Get patients without multiple comorbidities but also count the number of patients
# make sure count on unique number of patients #########
# ##########################################################
# data_c <- df_comorbidity_unique %>%
# tidyr::pivot_longer(cols = starts_with('Comorbidity'),
# names_to = 'Comorbidity_count',
# values_to = 'Comorbidity') %>%
# dplyr::mutate(Comorbidity = if_else(Comorbidity == "None", NA_character_, Comorbidity)) %>%
# distinct() %>%
# dplyr::group_by(id) %>%
# mutate(number_morbidities = sum(!is.na(Comorbidity)))
#
# data_unique_comorb <- data_c %>%
# tidyr::pivot_longer(cols = starts_with('Comorbidity'),
# names_to = 'Comorbidity_count',
# values_to = 'Comorbidity') %>%
# tidyr::drop_na('Comorbidity') %>%
# dplyr::select(-Comorbidity_count) %>%
# dplyr::distinct() %>%
# dplyr::mutate(Condition = 'Yes') %>%
# tidyr::pivot_wider(id_cols = -c(Comorbidity, Condition), names_from = Comorbidity, values_from = Condition, values_fill = list(Condition = 'No')) %>%
# dplyr::select(-Comorbidity_one)
# # # # #################################################
# # # # ######### Get a numeric dataset #################
# # # # #################################################
# data_model <- data_unique_comorb %>% # here make sure the dataset is ritght - either patients with multiple comorbidities or patients without multitple comorbidties
# dplyr::mutate(covid_tested = forcats::fct_recode(reason_for_help, !!!reason_for_help_levels)) %>%
# dplyr::select(-reason_for_help)
# data_model$gender <- as.factor(data_model$gender)
# data_model$country <- as.factor(data_model$country)
# data_model$chills <- as.factor(data_model$chills)
# data_model$cough <- as.factor(data_model$cough)
# data_model$diarrhoea <- as.factor(data_model$diarrhoea)
# data_model$fatigue <- as.factor(data_model$fatigue)
# data_model$headache <- as.factor(data_model$headache)
# data_model$loss_of_smell_and_taste <- as.factor(data_model$loss_of_smell_and_taste)
# data_model$muscle_ache <- as.factor(data_model$muscle_ache)
# data_model$nasal_congestion <- as.factor(data_model$nasal_congestion)
# data_model$nausea_vomiting <- as.factor(data_model$nausea_vomiting)
# data_model$self_diagnosis <- as.factor(data_model$self_diagnosis)
# data_model$shortness_breath <- as.factor(data_model$shortness_breath)
# data_model$sore_throat <- as.factor(data_model$sore_throat)
# data_model$sputum <- as.factor(data_model$sputum)
# data_model$temperature <- as.factor(data_model$temperature)
# data_model$health_care_worker <- as.factor(data_model$health_care_worker)
# data_model$care_home_worker <- as.factor(data_model$care_home_worker)
# data_model$asthma <- as.factor(data_model$`Asthma (managed with an inhaler)`)
# data_model$diabetes_type_two <- as.factor(data_model$`Diabetes Type 2`)
# data_model$obesity <- as.factor(data_model$Obesity)
# data_model$hypertension <- as.factor(data_model$`High Blood Pressure (hypertension)`)
# data_model$heart_disease <- as.factor(data_model$`Long-Standing Heart Disease`)
# data_model$kidney_disease <- as.factor(data_model$`Long-Standing Kidney Disease`)
# data_model$lung_condition <- as.factor(data_model$`Long-Standing Lung Condition`)
# data_model$liver_disease <- as.factor(data_model$`Long-Standing Liver Disease`)
# data_model$diabetes_type_one <- as.factor(data_model$`Diabetes Type 1 (controlled by insulin)`)
# data_model$how_unwell <- as.factor(data_model$how_unwell)
# data_model$covid_tested <- as.factor(data_model$covid_tested)
# data_model$id <- as.character(data_model$id)
# data_model$age <- as.numeric(data_model$age)
# data_model$gender <- as.factor(data_model$gender)
# data_model$pregnant <- as.factor(data_model$pregnant)
# data_model$date_completed <- as.Date(data_model$date_completed)
# data_model$location <- as.factor(data_model$location)
# data_model$loss_appetite <- as.factor(data_model$loss_appetite)
# data_model$sneezing <- as.factor(data_model$sneezing)
# data_model$chest_pain <- as.factor(data_model$chest_pain)
# data_model$itchy_eyes <- as.factor(data_model$itchy_eyes)
# data_model$joint_pain <- as.factor(data_model$joint_pain)
# # # #### Refactor the levels ##################################################
# data_sel <- data_model %>% # here make sure the dataset is ritght - either patients with multiple comorbidities or patients without multitple comorbidties
# dplyr::select(
# id,
# covid_tested,
# age,
# gender,
# country,
# location,
# date_completed,
# care_home_worker,
# chills,
# cough,
# diarrhoea,
# fatigue,
# headache,
# health_care_worker,
# how_unwell,
# loss_of_smell_and_taste,
# muscle_ache,
# nasal_congestion,
# nausea_vomiting,
# number_days_symptom_showing,
# pregnant,
# self_diagnosis,
# shortness_breath,
# sore_throat,
# sputum,
# temperature,
# language,
# loss_appetite,
# sneezing,
# chest_pain,
# itchy_eyes,
# joint_pain,
# covid_tested,
# asthma,
# diabetes_type_one,
# diabetes_type_two,
# obesity,
# hypertension,
# heart_disease,
# lung_condition,
# liver_disease,
# kidney_disease,
# number_morbidities
# )
# data_sel %>% distinct(cough)
#
# data_model %>% distinct(chills)
#
# level_key_chills <-
# c( 'Yes' = "Chills",
# 'Yes' = "Mild",
# 'Yes' = "Moderate",
# 'Yes' = "Severe",
# 'No' = "Location",
# 'No' = "Gender")
# level_key_cough <-
# c( 'Yes' = "Cough",
# 'Yes' = "Mild",
# 'Yes' = "Moderate",
# 'Yes' = "Severe",
# 'Yes' = 'Cough')
# data_sel %>% distinct(diarrhoea)
# level_key_diarrhoea <-
# c(
# 'Yes' = "Mild",
# 'Yes' = "Moderate",
# 'Yes' = "Severe",
# 'No' = "Diarrhoea",
# 'No' ='Country')
# data_sel %>% distinct(fatigue)
# level_key_fatigue <-
# c( 'No' = 'Date Completed',
# 'No' = "Fatigue",
# 'Yes' = "Mild",
# 'Yes' = "Moderate",
# 'Yes' = "Severe"
# )
# data_sel %>% distinct(headache)
# level_key_headache <-
# c('No' = 'Headache',
# 'No' = 'Care Home Worker',
# 'Yes' = "Mild",
# 'Yes' = "Moderate",
# 'Yes' = "Severe",
# 'Yes' = "Headcahe")
# data_sel %>% distinct(loss_of_smell_and_taste)
# level_key_loss_smell_taste <-
# c( 'No' = "Loss of smell and taste",
# 'No' = 'Brazil',
# 'No' = 'Peru',
# 'No' = 'Fatigue',
# 'Yes' = "Mild",
# 'Yes' = "Moderate",
# 'Yes' = "Severe")
# data_sel %>% distinct(muscle_ache)
# level_key_muschle_ache <-
# c( 'No' = "Muscle Ache",
# 'No' = "2020-08-04 17:11:00",
# 'No' = "2020-08-02 01:55:00",
# 'No' = "2020-08-01 15:11:00",
# 'No' = "Headcahe",
# 'Yes' = "Mild",
# 'Yes' = "Moderate",
# 'Yes' = "Severe")
# data_sel %>% distinct(nasal_congestion)
# level_key_nasal_congestion <-
# c( 'No' = "Healthcare Worker",
# 'Yes' = "Nasal Congestion",
# 'Yes' = "Mild",
# 'Yes' = "Moderate",
# 'Yes' = "Severe")
# data_sel %>% distinct(nausea_vomiting)
# level_key_nausea_vomiting <-
# c( 'No' = "How Unwell",
# 'Yes' = "Nausea and Vomiting",
# 'Yes' = "Mild",
# 'Yes' = "Moderate",
# 'Yes' = "Severe")
# data_sel %>% distinct(self_diagnosis)
# level_key_self_diagnosis <-
# c( 'No' = "None",
# 'Yes' = "Mild",
# 'Yes' = "Moderate",
# 'Yes' = "Severe",
# 'No' = "Self Diagnosis",
# 'No' = "Nasal Congestion")
# data_sel %>% distinct(shortness_breath)
# level_key_short_breath <-
# c( 'No' = "Nausea and Vomiting",
# 'Yes' = "Shortness of Breath",
# 'Yes' = "Mild",
# 'Yes' = "Moderate",
# 'Yes' = "Severe")
# data_sel %>% distinct(sore_throat)
# level_key_sore_throat <-
# c( 'No' = "Number Of Days Symptoms Showing",
# 'No' = '1',
# 'No' = "Sore Throat",
# 'Yes' = "Mild",
# 'Yes' = "Moderate",
# 'Yes' = "Severe")
# data_sel %>% distinct(sputum)
# level_key_sputum <-
# c( 'No' = "None",
# 'No' = "Long-Standing Lung Condition",
# 'No' = "Pregnant",
# "No" = 'High Blood Pressure (hypertension),No,No,Yes,No,2,No,Showing Symptoms But Not Tested,Mild,No,No,No,No,Portuguese,No, No,No,No,No\n380a7278-700f-441f-9c7c-6013e80f2f78,62,Male,"Cd. Madero Tamaulipas',
# 'Yes' = "Sputum",
# 'Yes' = "Mild",
# 'Yes' = "Moderate",
# 'Yes' = "Severe")
# level_key_care_home_worker <-
# c(
# 'No' = 'Care Home Worker',
# 'No' = 'Age')
# data_sel %>% distinct(temperature)
# level_key_temperature <-
# c('No' = 'Temperature',
# 'No' = "Mexico",
# 'No' = "Reason For Helping",
# 'Yes' = "37.5-38",
# 'Yes' = "38.1-39",
# 'Yes' = "39.1-41",
# 'Yes' = "38.2-39")
# data_sel %>% distinct(loss_appetite)
# level_key_loss_appetite <-
# c('No' = "Loss of Appetite",
# 'No' = "Shortness of Breath")
# data_sel %>% distinct(sneezing)
# level_key_sneezing <-
# c('No' = "Sneezing",
# 'No' = "Sore Throat")
# data_sel %>% distinct(chest_pain)
# level_key_chest_pain <-
# c('No' = 'Chest Pain',
# 'No' = '0',
# 'No' = 'Sputum')
# data_sel %>% distinct(itchy_eyes)
# level_key_itchy_eyes <-
# c('No' = "Itchy Eyes",
# 'No' = "Temperature")
# data_sel %>% distinct(joint_pain)
# level_key_joint_pain <-
# c('No' = 'Joint Pain',
# 'No' = "Showing Symptoms But Not Tested",
# 'No' = "Language")
# itchy_eyes_t <- table(data_sel$itchy_eyes)
# # # #### Refactor the levels ##################################################
# data_categ_nosev <- data_sel %>%
# dplyr::mutate(chills = forcats::fct_recode(chills, !!!level_key_chills),
# cough = forcats::fct_recode(cough, !!!level_key_cough),
# diarrhoea = forcats::fct_recode(diarrhoea, !!!level_key_diarrhoea),
# fatigue = forcats::fct_recode(fatigue, !!!level_key_fatigue),
# headache = forcats::fct_recode(headache, !!!level_key_headache),
# loss_smell_taste = forcats::fct_recode(loss_of_smell_and_taste, !!!level_key_loss_smell_taste),
# muscle_ache = forcats::fct_recode(muscle_ache, !!!level_key_muschle_ache),
# nasal_congestion = forcats::fct_recode(nasal_congestion, !!!level_key_nasal_congestion),
# nausea_vomiting = forcats::fct_recode(nausea_vomiting, !!!level_key_nausea_vomiting),
# self_diagnosis = forcats::fct_recode(self_diagnosis, !!!level_key_self_diagnosis),
# shortness_breath = forcats::fct_recode(shortness_breath, !!!level_key_short_breath),
# sore_throat = forcats::fct_recode(sore_throat, !!!level_key_sore_throat),
# sputum = forcats::fct_recode(sputum, !!!level_key_sputum),
# temperature = forcats::fct_recode(temperature, !!!level_key_temperature),
# loss_appetite = forcats::fct_recode(loss_appetite, !!!level_key_loss_appetite),
# sneezing = forcats::fct_recode(sneezing, !!!level_key_sneezing),
# chest_pain = forcats::fct_recode(chest_pain, !!!level_key_chest_pain),
# itchy_eyes = forcats::fct_recode(itchy_eyes, !!!level_key_itchy_eyes),
# joint_pain = forcats::fct_recode(joint_pain, !!!level_key_joint_pain))
# sputum_lev <-table(data_categ_nosev$sputum)
# data_categ_nosev_comorbidity_one <- data_categ_nosev
# write.csv(data_categ_nosev_comorbidity_one, file = "/Users/gabrielburcea/Rprojects/stats_data_whole/cleaned_data_18_08_2020.csv", row.names = FALSE)
gabrielburcea/cvindia documentation built on Feb. 17, 2021, 3:31 a.m.
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# library(tidyverse)
# library(naniar)
# library(forcats)
# data_rec <-
# read_csv("/Users/gabrielburcea/Rprojects/data/csvdata.csv")
# nrow(distinct(data_rec))
# data_rename <- data_rec %>%
# dplyr::rename(
# id = ID,
# age = Age,
# gender = Gender,
# location = Location,
# country = Country,
# chills = Chills,
# cough = Cough,
# diarrhoea = Diarrhoea,
# fatigue = Fatigue,
# headache = Headcahe,
# pregnant = Pregnant,
# sputum = Sputum,
# temperature = Temperature,
# sneezing = Sneezing,
# loss_of_smell_and_taste = "Loss of smell and taste",
# muscle_ache = 'Muscle Ache',
# nasal_congestion = "Nasal Congestion",
# nausea_vomiting = "Nausea and Vomiting",
# self_diagnosis = "Self Diagnosis",
# shortness_breath = "Shortness of Breath",
# sore_throat = "Sore Throat",
# loss_appetite = "Loss of Appetite",
# chest_pain = "Chest Pain",
# itchy_eyes = "Itchy Eyes",
# joint_pain = "Joint Pain",
# care_home_worker = 'Care Home Worker',
# health_care_worker = "Healthcare Worker",
# date_completed = 'Date Completed',
# how_unwell = "How Unwell",
# number_days_symptom_showing = "Number Of Days Symptoms Showing",
# reason_for_help = "Reason For Helping",
# language = Language,
# health_condition = "Long Standing Health Issues"
# ) %>%
# dplyr::mutate(id = str_sub(id, -10))
# data_com <- data_rename %>%
# rowwise() %>%
# mutate(health_condition =
# str_extract_all(health_condition,
# pattern = "None|Diabetes Type 2|Asthma \\(managed with an inhaler\\)|Obesity|High Blood Pressure \\(hypertension\\)|Long-Standing Lung Condition|Long-Standing Liver Disease|Long-Standing Heart Disease|Long-Standing Kidney Disease|Diabetes Type 1 \\(controlled by insulin\\)"),
# health_condition = paste(health_condition, collapse = ","))
# data_com$health_condition <- sub("^$", "None", data_com$health_condition)
# reason_for_help_levels <-
# c(
# "negative" = "Curious",
# "negative" = "Curious,Self-Isolating With No Symptoms" ,
# "negative" = "Live With Someone With Coronavirus",
# "negative" = "Live With Someone With Coronavirus,Curious" ,
# "negative" = "Live With Someone With Coronavirus,Curious,Self-Isolating With No Symptoms",
# "negative" = "Live With Someone With Coronavirus,Self-Isolating With No Symptoms",
# "negative" = "Muscle Ache",
# "negative" = "No",
# "negative" = "None",
# "negative" = "Reason For Helping",
# "showing symptoms" = "Recovered But Have New Symptoms",
# "showing symptoms" = "Recovered But Have New Symptoms,Curious",
# "showing symptoms" = "Recovered But Have New Symptoms,Curious,Self-Isolating With No Symptoms",
# "showing symptoms" = "Recovered But Have New Symptoms,Self-Isolating With No Symptoms",
# "negative" = "Self-Isolating With No Symptoms",
# "showing symptoms" = "Showing Symptoms But Not Tested",
# "showing symptoms" = "Showing Symptoms But Not Tested,Curious",
# "showing symptoms" = "Showing Symptoms But Not Tested,Curious,Self-Isolating With No Symptoms",
# "showing symptoms" = "Showing Symptoms But Not Tested,Live With Someone With Coronavirus",
# "showing symptoms" = "Showing Symptoms But Not Tested,Live With Someone With Coronavirus,Curious",
# "showing symptoms" = "Showing Symptoms But Not Tested,Live With Someone With Coronavirus,Recovered But Have New Symptoms",
# "showing symptoms" = "Showing Symptoms But Not Tested,Recovered But Have New Symptoms",
# "showing symptoms" = "Showing Symptoms But Not Tested,Recovered But Have New Symptoms,Curious",
# "showing symptoms" = "Showing Symptoms But Not Tested,Self-Isolating With No Symptoms",
# "showing symptoms" = "Tested Negative But Have Symptoms",
# "showing symptoms" = "Tested Negative But Have Symptoms,Curious",
# "showing symptoms" = "Tested Negative But Have Symptoms,Curious,Self-Isolating With No Symptoms",
# "showing symptoms" = "Tested Negative But Have Symptoms,Live With Someone With Coronavirus",
# "showing symptoms" = "Tested Negative But Have Symptoms,Live With Someone With Coronavirus,Recovered But Have New Symptoms",
# "showing symptoms" = "Tested Negative But Have Symptoms,Self-Isolating With No Symptoms",
# "showing symptoms" = "Tested Negative But Have Symptoms,Showing Symptoms But Not Tested",
# "showing symptoms" = "Tested Negative But Have Symptoms,Showing Symptoms But Not Tested,Curious",
# "showing symptoms" = "Tested Negative But Have Symptoms,Showing Symptoms But Not Tested,Recovered But Have New Symptoms,Curious,Self-Isolating With No Symptoms",
# "positive" = "Tested Positive",
# "positive" = "Tested Positive,Curious",
# "positive" = "Tested Positive,Live With Someone With Coronavirus",
# "positive" = "Tested Positive,Recovered But Have New Symptoms",
# "positive" = "Tested Positive,Recovered But Have New Symptoms,Curious",
# "positive" = "Tested Positive,Self-Isolating With No Symptom",
# "positive" = "Tested Positive,Showing Symptoms But Not Tested",
# "positive" = "Tested Positive,Tested Negative But Have Symptoms",
# "positive" = "Tested Positive,Tested Negative But Have Symptoms,Recovered But Have New Symptoms",
# "positive" = "Tested Positive,Tested Negative But Have Symptoms,Showing Symptoms But Not Tested",
# "positive" = "Tested Positive,Tested Negative But Have Symptoms,Showing Symptoms But Not Tested,Curious",
# "positive" = "Tested Positive,Tested Negative But Have Symptoms,Showing Symptoms But Not Tested,Live With Someone With Coronavirus,Recovered But Have New Symptoms,Curious,Self-Isolating With No Symptoms",
# "positive" = "Tested Positive,Tested Negative But Have Symptoms,Showing Symptoms But Not Tested,Recovered But Have New Symptoms,Curious,Self-Isolating With No Symptom)",
# "positive" = "Tested Positive,Tested Negative But Have Symptoms,Showing Symptoms But Not Tested,Recovered But Have New Symptoms,Curious,Self-Isolating With No Symptoms",
# "positive" = "Tested Positive,Self-Isolating With No Symptoms"
# )
# data_comorb <- data_com %>%
# tidyr::separate(
# health_condition,
# c(
# 'Comorbidity_one',
# 'Comorbidity_two',
# 'Comorbidity_three',
# 'Comorbidity_four',
# 'Comorbidity_five',
# 'Comorbidity_six',
# 'Comorbidity_seven',
# 'Comorbidity_eight',
# 'Comorbidity_nine'
# ),
# sep = ","
# )
# data_comorb %>% distinct(Comorbidity_one)
# data_comorb %>% distinct(Comorbidity_two)
# data_comorb %>% distinct(Comorbidity_three)
# data_comorb %>% distinct(Comorbidity_four)
# data_comorb %>% distinct(Comorbidity_five)
# data_comorb %>% distinct(Comorbidity_six)
# data_comorb %>% distinct(Comorbidity_seven)
# data_comorb %>% distinct(Comorbidity_eight)
# data_comorb %>% distinct(Comorbidity_nine)
# data_long_wid <- data_comorb %>%
# tidyr::pivot_longer(cols = starts_with('Comorbidity'),
# names_to = 'Comorbidity_count',
# values_to = 'Comorbidity') %>%
# naniar::replace_with_na(replace = list(Comorbidity = "None")) %>%
# distinct() %>%
# dplyr::group_by(id) %>%
# dplyr::mutate(number_morbidities = sum(!is.na(Comorbidity))) %>%
# tidyr::drop_na('Comorbidity') %>%
# dplyr::select(-Comorbidity_count) %>%
# dplyr::distinct() %>%
# dplyr::mutate(Condition = 'Yes') %>%
# tidyr::pivot_wider(names_from = Comorbidity, values_from = Condition, values_fill = list(Condition = 'No'))
#
# df_comorbidity_unique <- distinct(data_comorb, id, .keep_all = TRUE)
# ###########################################################
# ### Get patients without multiple comorbidities but also count the number of patients
# make sure count on unique number of patients #########
# ##########################################################
# data_c <- df_comorbidity_unique %>%
# tidyr::pivot_longer(cols = starts_with('Comorbidity'),
# names_to = 'Comorbidity_count',
# values_to = 'Comorbidity') %>%
# dplyr::mutate(Comorbidity = if_else(Comorbidity == "None", NA_character_, Comorbidity)) %>%
# distinct() %>%
# dplyr::group_by(id) %>%
# mutate(number_morbidities = sum(!is.na(Comorbidity)))
#
# data_unique_comorb <- data_c %>%
# tidyr::pivot_longer(cols = starts_with('Comorbidity'),
# names_to = 'Comorbidity_count',
# values_to = 'Comorbidity') %>%
# tidyr::drop_na('Comorbidity') %>%
# dplyr::select(-Comorbidity_count) %>%
# dplyr::distinct() %>%
# dplyr::mutate(Condition = 'Yes') %>%
# tidyr::pivot_wider(id_cols = -c(Comorbidity, Condition), names_from = Comorbidity, values_from = Condition, values_fill = list(Condition = 'No')) %>%
# dplyr::select(-Comorbidity_one)
# # # # #################################################
# # # # ######### Get a numeric dataset #################
# # # # #################################################
# data_model <- data_unique_comorb %>% # here make sure the dataset is ritght - either patients with multiple comorbidities or patients without multitple comorbidties
# dplyr::mutate(covid_tested = forcats::fct_recode(reason_for_help, !!!reason_for_help_levels)) %>%
# dplyr::select(-reason_for_help)
# data_model$gender <- as.factor(data_model$gender)
# data_model$country <- as.factor(data_model$country)
# data_model$chills <- as.factor(data_model$chills)
# data_model$cough <- as.factor(data_model$cough)
# data_model$diarrhoea <- as.factor(data_model$diarrhoea)
# data_model$fatigue <- as.factor(data_model$fatigue)
# data_model$headache <- as.factor(data_model$headache)
# data_model$loss_of_smell_and_taste <- as.factor(data_model$loss_of_smell_and_taste)
# data_model$muscle_ache <- as.factor(data_model$muscle_ache)
# data_model$nasal_congestion <- as.factor(data_model$nasal_congestion)
# data_model$nausea_vomiting <- as.factor(data_model$nausea_vomiting)
# data_model$self_diagnosis <- as.factor(data_model$self_diagnosis)
# data_model$shortness_breath <- as.factor(data_model$shortness_breath)
# data_model$sore_throat <- as.factor(data_model$sore_throat)
# data_model$sputum <- as.factor(data_model$sputum)
# data_model$temperature <- as.factor(data_model$temperature)
# data_model$health_care_worker <- as.factor(data_model$health_care_worker)
# data_model$care_home_worker <- as.factor(data_model$care_home_worker)
# data_model$asthma <- as.factor(data_model$`Asthma (managed with an inhaler)`)
# data_model$diabetes_type_two <- as.factor(data_model$`Diabetes Type 2`)
# data_model$obesity <- as.factor(data_model$Obesity)
# data_model$hypertension <- as.factor(data_model$`High Blood Pressure (hypertension)`)
# data_model$heart_disease <- as.factor(data_model$`Long-Standing Heart Disease`)
# data_model$kidney_disease <- as.factor(data_model$`Long-Standing Kidney Disease`)
# data_model$lung_condition <- as.factor(data_model$`Long-Standing Lung Condition`)
# data_model$liver_disease <- as.factor(data_model$`Long-Standing Liver Disease`)
# data_model$diabetes_type_one <- as.factor(data_model$`Diabetes Type 1 (controlled by insulin)`)
# data_model$how_unwell <- as.factor(data_model$how_unwell)
# data_model$covid_tested <- as.factor(data_model$covid_tested)
# data_model$id <- as.character(data_model$id)
# data_model$age <- as.numeric(data_model$age)
# data_model$gender <- as.factor(data_model$gender)
# data_model$pregnant <- as.factor(data_model$pregnant)
# data_model$date_completed <- as.Date(data_model$date_completed)
# data_model$location <- as.factor(data_model$location)
# data_model$loss_appetite <- as.factor(data_model$loss_appetite)
# data_model$sneezing <- as.factor(data_model$sneezing)
# data_model$chest_pain <- as.factor(data_model$chest_pain)
# data_model$itchy_eyes <- as.factor(data_model$itchy_eyes)
# data_model$joint_pain <- as.factor(data_model$joint_pain)
# # # #### Refactor the levels ##################################################
# data_sel <- data_model %>% # here make sure the dataset is ritght - either patients with multiple comorbidities or patients without multitple comorbidties
# dplyr::select(
# id,
# covid_tested,
# age,
# gender,
# country,
# location,
# date_completed,
# care_home_worker,
# chills,
# cough,
# diarrhoea,
# fatigue,
# headache,
# health_care_worker,
# how_unwell,
# loss_of_smell_and_taste,
# muscle_ache,
# nasal_congestion,
# nausea_vomiting,
# number_days_symptom_showing,
# pregnant,
# self_diagnosis,
# shortness_breath,
# sore_throat,
# sputum,
# temperature,
# language,
# loss_appetite,
# sneezing,
# chest_pain,
# itchy_eyes,
# joint_pain,
# covid_tested,
# asthma,
# diabetes_type_one,
# diabetes_type_two,
# obesity,
# hypertension,
# heart_disease,
# lung_condition,
# liver_disease,
# kidney_disease,
# number_morbidities
# )
# data_sel %>% distinct(cough)
#
# data_model %>% distinct(chills)
#
# level_key_chills <-
# c( 'Yes' = "Chills",
# 'Yes' = "Mild",
# 'Yes' = "Moderate",
# 'Yes' = "Severe",
# 'No' = "Location",
# 'No' = "Gender")
# level_key_cough <-
# c( 'Yes' = "Cough",
# 'Yes' = "Mild",
# 'Yes' = "Moderate",
# 'Yes' = "Severe",
# 'Yes' = 'Cough')
# data_sel %>% distinct(diarrhoea)
# level_key_diarrhoea <-
# c(
# 'Yes' = "Mild",
# 'Yes' = "Moderate",
# 'Yes' = "Severe",
# 'No' = "Diarrhoea",
# 'No' ='Country')
# data_sel %>% distinct(fatigue)
# level_key_fatigue <-
# c( 'No' = 'Date Completed',
# 'No' = "Fatigue",
# 'Yes' = "Mild",
# 'Yes' = "Moderate",
# 'Yes' = "Severe"
# )
# data_sel %>% distinct(headache)
# level_key_headache <-
# c('No' = 'Headache',
# 'No' = 'Care Home Worker',
# 'Yes' = "Mild",
# 'Yes' = "Moderate",
# 'Yes' = "Severe",
# 'Yes' = "Headcahe")
# data_sel %>% distinct(loss_of_smell_and_taste)
# level_key_loss_smell_taste <-
# c( 'No' = "Loss of smell and taste",
# 'No' = 'Brazil',
# 'No' = 'Peru',
# 'No' = 'Fatigue',
# 'Yes' = "Mild",
# 'Yes' = "Moderate",
# 'Yes' = "Severe")
# data_sel %>% distinct(muscle_ache)
# level_key_muschle_ache <-
# c( 'No' = "Muscle Ache",
# 'No' = "2020-08-04 17:11:00",
# 'No' = "2020-08-02 01:55:00",
# 'No' = "2020-08-01 15:11:00",
# 'No' = "Headcahe",
# 'Yes' = "Mild",
# 'Yes' = "Moderate",
# 'Yes' = "Severe")
# data_sel %>% distinct(nasal_congestion)
# level_key_nasal_congestion <-
# c( 'No' = "Healthcare Worker",
# 'Yes' = "Nasal Congestion",
# 'Yes' = "Mild",
# 'Yes' = "Moderate",
# 'Yes' = "Severe")
# data_sel %>% distinct(nausea_vomiting)
# level_key_nausea_vomiting <-
# c( 'No' = "How Unwell",
# 'Yes' = "Nausea and Vomiting",
# 'Yes' = "Mild",
# 'Yes' = "Moderate",
# 'Yes' = "Severe")
# data_sel %>% distinct(self_diagnosis)
# level_key_self_diagnosis <-
# c( 'No' = "None",
# 'Yes' = "Mild",
# 'Yes' = "Moderate",
# 'Yes' = "Severe",
# 'No' = "Self Diagnosis",
# 'No' = "Nasal Congestion")
# data_sel %>% distinct(shortness_breath)
# level_key_short_breath <-
# c( 'No' = "Nausea and Vomiting",
# 'Yes' = "Shortness of Breath",
# 'Yes' = "Mild",
# 'Yes' = "Moderate",
# 'Yes' = "Severe")
# data_sel %>% distinct(sore_throat)
# level_key_sore_throat <-
# c( 'No' = "Number Of Days Symptoms Showing",
# 'No' = '1',
# 'No' = "Sore Throat",
# 'Yes' = "Mild",
# 'Yes' = "Moderate",
# 'Yes' = "Severe")
# data_sel %>% distinct(sputum)
# level_key_sputum <-
# c( 'No' = "None",
# 'No' = "Long-Standing Lung Condition",
# 'No' = "Pregnant",
# "No" = 'High Blood Pressure (hypertension),No,No,Yes,No,2,No,Showing Symptoms But Not Tested,Mild,No,No,No,No,Portuguese,No, No,No,No,No\n380a7278-700f-441f-9c7c-6013e80f2f78,62,Male,"Cd. Madero Tamaulipas',
# 'Yes' = "Sputum",
# 'Yes' = "Mild",
# 'Yes' = "Moderate",
# 'Yes' = "Severe")
# level_key_care_home_worker <-
# c(
# 'No' = 'Care Home Worker',
# 'No' = 'Age')
# data_sel %>% distinct(temperature)
# level_key_temperature <-
# c('No' = 'Temperature',
# 'No' = "Mexico",
# 'No' = "Reason For Helping",
# 'Yes' = "37.5-38",
# 'Yes' = "38.1-39",
# 'Yes' = "39.1-41",
# 'Yes' = "38.2-39")
# data_sel %>% distinct(loss_appetite)
# level_key_loss_appetite <-
# c('No' = "Loss of Appetite",
# 'No' = "Shortness of Breath")
# data_sel %>% distinct(sneezing)
# level_key_sneezing <-
# c('No' = "Sneezing",
# 'No' = "Sore Throat")
# data_sel %>% distinct(chest_pain)
# level_key_chest_pain <-
# c('No' = 'Chest Pain',
# 'No' = '0',
# 'No' = 'Sputum')
# data_sel %>% distinct(itchy_eyes)
# level_key_itchy_eyes <-
# c('No' = "Itchy Eyes",
# 'No' = "Temperature")
# data_sel %>% distinct(joint_pain)
# level_key_joint_pain <-
# c('No' = 'Joint Pain',
# 'No' = "Showing Symptoms But Not Tested",
# 'No' = "Language")
# itchy_eyes_t <- table(data_sel$itchy_eyes)
# # # #### Refactor the levels ##################################################
# data_categ_nosev <- data_sel %>%
# dplyr::mutate(chills = forcats::fct_recode(chills, !!!level_key_chills),
# cough = forcats::fct_recode(cough, !!!level_key_cough),
# diarrhoea = forcats::fct_recode(diarrhoea, !!!level_key_diarrhoea),
# fatigue = forcats::fct_recode(fatigue, !!!level_key_fatigue),
# headache = forcats::fct_recode(headache, !!!level_key_headache),
# loss_smell_taste = forcats::fct_recode(loss_of_smell_and_taste, !!!level_key_loss_smell_taste),
# muscle_ache = forcats::fct_recode(muscle_ache, !!!level_key_muschle_ache),
# nasal_congestion = forcats::fct_recode(nasal_congestion, !!!level_key_nasal_congestion),
# nausea_vomiting = forcats::fct_recode(nausea_vomiting, !!!level_key_nausea_vomiting),
# self_diagnosis = forcats::fct_recode(self_diagnosis, !!!level_key_self_diagnosis),
# shortness_breath = forcats::fct_recode(shortness_breath, !!!level_key_short_breath),
# sore_throat = forcats::fct_recode(sore_throat, !!!level_key_sore_throat),
# sputum = forcats::fct_recode(sputum, !!!level_key_sputum),
# temperature = forcats::fct_recode(temperature, !!!level_key_temperature),
# loss_appetite = forcats::fct_recode(loss_appetite, !!!level_key_loss_appetite),
# sneezing = forcats::fct_recode(sneezing, !!!level_key_sneezing),
# chest_pain = forcats::fct_recode(chest_pain, !!!level_key_chest_pain),
# itchy_eyes = forcats::fct_recode(itchy_eyes, !!!level_key_itchy_eyes),
# joint_pain = forcats::fct_recode(joint_pain, !!!level_key_joint_pain))
# sputum_lev <-table(data_categ_nosev$sputum)
# data_categ_nosev_comorbidity_one <- data_categ_nosev
# write.csv(data_categ_nosev_comorbidity_one, file = "/Users/gabrielburcea/Rprojects/stats_data_whole/cleaned_data_18_08_2020.csv", row.names = FALSE)
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