38 lines
1.1 KiB
R
38 lines
1.1 KiB
R
require(tidyverse)
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inspectRead = 10
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dataPath = 'data'
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abNames = read_rds('data/abNames.rds')
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filename = list.files(dataPath, paste0('read_', inspectRead, '_*'))
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d = read_rds(file.path(dataPath, filename)) #%>%
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# left_join(abNames, by = c('ab.amr' = 'nameAMR'))
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# list a sampleid that occurs more often but not too often
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examples = d %>% count(sampleid) %>% arrange(desc(n)) %>% filter(n < 50)
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view_d = d %>%
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select(sampleid, date, IsolNr, MIC, mo, RIS, ab.amr, RAP) %>% #, name4d, nameAMRlong) %>%
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mutate(asmo = suppressWarnings(as.mo(mo))) %>%
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arrange(sampleid, IsolNr) #%>%
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# filter(sampleid == examples$sampleid[i])
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has_ecoli = view_d %>% filter(str_starts(asmo, 'B_ES'))
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examples_having_ecoli = has_ecoli %>%
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filter(sampleid %in% examples$sampleid) %>%
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pull(sampleid) %>%
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unique()
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e = 2
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view(view_d %>%
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filter(sampleid == examples_having_ecoli[e]) %>%
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mutate(IsolNr = as.numeric(IsolNr)) %>%
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arrange(IsolNr),# %>%
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#distinct(sampleid, date, IsolNr, mo, ab.amr, .keep_all = T),
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title = 'example')
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if (F) {
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view(view_d)
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view_d %>% filter(!is.na(mo)) %>% pull(mo) %>% unique()
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}
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