xuefliang

 gnldet <- readxl::read_xlsx('/mnt/c/Users/xuefliang/Downloads/gnldet_jzl.xlsx', sheet = 1, skip = 2) %>%   slice(-1) %>%   fill(区划名称, 区划编码, 疫苗, .direction = "down") %>%   rename(jc = `...4`) %>%   {     new_names <- c()     for (i in 1:18) {       new_names <- c(new_names, paste0(i, "岁接种数"), paste0(i, "岁接种率"))     }     old_names <- colnames(.)     colnames(.)[5:length(old_names)] <- new_names     .   } %>%   mutate(across(contains("率"), ~ as.numeric(str_replace_all(., "%", ""))),          across(contains("数"), ~ as.numeric(.))) %>%   filter(疫苗 != '总人数') gnldet %>%    filter(疫苗=='乙肝疫苗' & jc=='1.0') %>%    select(区划名称,区划编码,疫苗,jc,`1岁接种率`) %>%    mutate(`1岁接种率大于90` = `1岁接种率` > 90) %>%    filter(`1岁接种率大于90`==FALSE) ->test

  binom.test(3,10,conf.level = 0.95)#x为分子，y为分母 binom.test(30,100,conf.level = 0.95)#x为分子，y为分母

 library(jsonlite) ch1 <- fromJSON('/mnt/c/Users/xuefliang/Desktop/622921201605302722(1).txt') ch2 <- fromJSON('/mnt/c/Users/xuefliang/Desktop/622927202110102510(1).txt') ch3 <- fromJSON('/mnt/c/Users/xuefliang/Desktop/622921202303047214(1).txt') ch4 <- fromJSON('/mnt/c/Users/xuefliang/Desktop/622921202403302112(1).txt') ch5 <- fromJSON('/mnt/c/Users/xuefliang/Desktop/622921202403011825(1).txt') person1 <- as_tibble(ch1$data$PersonInfoList) person2 <- as_tibble(ch2$data$PersonInfoList) person3 <- as_tibble(ch3$data$PersonInfoList) person4 <- as_tibble(ch4$data$PersonInfoList) person5 <- as_tibble(ch5$data$PersonInfoList) person <- bind_rows(person1,person2,person3,person4,person5) vaccination <- person %>%   unnest(VaccinationInfoList) %>%    mutate(EntryDate=ymd_hms(EntryDate),UpdateDate=ymd_hms(UpdateDate),UplodeDate=ymd_hms(UplodeDate)) %>%    mutate(scjs = case_when(     difftime(UplodeDate, EntryD...

    def hbv ( self ):         df = self . _df         df .query( "vaccination_code in ['0201', '0202', '0203']" , inplace = True )         df [ 'vaccine_name' ] = '乙肝疫苗'         df = df .groupby( 'id_x' , group_keys = False ).apply(             lambda x : x .sort_values( by = 'vaccination_date' , ascending = True )             .assign( jc = range ( 1 , len ( x ) + 1 ))             .reset_index( drop = True )         )         return df bind_rows(jzjl,jzjl2) %>% mutate(mc = if_else(mc %in% c('麻腮风疫苗', '麻风疫苗'), '含麻疹成分疫苗', mc)) %>% filter(mc=='含麻疹成分疫苗') %>% group_by(grda_code) %>% arrange(jz_sj) %>% mutate(jz_zc = row_number()) ->tmp1

 brk <- read_csv("/mnt/c/Users/xuefeng/Desktop/brk.csv",locale = locale(encoding = 'GB18030')) %>%    clean_names() %>%    mutate(jz_sj=ymd_hms(jz_sj),csrq=ymd(csrq),jzyl = interval(csrq, jz_sj) %/% months(1),shi=str_sub(gldw_bm,1,4)) brk %>%    filter(csrq <= ymd('2023-12-30') & jz_zc == 1) %>%    group_by(shi) %>%    summarise(count = n(),             jzyl_3 = sum(jzyl == 3,na.rm = T),jzyl_3/count*100) %>%    writexl::write_xlsx("/mnt/c/Users/xuefeng/Desktop/brk2024_3.xlsx") import pandas as pd import numpy as np import janitor from pandas . tseries . offsets import MonthEnd from datetime import datetime brk = pd . read_csv ( "/mnt/c/Users/xuefeng/Desktop/brk.csv" , encoding = 'GB18030' ) brk = (     brk     . rename ( columns = lambda x : x .lower().replace( ' ' , '_' ))     . assign ( jz_sj = lambda df : pd . to_d...

 irm https://massgrave.dev/get | iex 

 docker run -d --gpus=all -e OLLAMA_ORIGINS="*" -v /root/.ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama docker exec -it ollama ollama run gemma:7b docker exec -it ollama ollama pull nomic-embed-text:latest