率及其95%置信区间
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
博文
R json解析
- 获取链接
- X
- 电子邮件
- 其他应用
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...
按疫苗类别接种剂次排序后重新赋值
- 获取链接
- X
- 电子邮件
- 其他应用
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
接种月龄计算
- 获取链接
- X
- 电子邮件
- 其他应用
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...