xuefliang

 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

 dbus-launch ibus-daemon -drx spyder

 # 安装和加载stringdist包 install.packages("stringdist") library(stringdist) # 定义字符串 str1 <- "疾控中心" str2 <- "疾病预防控制中心" str1 <- "卫健委" str2 <- "卫生健康委员会" # 计算 Jaro-Winkler 距离 jw_distance <- stringdist(str1, str2, method = "jaccard") # 自定义字符串相似度计算函数 custom_similarity <- function(str1, str2) {   # 将字符串转换为字符向量   chars1 <- strsplit(str1, "")[[1]]   chars2 <- strsplit(str2, "")[[1]]      # 获取字符向量的长度   len1 <- length(chars1)   len2 <- length(chars2)      # 如果 str1 比 str2 长,则交换它们的位置   if (len1 > len2) {     temp <- chars1     chars1 <- chars2     chars2 <- temp     len1 <- length(chars1)     len2 <- length(chars2)   }      # 检查 chars1 中的字符是否按顺序出现在 chars2 中   index <- 1   match_count <- 0   for (i in 1:len1) {     found <- FALSE     for (j in index:len2) {       if ...

  OLLAMA_ORIGINS="*" OLLAMA_HOST=‘0.0.0.0:11434 ’

conda create --name myenv -c conda-forge python=3.10 conda activate myenv conda env list conda install -c rapidsai -c conda-forge -c nvidia  cudf=24.02  python=3.10 cuda-version=12.2 conda install -c rapidsai dask-cudf