326 lines
5.2 KiB
Plaintext
326 lines
5.2 KiB
Plaintext
---
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title: "Data import"
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subtitle: 《区域水环境污染数据分析实践》<br>Data analysis practice of regional water environment pollution
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author: 苏命、王为东<br>中国科学院大学资源与环境学院<br>中国科学院生态环境研究中心
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date: today
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lang: zh
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format:
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revealjs:
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theme: dark
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slide-number: true
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chalkboard:
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buttons: true
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preview-links: auto
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lang: zh
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toc: true
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toc-depth: 1
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toc-title: 大纲
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logo: ./_extensions/inst/img/ucaslogo.png
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css: ./_extensions/inst/css/revealjs.css
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pointer:
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key: "p"
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color: "#32cd32"
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pointerSize: 18
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revealjs-plugins:
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- pointer
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filters:
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- d2
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---
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```{r}
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#| echo: false
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knitr::opts_chunk$set(echo = TRUE)
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source("../../coding/_common.R")
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library(tidyverse)
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```
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## tidyverse风格数据分析总体流程
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## 导入csv数据
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```{r}
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read_lines("../../data/students.csv") |> cat(sep = "\n")
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```
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## 导入csv数据
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```{r}
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read_csv("../../data/students.csv") |>
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knitr::kable()
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```
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## 读取数据
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```{r}
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(students <- read_csv("../../data/students.csv"))
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```
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## 读取数据
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```{r}
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#| message: false
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(students <- read_csv("../../data/students.csv", na = c("N/A", "")))
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```
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## 列名不要有空格
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```{r}
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students |>
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rename(
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student_id = `Student ID`,
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full_name = `Full Name`
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)
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```
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## `janitor`处理空格
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```{r}
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#| message: false
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students |> janitor::clean_names()
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```
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## `janitor`处理空格
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```{r}
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students |>
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janitor::clean_names() |>
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mutate(meal_plan = factor(meal_plan))
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```
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## `janitor`处理空格
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```{r}
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students <- students |>
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janitor::clean_names() |>
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mutate(
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meal_plan = factor(meal_plan),
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age = parse_number(if_else(age == "five", "5", age))
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)
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students
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```
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## 直接录入
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```{r}
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#| message: false
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read_csv(
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"The first line of metadata
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The second line of metadata
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x,y,z
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1,2,3",
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skip = 2
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)
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```
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## 直接录入
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```{r}
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#| message: false
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read_csv(
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"# A comment I want to skip
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x,y,z
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1,2,3",
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comment = "#"
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)
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```
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## 指定列名
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```{r}
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#| message: false
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read_csv(
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"1,2,3
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4,5,6",
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col_names = c("x", "y", "z")
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)
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```
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## 指定列的类型
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```{r}
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another_csv <- "
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x,y,z
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1,2,3"
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read_csv(
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another_csv,
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col_types = cols(.default = col_character())
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)
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read_csv(
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another_csv,
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col_types = cols_only(x = col_character())
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)
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```
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## 练习
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```{r}
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#| eval: false
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read_csv("a,b\n1,2,3\n4,5,6")
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read_csv("a,b,c\n1,2\n1,2,3,4")
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read_csv("a,b\n\"1")
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read_csv("a,b\n1,2\na,b")
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read_csv("a;b\n1;3")
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```
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## 练习
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```{r}
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#| eval: false
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annoying <- tibble(
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`1` = 1:10,
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`2` = `1` * 2 + rnorm(length(`1`))
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)
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```
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## 批量读取
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```{r}
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#| message: false
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sales_files <- c("../../data/01-sales.csv",
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"../../data/02-sales.csv",
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"../../data/03-sales.csv")
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read_csv(sales_files, id = "file")
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```
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## 读取Excel，建议用`readxl`包
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```{r}
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(surveydf <- readxl::read_xlsx("../../data/survey.xlsx"))
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```
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## 读取Excel
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```{r}
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(airqualitydf <- readxl::read_xlsx("../../data/airquality.xlsx", sheet = 2))
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```
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## 批量读取
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```{r}
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sales_files <- list.files("../../data",
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pattern = "sales\\.csv$", full.names = TRUE)
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sales_files
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```
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## 写入csv
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```{r}
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#| warning: false
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#| message: false
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students
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write_csv(students, "students-2.csv")
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read_csv("students-2.csv")
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```
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## 写入Excel
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```{r}
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writexl::write_xlsx(students, "../../data/writexldemo.xlsx")
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```
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## 读取数据库，以MySQL为例
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```{r}
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if (FALSE) {
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conn <- cctdb::get_dbconn("nationalairquality")
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DBI::dbListTables(conn)
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}
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```
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## 读取数据库，以MySQL为例
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```{r}
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if (FALSE) {
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conn <- cctdb::get_dbconn("nationalairquality")
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metadf <- tbl(conn, "metadf") |>
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head(100) |>
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collect()
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DBI::dbDisconnect(conn)
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saveRDS(metadf, file = "../../data/metadfdemo.RDS")
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}
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metadf <- readRDS(file = "../../data/metadfdemo.RDS")
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lang <- "cn"
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metadf |>
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ggplot(aes(lon, lat)) +
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geom_point(aes(fill = Area)) +
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dwfun::theme_sci()
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```
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## 练习
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```{r}
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#| eval: false
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metadf <- readxl::read_xlsx("../../data/airquality.xlsx")
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dir.create("../../data/metacity2/")
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metadf |>
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nest(sitedf = -site) |>
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mutate(flag = purrr::map2(site, sitedf,
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~ writexl::write_xlsx(.y, paste0("../../data/metacity2/", .x, ".xlsx"))))
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```
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## 练习
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```{r}
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#| include: false
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#| eval: false
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if (FALSE) {
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require(tidyverse)
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conn <- cctdb::get_dbconn("nationalairquality")
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metadf <- tbl(conn, "metadf") |>
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collect()
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DBI::dbDisconnect(conn)
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metanestdf <- metadf |>
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nest(citydf = -Area)
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names(metanestdf$citydf) <- metanestdf$Area
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writexl::write_xlsx(metanestdf$citydf, path = "../../data/meta_city.xlsx")
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dir.create("../../data/metacity/")
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metanestdf |>
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mutate(flag = purrr::map2(Area, citydf,
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~ writexl::write_xlsx(.y,
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path = paste0("../../data/metacity/", .x, ".xlsx")
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)))
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}
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```
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1. 从“../../data/sales.xlsx”读取第9到13行的数据
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2. 从“../../data/meta_city.xlsx”读取所有的数据，并保存至“../../data/meta_city_onetable1.xlsx”
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3. 从“../../data/metacity/”读取所有的数据，并保存至“../../data/meta_city_onetable2.xlsx”
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## 欢迎讨论！{.center}
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`r rmdify::slideend(wechat = FALSE, type = "public", tel = FALSE, thislink = "../")`
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