328 lines
4.1 KiB
Plaintext
328 lines
4.1 KiB
Plaintext
---
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title: "Data Transform"
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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(nycflights13)
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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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## [dplyr cheatsheet](../../image/cheatsheet/data-transformation.pdf)
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```{r}
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#| echo: false
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dwfun::ggsavep("../../image/cheatsheet/data-transformation.svg", loadit = TRUE)
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```
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## 查看数据
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```{r}
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flights
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```
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## 选择列
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```{r}
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#| results: false
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flights |>
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select(year, month, day)
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```
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## 选择列
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```{r}
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#| results: false
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flights |>
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select(year:day)
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```
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## 选择列
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```{r}
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flights |>
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select(3:5)
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```
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## 选择列
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```{r}
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flights |>
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select(!year:day)
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```
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## 选择列
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```{r}
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flights |>
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select(-(year:day))
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```
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## 选择列
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```{r}
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flights |>
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select(where(is.character))
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```
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## 选择列
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```{r}
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flights |>
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select(!where(is.character)) |>
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select(contains("_"))
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```
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## 选择列
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```{r}
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flights |>
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select(tail_num = tailnum)
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```
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## 选择列
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```{r}
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flights |>
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select(air_time, everything())
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```
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## 重命名
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```{r}
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flights |>
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rename(tail_num = tailnum)
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```
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## 重命名
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```{r}
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flights |>
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rename(年份 = 1) |>
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rename(月份 = 2)
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```
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## 重命名
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```{r}
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flights |> select(1:4) |> head(n = 3)
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# 重命名
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flights |> select(1:4) |> head(n = 3) |>
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rename_all(~c("c1", "c2", "c3", "c4"))
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```
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## 重命名
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```{r}
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flights |> select(1:4) |> head(n = 3)
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# 重命名
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flights |> select(1:4) |> head(n = 3) |>
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rename_all(toupper)
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```
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## 重命名
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```{r}
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flights |> select(1:4) |> head(n = 3)
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# 重命名
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flights |> select(1:4) |> head(n = 3) |>
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rename_all(~paste0(toupper(.), "_NEW"))
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```
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## 练习
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将含有下划线的列名中的下划线去掉。
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```{r}
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flights |> select(1:4) |> head(n = 3)
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```
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## 练习
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将`airqualitydf`中列名的单位信息去除（前5列）。
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```{r}
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airqualitydf <- readxl::read_xlsx("../../data/airquality.xlsx", sheet = 2)
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airqualitydf |> select(1:5)
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```
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## `filter`
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```{r}
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flights |>
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filter(dep_delay > 120)
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```
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## filter 练习
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Flights that departed on January 1.
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```{r}
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#| echo: false
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flights |>
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filter(month == 1 & day == 1)
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```
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## filter 练习
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Select flights that departed in January or February
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```{r}
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#| echo: false
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flights |>
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filter(month %in% c(1, 2))
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```
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## filter 练习
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```{r}
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jan1 <- flights |>
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filter(month == 1 & day == 1)
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```
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## filter
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```{r}
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#| error: true
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#| eval: false
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flights |>
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filter(month = 1)
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```
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## filter
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```{r}
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flights |>
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filter(month == 1 | 2)
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```
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## 排序
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```{r}
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flights |>
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arrange(year, month, day, dep_time)
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```
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## 排序
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```{r}
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flights |>
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arrange(desc(dep_delay))
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```
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## slice
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```{r}
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flights |> head(n = 5)
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flights |> slice(1:5)
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```
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## slice
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```{r}
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flights |>
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slice_max(dep_delay, n = 5)
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```
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## slice
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```{r}
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flights |>
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slice_min(dep_delay, prop = 0.005)
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```
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## 排序练习
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根据`origin`、`dest`、`air_time`倒序排序。
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```{r}
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#| echo: false
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flights |>
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arrange(origin, dest, desc(air_time)) |>
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select(origin, dest, air_time, everything())
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```
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## 去重
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```{r}
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# Remove duplicate rows, if any
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flights |>
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distinct()
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```
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## 去重
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```{r}
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# Find all unique origin and destination pairs
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flights |>
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distinct(origin, dest)
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```
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## 去重
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```{r}
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flights |>
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distinct(origin, dest, .keep_all = TRUE)
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```
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## 欢迎讨论！{.center}
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`r rmdify::slideend(wechat = FALSE, type = "public", tel = FALSE, thislink = "https://drwater.rcees.ac.cn/course/public/RWEP/@PUB/SD/")`
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