輕鬆學習 R 語言：資料輸入與輸出
如何使用 R 語言處理不同資料格式
Working with data provided by R packages is a great way to learn the tools of data science, but at some point you want to stop learning and start working with your own data.
Hadley Wickham
通過輕鬆學習 R 語言：自訂函數與輕鬆學習 R 語言：函數型程式設計的介紹，終於可以鬆一口氣了！基本功部分已經告一段落，接下來我們將會有水到渠成的感覺。先前我們利用手動的方式建立單純的資料結構來學習，然而在現實生活中，R 語言的應用情形多是輸入一組資料再針對它進行清理或者分析，最後再將結果輸出成一個處理後的檔案。
內建資料
R 語言有非常豐富的內建資料，這些資料絕大多數是以資料框（data.frame）這個結構儲存，並且在開啟 R 語言之後就可以直接使用，想要知道有哪些內建資料可以使用，只要使用 data() 函數就可以在來源（Source）區塊瀏覽一份內建資料集清單。
## Data sets in package ‘datasets’:
##
## AirPassengers Monthly Airline Passenger Numbers 1949-1960
## BJsales Sales Data with Leading Indicator
## BJsales.lead (BJsales)
## Sales Data with Leading Indicator
## BOD Biochemical Oxygen Demand
## CO2 Carbon Dioxide Uptake in Grass Plants
## ChickWeight Weight versus age of chicks on different diets
## DNase Elisa assay of DNase
## EuStockMarkets Daily Closing Prices of Major European Stock
## Indices, 1991-1998
## Formaldehyde Determination of Formaldehyde
## HairEyeColor Hair and Eye Color of Statistics Students
## Harman23.cor Harman Example 2.3
## Harman74.cor Harman Example 7.4
## Indometh Pharmacokinetics of Indomethacin
## InsectSprays Effectiveness of Insect Sprays
## JohnsonJohnson Quarterly Earnings per Johnson & Johnson Share
## LakeHuron Level of Lake Huron 1875-1972
## LifeCycleSavings Intercountry Life-Cycle Savings Data
## Loblolly Growth of Loblolly pine trees
## Nile Flow of the River Nile
## Orange Growth of Orange Trees
## OrchardSprays Potency of Orchard Sprays
## PlantGrowth Results from an Experiment on Plant Growth
## Puromycin Reaction Velocity of an Enzymatic Reaction
## Seatbelts Road Casualties in Great Britain 1969-84
## Theoph Pharmacokinetics of Theophylline
## Titanic Survival of passengers on the Titanic
## ToothGrowth The Effect of Vitamin C on Tooth Growth in
## Guinea Pigs
## UCBAdmissions Student Admissions at UC Berkeley
## UKDriverDeaths Road Casualties in Great Britain 1969-84
## UKgas UK Quarterly Gas Consumption
## USAccDeaths Accidental Deaths in the US 1973-1978
## USArrests Violent Crime Rates by US State
## USJudgeRatings Lawyers' Ratings of State Judges in the US
## Superior Court
## USPersonalExpenditure Personal Expenditure Data
## UScitiesD Distances Between European Cities and Between
## US Cities
## VADeaths Death Rates in Virginia (1940)
## WWWusage Internet Usage per Minute
## WorldPhones The World's Telephones
## ability.cov Ability and Intelligence Tests
## airmiles Passenger Miles on Commercial US Airlines,
## 1937-1960
## airquality New York Air Quality Measurements
## anscombe Anscombe's Quartet of 'Identical' Simple Linear
## Regressions
## attenu The Joyner-Boore Attenuation Data
## attitude The Chatterjee-Price Attitude Data
## austres Quarterly Time Series of the Number of
## Australian Residents
## beaver1 (beavers) Body Temperature Series of Two Beavers
## beaver2 (beavers) Body Temperature Series of Two Beavers
## cars Speed and Stopping Distances of Cars
## chickwts Chicken Weights by Feed Type
## co2 Mauna Loa Atmospheric CO2 Concentration
## crimtab Student's 3000 Criminals Data
## discoveries Yearly Numbers of Important Discoveries
## esoph Smoking, Alcohol and (O)esophageal Cancer
## euro Conversion Rates of Euro Currencies
## euro.cross (euro) Conversion Rates of Euro Currencies
## eurodist Distances Between European Cities and Between
## US Cities
## faithful Old Faithful Geyser Data
## fdeaths (UKLungDeaths)
## Monthly Deaths from Lung Diseases in the UK
## freeny Freeny's Revenue Data
## freeny.x (freeny) Freeny's Revenue Data
## freeny.y (freeny) Freeny's Revenue Data
## infert Infertility after Spontaneous and Induced
## Abortion
## iris Edgar Anderson's Iris Data
## iris3 Edgar Anderson's Iris Data
## islands Areas of the World's Major Landmasses
## ldeaths (UKLungDeaths)
## Monthly Deaths from Lung Diseases in the UK
## lh Luteinizing Hormone in Blood Samples
## longley Longley's Economic Regression Data
## lynx Annual Canadian Lynx trappings 1821-1934
## mdeaths (UKLungDeaths)
## Monthly Deaths from Lung Diseases in the UK
## morley Michelson Speed of Light Data
## mtcars Motor Trend Car Road Tests
## nhtemp Average Yearly Temperatures in New Haven
## nottem Average Monthly Temperatures at Nottingham,
## 1920-1939
## npk Classical N, P, K Factorial Experiment
## occupationalStatus Occupational Status of Fathers and their Sons
## precip Annual Precipitation in US Cities
## presidents Quarterly Approval Ratings of US Presidents
## pressure Vapor Pressure of Mercury as a Function of
## Temperature
## quakes Locations of Earthquakes off Fiji
## randu Random Numbers from Congruential Generator
## RANDU
## rivers Lengths of Major North American Rivers
## rock Measurements on Petroleum Rock Samples
## sleep Student's Sleep Data
## stack.loss (stackloss)
## Brownlee's Stack Loss Plant Data
## stack.x (stackloss) Brownlee's Stack Loss Plant Data
## stackloss Brownlee's Stack Loss Plant Data
## state.abb (state) US State Facts and Figures
## state.area (state) US State Facts and Figures
## state.center (state) US State Facts and Figures
## state.division (state)
## US State Facts and Figures
## state.name (state) US State Facts and Figures
## state.region (state) US State Facts and Figures
## state.x77 (state) US State Facts and Figures
## sunspot.month Monthly Sunspot Data, from 1749 to "Present"
## sunspot.year Yearly Sunspot Data, 1700-1988
## sunspots Monthly Sunspot Numbers, 1749-1983
## swiss Swiss Fertility and Socioeconomic Indicators
## (1888) Data
## treering Yearly Treering Data, -6000-1979
## trees Girth, Height and Volume for Black Cherry Trees
## uspop Populations Recorded by the US Census
## volcano Topographic Information on Auckland's Maunga
## Whau Volcano
## warpbreaks The Number of Breaks in Yarn during Weaving
## women Average Heights and Weights for American Women
##
##
## Use ‘data(package = .packages(all.available = TRUE))’
## to list the data sets in all *available* packages.
內建資料集是讓我們可以快速測試函數的好幫手，常常被眾多 R 語言使用者用來測試的內建資料集有 iris 、 cars 、 mtcars 與 airquality 等，如果對內建資料集的內容感到好奇，可以像查詢函數一般使用 ? 或 help() 函數查詢它們，右下角的查詢區塊就會顯示出詳細的文件資料。
輸入表格式資料：read.table() 函數
如果想要輸入一個表格式資料（tabular data），可以使用 R 內建的 read.table() 函數，表格式資料中每一筆代表一個觀測值，變數以符號區隔，常見的有空格（\s）、tab 鍵（\t）或逗號（,）。假如在電腦的桌面上 c:/Users/YOURUSERNAME/Desktop/ 有一個以空格（\s）區隔變數的表格式資料 friends_cast.txt。
"cast" "star"
"Rachel Green" "Jennifer Aniston"
"Monica Geller" "Courteney Cox"
"Phoebe Buffay" "Lisa Kudrow"
"Joey Tribbiani" "Matt LeBlanc"
"Chandler Bing" "Matthew Perry"
"Ross Geller" "David Schwimmer"使用 read.table() 函數讀入 .txt 檔案。
## > file_path <- "c:/Users/YOURUSERNAME/Desktop/friends_cast.txt"
## > friends_cast <- read.table(file_path, header = TRUE, stringsAsFactors = FALSE)
## > View(friends_cast)
值得注意的地方有三個：
file_path參數用於指定資料的路徑，這個範例是假設我將表格式資料儲存在 c:/Users/YOURUSERNAME/Desktop/ 路徑，亦即電腦的桌面。如果是 macOS 的使用者，需要寫成 /Users/YOURUSERNAME/Desktop/favorite_bands.txt`，特別注意斜線的方向，不論 windows 系統或 macOS 都必須使用正向斜線（/）區隔路徑header參數指定資料的第一列觀測值是否為變數名稱stringsAsFactors參數指定資料中的文字向量是否要以因素向量的結構型態儲存，在資料處理的階段我們會更偏愛使用文字向量而非因素向量。
假如在電腦的桌面上 c:/Users/YOURUSERNAME/Desktop/ 有一個以 tab（\t）區隔變數的表格式資料 friends_cast.tsv，副檔名 .tsv 是 tab-separated values 的縮寫。
"cast" "star""Rachel Green" "Jennifer Aniston""Monica Geller" "Courteney Cox""Phoebe Buffay" "Lisa Kudrow""Joey Tribbiani" "Matt LeBlanc""Chandler Bing" "Matthew Perry""Ross Geller" "David Schwimmer"使用 read.table() 函數讀入 .tsv 檔案，讀入這個資料的寫法不需要修改。
## > file_path <- "c:/Users/YOURUSERNAME/Desktop/friends_cast.tsv"
## > friends_cast <- read.table(file_path, header = TRUE, stringsAsFactors = FALSE)
## > View(friends_cast)假如在電腦的桌面上 c:/Users/YOURUSERNAME/Desktop/ 有一個以逗號（,）區隔變數的表格式資料 friends_cast.csv，副檔名 .csv 是 comma-separated values 的縮寫。
"cast","star""Rachel Green","Jennifer Aniston""Monica Geller","Courteney Cox""Phoebe Buffay","Lisa Kudrow""Joey Tribbiani","Matt LeBlanc""Chandler Bing","Matthew Perry""Ross Geller","David Schwimmer"讀入這個資料的寫法需要修改 sep 參數，因為預設 sep 參數只能辨識一個或多個空格，既然現在改以逗號區隔變數，就得指定對應的分隔符號。
## > file_path <- "/Users/YOURUSERNAME/Desktop/friends_cast.csv"
## > friends_cast <- read.table(file_path, header = TRUE, stringsAsFactors = FALSE, sep = ",")
## > View(friends_cast)前面的範例是從本機路徑讀取檔案，其實 read.table() 函數也可以從網路讀取表格式資料，只需要修改資料所在路徑，從一個本機路徑替換為一個網路位址即可。
## > file_url <- "https://s3-ap-northeast-1.amazonaws.com/r-essentials/friends_cast.csv"
## > friends_cast <- read.table(file_url, header = TRUE, stringsAsFactors = FALSE, sep = ",")
## > View(friends_cast)輸入非表格式資料：readLines() 函數
並非所有我們想讀入的檔案都是以分隔符號簡潔分隔的表格式資料，像是劇本形式的文字檔案（friends_script.txt）。
Ross: (mortified) Hi.Joey: This guy says hello, I wanna kill myself.Monica: Are you okay, sweetie?Ross: I just feel like someone reached down my throat, grabbed my small intestine, pulled it out of my mouth and tied it around my neck...Chandler: Cookie?Monica: (explaining to the others) Carol moved her stuff out today.Joey: Ohh.Monica: (to Ross) Let me get you some coffee.Ross: Thanks.Phoebe: Ooh! Oh! (She starts to pluck at the air just in front of Ross.)Ross: No, no don't! Stop cleansing my aura! No, just leave my aura alone, okay?Phoebe: Fine! Be murky!
我們可以利用 readLines() 函數一列一列讀入這些文字，回傳的物件是一個文字向量，並依照順序放置在一個文字向量中，每一列佔據一個索引值的空間。
## > file_path <- "https://s3-ap-northeast-1.amazonaws.com/r-essentials/friends_script.txt"
## > friends_script <- readLines(file_path)
## Warning message:
## In readLines(file_path) :
## incomplete final line found on 'https://s3-ap-northeast-1.amazonaws.com/r-essentials/friends_script.txt'
## > friends_script
## [1] "Ross: (mortified) Hi."
## [2] "Joey: This guy says hello, I wanna kill myself."
## [3] "Monica: Are you okay, sweetie?"
## [4] "Ross: I just feel like someone reached down my throat, grabbed my small intestine, pulled it out of my mouth and tied it around my neck..."
## [5] "Chandler: Cookie?"
## [6] "Monica: (explaining to the others) Carol moved her stuff out today."
## [7] "Joey: Ohh."
## [8] "Monica: (to Ross) Let me get you some coffee."
## [9] "Ross: Thanks."
## [10] "Phoebe: Ooh! Oh! (She starts to pluck at the air just in front of Ross.)"
## [11] "Ross: No, no don't! Stop cleansing my aura! No, just leave my aura alone, okay?"
## [12] "Phoebe: Fine! Be murky!"假使原始文字檔非常龐大，我們可以加入參數 n 限定讀入的筆數。
## > file_path <- "https://s3-ap-northeast-1.amazonaws.com/r-essentials/friends_script.txt"
## > friends_script <- readLines(file_path, n = 2)
## > friends_script
## [1] "Ross: (mortified) Hi."
## [2] "Joey: This guy says hello, I wanna kill myself."輸入常見資料格式
常見用來儲存資料的格式還有 Excel 試算表（spreadsheets）與 JSON（JavaScript Object Notations），我們必須仰賴套件來輔助輸入這些資料格式。
- Excel 試算表：Hadley Wickham 開發的
readxl套件 - JSON：Jeroen Ooms 開發的
jsonlite套件
R 語言使用套件的程序有兩個階段，一個是安裝，另外一個是載入。這兩者的區別就像是買工具書跟查詢工具書，安裝套件就像是將這本工具書買回家裡放置在書櫃；載入套件就像是有需求時將工具書從書櫃取下查詢。我們使用 install.pacakges() 函數來安裝套件，然後再使用 library() 函數載入套件。
- 安裝套件：
install.pacakges()，同樣的 R 版本執行一次 - 載入套件：
library()，每次使用套件都要執行
安裝與載入套件
我們可以利用前述兩個函數進行套件的安裝與載入。
## > # 安裝與載入套件
## > pkgs <- c("readxl", "jsonlite")
## > install.packages(pkgs) # 如果先前已經安裝過就不用執行這行
## trying URL 'https://cran.rstudio.com/bin/macosx/el-capitan/contrib/3.5/readxl_1.1.0.tgz'
## Content type 'application/x-gzip' length 1498484 bytes (1.4 MB)
## ==================================================
## downloaded 1.4 MB
##
## trying URL 'https://cran.rstudio.com/bin/macosx/el-capitan/contrib/3.5/jsonlite_1.6.tgz'
## Content type 'application/x-gzip' length 1114907 bytes (1.1 MB)
## ==================================================
## downloaded 1.1 MB
##
##
## The downloaded binary packages are in
## /var/folders/0b/r__z5mpn6ldgb_w2j7_y_ntr0000gn/T//Rtmp9VNgx9/downloaded_packages
## > library(readxl)
## > library(jsonlite)或者利用 RStudio 右下角的 Packages 區塊提供的使用者介面來安裝與載入套件。
輸入 Excel 試算表：read_excel()
假如在電腦的桌面上 c:/Users/YOURUSERNAME/Desktop/ 有一個 Excel 試算表 friends_cast.xlsx。
不論是使用指令安裝載入套件、或是以使用者介面安裝載入套件，完成以後都是利用 readxl 套件提供的 read_excel() 函數讀入 Excel 試算表。
## > library(readxl)
## >
## > file_path <- "~/Desktop/friends_cast.xlsx"
## > friends_cast <- read_excel(file_path)
## > View(friends_cast)輸入 JSON：fromJSON()
JSON（JavaScript Object Notation）是一種輕量級的文字檔案，常用於做資料交換，這種資料結構在 R 語言中的對應主要為有命名的清單（named list），處理具有鍵（Key）以及值（Value）的資料結構，表格式資料若以 JSON 儲存，則是以 Array of JSON 的形式。
[
{ "cast": "Rachel Green", "star": "Jennifer Aniston"},
{ "cast": "Monica Geller", "star": "Courteney Cox"},
{ "cast": "Phoebe Buffay", "star": "Lisa Kudrow"},
{ "cast": "Joey Tribbiani", "star": "Matt LeBlanc"},
{ "cast": "Chandler Bing", "star": "Matthew Perry"},
{ "cast": "Ross Geller", "star": "David Schwimmer"}
]
我們可以利用 jsonlite 套件提供的 fromJSON() 函數讀入 Array of JSON 成為資料框。
## > library(jsonlite)
## >
## > file_url <- "https://s3-ap-northeast-1.amazonaws.com/r-essentials/friends_cast.json"
## > friends_cast <- fromJSON(file_url)
## > View(friends_cast)輸出表格式資料：write.table()
我們可以將 R 語言的資料框以 write.table() 函數輸出副檔名為 .txt 的純文字檔，預設使用空格（\s）區隔變數。
## > star <- c("Jennifer Aniston", "Courteney Cox", "Lisa Kudrow", "Matt LeBlanc", "Matthew Perry", "David Schwimmer")
## > cast <- c("Rachel Green", "Monica Geller", "Phoebe Buffay", "Joey Tribbiani", "Chandler Bing", "Ross Geller")
## > friends_cast <- data.frame(cast, star, stringsAsFactors = FALSE)
## > write.table(friends_cast, file = "c:/Users/YOURUSERNAME/Desktop/friends_cast.txt",row.names = FALSE)執行完畢後可以在 c:/Users/YOURUSERNAME/Desktop 路徑（桌面）找到 friends_cast.txt 檔案，這裡值得注意的是 file 參數指定的是期望輸出檔案的路徑，row.names 參數指定不要將資料框的列索引值輸出，這樣一來輸出檔案的外觀比較接近平時熟悉的樣子。
write.table() 函數指定參數 sep="," ，可輸出以逗號區隔的純文字檔，副檔名為 .csv。執行完畢後可以在 c:/Users/YOURUSERNAME/Desktop 路徑（桌面）找到 friends_cast.csv 檔案。
## > star <- c("Jennifer Aniston", "Courteney Cox", "Lisa Kudrow", "Matt LeBlanc", "Matthew Perry", "David Schwimmer")
## > cast <- c("Rachel Green", "Monica Geller", "Phoebe Buffay", "Joey Tribbiani", "Chandler Bing", "Ross Geller")
## > friends_cast <- data.frame(cast, star, stringsAsFactors = FALSE)
## > write.table(friends_cast, file = "/Users/kuoyaojen/Desktop/friends_cast.txt",row.names = FALSE)
## > write.table(friends_cast, file = "c:/Users/YOURUSERNAME/Desktop/friends_cast.csv",row.names = FALSE, sep = ",")
輸出非表格式資料：toJSON()
我們可以將 R 語言的資料框以 toJSON() 函數輸出副檔名為 .json 的純文字檔，資料框會對應生成 Array of JSON 的文字向量，接著再以 writeLines() 函數輸出。執行完畢後可以在 c:/Users/YOURUSERNAME/Desktop 路徑（桌面）找到 friends_cast.json 檔案。
## > library(jsonlite)
## >
## > star <- c("Jennifer Aniston", "Courteney Cox", "Lisa Kudrow", "Matt LeBlanc", "Matthew Perry", "David Schwimmer")
## > cast <- c("Rachel Green", "Monica Geller", "Phoebe Buffay", "Joey Tribbiani", "Chandler Bing", "Ross Geller")
## > friends_cast <- data.frame(cast, star, stringsAsFactors = FALSE)
## > array_of_json <- toJSON(friends_cast)
## > writeLines(array_of_json, con = "c:/Users/YOURUSERNAME/Desktop/friends_cast.json")
小結
在這個小節中我們簡介如何以 R 語言處理資料的輸入與輸出，瀏覽內建資料、以 read.table() 函數輸入表格式資料、以 readLines() 函數輸入非表格式資料、以 readxl 套件的 read_exce() 函數輸入 Excel 試算表、以 jsonlite 套件的 fromJSON() 函數輸入 JSON 檔案、以 write.table() 函數輸出表格式資料和以 jsonlite 套件的 toJSON() 函數搭配 writeLines() 函數輸出 JSON 檔案。
