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class: center, middle
<span style="font-size: 60px;">第三章</span> <br>
<span style="font-size: 50px;">如何导入数据</span> <br>
<br>
<span style="font-size: 30px;">胡传鹏</span> <br>
<span style="font-size: 20px;"> </span> <br>
<span style="font-size: 30px;">2023-03-07</span> <br>
<span style="font-size: 20px;"> Made with Rmarkdown</span> <br>
---
# 补充
## 使r语言的报错变为英文
- <font size = 5.5>在自己代码的开头输入如下命令，可以让当前的session报错为英文
```r
# set local encoding to English
if (.Platform$OS.type == 'windows') {
Sys.setlocale(category = 'LC_ALL','English_United States.1250')
} else {
Sys.setlocale(category = 'LC_ALL','en_US.UTF-8')
}
```
```
## [1] "LC_COLLATE=English_United States.1250;LC_CTYPE=English_United States.1250;LC_MONETARY=English_United States.1250;LC_NUMERIC=C;LC_TIME=English_United States.1250"
```
```r
# set the feedback language to English
Sys.setenv(LANG = "en")
```
---
# 回顾与问题
## 回顾
- # <font size = 5.5> 问卷数据：Human Penguin Project </font>
- # <font size = 5.5> 实验数据：Perceptual matching </font>
---
# 回顾与问题
## 回顾
- # <font size = 5.5> 问卷数据：Human Penguin Project </font>
- # <font size = 5.5> 实验数据：Perceptual matching </font>
<br><br>
## 问题
- # <font size = 5.5> 如何将这些数据“输入”到R里进行分析？ </font>
# <font size = 4.5> 如何让R“识别”这些数据文件并读取它们？ </font>
---
# 3.1 路径与工作目录
## 什么是工作目录？<br><br>
- # <font size = 5.5> 工作目录（working directory）是指用户当前的工作台(console)所进行交互的目录/文件夹。在此目录/文件夹中，你可在此通过相对路径访问文件或者文件夹。</font>
- # <font size = 5.5> 当你打开R时，R会自动设置一个默认的工作目录，通常为你的用户文件夹。</font>
- # <font size = 5.5> 当你打开R project时，R会自动将这个R Project所在的目录作为工作目录，通常为你的用户文件夹。</font>
---
# 3.1 路径与工作目录
## 什么是路径？<br><br>
- <font size=5.5> 路径是指文件（或文件夹）所在位置，包含绝对路径和相对路劲。</font>
- <font size=5.5> 绝对路径：文件在硬盘上的真实路径，如</font> <br><br>
<font size=5.5> `D:/Documents/r_course/chapter_3/data` </font>
<br><br>
- <font size=5.5>相对路径：相对于当前文件（或当前工作目录）的路径,如</font> <br><br>
<font size=5.5> "data" 或者 "./data" <br><br></font>
---
# 3.1 路径与工作目录
## 什么是路径？<br><br>
- <font size=5.5> 注意：Windows与MacOS/Linux的目录结构上有差异</font> <br><br>
<font size=5.5>**此时我们的工作路径为chapter_3文件夹，也被称之为母文件夹(patent directory)，在工作路径之下的文件夹也被成为子文件夹（child directory）**
<br><br>
- 在数据分析时使用哪一种路径更好？</font>
---
# 3.1 路径与工作目录
## 获取及修改工作目录的基本操作
```r
# 查看当前工作目录
getwd()
```
```
## [1] "C:/Users/Pac.B/Desktop/test"
```
```r
# 修改当前工作路径
setwd("./picture/chapter3")
getwd()
```
```
## [1] "C:/Users/Pac.B/Desktop/test/picture/chapter3"
```
---
# 3.1 路径与工作目录
## Here包的使用
- <font size=5.5> Here是R的一个package，它可以帮助使用者方便快捷的获取路径</font><br>
<br>
- <font size=5.5> 请注意，here()获取的路径取决于你打开项目的位置</font><br>
<br>
- <font size=5.5> here()只能返回路径，并不能更改路径</font>
```r
# 将获取的路径储存到变量my.path中，方便调用
# 可以使用::来调用未加载包中的函数，推荐在少量调用时使用这种方式
here::here()
```
```
## [1] "D:/R assistant/PPT/chapter456/R_psy_class/chapter4"
```
---
# 3.1 路径与工作目录
## Here包的使用
```r
# 当我更改目录之后会出现什么情况？
setwd("./picture/chapter3")
getwd()
```
```
## [1] "C:/Users/Pac.B/Desktop/test/picture/chapter3"
```
```r
here::here()
```
```
## [1] "D:/R assistant/PPT/chapter456/R_psy_class/chapter4"
```
<font size=5.5>**不同的场合下选择适合的函数来简化你的代码**
---
# 3.1 路径与工作目录
## 需要注意在R中输入地址与Windows中地址栏的区别
```r
# r语言中的地址
first_path <- getwd()
cat(first_path,"\n")
```
```
## C:/Users/Pac.B/Desktop/test
```
```r
# Windows的地址
normalized_path <- normalizePath(first_path, winslash = "\\")
cat(normalized_path)
```
```
## C:\Users\Pac.B\Desktop\test
```
<font size=5.5>**因此注意不要直接复制Windows地址栏中的地址**
---
<br>
<br>
<br>
<br>
<br>
.center[ <font size=10>现在我们知道了工作目录和路径，看看我们的数据文件的绝对路径和相对路径是什么？</font> ]
---
# 3.2 读取数据
## 使用R语言读取数据<br><br>
- <font size=6>使用R读取数据，是处理数据的预备工作</font><br>
<span style="font-size: 20px;"> </span> <br>
- <font size=6>最好将数据放于工作目录下的子文件夹中</font><br>
<span style="font-size: 20px;"> </span> <br>
- <font size=6>通过相对路径读取数据，便于分享你的工作</font><br>
<span style="font-size: 20px;"> </span> <br>
---
# 3.2 读取数据
## 读取csv文件
```r
# 读取.csv类型文件
penguin.data <- read.csv('./data/penguin/penguin_rawdata.csv',
header = TRUE, sep=",",
stringsAsFactors = FALSE)
```
- <font size=5.5> './data/penguin/penguin_rawdata.csv' :表示csv文件的相对路径
- <font size=5.5> 'header = TRUE':表示文件中包含列名
- <font size=5.5> 'sep = ","':表示文件中数据之间用逗号分隔，这也是.csv文件的默认分隔方式
- <font size=5.5> 'stringsAsFactors = FALSE':表示读入的字符串数据不转化成 factors类，保持字符类
- <font size=5.5> 读取之后数据变量可以从Environment中找到，变量名为penguin.data </font>
---
# 3.2 读取数据
## 读取csv文件
```r
# 读取.csv类型文件
penguin.data <- read.csv('./data/penguin/penguin_rawdata.csv',
header = TRUE, sep=",",
stringsAsFactors = FALSE)
# 使用DT包中的datatable在ppt中展示表格
DT::datatable(head(penguin.data, 10),
fillContainer = TRUE, options = list(pageLength = 3))
```
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class=\"display fill-container\">\n <thead>\n <tr>\n <th> <\/th>\n <th>ď.żage<\/th>\n <th>ALEX1<\/th>\n <th>ALEX2<\/th>\n <th>ALEX3<\/th>\n <th>ALEX4<\/th>\n <th>ALEX5<\/th>\n <th>ALEX6<\/th>\n <th>ALEX7<\/th>\n <th>ALEX8<\/th>\n <th>ALEX9<\/th>\n <th>ALEX10<\/th>\n <th>ALEX11<\/th>\n <th>ALEX12<\/th>\n <th>ALEX13<\/th>\n <th>ALEX14<\/th>\n <th>ALEX15<\/th>\n <th>ALEX16<\/th>\n <th>anxiety<\/th>\n <th>artgluctot<\/th>\n <th>attachhome<\/th>\n <th>attachphone<\/th>\n <th>AvgHumidity<\/th>\n <th>avoidance<\/th>\n <th>cigs<\/th>\n <th>DIDF<\/th>\n <th>eatdrink<\/th>\n <th>ECR1<\/th>\n <th>ECR2<\/th>\n <th>ECR3<\/th>\n <th>ECR4<\/th>\n <th>ECR5<\/th>\n <th>ECR6<\/th>\n <th>ECR7<\/th>\n <th>ECR8<\/th>\n <th>ECR9<\/th>\n <th>ECR10<\/th>\n <th>ECR11<\/th>\n <th>ECR12<\/th>\n <th>ECR13<\/th>\n <th>ECR14<\/th>\n <th>ECR15<\/th>\n <th>ECR16<\/th>\n <th>ECR17<\/th>\n <th>ECR18<\/th>\n <th>ECR19<\/th>\n <th>ECR20<\/th>\n <th>ECR21<\/th>\n <th>ECR22<\/th>\n <th>ECR23<\/th>\n <th>ECR24<\/th>\n <th>ECR25<\/th>\n <th>ECR26<\/th>\n <th>ECR27<\/th>\n <th>ECR28<\/th>\n <th>ECR29<\/th>\n <th>ECR30<\/th>\n <th>ECR31<\/th>\n <th>ECR32<\/th>\n <th>ECR33<\/th>\n <th>ECR34<\/th>\n <th>ECR35<\/th>\n <th>ECR36<\/th>\n <th>endtime<\/th>\n <th>EOT<\/th>\n <th>exercise<\/th>\n <th>gluctot<\/th>\n <th>health<\/th>\n <th>HOME1<\/th>\n <th>HOME2<\/th>\n <th>HOME3<\/th>\n <th>HOME4<\/th>\n <th>HOME5<\/th>\n <th>HOME6<\/th>\n <th>HOME7<\/th>\n <th>HOME8<\/th>\n <th>HOME9<\/th>\n <th>KAMF1<\/th>\n <th>KAMF2<\/th>\n <th>KAMF3<\/th>\n <th>KAMF4<\/th>\n <th>KAMF5<\/th>\n <th>KAMF6<\/th>\n <th>KAMF7<\/th>\n <th>networksize<\/th>\n <th>nostalgia<\/th>\n <th>onlineid<\/th>\n <th>onlineid1<\/th>\n <th>onlineid2<\/th>\n <th>onlineid3<\/th>\n <th>onlineid4<\/th>\n <th>onlineid5<\/th>\n <th>onlineid6<\/th>\n <th>onlineid7<\/th>\n <th>onlineid8<\/th>\n <th>onlineid9<\/th>\n <th>onlineid10<\/th>\n <th>onlineide11<\/th>\n <th>phone1<\/th>\n <th>phone2<\/th>\n <th>phone3<\/th>\n <th>phone4<\/th>\n <th>phone5<\/th>\n <th>phone6<\/th>\n <th>phone7<\/th>\n <th>phone8<\/th>\n <th>phone9<\/th>\n <th>romantic<\/th>\n <th>scontrol1<\/th>\n <th>scontrol2<\/th>\n <th>scontrol3<\/th>\n <th>scontrol4<\/th>\n <th>scontrol5<\/th>\n <th>scontrol6<\/th>\n <th>scontrol7<\/th>\n <th>scontrol8<\/th>\n <th>scontrol9<\/th>\n <th>scontrol10<\/th>\n <th>scontrol11<\/th>\n <th>scontrol12<\/th>\n <th>scontrol13<\/th>\n <th>selfcontrol<\/th>\n <th>sex<\/th>\n <th>smoke<\/th>\n <th>SNI1<\/th>\n <th>SNI2<\/th>\n <th>SNI3<\/th>\n <th>SNI4<\/th>\n <th>SNI5<\/th>\n <th>SNI6<\/th>\n <th>SNI7<\/th>\n <th>SNI8<\/th>\n <th>SNI9<\/th>\n <th>SNI10<\/th>\n <th>SNI11<\/th>\n <th>SNI12<\/th>\n <th>SNI13<\/th>\n <th>SNI14<\/th>\n <th>SNI15<\/th>\n <th>SNI16<\/th>\n <th>SNI17<\/th>\n <th>SNI18<\/th>\n <th>SNI19<\/th>\n <th>SNI20<\/th>\n <th>SNI21<\/th>\n <th>SNI22<\/th>\n <th>SNI23<\/th>\n <th>SNI24<\/th>\n <th>SNI25<\/th>\n <th>SNI26<\/th>\n <th>SNI27<\/th>\n <th>SNI28<\/th>\n <th>SNI29<\/th>\n <th>SNI30<\/th>\n <th>SNI31<\/th>\n <th>SNI32<\/th>\n <th>SNS1<\/th>\n <th>SNS2<\/th>\n <th>SNS3<\/th>\n <th>SNS4<\/th>\n <th>SNS5<\/th>\n <th>SNS6<\/th>\n <th>SNS7<\/th>\n <th>socialdiversity<\/th>\n <th>socialembedded<\/th>\n <th>STRAQ_1<\/th>\n <th>STRAQ_2<\/th>\n <th>STRAQ_3<\/th>\n <th>STRAQ_4<\/th>\n <th>STRAQ_6<\/th>\n <th>STRAQ_7<\/th>\n <th>STRAQ_8<\/th>\n <th>STRAQ_9<\/th>\n <th>STRAQ_10<\/th>\n <th>STRAQ_11<\/th>\n <th>STRAQ_12<\/th>\n <th>STRAQ_19<\/th>\n <th>STRAQ_20<\/th>\n <th>STRAQ_21<\/th>\n <th>STRAQ_22<\/th>\n <th>STRAQ_23<\/th>\n <th>STRAQ_24<\/th>\n <th>STRAQ_25<\/th>\n <th>STRAQ_26<\/th>\n <th>STRAQ_27<\/th>\n <th>STRAQ_28<\/th>\n <th>STRAQ_29<\/th>\n <th>STRAQ_30<\/th>\n <th>STRAQ_31<\/th>\n <th>STRAQ_32<\/th>\n <th>STRAQ_33<\/th>\n <th>STRAQ_5<\/th>\n <th>STRAQ_13<\/th>\n <th>STRAQ_14<\/th>\n <th>STRAQ_15<\/th>\n <th>STRAQ_16<\/th>\n <th>STRAQ_17<\/th>\n <th>STRAQ_18<\/th>\n <th>STRAQ_34<\/th>\n <th>STRAQ_35<\/th>\n <th>STRAQ_36<\/th>\n <th>STRAQ_37<\/th>\n <th>STRAQ_38<\/th>\n <th>STRAQ_39<\/th>\n <th>STRAQ_40<\/th>\n <th>STRAQ_41<\/th>\n <th>STRAQ_42<\/th>\n <th>STRAQ_43<\/th>\n <th>STRAQ_44<\/th>\n <th>STRAQ_45<\/th>\n <th>STRAQ_46<\/th>\n <th>STRAQ_47<\/th>\n <th>STRAQ_48<\/th>\n <th>STRAQ_49<\/th>\n <th>STRAQ_50<\/th>\n <th>STRAQ_51<\/th>\n <th>STRAQ_52<\/th>\n <th>STRAQ_53<\/th>\n <th>STRAQ_54<\/th>\n <th>STRAQ_55<\/th>\n <th>STRAQ_56<\/th>\n <th>STRAQ_57<\/th>\n <th>stress<\/th>\n <th>stress1<\/th>\n <th>stress2<\/th>\n <th>stress3<\/th>\n <th>stress4<\/th>\n <th>stress5<\/th>\n <th>stress6<\/th>\n <th>stress7<\/th>\n <th>stress8<\/th>\n <th>stress9<\/th>\n <th>stress10<\/th>\n <th>stress11<\/th>\n <th>stress12<\/th>\n <th>stress13<\/th>\n <th>stress14<\/th>\n <th>Temperature_t1<\/th>\n <th>Temperature_t2<\/th>\n <th>thermotype<\/th>\n <th>avgtemp<\/th>\n <th>filter_.<\/th>\n <th>mintemp<\/th>\n <th>language<\/th>\n <th>langfamily<\/th>\n <th>Zanxiety<\/th>\n <th>Zavoidance<\/th>\n <th>Site<\/th>\n <\/tr>\n 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---
# 3.2 读取数据
## 对于常用的心理学数据文件，可用bruceR包读取csv文件
```r
# 函数的内嵌，记得要检查左右括号一一匹配，数量一致
penguin.Data <- bruceR::import(here::here('data',
'penguin',
'penguin_rawdata.csv'))
```
```
## <U+221A> Successfully imported: 1523 obs. of 247 variables
```
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class=\"display fill-container\">\n <thead>\n <tr>\n <th> <\/th>\n <th>age<\/th>\n <th>ALEX1<\/th>\n <th>ALEX2<\/th>\n <th>ALEX3<\/th>\n <th>ALEX4<\/th>\n <th>ALEX5<\/th>\n <th>ALEX6<\/th>\n <th>ALEX7<\/th>\n <th>ALEX8<\/th>\n <th>ALEX9<\/th>\n <th>ALEX10<\/th>\n <th>ALEX11<\/th>\n <th>ALEX12<\/th>\n <th>ALEX13<\/th>\n <th>ALEX14<\/th>\n <th>ALEX15<\/th>\n <th>ALEX16<\/th>\n <th>anxiety<\/th>\n <th>artgluctot<\/th>\n <th>attachhome<\/th>\n <th>attachphone<\/th>\n <th>AvgHumidity<\/th>\n <th>avoidance<\/th>\n <th>cigs<\/th>\n <th>DIDF<\/th>\n <th>eatdrink<\/th>\n <th>ECR1<\/th>\n <th>ECR2<\/th>\n <th>ECR3<\/th>\n <th>ECR4<\/th>\n <th>ECR5<\/th>\n <th>ECR6<\/th>\n <th>ECR7<\/th>\n <th>ECR8<\/th>\n <th>ECR9<\/th>\n <th>ECR10<\/th>\n <th>ECR11<\/th>\n <th>ECR12<\/th>\n <th>ECR13<\/th>\n <th>ECR14<\/th>\n <th>ECR15<\/th>\n <th>ECR16<\/th>\n <th>ECR17<\/th>\n <th>ECR18<\/th>\n <th>ECR19<\/th>\n <th>ECR20<\/th>\n <th>ECR21<\/th>\n <th>ECR22<\/th>\n <th>ECR23<\/th>\n <th>ECR24<\/th>\n <th>ECR25<\/th>\n <th>ECR26<\/th>\n <th>ECR27<\/th>\n <th>ECR28<\/th>\n <th>ECR29<\/th>\n <th>ECR30<\/th>\n <th>ECR31<\/th>\n <th>ECR32<\/th>\n <th>ECR33<\/th>\n <th>ECR34<\/th>\n <th>ECR35<\/th>\n <th>ECR36<\/th>\n <th>endtime<\/th>\n <th>EOT<\/th>\n <th>exercise<\/th>\n <th>gluctot<\/th>\n <th>health<\/th>\n <th>HOME1<\/th>\n <th>HOME2<\/th>\n <th>HOME3<\/th>\n <th>HOME4<\/th>\n <th>HOME5<\/th>\n <th>HOME6<\/th>\n <th>HOME7<\/th>\n <th>HOME8<\/th>\n <th>HOME9<\/th>\n <th>KAMF1<\/th>\n <th>KAMF2<\/th>\n <th>KAMF3<\/th>\n <th>KAMF4<\/th>\n <th>KAMF5<\/th>\n <th>KAMF6<\/th>\n <th>KAMF7<\/th>\n <th>networksize<\/th>\n <th>nostalgia<\/th>\n <th>onlineid<\/th>\n <th>onlineid1<\/th>\n <th>onlineid2<\/th>\n <th>onlineid3<\/th>\n <th>onlineid4<\/th>\n <th>onlineid5<\/th>\n <th>onlineid6<\/th>\n <th>onlineid7<\/th>\n <th>onlineid8<\/th>\n <th>onlineid9<\/th>\n <th>onlineid10<\/th>\n <th>onlineide11<\/th>\n <th>phone1<\/th>\n <th>phone2<\/th>\n <th>phone3<\/th>\n <th>phone4<\/th>\n <th>phone5<\/th>\n <th>phone6<\/th>\n <th>phone7<\/th>\n <th>phone8<\/th>\n <th>phone9<\/th>\n <th>romantic<\/th>\n <th>scontrol1<\/th>\n <th>scontrol2<\/th>\n <th>scontrol3<\/th>\n <th>scontrol4<\/th>\n <th>scontrol5<\/th>\n <th>scontrol6<\/th>\n <th>scontrol7<\/th>\n <th>scontrol8<\/th>\n <th>scontrol9<\/th>\n <th>scontrol10<\/th>\n <th>scontrol11<\/th>\n <th>scontrol12<\/th>\n <th>scontrol13<\/th>\n <th>selfcontrol<\/th>\n <th>sex<\/th>\n <th>smoke<\/th>\n <th>SNI1<\/th>\n <th>SNI2<\/th>\n <th>SNI3<\/th>\n <th>SNI4<\/th>\n <th>SNI5<\/th>\n <th>SNI6<\/th>\n <th>SNI7<\/th>\n <th>SNI8<\/th>\n <th>SNI9<\/th>\n <th>SNI10<\/th>\n <th>SNI11<\/th>\n <th>SNI12<\/th>\n <th>SNI13<\/th>\n <th>SNI14<\/th>\n <th>SNI15<\/th>\n <th>SNI16<\/th>\n <th>SNI17<\/th>\n <th>SNI18<\/th>\n <th>SNI19<\/th>\n <th>SNI20<\/th>\n <th>SNI21<\/th>\n <th>SNI22<\/th>\n <th>SNI23<\/th>\n <th>SNI24<\/th>\n <th>SNI25<\/th>\n <th>SNI26<\/th>\n <th>SNI27<\/th>\n <th>SNI28<\/th>\n <th>SNI29<\/th>\n <th>SNI30<\/th>\n <th>SNI31<\/th>\n <th>SNI32<\/th>\n <th>SNS1<\/th>\n <th>SNS2<\/th>\n <th>SNS3<\/th>\n <th>SNS4<\/th>\n <th>SNS5<\/th>\n <th>SNS6<\/th>\n <th>SNS7<\/th>\n <th>socialdiversity<\/th>\n <th>socialembedded<\/th>\n <th>STRAQ_1<\/th>\n <th>STRAQ_2<\/th>\n <th>STRAQ_3<\/th>\n <th>STRAQ_4<\/th>\n <th>STRAQ_6<\/th>\n <th>STRAQ_7<\/th>\n <th>STRAQ_8<\/th>\n <th>STRAQ_9<\/th>\n <th>STRAQ_10<\/th>\n <th>STRAQ_11<\/th>\n <th>STRAQ_12<\/th>\n <th>STRAQ_19<\/th>\n <th>STRAQ_20<\/th>\n <th>STRAQ_21<\/th>\n <th>STRAQ_22<\/th>\n <th>STRAQ_23<\/th>\n <th>STRAQ_24<\/th>\n <th>STRAQ_25<\/th>\n <th>STRAQ_26<\/th>\n <th>STRAQ_27<\/th>\n <th>STRAQ_28<\/th>\n <th>STRAQ_29<\/th>\n <th>STRAQ_30<\/th>\n <th>STRAQ_31<\/th>\n <th>STRAQ_32<\/th>\n <th>STRAQ_33<\/th>\n <th>STRAQ_5<\/th>\n <th>STRAQ_13<\/th>\n <th>STRAQ_14<\/th>\n <th>STRAQ_15<\/th>\n <th>STRAQ_16<\/th>\n <th>STRAQ_17<\/th>\n <th>STRAQ_18<\/th>\n <th>STRAQ_34<\/th>\n <th>STRAQ_35<\/th>\n <th>STRAQ_36<\/th>\n <th>STRAQ_37<\/th>\n <th>STRAQ_38<\/th>\n <th>STRAQ_39<\/th>\n <th>STRAQ_40<\/th>\n <th>STRAQ_41<\/th>\n <th>STRAQ_42<\/th>\n <th>STRAQ_43<\/th>\n <th>STRAQ_44<\/th>\n <th>STRAQ_45<\/th>\n <th>STRAQ_46<\/th>\n <th>STRAQ_47<\/th>\n <th>STRAQ_48<\/th>\n <th>STRAQ_49<\/th>\n <th>STRAQ_50<\/th>\n <th>STRAQ_51<\/th>\n <th>STRAQ_52<\/th>\n <th>STRAQ_53<\/th>\n <th>STRAQ_54<\/th>\n <th>STRAQ_55<\/th>\n <th>STRAQ_56<\/th>\n <th>STRAQ_57<\/th>\n <th>stress<\/th>\n <th>stress1<\/th>\n <th>stress2<\/th>\n <th>stress3<\/th>\n <th>stress4<\/th>\n <th>stress5<\/th>\n <th>stress6<\/th>\n <th>stress7<\/th>\n <th>stress8<\/th>\n <th>stress9<\/th>\n <th>stress10<\/th>\n <th>stress11<\/th>\n <th>stress12<\/th>\n <th>stress13<\/th>\n <th>stress14<\/th>\n <th>Temperature_t1<\/th>\n <th>Temperature_t2<\/th>\n <th>thermotype<\/th>\n <th>avgtemp<\/th>\n <th>filter_$<\/th>\n <th>mintemp<\/th>\n <th>language<\/th>\n <th>langfamily<\/th>\n <th>Zanxiety<\/th>\n <th>Zavoidance<\/th>\n <th>Site<\/th>\n <\/tr>\n <\/thead>\n<\/table>","options":{"pageLength":3,"columnDefs":[{"className":"dt-right","targets":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246]},{"orderable":false,"targets":0}],"order":[],"autoWidth":false,"orderClasses":false,"lengthMenu":[3,10,25,50,100]}},"evals":[],"jsHooks":[]}</script>
---
# 3.2 读取数据
## 读取txt文件
```r
# 读取.txt类型文件
match.data <- read.csv("./data/match/data_exp7_rep_categ_7302.out",
header = TRUE, sep = "\t",
stringsAsFactors = FALSE)
```
<font size=5.5>
- 'sep = "\t"': txt文件以“tab”作为分隔符时，参数为“\t”
- 'sep = ': 默认的分隔符为","，也有“;”，""，"\n"等。
- 也可以使用read.table()函数读取
---
# 3.2 读取数据
## 读取txt文件
```r
# 读取.txt类型文件
match.data <- read.csv("./data/match/data_exp7_rep_categ_7302.out",
header = TRUE, sep = "\t",
stringsAsFactors = FALSE)
```
<div class="datatables html-widget html-fill-item-overflow-hidden html-fill-item" id="htmlwidget-8d9f904d83aeaef6c733" style="width:100%;height:auto;"></div>
<script type="application/json" data-for="htmlwidget-8d9f904d83aeaef6c733">{"x":{"filter":"none","vertical":false,"fillContainer":true,"data":[["1","2","3","4","5","6","7","8","9","10"],["02-May-2018_14:36:40 7302 22 female R 1 1 1 self immoralOther J NA -1 1.0420 ","02-May-2018_14:36:42 7302 22 female R 1 1 2 self moralSelf H h 1 0.7564 ","02-May-2018_14:36:44 7302 22 female R 1 1 3 self immoralSelf H h 1 0.4825 ","02-May-2018_14:36:46 7302 22 female R 1 1 4 self moralSelf H h 1 0.5446 ","02-May-2018_14:36:47 7302 22 female R 1 1 5 self moralOther J j 1 0.5028 ","02-May-2018_14:36:49 7302 22 female R 1 1 6 self moralSelf H h 1 0.5228 ","02-May-2018_14:36:51 7302 22 female R 1 1 7 self immoralSelf H h 1 0.4969 ","02-May-2018_14:36:53 7302 22 female R 1 1 8 self moralOther J j 1 0.5110 ","02-May-2018_14:36:54 7302 22 female R 1 1 9 self immoralSelf H h 1 0.5591 ","02-May-2018_14:36:56 7302 22 female R 1 1 10 self immoralOther J j 1 0.7311 "]],"container":"<table class=\"display fill-container\">\n <thead>\n <tr>\n <th> <\/th>\n <th>Date.Sub.Age.Sex.Hand.Block.Bin.Trial.Task.Shape.corrResp.Resp.ACC.RT<\/th>\n <\/tr>\n <\/thead>\n<\/table>","options":{"pageLength":3,"columnDefs":[{"orderable":false,"targets":0}],"order":[],"autoWidth":false,"orderClasses":false,"lengthMenu":[3,10,25,50,100]}},"evals":[],"jsHooks":[]}</script>
---
# 3.3 认识R里的数据 （R语言中的对象）
- <font size=6> 经过以上的操作，我们的"Environment"里发生了什么变化？</font>
---
# 3.3 认识R里的数据 （R语言中的对象）
## 对象
<br>
<br>
<span style="font-size: 30px;"> partner × </span> <br>
<span style="font-size: 30px;"> object √ </span> <br>
- <span style="font-size: 30px;"> 在R中存储的数据称为对象，R语言数据处理实际上就是不断地创建和操控这些对象。 </span> <br>
---
# 3.3 认识R里的数据 （R语言中的对象）
## 查看对象
```r
class(first_path)
```
```
## [1] "character"
```
```r
class(match.data)
```
```
## [1] "data.frame"
```
```r
class(penguin.data)
```
```
## [1] "data.frame"
```
---
```r
str(first_path)
```
```
## chr "C:/Users/Pac.B/Desktop/test"
```
```r
str(penguin.data[, 1:5])
```
```
## 'data.frame': 1523 obs. of 5 variables:
## $ ď.żage: int 1975 1995 1995 1988 1991 1995 1996 1973 1996 1996 ...
## $ ALEX1 : int 1 2 4 2 2 2 1 3 2 3 ...
## $ ALEX2 : int 1 2 1 3 1 3 1 3 3 3 ...
## $ ALEX3 : int 1 2 1 4 1 1 1 2 1 1 ...
## $ ALEX4 : int 2 2 2 5 5 3 1 3 3 2 ...
```
---
```r
summary(penguin.data[, 1:5])
```
```
## ď.żage ALEX1 ALEX2 ALEX3
## Min. :1922 Min. :1.00 Min. :1.000 Min. :1.000
## 1st Qu.:1991 1st Qu.:2.00 1st Qu.:2.000 1st Qu.:1.000
## Median :1994 Median :2.00 Median :3.000 Median :2.000
## Mean :1991 Mean :2.51 Mean :2.756 Mean :2.027
## 3rd Qu.:1995 3rd Qu.:3.00 3rd Qu.:4.000 3rd Qu.:3.000
## Max. :1998 Max. :5.00 Max. :5.000 Max. :5.000
## NA's :39 NA's :15 NA's :15 NA's :15
## ALEX4
## Min. :1.000
## 1st Qu.:2.000
## Median :2.000
## Mean :2.654
## 3rd Qu.:3.000
## Max. :5.000
## NA's :15
```
```r
summary(first_path)
```
```
## Length Class Mode
## 1 character character
```
---
## 3.3 认识R里的数据 （R语言中的对象)
<br>
<p align="right"><font size=2>from http://venus.ifca.unican.es/Rintro/dataStruct.html</font></p>
---
# 3.3 了解R里的数据 （R语言中的对象)
## R中的对象类型<br><br>
- <font size=6>Vector(向量)</font>
- <font size=6>Matrix(矩阵)</font>
- <font size=6>Array(数组)</font>
- <font size=6>Data frame(数据框)</font>
- <font size=6>List(列表)</font>
---
class: center, middle
<span style="font-size: 60px;">Any questions?</span> <br>
</textarea>
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