Packages Used

library(dplyr)
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
library(openxlsx)
library(tibble)
library(readr)
library(utils)
library(haven)

Excel file Imported, Tibbled, and Printed

excel <- read.xlsx ("class3practice.xlsx")
excel <- tbl_df(excel)
excel
## # A tibble: 15 x 7
##    names row.1  row2  row3  row4  row5  row6
##  * <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
##  1   bob     1     2     9     8     7     6
##  2 betty     1     2     9     8     7     6
##  3  ruth     1     2     9     8     7     6
##  4  jenn     1     2     9     8     7     6
##  5 steve     1     2     9     8     7     6
##  6  kyle     1     2     9     8     7     6
##  7   sue     1     2     9     8     7     6
##  8  dave     1     2     9     8     7     6
##  9  daci     1     2     9     8     7     6
## 10  mark     1     2     9     8     7     6
## 11  gina     1     2     9     8     7     6
## 12  matt     1     2     9     8     7     6
## 13  sara     1     2     9     5     5     5
## 14  shan     1     2     4     4     4     4
## 15    ed     1     2     3     3     3     3

CSV file Imported, Tibbled, and Printed

csv <- read.csv("class3practice.csv")
csv <- tbl_df(csv)
csv
## # A tibble: 15 x 7
##     names row.1  row2  row3  row4  row5  row6
##    <fctr> <int> <int> <int> <int> <int> <int>
##  1    bob     1     2     9     8     7     6
##  2  betty     1     2     9     8     7     6
##  3   ruth     1     2     9     8     7     6
##  4   jenn     1     2     9     8     7     6
##  5  steve     1     2     9     8     7     6
##  6   kyle     1     2     9     8     7     6
##  7    sue     1     2     9     8     7     6
##  8   dave     1     2     9     8     7     6
##  9   daci     1     2     9     8     7     6
## 10   mark     1     2     9     8     7     6
## 11   gina     1     2     9     8     7     6
## 12   matt     1     2     9     8     7     6
## 13   sara     1     2     9     5     5     5
## 14   shan     1     2     4     4     4     4
## 15     ed     1     2     3     3     3     3

TXT file Imported, Tibbled, and Printed

txt <- read.table("class3practice.txt")
txt <- tbl_df(txt)
txt
## # A tibble: 15 x 7
##        V1    V2    V3    V4    V5    V6    V7
##    <fctr> <int> <int> <int> <int> <int> <int>
##  1    bob     1     2     9     8     7     6
##  2  betty     1     2     9     8     7     6
##  3   ruth     1     2     9     8     7     6
##  4   jenn     1     2     9     8     7     6
##  5  steve     1     2     9     8     7     6
##  6   kyle     1     2     9     8     7     6
##  7    sue     1     2     9     8     7     6
##  8   dave     1     2     9     8     7     6
##  9   daci     1     2     9     8     7     6
## 10   mark     1     2     9     8     7     6
## 11   gina     1     2     9     8     7     6
## 12   matt     1     2     9     8     7     6
## 13   sara     1     2     9     5     5     5
## 14   shan     1     2     4     4     4     4
## 15     ed     1     2     3     3     3     3

CSV Web files Imported, Tibbled, and Printed

webcsv <- read.csv("http://www.personal.psu.edu/dlp/alphaheight_weight_dataset.csv")
webcsv <- tbl_df(webcsv)
webcsv
## # A tibble: 200 x 4
##    Index Height Weight Gender
##    <int>  <dbl>  <dbl> <fctr>
##  1     1  65.78 112.99 female
##  2     2  71.52 136.49   male
##  3     3  69.40 153.03   male
##  4     4  68.22 142.34 female
##  5     5  67.79 144.30   male
##  6     6  68.70 123.30   male
##  7     7  69.80 141.49   male
##  8     8  70.01 136.46 female
##  9     9  67.90 112.37   male
## 10    10  66.78 120.67   male
## # ... with 190 more rows
httpcsv <- read.csv("http://www.personal.psu.edu/dlp/w540/datasets/titanicsurvival.csv")
httpcsv <- tbl_df(httpcsv)
httpcsv
## # A tibble: 2,201 x 4
##    Class   Age   Sex Survive
##    <int> <int> <int>   <int>
##  1     1     1     1       1
##  2     1     1     1       1
##  3     1     1     1       1
##  4     1     1     1       1
##  5     1     1     1       1
##  6     1     1     1       1
##  7     1     1     1       1
##  8     1     1     1       1
##  9     1     1     1       1
## 10     1     1     1       1
## # ... with 2,191 more rows

SPSS file Imported, Tibbled, and Printed

spsssav <- read_sav("http://cehd.gmu.edu/assets/dimitrovbook/EXAMPLE_23_1.sav")
spsssav <- tbl_df(spsssav)
spsssav
## # A tibble: 1,028 x 12
##      Illness    Item_1    Item_2    Item_3 Item_4    Item_5    Item_6
##    <dbl+lbl> <dbl+lbl> <dbl+lbl> <dbl+lbl>  <dbl> <dbl+lbl> <dbl+lbl>
##  1         1         4         3         3      3         4         2
##  2         0         3         2         4      3         4         3
##  3         0         4         3         4      3         3         2
##  4         1         5         5         4      5         4         5
##  5         1         2         2         2      2         2         2
##  6         0         3         2         2      3         2         1
##  7         0         2         1         1      2         1         2
##  8         0         3         2         4      4         2         2
##  9         0         2         4         3      3         3         3
## 10         1         1         1         1      1         1         1
## # ... with 1,018 more rows, and 5 more variables: Item_7 <dbl>,
## #   Item_8 <dbl+lbl>, Item_9 <dbl+lbl>, Item_10 <dbl+lbl>, Item_11 <dbl>
knitr::opts_chunk$set(echo = TRUE)