Last updated: 2020-05-23

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Knit directory: R-codes/

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html 5adafbc KaranSShakya 2020-05-16 panel regression + numeric/character
Rmd d927485 KaranSShakya 2020-05-16 GIT to R-Studio commits
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Home

Download Data - Online

To use data readily online. You need the readr package which reads csv files.

url <- "https://raw.githubusercontent.com/rafalab/dslabs/master/inst/extdata/murders.csv"
dat <- read_csv(url)

To download the file we can use: (or an alternative is to simply write.excel or write.csv).

download.file(url, tmp_filename)

Numeric / Character

If x is character and y is numeric, and you want to reverse both these:

y <- as.numeric(x)
x <- as.character(y)

Wide / Long

This is mainly used to change WorldBank datasets. Example table:

# A tibble: 3 x 4
  Country `2001` `2002` `2003`
  <chr>    <dbl>  <dbl>  <dbl>
1 Nepal       12    435   5524
2 India       31    355   2424
3 China       64    353   2244

key The columns to turn into rows. value what to call the data.

long <- wide %>% 
  gather(key="Year", value="Population", 2:4)
long
# A tibble: 9 x 3
  Country Year  Population
  <chr>   <chr>      <dbl>
1 Nepal   2001          12
2 India   2001          31
3 China   2001          64
4 Nepal   2002         435
5 India   2002         355
6 China   2002         353
7 Nepal   2003        5524
8 India   2003        2424
9 China   2003        2244

Column Name

names(data)[1] <- "New_name"


sessionInfo()
R version 4.0.0 (2020-04-24)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Catalina 10.15.4

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] readxl_1.3.1    forcats_0.5.0   stringr_1.4.0   dplyr_0.8.5    
 [5] purrr_0.3.4     readr_1.3.1     tidyr_1.0.3     tibble_3.0.1   
 [9] ggplot2_3.3.0   tidyverse_1.3.0 workflowr_1.6.2

loaded via a namespace (and not attached):
 [1] tidyselect_1.1.0 xfun_0.13        haven_2.2.0      lattice_0.20-41 
 [5] colorspace_1.4-1 vctrs_0.3.0      generics_0.0.2   htmltools_0.4.0 
 [9] yaml_2.2.1       utf8_1.1.4       rlang_0.4.6      later_1.0.0     
[13] pillar_1.4.4     withr_2.2.0      glue_1.4.1       DBI_1.1.0       
[17] dbplyr_1.4.3     modelr_0.1.7     lifecycle_0.2.0  munsell_0.5.0   
[21] gtable_0.3.0     cellranger_1.1.0 rvest_0.3.5      evaluate_0.14   
[25] knitr_1.28       httpuv_1.5.2     curl_4.3         fansi_0.4.1     
[29] broom_0.5.6      Rcpp_1.0.4.6     promises_1.1.0   backports_1.1.6 
[33] scales_1.1.1     jsonlite_1.6.1   fs_1.4.1         hms_0.5.3       
[37] digest_0.6.25    stringi_1.4.6    grid_4.0.0       rprojroot_1.3-2 
[41] cli_2.0.2        tools_4.0.0      magrittr_1.5     crayon_1.3.4    
[45] whisker_0.4      pkgconfig_2.0.3  ellipsis_0.3.0   xml2_1.3.2      
[49] reprex_0.3.0     lubridate_1.7.8  rstudioapi_0.11  assertthat_0.2.1
[53] rmarkdown_2.1    httr_1.4.1       R6_2.4.1         nlme_3.1-147    
[57] git2r_0.27.1     compiler_4.0.0