2 Loading data

2.1 Reading in data from the working directory

# Read in persson and tabellini dataset from working directory
persson_tabellini_original<-read_csv("persson_tabellini_workshop.csv")
## 
## ── Column specification ───────────────────────────────────────────────────────────────────────
## cols(
##   .default = col_double(),
##   country = col_character(),
##   continent = col_character()
## )
## ℹ Use `spec()` for the full column specifications.

2.2 Reading data directly from an online source (Alternative method)

# Read in persson and tabellini dataset from Github repo
persson_tabellini_original<-read_csv("https://raw.githubusercontent.com/aranganath24/r_primer/main/workshop_data/persson_tabellini_workshop.csv")
## 
## ── Column specification ───────────────────────────────────────────────────────────────────────
## cols(
##   .default = col_double(),
##   country = col_character(),
##   continent = col_character()
## )
## ℹ Use `spec()` for the full column specifications.

2.3 Make a copy of the dataset

# Make a copy of the dataset so we don't alter the original dataset; then, view
# the copied dataset 
pt_copy<-persson_tabellini_original
# Print contents of "pt_copy"
pt_copy
## # A tibble: 85 × 75
##     oecd country   pind pindo ctrycd col_uk t_indep col_uka col_espa col_otha legor_uk legor_so
##    <dbl> <chr>    <dbl> <dbl>  <dbl>  <dbl>   <dbl>   <dbl>    <dbl>    <dbl>    <dbl>    <dbl>
##  1     0 Argenti… 0     0        213      0     183   0        0.268    0            0        0
##  2     1 Austral… 1     1        193      1      98   0.608    0        0            1        0
##  3     1 Austria  0     0        122      0     250   0        0        0            0        0
##  4     0 Bahamas  1     1        313      1      26   0.896    0        0            1        0
##  5     0 Banglad… 1     1        513      0      28   0        0        0.888        1        0
##  6     0 Barbados 1     1        316      1      33   0.868    0        0            1        0
##  7     0 Belarus  1     1        913      0       8   0        0        0.968        0        1
##  8     1 Belgium  0     0        124      0     169   0        0        0.324        0        0
##  9     0 Belize   1     1        339      1      18   0.928    0        0            1        0
## 10     0 Bolivia  0.116 0.116    218      0     174   0        0.304    0            0        0
## # … with 75 more rows, and 63 more variables: legor_fr <dbl>, legor_ge <dbl>, legor_sc <dbl>,
## #   prot80 <dbl>, catho80 <dbl>, confu <dbl>, avelf <dbl>, govef <dbl>, graft <dbl>,
## #   logyl <dbl>, loga <dbl>, yrsopen <dbl>, gadp <dbl>, engfrac <dbl>, eurfrac <dbl>,
## #   frankrom <dbl>, latitude <dbl>, gastil <dbl>, cgexp <dbl>, cgrev <dbl>, ssw <dbl>,
## #   rgdph <dbl>, trade <dbl>, prop1564 <dbl>, prop65 <dbl>, federal <dbl>, eduger <dbl>,
## #   spropn <dbl>, yearele <dbl>, yearreg <dbl>, seats <dbl>, maj <dbl>, pres <dbl>, lyp <dbl>,
## #   semi <dbl>, majpar <dbl>, majpres <dbl>, propres <dbl>, dem_age <dbl>, lat01 <dbl>, …
View(pt_copy)
oecd country pind pindo ctrycd col_uk t_indep col_uka col_espa col_otha legor_uk legor_so legor_fr legor_ge legor_sc prot80 catho80 confu avelf govef graft logyl loga yrsopen gadp engfrac eurfrac frankrom latitude gastil cgexp cgrev ssw rgdph trade prop1564 prop65 federal eduger spropn yearele yearreg seats maj pres lyp semi majpar majpres propres dem_age lat01 age polityIV spl cpi9500 du_60ctry magn sdm oecd.x mining_gdp gini_8090 con2150 con5180 con81 list maj_bad maj_gin maj_old pres_bad pres_gin pres_old propar lpop continent
0 Argentina 0 0 213 0 183 0.000 0.268 0.000 0 0 1 0 0 2.7 91.6 0 0.1769318 4.475911 5.549095 9.60270 8.39295 0.089 0.579 0.000 0.836 1.723 -36.676 2.333333 14.00048 12.31048 6.7540784 5831.075 18.42008 61.37738 9.293244 1 94.8000 0.0 1983 1983 257.11111 0 1 8.670957 0 0.0000000 0.0000000 1 1983 0.4075111 0.085 7.000000 -0.5086034 6.506667 1 0.0933475 0.1889764 0 1.8993865 NA 0 0 1 257.1111 0.000000 NA 0.000 2.333333 NA 0.085 0 17.35051 laam
1 Australia 1 1 193 1 98 0.608 0.000 0.000 1 0 0 0 0 23.5 29.6 0 0.1127971 2.082613 1.797832 10.30421 8.67103 0.689 0.931 0.950 0.950 1.404 -32.219 1.000000 25.78327 24.22912 8.6001902 15499.723 38.79273 66.80672 11.663297 1 111.3375 0.0 1901 1901 147.66667 1 0 9.648578 0 1.0000000 0.0000000 0 1901 0.3579889 0.495 10.000000 -0.6793869 1.340000 1 1.0000000 0.1904762 1 4.4933643 39.860 0 0 0 0.0000 1.000000 39.860 0.495 0.000000 0 0.000 0 16.69928 other
1 Austria 0 0 122 0 250 0.000 0.000 0.000 0 0 0 1 0 6.5 88.8 0 0.0332123 2.562550 2.085785 10.13165 8.80521 0.778 0.949 0.000 0.980 3.601 48.231 1.000000 40.14563 36.20243 17.8820381 13313.135 78.26205 67.45173 15.100343 1 103.9571 0.0 1945 1945 183.00000 0 0 9.496507 0 0.0000000 0.0000000 0 1945 0.5359000 0.275 10.000000 -4.4101000 2.478333 1 0.0491803 0.0728745 1 0.3989157 29.000 1 0 0 183.0000 0.000000 0.000 0.000 0.000000 0 0.000 1 15.89130 other
0 Bahamas 1 1 313 1 26 0.896 0.000 0.000 1 0 0 0 0 47.2 25.5 0 0.0000000 4.052546 4.005234 NA NA NA 0.614 0.865 0.865 3.638 24.700 1.722222 18.80976 17.46011 0.9501425 11768.360 101.83389 63.95686 4.389884 0 95.3000 0.0 1973 1973 47.00000 1 0 9.373170 0 1.0000000 0.0000000 0 1973 0.2744445 0.135 NA -2.3542581 NA 1 1.0000000 1.0000000 0 0.5927405 45.000 0 1 0 0.0000 1.722222 45.000 0.135 0.000000 0 0.000 0 12.51776 laam
0 Bangladesh 1 1 513 0 28 0.000 0.000 0.888 1 0 0 0 0 0.2 0.2 0 0.0000000 6.129216 5.578219 8.41382 8.65712 0.000 0.313 0.000 0.000 2.333 23.880 3.166667 12.56501 13.79131 0.1292526 1611.785 25.35251 53.81113 3.232165 0 43.6000 0.1 1991 1991 330.00000 1 0 7.385097 0 0.8888889 0.1111111 0 1991 0.2653333 0.045 4.777778 1.1960450 7.710000 0 0.9090909 1.0000000 0 0.0184373 33.635 0 0 1 0.0000 3.166667 33.635 0.045 0.000000 0 0.000 0 NA asiae
0 Barbados 1 1 316 1 33 0.868 0.000 0.000 1 0 0 0 0 33.2 5.9 0 0.0733333 NA NA 9.56870 8.54757 1.000 0.739 1.000 1.000 4.027 13.179 1.000000 32.36219 NA NA 7094.703 116.35070 65.17910 11.119803 0 NA 0.0 1966 1966 27.88889 1 0 8.867104 0 1.0000000 0.0000000 0 1966 0.1464333 0.170 NA NA NA 1 1.0000000 1.0000000 0 0.5067325 49.000 0 1 0 0.0000 1.000000 49.000 0.170 0.000000 0 0.000 0 12.47983 laam