Assignment 1 - R Programming
Group 6 (Fatima Abbas,
Gulafsabanu Shaikh, Jane Nwakpuda, Joana Osei,
Sandra Arhin Amankwatiah, Sasirekha Nagaraj, Shafqat Mamun, Veronica
Opoku Mensah)
Sandra Arhin Amankwatiah, Sasirekha Nagaraj, Shafqat Mamun, Veronica Opoku Mensah)
July 6, 2025
1. Structure of dataset
The structure of the dataset is printed below.
## spc_tbl_ [2,938 × 22] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
## $ Country : chr [1:2938] "Afghanistan" "Afghanistan" "Afghanistan" "Afghanistan" ...
## $ Year : num [1:2938] 2015 2014 2013 2012 2011 ...
## $ Status : chr [1:2938] "Developing" "Developing" "Developing" "Developing" ...
## $ Life expectancy : num [1:2938] 65 59.9 59.9 59.5 59.2 58.8 58.6 58.1 57.5 57.3 ...
## $ Adult Mortality : num [1:2938] 263 271 268 272 275 279 281 287 295 295 ...
## $ infant deaths : num [1:2938] 62 64 66 69 71 74 77 80 82 84 ...
## $ Alcohol : num [1:2938] 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.03 0.02 0.03 ...
## $ percentage expenditure : num [1:2938] 71.3 73.5 73.2 78.2 7.1 ...
## $ Hepatitis B : num [1:2938] 65 62 64 67 68 66 63 64 63 64 ...
## $ Measles : num [1:2938] 1154 492 430 2787 3013 ...
## $ BMI : num [1:2938] 19.1 18.6 18.1 17.6 17.2 16.7 16.2 15.7 15.2 14.7 ...
## $ under-five deaths : num [1:2938] 83 86 89 93 97 102 106 110 113 116 ...
## $ Polio : num [1:2938] 6 58 62 67 68 66 63 64 63 58 ...
## $ Total expenditure : num [1:2938] 8.16 8.18 8.13 8.52 7.87 9.2 9.42 8.33 6.73 7.43 ...
## $ Diphtheria : num [1:2938] 65 62 64 67 68 66 63 64 63 58 ...
## $ HIV/AIDS : num [1:2938] 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 ...
## $ GDP : num [1:2938] 584.3 612.7 631.7 670 63.5 ...
## $ Population : num [1:2938] 33736494 327582 31731688 3696958 2978599 ...
## $ thinness 1-19 years : num [1:2938] 17.2 17.5 17.7 17.9 18.2 18.4 18.6 18.8 19 19.2 ...
## $ thinness 5-9 years : num [1:2938] 17.3 17.5 17.7 18 18.2 18.4 18.7 18.9 19.1 19.3 ...
## $ Income composition of resources: num [1:2938] 0.479 0.476 0.47 0.463 0.454 0.448 0.434 0.433 0.415 0.405 ...
## $ Schooling : num [1:2938] 10.1 10 9.9 9.8 9.5 9.2 8.9 8.7 8.4 8.1 ...
## - attr(*, "spec")=
## .. cols(
## .. Country = col_character(),
## .. Year = col_double(),
## .. Status = col_character(),
## .. `Life expectancy` = col_double(),
## .. `Adult Mortality` = col_double(),
## .. `infant deaths` = col_double(),
## .. Alcohol = col_double(),
## .. `percentage expenditure` = col_double(),
## .. `Hepatitis B` = col_double(),
## .. Measles = col_double(),
## .. BMI = col_double(),
## .. `under-five deaths` = col_double(),
## .. Polio = col_double(),
## .. `Total expenditure` = col_double(),
## .. Diphtheria = col_double(),
## .. `HIV/AIDS` = col_double(),
## .. GDP = col_double(),
## .. Population = col_double(),
## .. `thinness 1-19 years` = col_double(),
## .. `thinness 5-9 years` = col_double(),
## .. `Income composition of resources` = col_double(),
## .. Schooling = col_double()
## .. )
## - attr(*, "problems")=<externalptr>2. List of variables
The following is the full list of variables.
## [1] "Country" "Year"
## [3] "Status" "Life expectancy"
## [5] "Adult Mortality" "infant deaths"
## [7] "Alcohol" "percentage expenditure"
## [9] "Hepatitis B" "Measles"
## [11] "BMI" "under-five deaths"
## [13] "Polio" "Total expenditure"
## [15] "Diphtheria" "HIV/AIDS"
## [17] "GDP" "Population"
## [19] "thinness 1-19 years" "thinness 5-9 years"
## [21] "Income composition of resources" "Schooling"3. Top 15 rows of dataset
The top 15 rows of the dataset is printed below.
## # A tibble: 15 × 22
## Country Year Status `Life expectancy` `Adult Mortality` `infant deaths`
## <chr> <dbl> <chr> <dbl> <dbl> <dbl>
## 1 Afghanistan 2015 Develo… 65 263 62
## 2 Afghanistan 2014 Develo… 59.9 271 64
## 3 Afghanistan 2013 Develo… 59.9 268 66
## 4 Afghanistan 2012 Develo… 59.5 272 69
## 5 Afghanistan 2011 Develo… 59.2 275 71
## 6 Afghanistan 2010 Develo… 58.8 279 74
## 7 Afghanistan 2009 Develo… 58.6 281 77
## 8 Afghanistan 2008 Develo… 58.1 287 80
## 9 Afghanistan 2007 Develo… 57.5 295 82
## 10 Afghanistan 2006 Develo… 57.3 295 84
## 11 Afghanistan 2005 Develo… 57.3 291 85
## 12 Afghanistan 2004 Develo… 57 293 87
## 13 Afghanistan 2003 Develo… 56.7 295 87
## 14 Afghanistan 2002 Develo… 56.2 3 88
## 15 Afghanistan 2001 Develo… 55.3 316 88
## # ℹ 16 more variables: Alcohol <dbl>, `percentage expenditure` <dbl>,
## # `Hepatitis B` <dbl>, Measles <dbl>, BMI <dbl>, `under-five deaths` <dbl>,
## # Polio <dbl>, `Total expenditure` <dbl>, Diphtheria <dbl>, `HIV/AIDS` <dbl>,
## # GDP <dbl>, Population <dbl>, `thinness 1-19 years` <dbl>,
## # `thinness 5-9 years` <dbl>, `Income composition of resources` <dbl>,
## # Schooling <dbl>4. User defined function
A user defined function to create a new variable “Measle_Percentage” using Measles and population from the dataset is printed below.
## [1] 3.420628e-03 1.501914e-01 1.355112e-03 7.538630e-02 1.011549e-01
## [6] 6.898664e-02 1.006222e+00 5.858364e-02 4.286768e-03 7.685341e-02
## [11] 5.027192e-01 1.932088e-03 3.374420e-02 1.131032e-02 2.953686e-01
## [16] 2.223614e+00 0.000000e+00 0.000000e+00 0.000000e+00 3.060184e-01
## [21] 9.485256e-03 3.432640e-03 0.000000e+00 0.000000e+00 7.403170e-02
## [26] 2.272312e-03 1.926244e-03 2.141072e-03 2.355602e-03 4.557106e-01
## [31] 4.976087e-02 1.700619e+00 1.580075e-04 0.000000e+00 6.520850e-05
## [36] 4.791586e-05 3.041862e-04 2.851792e-04 3.016994e-03 6.223623e-03
## [41] 0.000000e+00 2.794725e-03 6.915314e-03 1.001768e-01 4.739921e-01
## [46] 1.832135e-01 8.502111e-03 0.000000e+00 4.235562e-03 4.345087e-01
## [51] 3.278286e-01 1.717158e+00 5.983013e-03 5.092188e-03 1.244814e-02
## [56] 1.217863e-02 3.382608e-02 3.381366e-02 1.319522e-03 1.537180e-04
## [61] 6.559287e-02 6.797495e-02 5.326420e-02 1.348998e-01 NA
## [66] NA NA NA NA NA
## [71] NA NA NA NA NA
## [76] NA NA NA NA NA
## [81] 0.000000e+00 2.326582e-06 0.000000e+00 4.654693e-05 7.201692e-06
## [86] 4.123822e-05 6.250690e-04 0.000000e+00 0.000000e+00 0.000000e+00
## [91] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [96] 1.596827e-04 1.131319e-02 4.388630e-02 3.455915e-03 0.000000e+00
## [101] 0.000000e+00 6.950934e-05 0.000000e+00 0.000000e+00 3.408827e-04
## [106] 4.630725e-01 7.651130e-02 4.936323e+01 1.258416e-02 1.197974e-02
## [111] 1.935212e-01 4.058573e-03 3.110637e-04 1.448847e-02 6.834693e-04
## [116] 8.755622e-04 8.504010e-02 3.136552e-02 4.794461e-02 3.058939e-02
## [121] 3.890225e-02 0.000000e+00 4.175714e-02 3.290401e-01 4.573922e-02
## [126] 1.628383e-02 7.263174e-01 5.638803e-01 3.579219e-03 1.369771e-03
## [131] 0.000000e+00 4.270467e-04 8.103300e-04 6.217537e-03 5.872960e-04
## [136] 5.383647e-03 2.410949e-04 2.781594e-04 1.093849e-04 1.835544e-04
## [141] 1.108180e-03 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [146] 0.000000e+00 1.741566e-02 0.000000e+00 0.000000e+00 0.000000e+00
## [151] 0.000000e+00 5.705548e-03 0.000000e+00 2.616521e-02 1.475241e-01
## [156] 9.886432e+00 2.402205e+00 5.326758e-01 7.076635e-01 2.474664e+00
## [161] NA NA NA NA NA
## [166] NA NA NA NA NA
## [171] NA NA NA NA NA
## [176] NA NA NA NA NA
## [181] NA NA NA NA NA
## [186] NA NA NA NA NA
## [191] NA NA 1.488016e-02 1.812449e-03 1.504081e-04
## [196] 1.275304e-02 3.654688e-03 5.179130e-03 4.645812e-02 1.786936e-02
## [201] 1.987234e-03 4.259523e-01 1.808115e-01 6.891606e-02 2.921884e+00
## [206] 2.549268e-01 3.289817e-01 3.874412e-03 NA NA
## [211] NA NA NA NA NA
## [216] NA NA NA NA NA
## [221] NA NA NA NA 2.107567e-05
## [226] 6.754966e-04 1.690260e-04 1.056580e-04 5.278063e-04 1.053094e-04
## [231] 0.000000e+00 0.000000e+00 1.044983e-04 1.544163e-02 1.034777e-05
## [236] 2.055190e-04 2.143568e-04 1.419080e-04 4.532384e-04 2.104291e-03
## [241] 4.168812e-04 6.197048e-02 3.487493e-04 9.794895e-04 5.018541e-02
## [246] 2.110165e-03 1.836912e-03 5.445261e-02 3.936766e-01 9.690185e-04
## [251] 1.758400e-03 4.292338e-03 3.197365e-03 0.000000e+00 6.451262e-02
## [256] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [261] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [266] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [271] 0.000000e+00 0.000000e+00 3.489954e-03 6.108593e-02 4.407999e+00
## [276] 2.960173e-02 4.499271e-01 4.261213e-03 1.633359e-01 1.067045e-02
## [281] 4.033216e-03 2.141928e-03 2.630845e-03 3.378901e+00 2.883510e-02
## [286] 2.176716e-02 7.543133e-01 6.181227e-02 1.397028e-03 0.000000e+00
## [291] 0.000000e+00 1.328079e-04 1.342102e-01 2.886039e-03 8.397974e-04
## [296] 8.805031e-01 1.601262e-03 2.975181e-04 1.675197e-03 4.666936e-03
## [301] 0.000000e+00 4.066326e-02 1.282225e+01 7.289647e-02 NA
## [306] NA NA NA NA NA
## [311] NA NA NA NA NA
## [316] NA NA NA NA NA
## [321] 4.742699e-02 8.412316e+00 0.000000e+00 6.030371e-02 2.710861e-04
## [326] 1.208755e-02 5.872052e-04 2.125625e-04 4.398516e+00 4.497988e-04
## [331] 6.082194e-03 7.404886e-04 4.762854e-04 7.415510e-03 0.000000e+00
## [336] 1.141565e-02 0.000000e+00 4.611327e-05 4.697990e-04 2.419508e-03
## [341] 3.182952e-03 3.969916e-01 9.293483e-03 0.000000e+00 5.223531e-05
## [346] 3.184311e-04 2.694180e-04 5.466482e-04 3.200625e-02 3.932688e-04
## [351] 5.698217e-05 1.545992e+00 8.242759e-03 3.617871e-03 9.783726e-03
## [356] 7.782616e-04 2.164211e-05 3.455350e-05 0.000000e+00 0.000000e+00
## [361] 0.000000e+00 3.013894e-04 3.209975e-06 0.000000e+00 1.095998e-06
## [366] 5.509275e-05 5.625667e-05 2.053768e-05 NA NA
## [371] NA NA NA NA NA
## [376] NA NA NA NA NA
## [381] NA NA NA NA 0.000000e+00
## [386] 0.000000e+00 1.927017e-04 1.358902e-04 2.136540e-03 2.975283e-01
## [391] 3.021045e-02 1.334657e-05 1.325322e-05 1.313681e-03 3.916975e-05
## [396] 0.000000e+00 0.000000e+00 0.000000e+00 8.974445e-03 5.629170e-03
## [401] 5.464710e-03 1.950418e-03 2.115390e-02 4.442643e-02 5.113143e-01
## [406] 1.604250e-01 3.574035e+00 2.688954e-03 8.419747e-04 9.038860e-04
## [411] 1.884975e-02 5.764811e-02 2.328003e-02 1.418682e+00 3.494470e-02
## [416] 5.200601e-01 7.504565e-03 0.000000e+00 0.000000e+00 5.257674e-03
## [421] 1.367134e-01 5.646218e-02 3.592754e-02 2.106605e-03 5.415908e-04
## [426] 1.021453e-02 0.000000e+00 2.784565e-05 3.221579e-03 1.507068e-02
## [431] 0.000000e+00 2.835547e+02 NA NA NA
## [436] NA NA NA NA NA
## [441] NA NA NA NA NA
## [446] NA NA NA 0.000000e+00 0.000000e+00
## [451] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [456] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [461] 0.000000e+00 0.000000e+00 0.000000e+00 4.589366e-03 0.000000e+00
## [466] 0.000000e+00 0.000000e+00 1.015100e-04 4.966334e-03 8.034808e-01
## [471] 3.201367e+01 3.032573e+00 2.880813e-03 1.395229e-03 1.989135e-01
## [476] 2.581824e-02 5.080477e-03 1.077190e-02 3.027028e-01 1.006965e-01
## [481] 7.922215e-03 3.736521e-02 3.509466e-03 2.790528e-02 1.996459e-01
## [486] 1.201505e-02 1.291648e-03 2.608283e+00 5.436145e-04 1.094999e-03
## [491] 3.471435e-02 2.110873e-02 5.443924e-03 8.594053e-02 1.527189e-01
## [496] 9.577567e-02 5.439541e-03 1.175989e-03 2.360943e-04 2.877247e-04
## [501] 2.338192e-02 2.867288e-02 4.163127e-05 1.864899e-04 3.071036e-04
## [506] 3.990729e-03 1.856895e-02 2.187842e-02 4.735446e-02 1.913143e-02
## [511] 1.068544e-01 5.464626e-01 3.299531e-01 4.650759e-03 1.324547e-02
## [516] 3.137405e-02 1.516928e-02 4.495872e-05 2.476195e-02 2.761550e-04
## [521] 1.145984e-01 7.113084e-04 1.141013e-01 2.707748e+00 1.637506e-02
## [526] 2.359084e-01 7.403000e-01 8.540644e-02 2.797615e-01 9.396115e-03
## [531] 1.720779e-03 9.410768e-03 7.039015e-02 1.632005e-02 1.431315e-02
## [536] 5.658414e-04 2.483416e-01 1.121274e-01 1.191185e-01 1.062763e+01
## [541] 1.689367e+00 7.936612e+00 2.875177e+00 4.250494e-02 5.066803e-05
## [546] 0.000000e+00 0.000000e+00 0.000000e+00 3.497858e-05 0.000000e+00
## [551] 5.941968e-06 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [556] 0.000000e+00 6.329297e-06 0.000000e+00 0.000000e+00 0.000000e+00
## [561] 3.089293e+01 3.857594e+01 1.980507e+01 4.556542e+00 7.397350e+00
## [566] 2.852476e+01 3.940703e+01 9.922659e+00 8.272573e+00 7.596248e+02
## [571] 9.289485e+02 5.440447e+01 5.578935e+02 4.543692e+03 6.994693e+01
## [576] 5.630482e+00 2.073454e-06 0.000000e+00 2.112246e-06 2.133039e-06
## [581] 1.291254e-04 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [586] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 3.343557e-04
## [591] 6.013241e-04 2.252465e-04 0.000000e+00 0.000000e+00 0.000000e+00
## [596] 1.381467e-04 3.918035e-03 0.000000e+00 1.485328e-04 0.000000e+00
## [601] 0.000000e+00 1.356906e-02 1.491105e-01 0.000000e+00 0.000000e+00
## [606] 0.000000e+00 0.000000e+00 0.000000e+00 NA NA
## [611] NA NA NA NA NA
## [616] NA NA NA NA NA
## [621] NA NA NA NA NA
## [626] 0.000000e+00 2.101911e-05 0.000000e+00 0.000000e+00 0.000000e+00
## [631] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [636] 2.354137e-05 0.000000e+00 2.423672e-05 0.000000e+00 0.000000e+00
## [641] 0.000000e+00 4.862619e-01 0.000000e+00 0.000000e+00 4.686521e-05
## [646] 2.799670e-03 1.584506e-04 4.514897e-04 1.150053e-02 0.000000e+00
## [651] 2.252252e-01 4.502476e-02 1.216490e+00 4.279279e+00 1.351351e+00
## [656] 1.801802e+00 2.033439e-01 NA NA NA
## [661] NA NA NA NA NA
## [666] NA NA NA NA NA
## [671] NA NA NA 0.000000e+00 8.677618e-03
## [676] 0.000000e+00 8.805762e-04 0.000000e+00 1.617730e-02 0.000000e+00
## [681] 5.507730e-04 0.000000e+00 0.000000e+00 7.833430e-04 0.000000e+00
## [686] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 NA
## [691] NA NA NA NA NA
## [696] NA NA NA NA NA
## [701] NA NA NA NA NA
## [706] NA NA NA NA NA
## [711] NA NA NA NA NA
## [716] NA NA NA NA NA
## [721] NA NA NA NA NA
## [726] NA NA NA NA NA
## [731] NA NA NA NA NA
## [736] NA NA 1.583536e-04 4.784286e-04 3.027641e-04
## [741] 3.576812e-05 1.506532e-02 9.012772e-05 1.086179e-03 2.548410e-04
## [746] 3.662039e-05 4.965725e-04 3.690424e-05 0.000000e+00 0.000000e+00
## [751] 5.952457e-04 2.052705e-04 2.621911e-04 5.067855e-03 0.000000e+00
## [756] 3.122602e-03 8.045984e-02 5.658610e-03 8.224206e-04 5.735863e-02
## [761] 1.737685e-02 2.683963e-01 6.153614e-02 3.804641e-02 9.131598e-02
## [766] 4.877309e-03 6.700428e-03 1.078188e-02 2.550224e-02 NA
## [771] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 1.563111e-02
## [776] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [781] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 1.299280e-03
## [786] 2.954702e-03 0.000000e+00 0.000000e+00 0.000000e+00 4.669362e-04
## [791] 1.693312e-03 0.000000e+00 0.000000e+00 6.921583e-06 0.000000e+00
## [796] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [801] 1.556087e-05 0.000000e+00 NA NA NA
## [806] NA NA NA NA NA
## [811] NA NA NA NA NA
## [816] NA NA NA 0.000000e+00 0.000000e+00
## [821] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [826] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [831] 0.000000e+00 0.000000e+00 3.355919e-04 0.000000e+00 1.063478e-01
## [836] 1.151029e-03 1.746977e-01 8.586292e-01 0.000000e+00 0.000000e+00
## [841] 7.869964e-02 5.020624e-02 6.028985e-04 0.000000e+00 0.000000e+00
## [846] 5.242703e-03 2.591378e-03 3.601062e-02 2.092966e-01 0.000000e+00
## [851] NA NA NA NA 1.072700e-02
## [856] 1.159513e-01 1.901079e-02 0.000000e+00 1.324238e-03 2.742967e-02
## [861] 4.786256e-02 6.219835e-04 1.005814e-02 1.272603e-02 5.833365e-03
## [866] 2.325506e-01 3.040738e-03 0.000000e+00 1.517454e-04 3.024126e-04
## [871] 5.273312e-04 0.000000e+00 0.000000e+00 0.000000e+00 7.425007e-03
## [876] 2.004737e-02 1.476260e-04 0.000000e+00 0.000000e+00 0.000000e+00
## [881] 0.000000e+00 6.442446e-04 1.776751e-01 1.308352e-02 5.536016e-03
## [886] 4.702297e-03 3.438056e-01 4.827493e-01 1.376787e-03 4.220718e-03
## [891] 1.774451e+01 1.840042e-02 4.652810e-03 9.782317e-04 3.142871e-04
## [896] 4.444331e-02 3.454405e-03 2.494840e-03 0.000000e+00 0.000000e+00
## [901] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 1.173754e-04
## [906] 0.000000e+00 0.000000e+00 1.643681e-02 0.000000e+00 4.521271e-03
## [911] 3.734871e-02 3.726901e-02 2.087893e-03 0.000000e+00 3.649947e-05
## [916] 0.000000e+00 3.677165e-05 0.000000e+00 5.010883e-04 9.322528e-05
## [921] 3.746110e-05 9.410172e-05 0.000000e+00 0.000000e+00 1.905865e-04
## [926] 0.000000e+00 0.000000e+00 0.000000e+00 1.927228e-03 0.000000e+00
## [931] 2.356484e-03 4.025209e-04 4.121301e-03 0.000000e+00 2.287782e-02
## [936] 7.733421e-02 2.379026e-01 9.382526e-03 6.078337e-04 6.287195e-05
## [941] 5.698064e-05 7.088563e-02 0.000000e+00 8.382823e-02 0.000000e+00
## [946] 1.446655e-01 1.397696e-02 1.759331e-03 6.713363e-03 1.138422e-04
## [951] 1.178474e-03 6.089763e-03 0.000000e+00 1.952603e-04 0.000000e+00
## [956] 6.229046e-03 0.000000e+00 4.617922e-02 0.000000e+00 8.497555e-02
## [961] 4.063350e-01 1.218401e-03 NA NA NA
## [966] NA NA NA NA NA
## [971] NA NA NA NA NA
## [976] NA NA NA 1.159506e+00 8.553797e+01
## [981] 2.084746e+02 8.104575e-01 1.651613e+00 5.603668e-01 5.781800e-01
## [986] 1.302326e+02 9.128631e+00 8.075435e+00 3.236277e+02 1.612956e+02
## [991] 5.011601e+01 4.567363e+00 7.979208e-02 1.131657e-01 3.016406e-03
## [996] 4.931812e-01 2.048429e-01 1.970134e-03 1.941998e-02 9.538142e-03
## [1001] 7.006519e-02 1.116663e-01 6.892245e-04 2.800558e-03 9.433800e-04
## [1006] 1.466378e-03 9.438514e-04 5.645636e-03 7.315125e-03 0.000000e+00
## [1011] 8.338523e-05 4.598969e-04 1.210798e-03 6.268097e-02 4.776729e-04
## [1016] 2.615031e-02 4.219178e-03 3.519519e-03 2.640706e-03 1.899299e-03
## [1021] 2.019227e-01 2.009016e-03 7.924695e-02 6.167777e-02 6.938648e-01
## [1026] 1.218031e-01 5.467977e-04 5.284259e-05 1.526554e-04 2.619836e-03
## [1031] 3.587769e-03 1.339766e-03 1.790238e-03 8.490110e-05 1.741443e-04
## [1036] 0.000000e+00 6.138939e-03 5.114721e-05 0.000000e+00 2.601186e-02
## [1041] 6.444226e-04 3.012696e-01 NA NA NA
## [1046] NA NA NA NA NA
## [1051] NA NA NA NA NA
## [1056] NA NA NA 0.000000e+00 0.000000e+00
## [1061] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [1066] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [1071] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 1.881485e-02
## [1076] 1.476058e-01 4.594069e-04 5.318456e-05 9.690179e-03 2.508124e-02
## [1081] 1.696087e-02 6.726413e-03 1.524956e-03 4.047998e-05 1.022754e-03
## [1086] 1.053487e-03 2.656813e-01 2.354076e-02 8.257591e-02 1.271065e+00
## [1091] 8.618456e-02 5.794602e-05 0.000000e+00 0.000000e+00 0.000000e+00
## [1096] 1.671080e-02 0.000000e+00 8.062295e-03 6.915830e-05 0.000000e+00
## [1101] 0.000000e+00 2.605194e+00 8.764627e-01 2.303786e-02 9.940734e-03
## [1106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [1111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [1116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [1121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [1126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [1131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [1136] 0.000000e+00 1.829149e-03 1.160342e+00 0.000000e+00 0.000000e+00
## [1141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [1146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [1151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [1156] 0.000000e+00 1.010732e-04 2.015394e-04 5.014177e-05 0.000000e+00
## [1161] 8.153282e-03 0.000000e+00 0.000000e+00 5.835327e-03 1.065814e-02
## [1166] 0.000000e+00 0.000000e+00 0.000000e+00 1.684103e-03 8.198670e-04
## [1171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [1176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [1181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [1186] 0.000000e+00 6.477507e+00 6.149278e-03 1.081058e-02 1.477298e-02
## [1191] 2.696682e-02 2.537203e-01 4.627302e-02 3.696956e-02 3.487722e-03
## [1196] 5.523772e-03 3.208671e-03 4.923296e-03 3.986101e-01 2.109010e-01
## [1201] 3.019632e-02 2.528465e+00 5.848651e-03 5.073078e-03 3.336601e-02
## [1206] 6.223400e-03 8.907737e-02 7.780257e-03 8.697913e-02 6.507896e-03
## [1211] 8.350604e-03 8.885380e-02 6.992550e-02 1.304521e-02 1.084798e-01
## [1216] 6.660358e-01 1.782675e-01 1.580756e-02 NA NA
## [1221] NA NA NA NA NA
## [1226] NA NA NA NA NA
## [1231] NA NA NA NA 3.967809e-03
## [1236] 3.691143e+01 1.974433e-03 4.576440e-05 4.727755e-04 1.307568e-01
## [1241] 1.014496e-01 1.887232e-02 8.100209e-03 1.711320e-03 3.261190e-01
## [1246] 3.450662e-01 0.000000e+00 0.000000e+00 1.685659e-02 3.080786e-03
## [1251] 8.552793e-05 7.147150e-04 1.109107e-03 2.332732e-03 6.227066e-03
## [1256] 9.711611e-02 3.616019e-03 1.269617e-03 1.454895e-03 2.035759e-03
## [1261] 2.283701e-03 7.066988e-01 1.461271e-02 6.180144e-03 6.233442e-03
## [1266] 0.000000e+00 9.545400e-01 7.303090e-03 5.817336e-01 2.665824e+00
## [1271] 9.013881e-02 3.016947e-02 6.679491e-03 1.260152e+01 7.505918e+00
## [1276] 1.194109e-01 2.885586e-02 1.683599e+01 1.853596e-01 3.044140e-01
## [1281] 2.950769e-01 5.724280e-01 2.360514e-02 0.000000e+00 0.000000e+00
## [1286] 6.315112e-04 8.738714e-03 6.275577e-04 5.854523e-03 2.748750e-03
## [1291] 5.492972e-03 7.550223e-04 2.328811e-04 1.038392e-03 1.916137e-01
## [1296] 1.629425e+01 0.000000e+00 2.558736e-02 0.000000e+00 0.000000e+00
## [1301] 0.000000e+00 0.000000e+00 3.534202e-05 0.000000e+00 0.000000e+00
## [1306] 7.165326e-04 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [1311] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 2.752849e-02
## [1316] 3.629907e-01 1.796854e-01 1.786428e-01 3.395054e-01 3.496503e+01
## [1321] 5.767884e+00 8.563321e+01 0.000000e+00 4.067139e-01 0.000000e+00
## [1326] 6.850291e+00 6.487731e+00 2.653066e+01 1.773667e+01 1.773610e+01
## [1331] 0.000000e+00 2.248808e-02 1.426285e-03 3.753485e-05 0.000000e+00
## [1336] 0.000000e+00 0.000000e+00 3.081749e-05 6.620174e-04 1.685138e-05
## [1341] 4.900150e-04 3.793630e-04 1.408249e-03 3.593389e-04 1.174549e-03
## [1346] 6.236236e-02 2.998154e-03 1.856648e-03 4.206826e-03 3.275481e-04
## [1351] 7.670657e-02 2.450743e-05 0.000000e+00 1.275998e-01 8.395659e-05
## [1356] 7.083258e-02 1.064085e+00 1.456723e-01 1.600875e-02 1.211391e-04
## [1361] 6.326415e-04 1.646104e-03 2.011167e-04 7.655295e-02 4.238531e-04
## [1366] 0.000000e+00 5.637040e-03 2.297376e-03 2.874513e-01 3.274717e-03
## [1371] 3.901194e-01 4.922052e+00 4.193748e-03 5.594514e-04 1.904008e-03
## [1376] 2.306194e-01 3.497364e-02 6.676876e-01 0.000000e+00 0.000000e+00
## [1381] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [1386] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [1391] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 NA
## [1396] NA NA NA NA NA
## [1401] NA NA NA NA NA
## [1406] NA NA NA NA NA
## [1411] NA NA NA NA NA
## [1416] NA NA NA NA NA
## [1421] NA NA NA NA NA
## [1426] NA NA NA NA NA
## [1431] NA NA NA NA NA
## [1436] NA NA NA NA NA
## [1441] NA NA 0.000000e+00 1.805614e-03 0.000000e+00
## [1446] 1.280306e-03 3.849263e-03 0.000000e+00 0.000000e+00 1.377839e-04
## [1451] 0.000000e+00 3.155488e-04 8.933361e-05 0.000000e+00 0.000000e+00
## [1456] 0.000000e+00 4.278679e-04 0.000000e+00 6.664982e-04 1.988357e-02
## [1461] 3.337680e-01 1.830593e-03 1.961482e-04 2.766800e-04 5.259187e-04
## [1466] 5.837328e-03 7.667545e-02 2.090303e+00 1.550095e-02 5.513468e-03
## [1471] 1.416019e-01 1.021904e-03 2.381052e-04 1.545420e-04 0.000000e+00
## [1476] 0.000000e+00 2.436996e-02 6.173947e-02 6.511057e-02 1.013401e+01
## [1481] 0.000000e+00 0.000000e+00 1.008936e-04 5.087345e-05 0.000000e+00
## [1486] 1.603121e-03 5.211129e-04 0.000000e+00 1.150611e-02 3.531869e-02
## [1491] 2.355754e-02 7.731894e-03 0.000000e+00 1.028324e-03 5.915153e-01
## [1496] 5.572265e-02 1.574172e-04 2.730008e-05 2.846625e-05 5.924455e-04
## [1501] 2.453062e-03 1.259282e-04 4.556784e-03 3.610178e-02 4.610295e-02
## [1506] 2.072094e-01 NA NA NA NA
## [1511] NA NA NA NA NA
## [1516] NA NA NA NA NA
## [1521] NA NA 1.695433e-01 3.751236e-04 1.183356e-03
## [1526] 0.000000e+00 2.133398e-03 5.034207e-04 0.000000e+00 3.126728e-05
## [1531] 0.000000e+00 3.058113e-04 3.009756e-05 2.960551e-04 2.928075e-05
## [1536] 2.990995e-02 2.012547e-03 5.429291e-04 0.000000e+00 0.000000e+00
## [1541] 0.000000e+00 3.707411e-03 1.157526e-03 0.000000e+00 0.000000e+00
## [1546] 2.046455e-03 0.000000e+00 1.692631e-03 0.000000e+00 0.000000e+00
## [1551] 2.214202e-03 0.000000e+00 0.000000e+00 0.000000e+00 1.237885e-04
## [1556] 1.271736e-04 2.613110e-05 8.949918e-06 0.000000e+00 4.727766e-05
## [1561] 0.000000e+00 1.500265e-05 0.000000e+00 1.059172e-04 0.000000e+00
## [1566] 1.994283e+00 3.601626e-01 6.438965e-02 5.751316e-01 2.236083e+00
## [1571] 0.000000e+00 1.696029e-04 6.032401e-06 6.480690e-03 1.663721e-04
## [1576] 7.826503e+00 1.427152e-03 1.401421e-04 1.032514e-02 7.446426e-06
## [1581] 1.373431e-02 8.803775e-02 1.353686e-03 7.580058e-03 1.282505e-03
## [1586] 2.672252e-03 3.540008e-02 6.845984e-02 6.550826e-03 6.402839e-02
## [1591] 5.479284e-03 2.596729e-04 5.532688e-03 1.231941e-02 1.479765e-03
## [1596] 2.157319e-03 5.483372e-03 2.275744e-01 2.559872e-02 1.686033e-03
## [1601] 9.274665e-02 2.668457e-01 0.000000e+00 0.000000e+00 0.000000e+00
## [1606] 0.000000e+00 0.000000e+00 0.000000e+00 1.666667e+01 0.000000e+00
## [1611] 5.730659e+00 1.411411e+01 4.345794e+02 1.185897e+01 2.205882e+02
## [1616] 3.117845e+02 0.000000e+00 6.993007e+00 1.230826e-02 1.709619e-03
## [1621] 1.341197e-03 2.045959e+00 1.543419e-03 1.090840e+00 2.003959e-01
## [1626] 6.931568e-04 1.462452e-04 9.676707e-03 2.578374e-04 1.387997e-02
## [1631] 1.854101e-01 6.160361e-03 3.952801e-02 8.019556e-01 4.630980e-04
## [1636] 0.000000e+00 0.000000e+00 0.000000e+00 7.206896e-04 0.000000e+00
## [1641] 2.424378e-04 2.025152e-03 4.280455e-03 2.203614e-02 1.368800e-02
## [1646] 9.692740e-03 1.003558e-03 1.767815e-03 5.085435e-03 5.016303e-02
## [1651] NA 2.391005e-05 3.017762e-02 1.571144e-02 9.132682e-03
## [1656] 6.294262e-03 3.496210e-01 9.037632e-02 1.150943e-03 3.320589e-04
## [1661] 6.818471e-03 4.048196e-01 1.469855e+00 1.221122e-01 3.073199e-02
## [1666] 4.997694e-01 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [1671] 0.000000e+00 1.596883e-03 9.569378e-01 1.202473e-03 9.645364e-04
## [1676] 1.048700e-02 2.431126e-04 5.699147e-04 2.292639e-01 6.403653e-01
## [1681] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 2.415039e-04
## [1686] 0.000000e+00 0.000000e+00 2.501730e-03 0.000000e+00 0.000000e+00
## [1691] 0.000000e+00 0.000000e+00 1.928919e-03 3.248119e-05 3.765684e-04
## [1696] 2.812485e-03 0.000000e+00 2.193496e-03 2.559798e-04 NA
## [1701] NA NA NA NA NA
## [1706] NA NA NA NA NA
## [1711] NA NA NA NA NA
## [1716] NA 6.839046e-01 0.000000e+00 0.000000e+00 0.000000e+00
## [1721] 0.000000e+00 2.580502e-03 2.998176e-04 1.179545e-03 4.630219e-03
## [1726] 1.016371e-02 0.000000e+00 0.000000e+00 7.289557e-04 4.931130e-02
## [1731] 4.412392e-01 3.858289e-02 0.000000e+00 0.000000e+00 0.000000e+00
## [1736] 0.000000e+00 7.963051e-02 8.071963e-04 0.000000e+00 0.000000e+00
## [1741] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [1746] 0.000000e+00 0.000000e+00 0.000000e+00 4.880399e-04 2.913853e-04
## [1751] 2.719900e-04 2.003973e-03 2.988543e-03 1.947909e-02 2.607073e-03
## [1756] 4.604889e-03 7.199156e-03 3.145234e-02 0.000000e+00 2.012717e-01
## [1761] 3.632564e-02 2.033046e-02 9.334575e-03 2.553933e-02 2.804491e-02
## [1766] 3.307318e-05 3.026363e-05 5.647152e-03 7.097175e-02 9.582416e-02
## [1771] 2.550518e-03 1.750795e-05 1.203332e-03 8.492879e-04 4.308924e+01
## [1776] 4.062696e+00 1.465669e-01 3.738311e-02 3.811443e-02 3.948734e-01
## [1781] 1.144237e-04 2.349580e-04 1.963140e-03 3.633166e-02 3.684289e-01
## [1786] 3.685101e-03 6.597285e-01 6.730026e-04 2.212660e-03 1.555895e-03
## [1791] 6.476548e-04 2.726842e-01 1.742786e-03 1.561234e-01 5.402334e-03
## [1796] 1.799610e-02 8.740246e-03 2.004269e-01 4.437691e-01 3.798697e-03
## [1801] 3.565592e-03 1.443974e+00 1.906990e+01 0.000000e+00 7.502277e-03
## [1806] 1.173094e-03 1.722683e-03 1.368551e-02 1.318879e-02 6.513273e-02
## [1811] 2.151432e-02 2.469387e-02 NA 5.579928e-03 4.515726e-03
## [1816] 6.649917e-02 1.215916e-02 8.632442e-03 6.977247e-03 7.067764e-03
## [1821] 7.890207e-03 5.397705e-03 1.093803e-01 1.958829e-01 4.754575e-01
## [1826] 5.346961e-01 2.747255e-02 4.490150e-02 3.956780e-01 4.132250e-05
## [1831] 8.300822e-02 1.562545e-01 5.968381e-05 3.055037e-03 9.027773e-05
## [1836] 9.072281e-04 6.627915e-04 6.104374e-05 6.117663e-05 2.451000e-05
## [1841] 6.756018e-05 2.465283e-04 1.857708e-05 0.000000e+00 6.398538e-03
## [1846] NA NA NA NA NA
## [1851] NA NA NA NA NA
## [1856] NA NA NA NA NA
## [1861] NA 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [1866] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [1871] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [1876] 0.000000e+00 0.000000e+00 3.866419e-02 5.964001e-03 6.642653e-03
## [1881] 1.533982e-03 4.369173e-02 2.264760e-03 5.065160e-03 8.648244e-03
## [1886] 1.922508e-03 4.174733e-03 1.602973e-02 4.803567e+00 4.281469e+00
## [1891] 2.575763e+02 5.199467e-01 1.877834e-01 6.856651e-03 3.884619e-01
## [1896] 3.075843e-01 3.853619e-03 1.156880e-01 5.354454e-03 8.237178e-03
## [1901] 6.489703e-01 1.784626e-02 4.936369e-03 7.983836e-02 2.328101e-02
## [1906] 1.070359e-01 3.264792e-01 1.339888e-01 1.734189e+01 NA
## [1911] 2.698187e-03 5.839721e-05 1.380207e-03 7.713475e-04 7.872617e-03
## [1916] 6.135908e-05 4.141879e-05 8.388889e-05 0.000000e+00 0.000000e+00
## [1921] 0.000000e+00 1.524420e-03 1.752520e-04 1.101768e-04 8.861809e-05
## [1926] 0.000000e+00 NA NA NA NA
## [1931] NA NA NA NA NA
## [1936] NA NA NA NA NA
## [1941] NA NA 2.038175e-03 7.383604e-04 4.814746e-03
## [1946] 4.522472e-03 2.518023e-03 2.460451e-01 5.152368e-02 6.899096e-03
## [1951] 1.714936e-02 4.837915e-02 1.935756e-02 2.691504e+01 3.208467e-01
## [1956] 2.698160e-03 2.717945e-02 1.490002e-03 0.000000e+00 0.000000e+00
## [1961] 0.000000e+00 0.000000e+00 0.000000e+00 1.058812e-03 0.000000e+00
## [1966] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [1971] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [1976] 4.798086e-04 2.964239e-02 1.580431e-04 0.000000e+00 0.000000e+00
## [1981] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 1.544946e-04
## [1986] 1.935140e-01 2.247823e-02 6.258506e+00 3.005638e-01 7.037951e-02
## [1991] 1.280459e-01 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [1996] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2001] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2006] 0.000000e+00 0.000000e+00 1.274833e-05 0.000000e+00 0.000000e+00
## [2011] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 3.491379e-05
## [2016] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2021] 0.000000e+00 0.000000e+00 3.858787e-06 5.283211e-03 5.242630e+01
## [2026] 2.965029e-02 1.585685e-03 6.862029e-02 6.794227e-03 1.592778e-02
## [2031] 3.496767e-03 5.935483e-03 1.023958e-04 1.367732e-04 3.572336e-03
## [2036] 1.261529e-01 8.608207e-01 9.238650e-03 9.129192e-03 0.000000e+00
## [2041] 0.000000e+00 2.186384e-02 1.837872e-03 0.000000e+00 3.382955e-04
## [2046] 3.014288e-03 0.000000e+00 1.049164e-02 3.146199e-04 3.406223e-05
## [2051] 2.880922e-05 1.255043e-02 8.892692e-04 3.477237e-03 2.012618e-04
## [2056] 5.887721e-03 0.000000e+00 6.862029e-05 1.518308e-03 1.284060e-03
## [2061] 3.178437e-02 1.912964e-04 6.417756e-05 0.000000e+00 0.000000e+00
## [2066] 4.565317e-02 3.369588e-04 5.483880e-04 5.635267e-04 0.000000e+00
## [2071] 3.488648e-03 NA NA NA NA
## [2076] NA NA NA NA NA
## [2081] NA NA NA NA NA
## [2086] NA NA NA NA NA
## [2091] NA NA NA NA NA
## [2096] NA NA NA NA NA
## [2101] NA NA NA NA NA
## [2106] NA NA NA NA NA
## [2111] NA NA NA NA NA
## [2116] NA NA NA NA 2.018624e-05
## [2121] 2.951507e-03 5.799729e-03 2.883685e+01 1.950615e-01 8.589723e-03
## [2126] 3.379110e-04 4.728365e-04 1.224427e-02 1.507991e-01 2.365420e-02
## [2131] 5.454101e-04 4.171625e-05 6.441236e-04 4.518351e-04 1.559508e-04
## [2136] 5.815048e-02 3.275630e-03 1.629181e-02 1.482368e-02 4.399565e-03
## [2141] 9.030486e-05 7.073555e-05 1.891520e-04 1.210986e-02 7.993294e-03
## [2146] 3.163355e-04 1.689299e-01 2.275174e-03 3.989967e-02 1.419403e-02
## [2151] 3.274292e-03 8.598783e-06 8.814178e-05 1.459038e-03 4.192631e-03
## [2156] 2.043898e-02 9.704517e-03 5.011302e-05 6.133909e-04 2.752074e-03
## [2161] 5.331434e-01 1.434651e-03 4.377192e-03 1.225318e-01 3.207497e-01
## [2166] 1.075700e-01 2.537149e+00 NA NA NA
## [2171] NA NA NA NA NA
## [2176] NA NA NA NA NA
## [2181] NA NA NA NA NA
## [2186] NA NA NA NA NA
## [2191] NA NA NA NA NA
## [2196] NA NA NA NA NA
## [2201] 0.000000e+00 0.000000e+00 0.000000e+00 5.285580e-04 0.000000e+00
## [2206] 4.295302e-02 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2211] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2216] 0.000000e+00 NA 0.000000e+00 0.000000e+00 0.000000e+00
## [2221] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2226] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2231] 0.000000e+00 0.000000e+00 0.000000e+00 NA NA
## [2236] NA NA NA NA NA
## [2241] NA NA NA NA NA
## [2246] NA NA NA NA 3.872606e-04
## [2251] 2.199901e-04 1.203693e-02 3.349076e-03 1.344186e-01 3.313661e-03
## [2256] 7.954347e-02 4.902133e-04 9.264284e-05 2.595883e-05 0.000000e+00
## [2261] 1.584912e-03 9.042205e+00 1.301776e+00 2.185021e+00 5.907217e-01
## [2266] 4.815290e-02 5.185152e-03 1.395843e-05 0.000000e+00 5.114036e-02
## [2271] 2.742944e-04 1.364498e-03 2.720267e-04 2.722995e-03 2.698484e-05
## [2276] 2.685396e-04 1.473907e-04 2.003764e-03 8.403897e-04 4.645403e-03
## [2281] 5.055648e-04 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2286] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 1.171921e-02
## [2291] 1.182033e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2296] 0.000000e+00 0.000000e+00 8.387164e-02 1.291131e-01 2.166756e-03
## [2301] 1.002050e-01 2.820761e-02 1.686093e-01 4.910813e-02 7.136633e-04
## [2306] 0.000000e+00 5.642287e-04 5.125143e-04 1.286837e-04 1.127021e-02
## [2311] 1.145804e-02 1.369445e-02 7.832531e-02 NA NA
## [2316] NA NA NA NA NA
## [2321] NA NA NA NA NA
## [2326] NA NA NA NA NA
## [2331] NA NA NA NA NA
## [2336] NA NA NA NA NA
## [2341] NA NA NA NA NA
## [2346] 6.830316e-03 1.984884e-01 3.846849e-04 7.777290e-04 8.701052e-03
## [2351] 8.045602e-04 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2356] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2361] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2366] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2371] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2376] 0.000000e+00 0.000000e+00 NA NA NA
## [2381] NA NA NA NA NA
## [2386] NA NA NA NA NA
## [2391] NA NA NA 3.084193e-04 1.218910e-04
## [2396] 4.689380e-05 6.087683e-04 1.778488e-04 2.090332e-01 1.114385e-01
## [2401] 7.869635e-05 6.341563e-05 1.679319e-03 1.290208e-01 1.759224e+01
## [2406] 5.256560e-04 2.274537e-03 2.573217e-03 3.249671e-03 7.389244e-03
## [2411] 3.821587e-02 4.696940e-02 1.073555e-01 8.668902e-02 0.000000e+00
## [2416] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2421] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2426] 2.475903e-04 3.312624e-03 2.809682e-02 2.574104e-02 8.133891e-03
## [2431] 6.483901e-04 8.843269e-05 6.462962e-03 5.903575e-03 8.153645e-04
## [2436] 5.039727e-05 6.057514e-05 6.068127e-04 1.617125e-04 0.000000e+00
## [2441] 3.327595e-03 5.286581e+01 6.084446e+01 8.150870e+01 2.103093e+00
## [2446] 2.642008e+00 3.728174e+00 1.051683e-01 1.665237e-01 2.237136e-01
## [2451] 0.000000e+00 1.548547e-02 1.820262e-01 3.277862e+00 7.339353e-01
## [2456] 1.643879e+00 8.859287e+01 9.276071e-02 1.791302e-03 7.633667e-03
## [2461] 2.368031e-01 1.596937e-02 1.977551e-03 2.020431e-03 3.914370e-04
## [2466] 1.012932e-03 7.197788e-02 3.512347e-02 3.000934e-01 1.488316e-02
## [2471] 1.579173e-02 1.560895e+00 1.054839e-01 0.000000e+00 0.000000e+00
## [2476] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2481] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2486] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2491] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 2.547968e-01
## [2496] 2.190857e-02 8.628895e-05 0.000000e+00 0.000000e+00 0.000000e+00
## [2501] 0.000000e+00 1.867742e-01 1.954569e+00 2.833566e-02 6.193178e-03
## [2506] 2.245084e-04 2.681488e-03 5.291609e-02 3.151468e-04 2.751552e-04
## [2511] 6.397867e-05 3.226322e-05 2.711604e-04 1.093025e-04 1.927955e-01
## [2516] 1.398493e-03 5.559552e-05 3.348876e-05 1.008408e-04 5.620529e-04
## [2521] 6.649993e-03 4.225830e-04 2.808766e-04 1.967738e-02 7.627993e-04
## [2526] 7.848442e-03 9.840268e-03 1.237114e-02 2.643941e-02 1.344172e-02
## [2531] 0.000000e+00 8.067645e-04 5.277670e-04 7.821122e-01 0.000000e+00
## [2536] 9.682077e-03 0.000000e+00 2.401923e-04 3.087479e+00 3.720199e-02
## [2541] 5.356186e-02 4.539117e-04 1.227090e-03 7.787906e-04 8.170486e-04
## [2546] 2.052681e-02 2.733284e-03 2.049784e-03 1.057853e-02 4.599413e-03
## [2551] 3.009100e-01 1.729598e-03 8.892419e-03 3.509326e-05 0.000000e+00
## [2556] 1.222809e-04 2.001096e-03 1.279435e-05 0.000000e+00 0.000000e+00
## [2561] 0.000000e+00 2.796270e-05 3.969829e-02 0.000000e+00 5.958729e-05
## [2566] 3.259906e-02 1.437725e-02 6.005887e-04 3.088679e-02 2.243015e-02
## [2571] 0.000000e+00 3.875636e-02 7.660223e-03 4.673388e-01 3.838677e-01
## [2576] 9.077199e-03 1.170623e-01 5.881054e-03 5.450886e-03 5.389338e-02
## [2581] 6.385774e-01 7.000238e-03 1.593502e-01 1.151813e-02 6.470959e-02
## [2586] NA NA NA NA NA
## [2591] NA NA NA NA NA
## [2596] NA NA NA NA NA
## [2601] NA 3.440633e-02 3.875285e-03 3.377334e-04 1.383174e-02
## [2606] 6.743124e-02 4.180917e-02 5.202643e-02 0.000000e+00 0.000000e+00
## [2611] 6.055672e-02 1.604946e-01 4.113583e-03 9.705530e-02 0.000000e+00
## [2616] 0.000000e+00 0.000000e+00 2.696573e-03 7.981834e-03 7.591379e-02
## [2621] 3.469650e-03 2.799702e-03 1.837807e-02 6.709057e-02 3.034829e-03
## [2626] 1.333915e-04 4.453739e-04 6.686294e-04 1.102158e-03 5.471667e-02
## [2631] 6.912348e-03 3.585842e-01 7.193883e-01 0.000000e+00 0.000000e+00
## [2636] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2641] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2646] 0.000000e+00 0.000000e+00 4.056343e-03 0.000000e+00 0.000000e+00
## [2651] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2656] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2661] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2666] 1.419237e-04 1.346018e-03 1.435547e-03 2.544168e-03 6.244795e-04
## [2671] 6.097818e-05 6.571019e-05 1.357441e-03 3.079600e-03 2.508076e-04
## [2676] 1.333547e-02 8.502678e-03 2.213351e-04 9.934789e-04 2.360585e-02
## [2681] 4.845762e-04 4.369408e-04 7.303252e-02 9.770762e-03 4.680175e-04
## [2686] 1.510316e-03 9.678278e-06 5.607017e-06 0.000000e+00 4.310513e-06
## [2691] 4.944487e-04 9.126425e-01 1.316948e+00 8.740874e-01 1.200887e-01
## [2696] 4.752812e-02 2.568578e-01 0.000000e+00 0.000000e+00 0.000000e+00
## [2701] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2706] 1.211158e-02 9.976099e-02 0.000000e+00 2.112387e-04 2.147886e-05
## [2711] 2.385082e-01 1.971609e-02 2.502142e-03 0.000000e+00 1.153233e-01
## [2716] 8.085836e-04 2.097795e-02 5.573587e-02 9.216262e-02 3.871428e-03
## [2721] 4.885284e-03 4.165628e-03 1.050386e+00 1.940682e-01 7.707415e-04
## [2726] 5.114545e-04 1.105322e+00 1.939111e+00 1.953056e-01 1.744535e+00
## [2731] 2.325360e-03 0.000000e+00 0.000000e+00 2.795586e+00 2.912961e+00
## [2736] 8.500992e-02 0.000000e+00 1.037654e-02 2.156953e-01 9.131450e-01
## [2741] 5.073009e-01 3.076819e-02 8.595998e-03 1.573250e+01 3.485754e-02
## [2746] 1.661385e-03 NA NA NA NA
## [2751] NA NA NA NA NA
## [2756] NA NA NA NA NA
## [2761] NA NA NA NA NA
## [2766] NA NA NA NA NA
## [2771] NA NA NA NA NA
## [2776] NA NA NA NA NA
## [2781] NA NA NA NA NA
## [2786] NA NA NA NA NA
## [2791] NA NA NA NA NA
## [2796] NA NA NA NA NA
## [2801] NA NA NA NA NA
## [2806] NA NA NA NA NA
## [2811] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2816] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2821] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2826] 0.000000e+00 7.029001e-03 2.128962e-02 0.000000e+00 0.000000e+00
## [2831] 1.622392e-01 4.096294e-02 0.000000e+00 7.318501e-03 3.211999e+00
## [2836] 3.107038e-02 2.816525e+00 2.899744e-03 3.324514e-03 9.892430e-04
## [2841] 8.812531e-04 3.244910e-01 1.473756e-01 3.863241e-02 0.000000e+00
## [2846] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2851] 0.000000e+00 0.000000e+00 1.021450e-01 0.000000e+00 8.292958e-02
## [2856] 5.207367e-02 3.698029e-02 4.848354e-02 NA NA
## [2861] NA NA NA NA NA
## [2866] NA NA NA NA NA
## [2871] NA NA NA NA NA
## [2876] NA NA NA NA NA
## [2881] NA NA NA NA NA
## [2886] NA NA NA NA NA
## [2891] NA NA NA NA NA
## [2896] NA NA NA NA NA
## [2901] NA NA NA NA NA
## [2906] NA 5.569755e-03 5.758253e-04 2.309742e-03 6.095264e-03
## [2911] 9.277411e-02 1.137202e+01 1.932164e-04 1.012646e-02 4.204000e-03
## [2916] 3.706561e-03 3.593801e-03 2.983358e-04 7.713196e-03 2.250447e+01
## [2921] 9.317892e-01 2.019957e+00 0.000000e+00 0.000000e+00 0.000000e+00
## [2926] 0.000000e+00 0.000000e+00 6.523507e-01 6.174006e-02 0.000000e+00
## [2931] 1.815455e-02 1.615328e-03 3.244947e-01 2.426138e-04 7.899384e-03
## [2936] 2.421828e-01 4.277802e-03 1.213361e-025. Use of data manipulation techniques and filtering rows
The following is the data of five variables including Country, Year, Measles, Population, Measle_Percentage in the year 2015.
## # A tibble: 183 × 5
## Country Year Measles Population Measle_Percentage
## <chr> <dbl> <dbl> <dbl> <dbl>
## 1 Afghanistan 2015 1154 33736494 0.00342
## 2 Albania 2015 0 28873 0
## 3 Algeria 2015 63 39871528 0.000158
## 4 Angola 2015 118 2785935 0.00424
## 5 Antigua and Barbuda 2015 0 NA NA
## 6 Argentina 2015 0 43417765 0
## 7 Armenia 2015 33 291695 0.0113
## 8 Australia 2015 74 23789338 0.000311
## 9 Austria 2015 309 8633169 0.00358
## 10 Azerbaijan 2015 0 9649341 0
## # ℹ 173 more rows6. New data frame by joining the dependent and independent variables
The following is the new data frame by created by joining dependent and independent variables from the dataset.
## Country Year Population Measles
## [1,] "United States Of America" "2014" "318563456" "667"
## [2,] "United States Of America" "2015" "320635163" "188"
## [3,] "Canada" "2014" "35152370" "400"
## [4,] "Canada" "2015" "35540419" "196"7. Removing missing values
Missing values are removed from the dataset and printed below.
## Country Year
## 0 0
## Status Life expectancy
## 0 10
## Adult Mortality infant deaths
## 10 0
## Alcohol percentage expenditure
## 194 0
## Hepatitis B Measles
## 553 0
## BMI under-five deaths
## 34 0
## Polio Total expenditure
## 19 226
## Diphtheria HIV/AIDS
## 19 0
## GDP Population
## 448 652
## thinness 1-19 years thinness 5-9 years
## 34 34
## Income composition of resources Schooling
## 167 163
## Measle_Percentage
## 652## # A tibble: 1,649 × 23
## Country Year Status `Life expectancy` `Adult Mortality` `infant deaths`
## <chr> <dbl> <chr> <dbl> <dbl> <dbl>
## 1 Afghanistan 2015 Develo… 65 263 62
## 2 Afghanistan 2014 Develo… 59.9 271 64
## 3 Afghanistan 2013 Develo… 59.9 268 66
## 4 Afghanistan 2012 Develo… 59.5 272 69
## 5 Afghanistan 2011 Develo… 59.2 275 71
## 6 Afghanistan 2010 Develo… 58.8 279 74
## 7 Afghanistan 2009 Develo… 58.6 281 77
## 8 Afghanistan 2008 Develo… 58.1 287 80
## 9 Afghanistan 2007 Develo… 57.5 295 82
## 10 Afghanistan 2006 Develo… 57.3 295 84
## # ℹ 1,639 more rows
## # ℹ 17 more variables: Alcohol <dbl>, `percentage expenditure` <dbl>,
## # `Hepatitis B` <dbl>, Measles <dbl>, BMI <dbl>, `under-five deaths` <dbl>,
## # Polio <dbl>, `Total expenditure` <dbl>, Diphtheria <dbl>, `HIV/AIDS` <dbl>,
## # GDP <dbl>, Population <dbl>, `thinness 1-19 years` <dbl>,
## # `thinness 5-9 years` <dbl>, `Income composition of resources` <dbl>,
## # Schooling <dbl>, Measle_Percentage <dbl>8. Identifying and removing duplicated data
Duplicated data are removed from the dataset and printed below
## [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [49] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [61] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [73] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [85] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [97] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [109] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [121] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [133] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [145] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [157] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [169] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [181] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [193] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [205] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [217] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [229] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [241] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [253] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [265] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [277] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [289] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [301] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [313] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [325] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [337] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [349] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [361] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [373] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [385] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [397] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [409] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [421] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [433] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [445] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [457] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [469] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [481] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [493] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [505] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [517] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [529] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [541] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [553] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [565] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [577] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [589] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [601] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [613] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [625] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [637] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [649] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [661] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [673] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [685] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [697] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [709] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [721] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [733] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [745] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [757] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [769] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [781] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [793] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [805] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [817] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [829] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [841] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [853] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [865] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [877] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [889] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [901] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [913] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [925] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [937] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [949] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [961] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [973] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [985] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [997] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1009] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1021] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1033] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1045] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1057] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1069] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1081] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1093] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1105] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1117] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1129] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1141] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1153] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1165] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1177] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1189] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1201] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1213] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1225] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1237] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1249] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1261] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1273] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1285] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1297] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1309] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1321] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1333] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1345] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1357] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1369] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1381] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1393] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1405] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1417] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1429] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1441] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1453] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1465] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1477] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1489] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1501] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1513] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1525] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1537] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1549] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1561] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1573] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1585] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1597] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1609] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1621] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1633] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1645] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1657] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1669] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1681] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1693] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1705] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1717] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1729] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1741] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1753] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1765] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1777] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1789] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1801] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1813] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1825] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1837] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1849] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1861] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1873] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1885] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1897] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1909] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1921] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1933] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1945] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1957] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1969] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1981] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [1993] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2005] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2017] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2029] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2041] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2053] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2065] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2077] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2089] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2101] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2113] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2125] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2137] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2149] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2161] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2173] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2185] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2197] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2209] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2221] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2233] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2245] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2257] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2269] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2281] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2293] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2305] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2317] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2329] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2341] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2353] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2365] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2377] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2389] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2401] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2413] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2425] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2437] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2449] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2461] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2473] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2485] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2497] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2509] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2521] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2533] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2545] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2557] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2569] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2581] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2593] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2605] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2617] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2629] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2641] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2653] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2665] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2677] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2689] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2701] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2713] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2725] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2737] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2749] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2761] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2773] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2785] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2797] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2809] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2821] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2833] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2845] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2857] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2869] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2881] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2893] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2905] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2917] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [2929] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE## # A tibble: 2,938 × 23
## Country Year Status `Life expectancy` `Adult Mortality` `infant deaths`
## <chr> <dbl> <chr> <dbl> <dbl> <dbl>
## 1 Afghanistan 2015 Develo… 65 263 62
## 2 Afghanistan 2014 Develo… 59.9 271 64
## 3 Afghanistan 2013 Develo… 59.9 268 66
## 4 Afghanistan 2012 Develo… 59.5 272 69
## 5 Afghanistan 2011 Develo… 59.2 275 71
## 6 Afghanistan 2010 Develo… 58.8 279 74
## 7 Afghanistan 2009 Develo… 58.6 281 77
## 8 Afghanistan 2008 Develo… 58.1 287 80
## 9 Afghanistan 2007 Develo… 57.5 295 82
## 10 Afghanistan 2006 Develo… 57.3 295 84
## # ℹ 2,928 more rows
## # ℹ 17 more variables: Alcohol <dbl>, `percentage expenditure` <dbl>,
## # `Hepatitis B` <dbl>, Measles <dbl>, BMI <dbl>, `under-five deaths` <dbl>,
## # Polio <dbl>, `Total expenditure` <dbl>, Diphtheria <dbl>, `HIV/AIDS` <dbl>,
## # GDP <dbl>, Population <dbl>, `thinness 1-19 years` <dbl>,
## # `thinness 5-9 years` <dbl>, `Income composition of resources` <dbl>,
## # Schooling <dbl>, Measle_Percentage <dbl>9. Reorder multiple rows in descending order
Countries are arranged in descending orders of population below
## # A tibble: 2,938 × 23
## Country Year Status `Life expectancy` `Adult Mortality` `infant deaths`
## <chr> <dbl> <chr> <dbl> <dbl> <dbl>
## 1 Zimbabwe 2015 Developing 67 336 22
## 2 Zimbabwe 2014 Developing 59.2 371 23
## 3 Zimbabwe 2011 Developing 54.9 464 28
## 4 Zimbabwe 2008 Developing 48.2 632 30
## 5 Zimbabwe 2006 Developing 45.4 7 28
## 6 Zimbabwe 2004 Developing 44.3 723 27
## 7 Zimbabwe 2003 Developing 44.5 715 26
## 8 Zimbabwe 2001 Developing 45.3 686 25
## 9 Zimbabwe 2000 Developing 46 665 24
## 10 Zimbabwe 2010 Developing 52.4 527 29
## # ℹ 2,928 more rows
## # ℹ 17 more variables: Alcohol <dbl>, `percentage expenditure` <dbl>,
## # `Hepatitis B` <dbl>, Measles <dbl>, BMI <dbl>, `under-five deaths` <dbl>,
## # Polio <dbl>, `Total expenditure` <dbl>, Diphtheria <dbl>, `HIV/AIDS` <dbl>,
## # GDP <dbl>, Population <dbl>, `thinness 1-19 years` <dbl>,
## # `thinness 5-9 years` <dbl>, `Income composition of resources` <dbl>,
## # Schooling <dbl>, Measle_Percentage <dbl>10. Renaming column names
The “Measles” and “Status” columns of the dataset are renamed as “Measles_case” and “Country_Status” as showing below.
## # A tibble: 2,938 × 23
## Country Year Country_Status `Life expectancy` `Adult Mortality`
## <chr> <dbl> <chr> <dbl> <dbl>
## 1 Afghanistan 2015 Developing 65 263
## 2 Afghanistan 2014 Developing 59.9 271
## 3 Afghanistan 2013 Developing 59.9 268
## 4 Afghanistan 2012 Developing 59.5 272
## 5 Afghanistan 2011 Developing 59.2 275
## 6 Afghanistan 2010 Developing 58.8 279
## 7 Afghanistan 2009 Developing 58.6 281
## 8 Afghanistan 2008 Developing 58.1 287
## 9 Afghanistan 2007 Developing 57.5 295
## 10 Afghanistan 2006 Developing 57.3 295
## # ℹ 2,928 more rows
## # ℹ 18 more variables: `infant deaths` <dbl>, Alcohol <dbl>,
## # `percentage expenditure` <dbl>, `Hepatitis B` <dbl>, Measles_case <dbl>,
## # BMI <dbl>, `under-five deaths` <dbl>, Polio <dbl>,
## # `Total expenditure` <dbl>, Diphtheria <dbl>, `HIV/AIDS` <dbl>, GDP <dbl>,
## # Population <dbl>, `thinness 1-19 years` <dbl>, `thinness 5-9 years` <dbl>,
## # `Income composition of resources` <dbl>, Schooling <dbl>, …11. Adding new variables using a mathematical function
A new variable named “Population_Double” is added by doubling the variable named “Population” as shown below.
## # A tibble: 2,938 × 24
## Country Year Status `Life expectancy` `Adult Mortality` `infant deaths`
## <chr> <dbl> <chr> <dbl> <dbl> <dbl>
## 1 Afghanistan 2015 Develo… 65 263 62
## 2 Afghanistan 2014 Develo… 59.9 271 64
## 3 Afghanistan 2013 Develo… 59.9 268 66
## 4 Afghanistan 2012 Develo… 59.5 272 69
## 5 Afghanistan 2011 Develo… 59.2 275 71
## 6 Afghanistan 2010 Develo… 58.8 279 74
## 7 Afghanistan 2009 Develo… 58.6 281 77
## 8 Afghanistan 2008 Develo… 58.1 287 80
## 9 Afghanistan 2007 Develo… 57.5 295 82
## 10 Afghanistan 2006 Develo… 57.3 295 84
## # ℹ 2,928 more rows
## # ℹ 18 more variables: Alcohol <dbl>, `percentage expenditure` <dbl>,
## # `Hepatitis B` <dbl>, Measles <dbl>, BMI <dbl>, `under-five deaths` <dbl>,
## # Polio <dbl>, `Total expenditure` <dbl>, Diphtheria <dbl>, `HIV/AIDS` <dbl>,
## # GDP <dbl>, Population <dbl>, `thinness 1-19 years` <dbl>,
## # `thinness 5-9 years` <dbl>, `Income composition of resources` <dbl>,
## # Schooling <dbl>, Measle_Percentage <dbl>, Population_Double <dbl>12. Training set using random data generator engine
A training set is generated from the existing dataset and is shown below.
## # A tibble: 30 × 24
## Country Year Status `Life expectancy` `Adult Mortality` `infant deaths`
## <chr> <dbl> <chr> <dbl> <dbl> <dbl>
## 1 Venezuela (… 2005 Devel… 73.6 158 9
## 2 Afghanistan 2006 Devel… 57.3 295 84
## 3 France 2005 Devel… 81 93 3
## 4 Bosnia and … 2002 Devel… 75.4 11 0
## 5 Trinidad an… 2005 Devel… 69.5 189 0
## 6 Jordan 2006 Devel… 72.8 121 4
## 7 Equatorial … 2015 Devel… 58.2 32 3
## 8 Costa Rica 2008 Devel… 78.9 99 1
## 9 Austria 2014 Devel… 81.4 66 0
## 10 Indonesia 2000 Devel… 66.3 188 187
## # ℹ 20 more rows
## # ℹ 18 more variables: Alcohol <dbl>, `percentage expenditure` <dbl>,
## # `Hepatitis B` <dbl>, Measles <dbl>, BMI <dbl>, `under-five deaths` <dbl>,
## # Polio <dbl>, `Total expenditure` <dbl>, Diphtheria <dbl>, `HIV/AIDS` <dbl>,
## # GDP <dbl>, Population <dbl>, `thinness 1-19 years` <dbl>,
## # `thinness 5-9 years` <dbl>, `Income composition of resources` <dbl>,
## # Schooling <dbl>, Measle_Percentage <dbl>, Population_Double <dbl>13. Summary statistics
The summary statistics of the dataset is printed below
## Country Year Status Life expectancy
## Length:2938 Min. :2000 Length:2938 Min. :36.30
## Class :character 1st Qu.:2004 Class :character 1st Qu.:63.10
## Mode :character Median :2008 Mode :character Median :72.10
## Mean :2008 Mean :69.22
## 3rd Qu.:2012 3rd Qu.:75.70
## Max. :2015 Max. :89.00
## NA's :10
## Adult Mortality infant deaths Alcohol percentage expenditure
## Min. : 1.0 Min. : 0.0 Min. : 0.0100 Min. : 0.000
## 1st Qu.: 74.0 1st Qu.: 0.0 1st Qu.: 0.8775 1st Qu.: 4.685
## Median :144.0 Median : 3.0 Median : 3.7550 Median : 64.913
## Mean :164.8 Mean : 30.3 Mean : 4.6029 Mean : 738.251
## 3rd Qu.:228.0 3rd Qu.: 22.0 3rd Qu.: 7.7025 3rd Qu.: 441.534
## Max. :723.0 Max. :1800.0 Max. :17.8700 Max. :19479.912
## NA's :10 NA's :194
## Hepatitis B Measles BMI under-five deaths
## Min. : 1.00 Min. : 0.0 Min. : 1.00 Min. : 0.00
## 1st Qu.:77.00 1st Qu.: 0.0 1st Qu.:19.30 1st Qu.: 0.00
## Median :92.00 Median : 17.0 Median :43.50 Median : 4.00
## Mean :80.94 Mean : 2419.6 Mean :38.32 Mean : 42.04
## 3rd Qu.:97.00 3rd Qu.: 360.2 3rd Qu.:56.20 3rd Qu.: 28.00
## Max. :99.00 Max. :212183.0 Max. :87.30 Max. :2500.00
## NA's :553 NA's :34
## Polio Total expenditure Diphtheria HIV/AIDS
## Min. : 3.00 Min. : 0.370 Min. : 2.00 Min. : 0.100
## 1st Qu.:78.00 1st Qu.: 4.260 1st Qu.:78.00 1st Qu.: 0.100
## Median :93.00 Median : 5.755 Median :93.00 Median : 0.100
## Mean :82.55 Mean : 5.938 Mean :82.32 Mean : 1.742
## 3rd Qu.:97.00 3rd Qu.: 7.492 3rd Qu.:97.00 3rd Qu.: 0.800
## Max. :99.00 Max. :17.600 Max. :99.00 Max. :50.600
## NA's :19 NA's :226 NA's :19
## GDP Population thinness 1-19 years
## Min. : 1.68 Min. :3.400e+01 Min. : 0.10
## 1st Qu.: 463.94 1st Qu.:1.958e+05 1st Qu.: 1.60
## Median : 1766.95 Median :1.387e+06 Median : 3.30
## Mean : 7483.16 Mean :1.275e+07 Mean : 4.84
## 3rd Qu.: 5910.81 3rd Qu.:7.420e+06 3rd Qu.: 7.20
## Max. :119172.74 Max. :1.294e+09 Max. :27.70
## NA's :448 NA's :652 NA's :34
## thinness 5-9 years Income composition of resources Schooling
## Min. : 0.10 Min. :0.0000 Min. : 0.00
## 1st Qu.: 1.50 1st Qu.:0.4930 1st Qu.:10.10
## Median : 3.30 Median :0.6770 Median :12.30
## Mean : 4.87 Mean :0.6276 Mean :11.99
## 3rd Qu.: 7.20 3rd Qu.:0.7790 3rd Qu.:14.30
## Max. :28.60 Max. :0.9480 Max. :20.70
## NA's :34 NA's :167 NA's :163
## Measle_Percentage Population_Double
## Min. : 0.000 Min. :6.800e+01
## 1st Qu.: 0.000 1st Qu.:3.916e+05
## Median : 0.001 Median :2.773e+06
## Mean : 4.771 Mean :2.551e+07
## 3rd Qu.: 0.025 3rd Qu.:1.484e+07
## Max. :4543.692 Max. :2.588e+09
## NA's :652 NA's :65214. Statistical functions using one numerical variable
The statistical functions including the mean, median, mode, and range of the variable “Life expectancy” is displayed below
## [1] 69.22493## [1] 72.1## [1] 73## [1] 36.3 89.015. A scatter plot of GDP vs Life expextancy
The scatter plot shows a positive relationship between GDP and life expectancy, where higher GDP is generally associated with higher life expectancy. However, most data points cluster at lower GDP values, indicating many countries have low GDP but varying life expectancies.
16. A bar plot of Measles case in 2015
The graph shows that Afghanistan had by far the highest number of measles cases in 2015, reaching nearly 1200 cases. In contrast, other countries such as Algeria and Azerbaijan had noticeably fewer cases, around 100–300, while most other countries reported very low numbers.
17. Finding the correlation between measles cases from 2000-2015 by applying least square linear regression model
The graph shows that most countries reported relatively low measles cases from 2000 to 2015, with a few countries experiencing large outbreaks exceeding 100,000 cases in certain years. There is no clear upward or downward trend, but significant variability exists between countries and years.
