your help is very much apreciated
dput(excel_file)
structure(list(FDI = c(-3.23, -3.02, -1.46, -7.12, 3.66, 10.03,
-0.18, -7.4, -6.46, -4.1, 0.12, 0.1, 0.13, 0.09, 0.18, 0.1, 0.13,
0.11, 0.11, 0.11, 2.73, 1.98, 0.99, 0.58, 0.17, 0.23, 0.05, 0.3,
0.4, 0.45, 0.03, 0.03, 0.01, 0.02, 0.03, 0.02, 0.01, 0.02, 0.02,
0.03, 1.26, 3.66, 5.64, 6.7, 5, 3.87, 3.13, 2.32, 2.68, 2.18,
0.05, 0.03, 0.02, 0.01, 0.03, 0.03, 0.02, 0.03, 0.02, 0.03),
Trade_openness = c(104.12, 99.98, 91.8, 86.81, 79.33, 62.89,
53.37, 52.26, 66.38, 0, 94.44, 99.85, 100.28, 95.34, 101.05,
104.07, 104.19, 113.3, 117.27, 116.21, 144.67, 114.38, 116.68,
106.89, 104.38, 98.88, 92.6, 102.43, 104.51, 107.38, 50.13,
56.62, 41.17, 44.08, 51.59, 59.78, 57.81, 60.85, 57.79, 57.01,
70.79, 80.23, 101.87, 103.15, 111.47, 93.91, 105.64, 99.72,
131.99, 112.15, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), Government_effectiveness = c(-1.12,
-1.15, -0.99, -1.22, -1.12, -1, -1.04, -1.03, -1.05, -1.12,
-0.02, 0.15, 0.12, 0.1, 0.07, 0.17, 0.13, 0.17, 0.32, 0.29,
-1.68, -1.63, -1.61, -1.54, -1.5, -1.42, -1.41, -1.44, -1.29,
-1.34, -1.03, -1.03, -1.23, -1.43, -1.58, -1.61, -1.64, -1.77,
-1.49, -1.51, -0.58, -0.64, -0.63, -0.61, -0.72, -0.75, -0.86,
-0.89, -0.87, -0.82, -0.79, -0.7, -0.68, -0.73, -0.82, -0.75,
-0.67, -0.75, -0.64, -0.63), Political_stability = c(-0.23,
-0.37, -0.39, -0.39, -0.33, -0.5, -0.32, -0.33, -0.32, -0.31,
0.84, 0.72, 0.81, 0.78, 0.35, 0.87, 0.89, 0.77, 0.85, 0.88,
0.24, 0.15, 0.23, 0.12, -0.37, -0.21, -0.14, -0.17, -0.08,
-0.19, -0.69, -0.75, -0.97, -0.9, -0.71, -0.52, -0.44, -0.5,
-0.68, -0.56, 0.39, 0.33, 0.39, -0.23, -0.34, -0.51, -1.09,
-0.93, -0.81, -0.75, 0.12, 0.01, 0.01, 0.11, 0.18, 0.14,
0.22, 0.19, 0.53, 0.52), Corruption = c(19, 20, 22, 23, 19,
15, 18, 19, 19, 26, 51, 55, 60, 58, 57, 55, 59, 55, 57, 58,
19, 19, 20, 19, 19, 0, 0, 17, 16, 16, 0, 0, 25, 19, 19, 17,
16, 17, 16, 18, 27, 27, 31, 30, 31, 31, 27, 25, 23, 26, 30,
30, 42, 42, 42, 42, 46, 46, 46, 46), Economic_freedom = c(48,
46, 47, 47, 48, 48, 49, 49, 49, 51, 62, 65, 64, 64, 66, 66,
67, 57, 60, 63, 49, 48, 43, 42, 44, 40, 44, 45, 42, 41, 44,
47, 50, 51, 51, 52, 52, 56, 57, 54, 56, 57, 57, 55, 55, 55,
53, 50, 46, 49, 49, 50, 50, 48, 49, 53, 57, 55, 54, 54),
GDP_total = c(83.8, 111.79, 128.05, 136.71, 145.71, 116.19,
101.12, 122.12, 101.35, 94.64, 1.66, 1.87, 1.74, 1.85, 1.86,
1.6, 1.66, 1.77, 1.97, 1.98, 16.31, 21.36, 22.39, 21.95,
21.77, 13.19, 11.24, 12.2, 13.28, 11.03, 0.85, 1.1, 0.99,
1.05, 1.05, 1.05, 1.18, 1.35, 1.46, 1.34, 11.09, 14.38, 16.35,
16.97, 17.72, 15.95, 11.94, 13.22, 14.72, 14.93, 0.2, 0.23,
0.25, 0.3, 0.35, 0.32, 0.35, 0.38, 0.42, 0.43), GDP_per_capita = c(3587.88,
4615.47, 5100.1, 5254.88, 5408.41, 4166.98, 3506.07, 4095.81,
3289.65, 2973.59, 3378.25, 3740.39, 3447.52, 3615.98, 3588.67,
3043.01, 3130.96, 3292.65, 3617.33, 3603.78, 17288.86, 21641.87,
21711.15, 20390.72, 19394.03, 11283.47, 9250.33, 9667.91,
10144.2, 8131.92, 557.63, 702.74, 616.41, 634.48, 622.48,
603.16, 661.01, 736.73, 777.97, 697.78, 471.18, 594.59, 657.65,
664.08, 673.97, 589.86, 428.93, 461.42, 498.96, 491.8, 1094.71,
1263.87, 1340.53, 1577.02, 1782.8, 1595.86, 1710.13, 1811.01,
2001.14, 1994.91), Population_total = c(23.36, 24.22, 25.11,
26.02, 26.94, 27.88, 28.84, 29.82, 30.81, 31.83, 0.49, 0.5,
0.51, 0.51, 0.52, 0.52, 0.53, 0.54, 0.54, 0.55, 0.94, 0.99,
1.03, 1.08, 1.12, 1.17, 1.22, 1.26, 1.31, 1.36, 1.52, 1.56,
1.6, 1.65, 1.69, 1.74, 1.78, 1.83, 1.87, 1.92, 23.53, 24.19,
24.86, 25.56, 26.29, 27.04, 27.83, 28.65, 29.5, 30.37, 0.18,
0.18, 0.19, 0.19, 0.2, 0.2, 0.2, 0.21, 0.21, 0.22)), row.names = c(NA,
-60L), class = c("tbl_df", "tbl", "data.frame"))