我正在尝试根据Excel中VLOOKUP表的等效性将数据从一个数据帧拉到另一数据帧。我看过R中最流行的VLOOKUP问题，但看不到它如何适用于我的特定问题。关键是我不想将第二个数据帧中的所有列都拉入我的第一个数据框中-我只想拉入一个列。我很确定这将是merge函数的某种派生。
参考以下数据，我正在尝试创建一个名为df1$Trait1Percentile的新列。这需要根据LookupTable$Trait1Percentiles和df1$Trait1Scores。
LookupTable$Scores您可以在这里使用#Import data.
df1 <- structure(list(JobNumber = c(634L, 21L, 300L, 797L, 1112L, 147L,
1L, 4L, 260L, 194L, 981L, 1110L, 634L, 554L, 213L, 722L, 1036L,
855L, 624L, 1113L, 681L, 547L, 195L, 624L, 546L, 201L, 918L,
1069L, 300L, 294L, 587L, 933L, 918L, 620L, 918L, 298L, 749L,
295L, 635L, 515L, 624L, 147L, 200L, 527L, 800L, 827L, 4L, 568L,
252L, 655L, 559L, 629L, 639L, 933L, 214L, 750L, 1066L, 495L,
1113L, 1L, 1113L, 12L, 561L, 741L, 495L, 981L, 147L, 199L, 629L,
163L, 615L, 294L, 49L, 624L, 260L, 1L, 299L, 193L, 108L, 113L,
426L, 299L, 708L, 749L, 749L, 483L, 935L, 1036L, 295L, 12L, 1113L,
1038L, 4L, 973L, 448L, 295L, 197L, 76L, 1L, 1L), Trait1Score = c(3.89,
4.39, 4.22, 4.21, 3.94, 3.9, 4.58, 4.5, 4.29, 4.47, 4.41, 4.4,
4.14, 4.78, 4.09, 4.58, 4.27, 4.24, 3.96, 3.94, 4.3, 4.07, 4.28,
4.19, 4.57, 4.74, 3.29, 4.23, 3.51, 3.77, 4.46, 5.04, 4.25, 3.92,
3.78, 4.43, 4.12, 4.18, 4.63, 3.25, 3.87, 4.4, 3.83, 4.03, 3.42,
4.9, 4.09, 4.58, 4.29, 4.7, 4.38, 4.61, 4.41, 4.5, 4.6, 4.22,
3.72, 4.34, 4.34, 4.38, 4.15, 4.22, 3.93, 5, 3.81, 4.3, 4.6,
4.96, 4.29, 4.8, 5.05, 3.76, 4.81, 4.77, 4.25, 4.17, 4.75, 4.15,
4.35, 4.23, 5.31, 4.18, 3.67, 3.84, 4.06, 3.66, 3.58, 4.37, 4.43,
4.63, 4.74, 4.79, 5.04, 3.55, 3.64, 4.9, 4.38, 4.01, 4.47, 4.53
), Trait2Score = c(4, 2.94, 3.17, 3.83, 4.22, 3.83, 5.11, 3,
2.83, 2.78, 2.22, 2.22, 4.11, 2.39, 2.22, 2.06, 2.89, 3.61, 3.89,
4.89, 3.78, 4.22, 4.5, 4.39, 1.89, 4.78, 4.56, 3.78, 2.28, 4.61,
2.72, 1.89, 4.44, 4.06, 3.72, 2.44, 3.61, 2.06, 2.17, 6.44, 3.22,
2.78, 4.61, 2.72, 2.83, 2.44, 6.5, 2.28, 2.89, 2.11, 4.44, 2.83,
3, 6.33, 3.11, 3.17, 3.67, 4.5, 2.5, 4.33, 5, 2.89, 3.89, 1.72,
3.33, 4.28, 2.17, 3.17, 2.61, 2.89, 1.22, 3.39, 1.28, 2.61, 2.5,
4.56, 2.89, 4.89, 3.11, 3.5, 1.44, 2.39, 5.33, 3.78, 1.5, 3.44,
5.83, 3.17, 3.78, 2.67, 1.61, 1.83, 4.56, 4.67, 4.61, 2.5, 4.94,
3.94, 4.33, 2.72)), row.names = c(NA, -100L), class = "data.frame")
LookupTable <- structure(list(Scores = c(0, 0.01, 0.02, 0.03, 0.04, 0.05, 0.06,
0.07, 0.08, 0.09, 0.1, 0.11, 0.12, 0.13, 0.14, 0.15, 0.16, 0.17,
0.18, 0.19, 0.2, 0.21, 0.22, 0.23, 0.24, 0.25, 0.26, 0.27, 0.28,
0.29, 0.3, 0.31, 0.32, 0.33, 0.34, 0.35, 0.36, 0.37, 0.38, 0.39,
0.4, 0.41, 0.42, 0.43, 0.44, 0.45, 0.46, 0.47, 0.48, 0.49, 0.5,
0.51, 0.52, 0.53, 0.54, 0.55, 0.56, 0.57, 0.58, 0.59, 0.6, 0.61,
0.62, 0.63, 0.64, 0.65, 0.66, 0.67, 0.68, 0.69, 0.7, 0.71, 0.72,
0.73, 0.74, 0.75, 0.76, 0.77, 0.78, 0.79, 0.8, 0.81, 0.82, 0.83,
0.84, 0.85, 0.86, 0.87, 0.88, 0.89, 0.9, 0.91, 0.92, 0.93, 0.94,
0.95, 0.96, 0.97, 0.98, 0.99, 1, 1.01, 1.02, 1.03, 1.04, 1.05,
1.06, 1.07, 1.08, 1.09, 1.1, 1.11, 1.12, 1.13, 1.14, 1.15, 1.16,
1.17, 1.18, 1.19, 1.2, 1.21, 1.22, 1.23, 1.24, 1.25, 1.26, 1.27,
1.28, 1.29, 1.3, 1.31, 1.32, 1.33, 1.34, 1.35, 1.36, 1.37, 1.38,
1.39, 1.4, 1.41, 1.42, 1.43, 1.44, 1.45, 1.46, 1.47, 1.48, 1.49,
1.5, 1.51, 1.52, 1.53, 1.54, 1.55, 1.56, 1.57, 1.58, 1.59, 1.6,
1.61, 1.62, 1.63, 1.64, 1.65, 1.66, 1.67, 1.68, 1.69, 1.7, 1.71,
1.72, 1.73, 1.74, 1.75, 1.76, 1.77, 1.78, 1.79, 1.8, 1.81, 1.82,
1.83, 1.84, 1.85, 1.86, 1.87, 1.88, 1.89, 1.9, 1.91, 1.92, 1.93,
1.94, 1.95, 1.96, 1.97, 1.98, 1.99, 2, 2.01, 2.02, 2.03, 2.04,
2.05, 2.06, 2.07, 2.08, 2.09, 2.1, 2.11, 2.12, 2.13, 2.14, 2.15,
2.16, 2.17, 2.18, 2.19, 2.2, 2.21, 2.22, 2.23, 2.24, 2.25, 2.26,
2.27, 2.28, 2.29, 2.3, 2.31, 2.32, 2.33, 2.34, 2.35, 2.36, 2.37,
2.38, 2.39, 2.4, 2.41, 2.42, 2.43, 2.44, 2.45, 2.46, 2.47, 2.48,
2.49, 2.5, 2.51, 2.52, 2.53, 2.54, 2.55, 2.56, 2.57, 2.58, 2.59,
2.6, 2.61, 2.62, 2.63, 2.64, 2.65, 2.66, 2.67, 2.68, 2.69, 2.7,
2.71, 2.72, 2.73, 2.74, 2.75, 2.76, 2.77, 2.78, 2.79, 2.8, 2.81,
2.82, 2.83, 2.84, 2.85, 2.86, 2.87, 2.88, 2.89, 2.9, 2.91, 2.92,
2.93, 2.94, 2.95, 2.96, 2.97, 2.98, 2.99, 3, 3.01, 3.02, 3.03,
3.04, 3.05, 3.06, 3.07, 3.08, 3.09, 3.1, 3.11, 3.12, 3.13, 3.14,
3.15, 3.16, 3.17, 3.18, 3.19, 3.2, 3.21, 3.22, 3.23, 3.24, 3.25,
3.26, 3.27, 3.28, 3.29, 3.3, 3.31, 3.32, 3.33, 3.34, 3.35, 3.36,
3.37, 3.38, 3.39, 3.4, 3.41, 3.42, 3.43, 3.44, 3.45, 3.46, 3.47,
3.48, 3.49, 3.5, 3.51, 3.52, 3.53, 3.54, 3.55, 3.56, 3.57, 3.58,
3.59, 3.6, 3.61, 3.62, 3.63, 3.64, 3.65, 3.66, 3.67, 3.68, 3.69,
3.7, 3.71, 3.72, 3.73, 3.74, 3.75, 3.76, 3.77, 3.78, 3.79, 3.8,
3.81, 3.82, 3.83, 3.84, 3.85, 3.86, 3.87, 3.88, 3.89, 3.9, 3.91,
3.92, 3.93, 3.94, 3.95, 3.96, 3.97, 3.98, 3.99, 4, 4.01, 4.02,
4.03, 4.04, 4.05, 4.06, 4.07, 4.08, 4.09, 4.1, 4.11, 4.12, 4.13,
4.14, 4.15, 4.16, 4.17, 4.18, 4.19, 4.2, 4.21, 4.22, 4.23, 4.24,
4.25, 4.26, 4.27, 4.28, 4.29, 4.3, 4.31, 4.32, 4.33, 4.34, 4.35,
4.36, 4.37, 4.38, 4.39, 4.4, 4.41, 4.42, 4.43, 4.44, 4.45, 4.46,
4.47, 4.48, 4.49, 4.5, 4.51, 4.52, 4.53, 4.54, 4.55, 4.56, 4.57,
4.58, 4.59, 4.6, 4.61, 4.62, 4.63, 4.64, 4.65, 4.66, 4.67, 4.68,
4.69, 4.7, 4.71, 4.72, 4.73, 4.74, 4.75, 4.76, 4.77, 4.78, 4.79,
4.8, 4.81, 4.82, 4.83, 4.84, 4.85, 4.86, 4.87, 4.88, 4.89, 4.9,
4.91, 4.92, 4.93, 4.94, 4.95, 4.96, 4.97, 4.98, 4.99, 5, 5.01,
5.02, 5.03, 5.04, 5.05, 5.06, 5.07, 5.08, 5.09, 5.1, 5.11, 5.12,
5.13, 5.14, 5.15, 5.16, 5.17, 5.18, 5.19, 5.2, 5.21, 5.22, 5.23,
5.24, 5.25, 5.26, 5.27, 5.28, 5.29, 5.3, 5.31, 5.32, 5.33, 5.34,
5.35, 5.36, 5.37, 5.38, 5.39, 5.4, 5.41, 5.42, 5.43, 5.44, 5.45,
5.46, 5.47, 5.48, 5.49, 5.5, 5.51, 5.52, 5.53, 5.54, 5.55, 5.56,
5.57, 5.58, 5.59, 5.6, 5.61, 5.62, 5.63, 5.64, 5.65, 5.66, 5.67,
5.68, 5.69, 5.7, 5.71, 5.72, 5.73, 5.74, 5.75, 5.76, 5.77, 5.78,
5.79, 5.8, 5.81, 5.82, 5.83, 5.84, 5.85, 5.86, 5.87, 5.88, 5.89,
5.9, 5.91, 5.92, 5.93, 5.94, 5.95, 5.96, 5.97, 5.98, 5.99, 6,
6.01, 6.02, 6.03, 6.04, 6.05, 6.06, 6.07, 6.08, 6.09, 6.1, 6.11,
6.12, 6.13, 6.14, 6.15, 6.16, 6.17, 6.18, 6.19, 6.2, 6.21, 6.22,
6.23, 6.24, 6.25, 6.26, 6.27, 6.28, 6.29, 6.3, 6.31, 6.32, 6.33,
6.34, 6.35, 6.36, 6.37, 6.38, 6.39, 6.4, 6.41, 6.42, 6.43, 6.44,
6.45, 6.46, 6.47, 6.48, 6.49, 6.5, 6.51, 6.52, 6.53, 6.54, 6.55,
6.56, 6.57, 6.58, 6.59, 6.6, 6.61, 6.62, 6.63, 6.64, 6.65, 6.66,
6.67, 6.68, 6.69, 6.7, 6.71, 6.72, 6.73, 6.74, 6.75, 6.76, 6.77,
6.78, 6.79, 6.8, 6.81, 6.82, 6.83, 6.84, 6.85, 6.86, 6.87, 6.88,
6.89, 6.9, 6.91, 6.92, 6.93, 6.94, 6.95, 6.96, 6.97, 6.98, 6.99,
7), Trait1Percentiles = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03,
0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.06, 0.06, 0.06, 0.06,
0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06,
0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06,
0.06, 0.06, 0.09, 0.09, 0.09, 0.09, 0.09, 0.09, 0.13, 0.13, 0.13,
0.13, 0.13, 0.13, 0.13, 0.13, 0.13, 0.16, 0.19, 0.19, 0.19, 0.19,
0.25, 0.28, 0.35, 0.38, 0.41, 0.5, 0.5, 0.5, 0.5, 0.54, 0.57,
0.57, 0.6, 0.6, 0.66, 0.66, 0.69, 0.69, 0.85, 0.85, 0.91, 1.01,
1.04, 1.07, 1.1, 1.13, 1.2, 1.23, 1.32, 1.42, 1.48, 1.48, 1.67,
1.73, 1.89, 1.98, 2.14, 2.14, 2.14, 2.33, 2.33, 2.52, 2.52, 2.77,
2.77, 3.12, 3.34, 3.46, 3.75, 3.97, 4.16, 4.57, 4.82, 5.1, 5.26,
5.45, 5.61, 5.73, 6.14, 6.36, 6.65, 7.09, 7.43, 7.43, 8.31, 8.31,
9.01, 9.01, 9.51, 9.51, 10.65, 11.15, 11.69, 12.03, 12.6, 13.39,
14.08, 14.61, 14.96, 15.59, 16.5, 17.23, 18.02, 18.8, 19.78,
20.79, 21.57, 22.33, 22.93, 22.93, 25.01, 25.92, 26.9, 26.9,
28.79, 29.83, 31.28, 32.35, 33.45, 34.43, 35.43, 36.91, 37.95,
39.31, 40.88, 42.05, 43.15, 44.22, 45.61, 46.87, 48.22, 49.23,
50.77, 52.03, 52.03, 54.46, 55.81, 56.94, 56.94, 59.37, 60.66,
61.95, 61.95, 64.28, 65.48, 66.96, 68, 68.79, 69.73, 70.55, 71.43,
72.44, 73.48, 74.3, 74.99, 75.81, 76.76, 77.73, 78.46, 78.46,
80.16, 80.79, 81.64, 81.64, 83.28, 83.97, 84.63, 84.63, 85.76,
86.27, 86.99, 87.46, 87.91, 88.35, 88.69, 88.91, 89.32, 89.73,
90.11, 90.43, 90.8, 91.24, 91.5, 91.69, 91.69, 92.44, 92.72,
93.2, 93.2, 93.76, 93.92, 94.17, 94.17, 94.52, 94.83, 95.21,
95.46, 95.72, 95.87, 95.94, 96.19, 96.35, 96.6, 96.85, 96.98,
97.1, 97.1, 97.2, 97.32, 97.32, 97.54, 97.64, 97.76, 97.76, 97.92,
97.98, 98.05, 98.05, 98.24, 98.3, 98.36, 98.39, 98.55, 98.58,
98.68, 98.77, 98.83, 98.87, 98.87, 98.99, 99.06, 99.06, 99.06,
99.06, 99.06, 99.06, 99.15, 99.15, 99.15, 99.28, 99.28, 99.31,
99.31, 99.31, 99.5, 99.53, 99.59, 99.62, 99.62, 99.65, 99.65,
99.65, 99.65, 99.69, 99.69, 99.72, 99.78, 99.78, 99.81, 99.81,
99.81, 99.81, 99.81, 99.81, 99.81, 99.81, 99.81, 99.81, 99.81,
99.81, 99.81, 99.81, 99.81, 99.81, 99.81, 99.81, 99.81, 99.87,
99.87, 99.91, 99.91, 99.94, 99.94, 99.97, 99.97, 99.97, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100), Trait2Percentiles = c(0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.03, 0.03, 0.03,
0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.06, 0.06, 0.06, 0.09, 0.09,
0.09, 0.09, 0.13, 0.13, 0.13, 0.13, 0.19, 0.19, 0.19, 0.22, 0.25,
0.28, 0.31, 0.31, 0.31, 0.41, 0.41, 0.41, 0.41, 0.41, 0.41, 0.57,
0.6, 0.63, 0.69, 0.76, 0.82, 0.82, 0.91, 0.98, 0.98, 1.13, 1.23,
1.23, 1.35, 1.51, 1.54, 1.57, 1.67, 1.67, 1.89, 1.89, 2.08, 2.08,
2.55, 2.55, 2.93, 3.02, 3.15, 3.34, 3.53, 3.94, 4.19, 4.6, 4.85,
5.04, 5.35, 5.57, 6.02, 6.27, 6.65, 7.02, 7.56, 8.06, 8.06, 8.85,
8.85, 9.7, 9.7, 10.55, 10.55, 11.62, 12.38, 12.98, 13.64, 14.3,
14.93, 15.62, 16.35, 17.35, 18.11, 19.15, 20.19, 21.39, 22.52,
23.5, 24.85, 25.61, 26.68, 26.68, 29.13, 29.13, 31.78, 31.78,
34.2, 34.2, 36.91, 38.33, 39.53, 41.35, 42.93, 44.72, 46.52,
48, 49.57, 50.96, 52.41, 54.27, 55.69, 57.64, 58.96, 60.85, 62.2,
64, 65.48, 65.48, 68.31, 69.86, 71.21, 71.21, 73.73, 75.02, 76.54,
77.45, 78.46, 79.78, 80.63, 81.8, 82.8, 83.81, 84.91, 85.86,
86.68, 87.4, 88.16, 88.54, 89.04, 89.86, 90.52, 90.93, 90.93,
91.81, 92.16, 92.47, 92.47, 93.48, 93.8, 94.27, 94.27, 94.68,
95.02, 95.37, 95.59, 95.94, 96.13, 96.41, 96.66, 96.76, 96.79,
97.01, 97.13, 97.32, 97.45, 97.51, 97.57, 97.57, 97.57, 97.95,
98.05, 98.05, 98.24, 98.36, 98.39, 98.39, 98.61, 98.61, 98.74,
98.77, 98.87, 98.93, 98.99, 99.02, 99.12, 99.21, 99.31, 99.4,
99.43, 99.53, 99.59, 99.59, 99.59, 99.59, 99.62, 99.65, 99.65,
99.65, 99.75, 99.75, 99.75, 99.78, 99.81, 99.84, 99.87, 99.87,
99.87, 99.87, 99.87, 99.87, 99.91, 99.91, 99.91, 99.94, 99.94,
99.94, 99.94, 99.94, 99.94, 99.94, 99.97, 99.97, 99.97, 99.97,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100)), class = "data.frame", row.names = c(NA, -701L))
：
match使用df1$Trait1Percentile <- LookupTable$Trait1Percentiles[match(df1$Trait1Score, LookupTable$Scores)]
head(df1)
# JobNumber Trait1Score Trait2Score Trait1Percentile
#1 634 3.89 4.00 14.08
#2 21 4.39 2.94 68.00
#3 300 4.22 3.17 46.87
#4 797 4.21 3.83 45.61
#5 1112 3.94 4.22 17.23
#6 147 3.90 3.83 14.61
，您需要选择相关列
merge类似地在merge(df1, LookupTable, by.x = 'Trait1Score', by.y = 'Scores')[1:4]
中：
dplyr