计算问题意味着在 R 中使用 tapply()
Problems calculating means using tapply() in R
我正在尝试使用 tapply() 函数计算 data.frame 的均值。
这是我的数据框。
record island locale capture_type age_at_capt date_yyyy_mm_dd sex net mass (g) svl (mm)
6 1939 Big Ambergris Cay ELC recap Adult 2018-03-24 F 740 254
7 1940 Big Ambergris Cay ELC recap Adult 2018-03-24 F 815 270
8 1941 Big Ambergris Cay ELC recap Adult 2018-03-24 F 735 262
9 1942 Big Ambergris Cay ELC recap Adult 2018-03-24 M 1440 330
10 1943 Big Ambergris Cay ELC newcap Adult 2018-03-25 M 1060 284
11 1944 Big Ambergris Cay ELC newcap Adult 2018-03-25 M 810 275
12 1945 Big Ambergris Cay ELC recap Adult 2018-03-25 M 1375 310
13 1946 Big Ambergris Cay ELC recap Adult 2018-03-25 M 1395 325
14 1947 Big Ambergris Cay ELC recap Adult 2018-03-25 F 622 257
15 1948 Big Ambergris Cay ELC recap Adult 2018-03-25 M 1120 294
16 1949 Big Ambergris Cay ELC newcap Adult 2018-03-25 F 690 247
18 1951 Big Ambergris Cay ELC recap Adult 2018-03-26 F 935 274
19 1952 Big Ambergris Cay Calico Jack recap Adult 2018-03-27 M 2505 370
20 1953 Big Ambergris Cay Calico Jack newcap Adult 2018-03-27 F 1110 279
21 1954 Big Ambergris Cay Calico Jack newcap Adult 2018-03-27 F 1590 313
22 1955 Big Ambergris Cay Calico Jack recap Adult 2018-03-27 M 1575 319
23 1956 Big Ambergris Cay Calico Jack newcap Adult 2018-03-27 M 1110 284
24 1957 Big Ambergris Cay Calico Jack recap Adult 2018-03-27 M 2380 357
25 1958 Big Ambergris Cay Calico Jack recap Adult 2018-03-27 M 2080 364
26 1959 Big Ambergris Cay Calico Jack newcap Adult 2018-03-27 F 1010 286
27 1960 Big Ambergris Cay Calico Jack newcap Adult 2018-03-27 M 830 259
28 1961 Big Ambergris Cay Calico Jack newcap Adult 2018-03-27 M 1850 348
29 1962 Big Ambergris Cay Calico Jack recap Adult 2018-03-27 F 1250 296
30 1963 Big Ambergris Cay Calico Jack recap Adult 2018-03-27 F 1075 282
31 1964 Big Ambergris Cay Calico Jack recap Adult 2018-03-28 M 2240 362
32 1965 Big Ambergris Cay Calico Jack recap Adult 2018-03-28 M 1775 338
33 1966 Big Ambergris Cay Calico Jack recap Adult 2018-03-28 F 1420 300
34 1967 Big Ambergris Cay Calico Jack recap Adult 2018-03-28 F 1010 263
35 1968 Big Ambergris Cay Calico Jack recap Adult 2018-03-28 M 2090 372
36 1969 Big Ambergris Cay Calico Jack newcap Adult 2018-03-28 F 1440 304
37 1970 Big Ambergris Cay Calico Jack recap Adult 2018-03-28 M 755 254
38 1971 Big Ambergris Cay Calico Jack newcap Adult 2018-03-28 F 1360 315
40 1973 Big Ambergris Cay Calico Jack recap Adult 2018-03-28 M 2700 371
41 1974 Big Ambergris Cay Calico Jack recap Adult 2018-03-28 M 1820 331
42 1975 Big Ambergris Cay ELC recap Adult 2018-03-29 M 1450 326
43 1976 Big Ambergris Cay ELC recap Adult 2018-03-29 F 790 262
44 1977 Big Ambergris Cay ELC recap Adult 2018-03-29 F 605 246
这是使用 dput()
输出的相同数据集
structure(list(record = c(1939, 1940, 1941, 1942, 1943, 1944,
1945, 1946, 1947, 1948, 1949, 1951, 1952, 1953, 1954, 1955, 1956,
1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967,
1968, 1969, 1970, 1971, 1973, 1974, 1975, 1976, 1977), island = c("Big Ambergris Cay",
"Big Ambergris Cay", "Big Ambergris Cay", "Big Ambergris Cay",
"Big Ambergris Cay", "Big Ambergris Cay", "Big Ambergris Cay",
"Big Ambergris Cay", "Big Ambergris Cay", "Big Ambergris Cay",
"Big Ambergris Cay", "Big Ambergris Cay", "Big Ambergris Cay",
"Big Ambergris Cay", "Big Ambergris Cay", "Big Ambergris Cay",
"Big Ambergris Cay", "Big Ambergris Cay", "Big Ambergris Cay",
"Big Ambergris Cay", "Big Ambergris Cay", "Big Ambergris Cay",
"Big Ambergris Cay", "Big Ambergris Cay", "Big Ambergris Cay",
"Big Ambergris Cay", "Big Ambergris Cay", "Big Ambergris Cay",
"Big Ambergris Cay", "Big Ambergris Cay", "Big Ambergris Cay",
"Big Ambergris Cay", "Big Ambergris Cay", "Big Ambergris Cay",
"Big Ambergris Cay", "Big Ambergris Cay", "Big Ambergris Cay"
), locale = c("ELC", "ELC", "ELC", "ELC", "ELC", "ELC", "ELC",
"ELC", "ELC", "ELC", "ELC", "ELC", "Calico Jack", "Calico Jack",
"Calico Jack", "Calico Jack", "Calico Jack", "Calico Jack", "Calico Jack",
"Calico Jack", "Calico Jack", "Calico Jack", "Calico Jack", "Calico Jack",
"Calico Jack", "Calico Jack", "Calico Jack", "Calico Jack", "Calico Jack",
"Calico Jack", "Calico Jack", "Calico Jack", "Calico Jack", "Calico Jack",
"ELC", "ELC", "ELC"), capture_type = c("recap", "recap", "recap",
"recap", "newcap", "newcap", "recap", "recap", "recap", "recap",
"newcap", "recap", "recap", "newcap", "newcap", "recap", "newcap",
"recap", "recap", "newcap", "newcap", "newcap", "recap", "recap",
"recap", "recap", "recap", "recap", "recap", "newcap", "recap",
"newcap", "recap", "recap", "recap", "recap", "recap"), age_at_capt = c("Adult",
"Adult", "Adult", "Adult", "Adult", "Adult", "Adult", "Adult",
"Adult", "Adult", "Adult", "Adult", "Adult", "Adult", "Adult",
"Adult", "Adult", "Adult", "Adult", "Adult", "Adult", "Adult",
"Adult", "Adult", "Adult", "Adult", "Adult", "Adult", "Adult",
"Adult", "Adult", "Adult", "Adult", "Adult", "Adult", "Adult",
"Adult"), date_yyyy_mm_dd = c("2018-03-24", "2018-03-24", "2018-03-24",
"2018-03-24", "2018-03-25", "2018-03-25", "2018-03-25", "2018-03-25",
"2018-03-25", "2018-03-25", "2018-03-25", "2018-03-26", "2018-03-27",
"2018-03-27", "2018-03-27", "2018-03-27", "2018-03-27", "2018-03-27",
"2018-03-27", "2018-03-27", "2018-03-27", "2018-03-27", "2018-03-27",
"2018-03-27", "2018-03-28", "2018-03-28", "2018-03-28", "2018-03-28",
"2018-03-28", "2018-03-28", "2018-03-28", "2018-03-28", "2018-03-28",
"2018-03-28", "2018-03-29", "2018-03-29", "2018-03-29"), sex = c("F",
"F", "F", "M", "M", "M", "M", "M", "F", "M", "F", "F", "M", "F",
"F", "M", "M", "M", "M", "F", "M", "M", "F", "F", "M", "M", "F",
"F", "M", "F", "M", "F", "M", "M", "M", "F", "F"), `net mass (g)` = c(740,
815, 735, 1440, 1060, 810, 1375, 1395, 622, 1120, 690, 935, 2505,
1110, 1590, 1575, 1110, 2380, 2080, 1010, 830, 1850, 1250, 1075,
2240, 1775, 1420, 1010, 2090, 1440, 755, 1360, 2700, 1820, 1450,
790, 605), `svl (mm)` = c(254, 270, 262, 330, 284, 275, 310,
325, 257, 294, 247, 274, 370, 279, 313, 319, 284, 357, 364, 286,
259, 348, 296, 282, 362, 338, 300, 263, 372, 304, 254, 315, 371,
331, 326, 262, 246)), row.names = c(6L, 7L, 8L, 9L, 10L, 11L,
12L, 13L, 14L, 15L, 16L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L,
26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L,
40L, 41L, 42L, 43L, 44L), class = "data.frame")
我想做的是根据两个变量计算 'net mass (g)' 变量的平均值，每个变量有 2 个因子水平：1)'locale'，水平 "ELC" 和"Calico Jack"; 2) 'sex'，等级 "M" 和 "F"。换句话说，我希望最终得到 4 个平均值。这是我正在使用的 tapply() 函数（我已经成功地在其他数据库上使用了这个函数）。
MeanMass.2018 <- tapply(Records.2018.BA.ad$`net mass (g)`,
INDEX = Records.2018.BA.ad$locale : Records.2018.BA.ad$sex,
FUN = mean)
不幸的是我没有得到平均值。相反，出现了这个令人讨厌的错误消息，我真的很沮丧，因为我无法弄清楚我在处理这个数据集时做错了什么。
Error in Records.2018.BA.ad$locale:Records.2018.BA.ad$sex :
NA/NaN argument
In addition: Warning messages:
1: In Records.2018.BA.ad$locale:Records.2018.BA.ad$sex :
numerical expression has 37 elements: only the first used
2: In Records.2018.BA.ad$locale:Records.2018.BA.ad$sex :
numerical expression has 37 elements: only the first used
3: In tapply(Records.2018.BA.ad$`net mass (g)`, INDEX = Records.2018.BA.ad$locale:Records.2018.BA.ad$sex, :
NAs introduced by coercion
4: In tapply(Records.2018.BA.ad$`net mass (g)`, INDEX = Records.2018.BA.ad$locale:Records.2018.BA.ad$sex, :
NAs introduced by coercion
如有任何帮助，我们将不胜感激。
干杯
我稍微修改了您的示例数据框，但我认为我的最后一行 aggregate() 函数将带您到达所需位置：
df <- read.table(text = "
record island locale capture_type age_at_capt date_yyyy_mm_dd sex netmass svl
1939 BigAmbergrisCay ELC recap Adult 2018-03-24 F 740 254
1940 BigAmbergrisCay ELC recap Adult 2018-03-24 F 815 270
1941 BigAmbergrisCay ELC recap Adult 2018-03-24 F 735 262
1942 BigAmbergrisCay ELC recap Adult 2018-03-24 M 1440 330
1943 BigAmbergrisCay ELC newcap Adult 2018-03-25 M 1060 284
1944 BigAmbergrisCay ELC newcap Adult 2018-03-25 M 810 275
", header = T)
df <- rbind(df, df)
df$locale <- as.character(df$locale)
df$locale[7:12] <- "other locale"
df$netmass[7:12] <- seq(1500,2000,100)
aggregate(netmass ~ locale + sex, df, mean)
locale sex netmass
1 ELC F 763.3333
2 otherlocale F 1600.0000
3 ELC M 1103.3333
4 otherlocale M 1900.0000
点击：
tapply(df$netmass, list(df$locale, df$sex), mean)
或
with(df, tapply(netmass, list(locale, sex), mean))
两者都给出：
F M
ELC 763.3333 1103.333
other locale 1600.0000 1900.000
我正在尝试使用 tapply() 函数计算 data.frame 的均值。
这是我的数据框。
record island locale capture_type age_at_capt date_yyyy_mm_dd sex net mass (g) svl (mm)
6 1939 Big Ambergris Cay ELC recap Adult 2018-03-24 F 740 254
7 1940 Big Ambergris Cay ELC recap Adult 2018-03-24 F 815 270
8 1941 Big Ambergris Cay ELC recap Adult 2018-03-24 F 735 262
9 1942 Big Ambergris Cay ELC recap Adult 2018-03-24 M 1440 330
10 1943 Big Ambergris Cay ELC newcap Adult 2018-03-25 M 1060 284
11 1944 Big Ambergris Cay ELC newcap Adult 2018-03-25 M 810 275
12 1945 Big Ambergris Cay ELC recap Adult 2018-03-25 M 1375 310
13 1946 Big Ambergris Cay ELC recap Adult 2018-03-25 M 1395 325
14 1947 Big Ambergris Cay ELC recap Adult 2018-03-25 F 622 257
15 1948 Big Ambergris Cay ELC recap Adult 2018-03-25 M 1120 294
16 1949 Big Ambergris Cay ELC newcap Adult 2018-03-25 F 690 247
18 1951 Big Ambergris Cay ELC recap Adult 2018-03-26 F 935 274
19 1952 Big Ambergris Cay Calico Jack recap Adult 2018-03-27 M 2505 370
20 1953 Big Ambergris Cay Calico Jack newcap Adult 2018-03-27 F 1110 279
21 1954 Big Ambergris Cay Calico Jack newcap Adult 2018-03-27 F 1590 313
22 1955 Big Ambergris Cay Calico Jack recap Adult 2018-03-27 M 1575 319
23 1956 Big Ambergris Cay Calico Jack newcap Adult 2018-03-27 M 1110 284
24 1957 Big Ambergris Cay Calico Jack recap Adult 2018-03-27 M 2380 357
25 1958 Big Ambergris Cay Calico Jack recap Adult 2018-03-27 M 2080 364
26 1959 Big Ambergris Cay Calico Jack newcap Adult 2018-03-27 F 1010 286
27 1960 Big Ambergris Cay Calico Jack newcap Adult 2018-03-27 M 830 259
28 1961 Big Ambergris Cay Calico Jack newcap Adult 2018-03-27 M 1850 348
29 1962 Big Ambergris Cay Calico Jack recap Adult 2018-03-27 F 1250 296
30 1963 Big Ambergris Cay Calico Jack recap Adult 2018-03-27 F 1075 282
31 1964 Big Ambergris Cay Calico Jack recap Adult 2018-03-28 M 2240 362
32 1965 Big Ambergris Cay Calico Jack recap Adult 2018-03-28 M 1775 338
33 1966 Big Ambergris Cay Calico Jack recap Adult 2018-03-28 F 1420 300
34 1967 Big Ambergris Cay Calico Jack recap Adult 2018-03-28 F 1010 263
35 1968 Big Ambergris Cay Calico Jack recap Adult 2018-03-28 M 2090 372
36 1969 Big Ambergris Cay Calico Jack newcap Adult 2018-03-28 F 1440 304
37 1970 Big Ambergris Cay Calico Jack recap Adult 2018-03-28 M 755 254
38 1971 Big Ambergris Cay Calico Jack newcap Adult 2018-03-28 F 1360 315
40 1973 Big Ambergris Cay Calico Jack recap Adult 2018-03-28 M 2700 371
41 1974 Big Ambergris Cay Calico Jack recap Adult 2018-03-28 M 1820 331
42 1975 Big Ambergris Cay ELC recap Adult 2018-03-29 M 1450 326
43 1976 Big Ambergris Cay ELC recap Adult 2018-03-29 F 790 262
44 1977 Big Ambergris Cay ELC recap Adult 2018-03-29 F 605 246
这是使用 dput()
输出的相同数据集structure(list(record = c(1939, 1940, 1941, 1942, 1943, 1944,
1945, 1946, 1947, 1948, 1949, 1951, 1952, 1953, 1954, 1955, 1956,
1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967,
1968, 1969, 1970, 1971, 1973, 1974, 1975, 1976, 1977), island = c("Big Ambergris Cay",
"Big Ambergris Cay", "Big Ambergris Cay", "Big Ambergris Cay",
"Big Ambergris Cay", "Big Ambergris Cay", "Big Ambergris Cay",
"Big Ambergris Cay", "Big Ambergris Cay", "Big Ambergris Cay",
"Big Ambergris Cay", "Big Ambergris Cay", "Big Ambergris Cay",
"Big Ambergris Cay", "Big Ambergris Cay", "Big Ambergris Cay",
"Big Ambergris Cay", "Big Ambergris Cay", "Big Ambergris Cay",
"Big Ambergris Cay", "Big Ambergris Cay", "Big Ambergris Cay",
"Big Ambergris Cay", "Big Ambergris Cay", "Big Ambergris Cay",
"Big Ambergris Cay", "Big Ambergris Cay", "Big Ambergris Cay",
"Big Ambergris Cay", "Big Ambergris Cay", "Big Ambergris Cay",
"Big Ambergris Cay", "Big Ambergris Cay", "Big Ambergris Cay",
"Big Ambergris Cay", "Big Ambergris Cay", "Big Ambergris Cay"
), locale = c("ELC", "ELC", "ELC", "ELC", "ELC", "ELC", "ELC",
"ELC", "ELC", "ELC", "ELC", "ELC", "Calico Jack", "Calico Jack",
"Calico Jack", "Calico Jack", "Calico Jack", "Calico Jack", "Calico Jack",
"Calico Jack", "Calico Jack", "Calico Jack", "Calico Jack", "Calico Jack",
"Calico Jack", "Calico Jack", "Calico Jack", "Calico Jack", "Calico Jack",
"Calico Jack", "Calico Jack", "Calico Jack", "Calico Jack", "Calico Jack",
"ELC", "ELC", "ELC"), capture_type = c("recap", "recap", "recap",
"recap", "newcap", "newcap", "recap", "recap", "recap", "recap",
"newcap", "recap", "recap", "newcap", "newcap", "recap", "newcap",
"recap", "recap", "newcap", "newcap", "newcap", "recap", "recap",
"recap", "recap", "recap", "recap", "recap", "newcap", "recap",
"newcap", "recap", "recap", "recap", "recap", "recap"), age_at_capt = c("Adult",
"Adult", "Adult", "Adult", "Adult", "Adult", "Adult", "Adult",
"Adult", "Adult", "Adult", "Adult", "Adult", "Adult", "Adult",
"Adult", "Adult", "Adult", "Adult", "Adult", "Adult", "Adult",
"Adult", "Adult", "Adult", "Adult", "Adult", "Adult", "Adult",
"Adult", "Adult", "Adult", "Adult", "Adult", "Adult", "Adult",
"Adult"), date_yyyy_mm_dd = c("2018-03-24", "2018-03-24", "2018-03-24",
"2018-03-24", "2018-03-25", "2018-03-25", "2018-03-25", "2018-03-25",
"2018-03-25", "2018-03-25", "2018-03-25", "2018-03-26", "2018-03-27",
"2018-03-27", "2018-03-27", "2018-03-27", "2018-03-27", "2018-03-27",
"2018-03-27", "2018-03-27", "2018-03-27", "2018-03-27", "2018-03-27",
"2018-03-27", "2018-03-28", "2018-03-28", "2018-03-28", "2018-03-28",
"2018-03-28", "2018-03-28", "2018-03-28", "2018-03-28", "2018-03-28",
"2018-03-28", "2018-03-29", "2018-03-29", "2018-03-29"), sex = c("F",
"F", "F", "M", "M", "M", "M", "M", "F", "M", "F", "F", "M", "F",
"F", "M", "M", "M", "M", "F", "M", "M", "F", "F", "M", "M", "F",
"F", "M", "F", "M", "F", "M", "M", "M", "F", "F"), `net mass (g)` = c(740,
815, 735, 1440, 1060, 810, 1375, 1395, 622, 1120, 690, 935, 2505,
1110, 1590, 1575, 1110, 2380, 2080, 1010, 830, 1850, 1250, 1075,
2240, 1775, 1420, 1010, 2090, 1440, 755, 1360, 2700, 1820, 1450,
790, 605), `svl (mm)` = c(254, 270, 262, 330, 284, 275, 310,
325, 257, 294, 247, 274, 370, 279, 313, 319, 284, 357, 364, 286,
259, 348, 296, 282, 362, 338, 300, 263, 372, 304, 254, 315, 371,
331, 326, 262, 246)), row.names = c(6L, 7L, 8L, 9L, 10L, 11L,
12L, 13L, 14L, 15L, 16L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L,
26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L,
40L, 41L, 42L, 43L, 44L), class = "data.frame")
我想做的是根据两个变量计算 'net mass (g)' 变量的平均值，每个变量有 2 个因子水平：1)'locale'，水平 "ELC" 和"Calico Jack"; 2) 'sex'，等级 "M" 和 "F"。换句话说，我希望最终得到 4 个平均值。这是我正在使用的 tapply() 函数（我已经成功地在其他数据库上使用了这个函数）。
MeanMass.2018 <- tapply(Records.2018.BA.ad$`net mass (g)`,
INDEX = Records.2018.BA.ad$locale : Records.2018.BA.ad$sex,
FUN = mean)
不幸的是我没有得到平均值。相反，出现了这个令人讨厌的错误消息，我真的很沮丧，因为我无法弄清楚我在处理这个数据集时做错了什么。
Error in Records.2018.BA.ad$locale:Records.2018.BA.ad$sex :
NA/NaN argument
In addition: Warning messages:
1: In Records.2018.BA.ad$locale:Records.2018.BA.ad$sex :
numerical expression has 37 elements: only the first used
2: In Records.2018.BA.ad$locale:Records.2018.BA.ad$sex :
numerical expression has 37 elements: only the first used
3: In tapply(Records.2018.BA.ad$`net mass (g)`, INDEX = Records.2018.BA.ad$locale:Records.2018.BA.ad$sex, :
NAs introduced by coercion
4: In tapply(Records.2018.BA.ad$`net mass (g)`, INDEX = Records.2018.BA.ad$locale:Records.2018.BA.ad$sex, :
NAs introduced by coercion
如有任何帮助，我们将不胜感激。
干杯
我稍微修改了您的示例数据框，但我认为我的最后一行 aggregate() 函数将带您到达所需位置：
df <- read.table(text = "
record island locale capture_type age_at_capt date_yyyy_mm_dd sex netmass svl
1939 BigAmbergrisCay ELC recap Adult 2018-03-24 F 740 254
1940 BigAmbergrisCay ELC recap Adult 2018-03-24 F 815 270
1941 BigAmbergrisCay ELC recap Adult 2018-03-24 F 735 262
1942 BigAmbergrisCay ELC recap Adult 2018-03-24 M 1440 330
1943 BigAmbergrisCay ELC newcap Adult 2018-03-25 M 1060 284
1944 BigAmbergrisCay ELC newcap Adult 2018-03-25 M 810 275
", header = T)
df <- rbind(df, df)
df$locale <- as.character(df$locale)
df$locale[7:12] <- "other locale"
df$netmass[7:12] <- seq(1500,2000,100)
aggregate(netmass ~ locale + sex, df, mean)
locale sex netmass
1 ELC F 763.3333
2 otherlocale F 1600.0000
3 ELC M 1103.3333
4 otherlocale M 1900.0000
点击：
tapply(df$netmass, list(df$locale, df$sex), mean)
或
with(df, tapply(netmass, list(locale, sex), mean))
两者都给出：
F M
ELC 763.3333 1103.333
other locale 1600.0000 1900.000