分组后所有raws的值相同吗？
分组后所有raws的值相同吗？
提问于 2022-07-15 03:36:46
在做了一些转换之后，我得到了重复的数据。
分组：
paid <- df%>%
group_by(date) %>%
summarise(sessions = sum(sessions),
revenue_usd = sum(transaction_revenue)/3.8,
bounceRate = bounces/sessions,
transactions = sum(transactions))原始数据：
df <- structure(list(date = structure(c(19186, 19186, 19186, 19186,
19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186,
19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186,
19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186,
19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186,
19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186,
19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186,
19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186,
19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186,
19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186,
19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186,
19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186,
19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186,
19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186,
19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186,
19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186,
19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186,
19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186,
19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186,
19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186,
19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186,
19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186, 19186,
19186, 19186, 19186, 19186, 19186, 19186, 19186), class = "Date"),
source = c("(direct)", "(not set)", "127.0.0.1:20489", "13d612549ae98efa4eebca49fbda5aa9.safeframe.googlesyndication.com",
"214791a1533c2a50e91a0172b59da402.safeframe.googlesyndication.com",
"408b8fdfaa1d06bb140607437bd90f10.safeframe.googlesyndication.com",
"5e1452d421694493662f87729e4e130d.safeframe.googlesyndication.com",
"8042dc59e10779732adc12d6359c3ab9.safeframe.googlesyndication.com",
"84c4aa5f9449946d1cb5812ca3ea633a.safeframe.googlesyndication.com",
"89a3e733827acf8133fab396ec550646.safeframe.googlesyndication.com",
"9ad91f3bc7d10dce0ba6fb1c18d32c0e.safeframe.googlesyndication.com",
"9d81febecab8a704ce297781effecc07.safeframe.googlesyndication.com",
"accounts.google.com", "actitudfem.com", "admin.pagoefectivo.pe",
"ads.us.criteo.com", "adsintegrity.net", "anmosugoi.com",
"beneficios.bbva.pe", "biggestchef.com", "bing", "content.jwplatform.com",
"criteo", "criteo", "Criteo", "Criteo,criteo", "cse.google.com",
"cuotealo.viabcp.com", "cyberwow.pe", "diariocorreo.pe",
"dinersclub.pe", "docs.google.com", "duckduckgo", "ecosia.org",
"edmmkt", "elcomercio", "elcomercio", "estudiantes.samsung.com.pe",
"facebook", "facebook", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network", "facebook-network",
"facebook-network", "facebook-network"), medium = c("(none)",
"(not set)", "referral", "referral", "referral", "referral",
"referral", "referral", "referral", "referral", "referral",
"referral", "referral", "referral", "referral", "referral",
"referral", "referral", "referral", "referral", "organic",
"referral", "consideration", "retargeting", "(not set)",
"consideration", "referral", "referral", "referral", "referral",
"referral", "referral", "organic", "organic", "image", "cpm",
"cpm", "referral", "cpm", "social", "(not set)", "cpa", "cpa",
"cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa",
"cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa",
"cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa",
"cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa",
"cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa",
"cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa",
"cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa",
"cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa",
"cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa",
"cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa",
"cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa",
"cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa",
"cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa",
"cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa",
"cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa",
"cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa",
"cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa", "cpa",
"cpa", "cpa", "cpa", "cpa"), sessions = c(1746, 4, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 40, 1, 1, 13, 1, 40, 1,
3636, 2921, 4, 1, 4, 54, 20, 1, 66, 1, 1, 3, 1, 1, 29, 9,
1, 86, 75, 1, 1, 3, 1, 1, 7, 1, 3, 1, 1, 3, 1, 2, 3, 1, 1,
2, 1, 4, 6, 1, 2, 6, 12, 5, 73, 2, 7, 1, 131, 22, 5, 14,
69, 8, 1, 4, 72, 2, 3, 1, 6, 21, 20, 72, 17, 7, 1, 15, 218,
148, 278, 159, 30, 2, 373, 1, 1, 3, 5, 1, 3, 1, 1, 1, 1,
1, 5, 1, 1, 2, 2, 2, 2, 1, 2, 12, 1, 1, 2, 1, 1, 1, 2, 1,
144, 14, 1, 4, 54, 1, 1, 2, 2, 1, 1, 1, 2, 1, 1, 1, 5, 1,
1, 5, 1, 10, 156, 2, 9, 2, 19, 34, 179, 1, 2, 4, 447, 1,
4, 2, 321, 1, 1, 5, 163, 3, 4, 318, 6, 2, 9, 162, 2, 59,
1, 5, 414, 1, 4, 3, 312, 7, 701, 2, 2, 2, 147, 1, 4, 30,
137, 28, 1, 14, 1, 1, 1, 451), transactions = c(17, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0,
0, 2, 0, 0, 0, 29, 0, 0, 3, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 3), transaction_revenue = c(44183, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1115.52, 0, 0, 1375.67,
0, 0, 0, 0, 4198, 0, 0, 0, 59269, 0, 0, 6147, 0, 0, 0, 0,
0, 0, 1999, 0, 599, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 2599, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 4199, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2599, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7397), bounces = c(1278,
4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 8, 1, 1, 6, 1,
23, 1, 3294, 2333, 2, 1, 3, 4, 12, 0, 32, 1, 1, 3, 1, 1,
29, 7, 1, 66, 49, 0, 1, 3, 1, 1, 5, 1, 0, 0, 1, 2, 1, 2,
3, 0, 1, 2, 1, 4, 6, 0, 1, 4, 9, 5, 61, 2, 6, 1, 115, 20,
4, 12, 63, 7, 1, 4, 62, 2, 2, 1, 5, 17, 16, 59, 17, 6, 1,
10, 194, 132, 235, 136, 27, 2, 274, 1, 1, 3, 4, 1, 3, 1,
1, 0, 1, 1, 3, 1, 1, 1, 2, 1, 2, 0, 2, 7, 0, 1, 1, 1, 1,
1, 1, 1, 129, 12, 1, 4, 49, 0, 0, 1, 1, 0, 1, 0, 1, 1, 1,
0, 5, 1, 1, 2, 1, 3, 133, 2, 5, 2, 16, 27, 150, 0, 1, 4,
377, 1, 4, 1, 254, 1, 1, 3, 120, 3, 3, 248, 6, 1, 9, 123,
2, 47, 1, 4, 340, 1, 4, 3, 244, 7, 557, 2, 2, 2, 117, 1,
4, 23, 100, 22, 1, 12, 0, 1, 0, 325)), totals = list(list(
sessions = "89600", transactions = "247", transactionRevenue = "547126.09",
bounces = "73354")), minimums = list(list(sessions = "1",
transactions = "0", transactionRevenue = "0.0", bounces = "0")), maximums = list(
list(sessions = "8355", transactions = "65", transactionRevenue = "145010.41",
bounces = "7614")), isDataGolden = TRUE, rowCount = 737L, row.names = c(NA,
200L), class = "data.frame")sessioninfo:
> sessionInfo()
R version 4.2.1 (2022-06-23 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 22000)
Matrix products: default
locale:
[1] LC_COLLATE=Spanish_Peru.utf8 LC_CTYPE=Spanish_Peru.utf8 LC_MONETARY=Spanish_Peru.utf8
[4] LC_NUMERIC=C LC_TIME=Spanish_Peru.utf8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] openxlsx_4.2.5 janitor_2.1.0 forcats_0.5.1 stringr_1.4.0 dplyr_1.0.9
[6] purrr_0.3.4 readr_2.1.2 tidyr_1.2.0 tibble_3.1.7 ggplot2_3.3.6
[11] tidyverse_1.3.1 googleAnalyticsR_1.0.1
loaded via a namespace (and not attached):
[1] Rcpp_1.0.8.3 lubridate_1.8.0 assertthat_0.2.1 digest_0.6.29
[5] utf8_1.2.2 R6_2.5.1 cellranger_1.1.0 backports_1.4.1
[9] reprex_2.0.1 httr_1.4.3 pillar_1.7.0 rlang_1.0.3
[13] curl_4.3.2 readxl_1.4.0 rstudioapi_0.13 whisker_0.4
[17] googleAuthR_2.0.0 munsell_0.5.0 broom_1.0.0 compiler_4.2.1
[21] modelr_0.1.8 askpass_1.1 pkgconfig_2.0.3 openssl_2.0.2
[25] tidyselect_1.1.2 fansi_1.0.3 crayon_1.5.1 tzdb_0.3.0
[29] dbplyr_2.2.1 withr_2.5.0 rappdirs_0.3.3 grid_4.2.1
[33] jsonlite_1.8.0 gtable_0.3.0 lifecycle_1.0.1 DBI_1.1.3
[37] magrittr_2.0.3 scales_1.2.0 zip_2.2.0 cli_3.3.0
[41] stringi_1.7.6 cachem_1.0.6 fs_1.5.2 snakecase_0.11.0
[45] xml2_1.3.3 ellipsis_0.3.2 generics_0.1.3 vctrs_0.4.1
[49] tools_4.2.1 measurementProtocol_0.1.0 glue_1.6.2 hms_1.1.1
[53] fastmap_1.1.0 colorspace_2.0-3 gargle_1.2.0 rvest_1.0.2
[57] memoise_2.0.1 haven_2.5.0 usethis_2.1.6 Stack Overflow用户
发布于 2022-07-15 05:31:52
我从我身边做了测试，结果和你的一样。我很惊讶，并开始研究它。这就是我发现的，
列bounceRate的计算没有任何聚合函数，它只是一个简单的除法，应该在行级发生/执行，并且由于没有给出用于汇总的函数，结果仍停留在行级。
让我解释一下，
paid <- df%>%
group_by(date) %>%
summarise(sessions = sum(sessions),
revenue_usd = sum(transaction_revenue)/3.8,
bounceRate = bounces/sessions,
transactions = sum(transactions))这段代码的结果是所有行都完好无损，因为bounceRate = result /sessions是行操作。
如果您注释本行并计算，这将将数据汇总为单行，因为只有一个日期2022-07-13。
paid <- df%>%
group_by(date) %>%
summarise(sessions = sum(sessions),
revenue_usd = sum(transaction_revenue)/3.8,
# bounceRate = bounces/sessions,
transactions = sum(transactions))所以在我看来，你可以在这个比率上使用任何一个和，如果你觉得它不正确，你可以先总结一下，然后取这个比率。我的建议是在总结后采用第二种方法。我把下面这两个代码，
批准01：
paid <- df%>%
group_by(date) %>%
summarise(sessions = sum(sessions),
revenue_usd = sum(transaction_revenue)/3.8,
bounceRate = sum(bounces/sessions),
transactions = sum(transactions))这会给你结果
约02：
paid <- df%>%
group_by(date) %>%
summarise(sessions = sum(sessions),
revenue_usd = sum(transaction_revenue)/3.8,
transactions = sum(transactions),
total_bounces = sum(bounces),
total_sessions = sum(sessions)) %>%
mutate(bounceRate = total_bounces/total_sessions)这将导致以下结果，我认为这是比较合适的。
如果这解决了您的问题，喜欢/向上投票。编码愉快！
页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/72988803
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