Gini_region |> filter(地区 %in% c("北京","上海","广东","黑龙江")) |> plot_gini(年份, Gini系数, 地区) 可见,越发达的地区收入越不平等! 想写出这样简洁、优雅的代码,学习全网最新的 R 语言编程技术,掌握真正的数据编程思维: 更多内容参阅: 张敬信:《R语言编程:基于tidyverse》同类资源汇总140 赞同 ...
starships <list>, and abbreviated variable names ## # 1: hair_color, 2: skin_color, 3: eye_color, 4: birth_year, 5: homeworld #多个条件用","隔开 df_dup %>% filter(sex == "male", #筛选条件一 (skin_color == "pale" | hair_color == "none"))#条件二 ## # A tibble...
filter_if(.tbl,predicate,vars_predicate)用的比较多 参数解释: .tbl:数据框 .predicate:应用在列上的函数,一般作为列的选择条件 .vars_predicate:应用在一行上的函数,通过all_vars(),any_vars() 返回值决定是否选择该行。mtcars %>% filter_if(~all(floor(.)==.),all_vars(.!=0)) #这里floor是向下...
rm = TRUE)) %>% filter(n > 1, mass > 50) ## # A tibble: 8 x 3 ## species n mass ## <chr> <int> <dbl> ## 1 Droid 6 69.8 ## 2 Gungan 3 74 ## 3 Human 35 82.8 ## 4 Kaminoan 2 88 ## 5 Mirialan 2 53.1 ## 6 Twi'lek 2 55 ## 7 Wookiee 2 124 ## 8 Zab...
filter(): Filter out certain rows that meet your criteria(s) group_by(): Group different observations together such that the original dataset does not change. Only the way it is represented is changed in the form of a list summarise(): Summarise any of the above functions ...
bug detected in an Rmd, If the filter (from dplyr) generates 0 lines with one column typed hms #116 opened Mar 31, 2023 by Cervangirard Tools for decomposing a datetime into date + hms + timezone and back #113 opened Jan 30, 2023 by krlmlr 1 Inconsistency between tibble and ...
5 5 89*90>df_3 %>% filter(str_detect(ab,"2$"))id ab 1 1 81*82#统计匹配的数量>x <- c("apple","banana","pear")>str_count(x,"an")[1] 0 2 0#统计ab列中8的次数。>df_3 %>% mutate( count = str_count(ab,"8"))id ab count ...
# pick cases based on their values using filter()filter(stocks_value, X >20) R # add new variables that are functions of existing variables using mutate()library(lubridate) stocks_wday <- stocks %>% select(time:Z) %>% mutate( weekday = wday(time) ) stocks_wday ...
filter()picks cases based on their values. summarise()reduces multiple values down to a single summary. arrange()changes the ordering of the rows. These all combine naturally withgroup_by()which allows you to perform any operation “by group”. You can learn more about them invignette("dplyr...
三个逻辑操作符 &,|,!,可以运用在filter()中实现多条件筛选jan1 <- filter(flights, month == 1, day == 1) filter(flights, month == 11 | month == 12) 按列(变量)截选 select()# Select columns by name select(flights, year, month, day) # 用冒号选取两变量间所有变量 select(flights, ...