library(tidyverse)
## -- Attaching packages ---- tidyverse 1.3.0 --
## √ ggplot2 3.3.0 √ purrr 0.3.3
## √ tibble 2.1.3 √ dplyr 0.8.5
## √ tidyr 1.0.2 √ stringr 1.4.0
## √ readr 1.3.1 √ forcats 0.5.0
## -- Conflicts ------- tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
library(purrr)
library(readxl)
library(here)
## here() starts at D:/RBookLearning/Data-Science-and-Economics
library(writexl)
library(furrr)
## Loading required package: future
library(tictoc)
data <- tibble(x = 1:60,
y = 2 + x + rnorm(60))
data %>%
ggplot(aes(x,y)) +
geom_point() +
geom_smooth(method = "lm")
## `geom_smooth()` using formula 'y ~ x'
x = 1:10
map(x,function(x){
return(x)
})->df
df # 最终形成一个列表
## [[1]]
## [1] 1
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## [1] 2
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## [1] 3
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## [1] 4
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## [1] 5
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## [1] 6
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## [1] 9
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df %>% bind_cols()
## # A tibble: 1 x 10
## V1 V2 V3 V4 V5 V6 V7 V8 V9 V10
## <int> <int> <int> <int> <int> <int> <int> <int> <int> <int>
## 1 1 2 3 4 5 6 7 8 9 10
x <- as.character(1:100)
x
## [1] "1" "2" "3" "4" "5" "6" "7" "8" "9" "10" "11" "12"
## [13] "13" "14" "15" "16" "17" "18" "19" "20" "21" "22" "23" "24"
## [25] "25" "26" "27" "28" "29" "30" "31" "32" "33" "34" "35" "36"
## [37] "37" "38" "39" "40" "41" "42" "43" "44" "45" "46" "47" "48"
## [49] "49" "50" "51" "52" "53" "54" "55" "56" "57" "58" "59" "60"
## [61] "61" "62" "63" "64" "65" "66" "67" "68" "69" "70" "71" "72"
## [73] "73" "74" "75" "76" "77" "78" "79" "80" "81" "82" "83" "84"
## [85] "85" "86" "87" "88" "89" "90" "91" "92" "93" "94" "95" "96"
## [97] "97" "98" "99" "100"
tic()
map(x,function(x){
write_xlsx(data,path = str_c(here::here(),"/R高级编程","/data/",x,".xlsx"))
})
toc()
x <- as.character(1:100)
tic()
map(x,function(x){
data <- read_excel(str_c(here::here(),"/R高级编程/data/",x,".xlsx"))
return(data)
})->df
toc()
## 1.36 sec elapsed
Great!!!
df %>%
bind_rows() %>%
datatable()
\[ y = 2 + x + rnorm(60) \]
df %>%
bind_rows() %>%
group_by(x) %>%
summarise(mean_y = mean(y))->df1
df1 %>%
ggplot(aes(x,mean_y)) +
geom_point() +
geom_smooth(method = "lm")
## `geom_smooth()` using formula 'y ~ x'