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Let’s say I uploaded a dataset to R.

#install.packages("readr")
library(readr) 
github="https://raw.githubusercontent.com/agronomy4future/raw_data_practice/main/soybean_yield.csv" 

dataA=data.frame(read_csv(url(github), show_col_types=FALSE))

dataA
   season    crop plot treatment grain_yield
1    2023 Soybean    1       tr1        32.2
2    2023 Soybean    1       tr2         5.0
3    2023 Soybean    1       tr3         4.3
4    2023 Soybean    1       tr3         1.0
5    2023 Soybean    1       tr5         8.7
6    2023 Soybean    2       tr1        25.6
7    2023 Soybean    2       tr2        35.7
8    2023 Soybean    2       tr3        29.2
9    2023 Soybean    2       tr3        39.9
10   2023 Soybean    2       tr5        20.7
11   2023 Soybean    3       tr1        15.5
12   2023 Soybean    3       tr2        23.2
13   2023 Soybean    3       tr3        44.6
14   2023 Soybean    3       tr3        45.0
15   2023 Soybean    3       tr5        32.4
16   2023 Soybean    4       tr1        20.5
17   2023 Soybean    4       tr2        35.2
18   2023 Soybean    4       tr3        37.3
19   2023 Soybean    4       tr3         9.6
20   2023 Soybean    4       tr5        16.8
21   2023 Soybean    5   control       103.2
22   2023 Soybean    6   control        60.8
23   2023 Soybean    7   control        33.0
24   2023 Soybean    8   control        66.2

Now, I want to save this data as code so that I can store it in my web note. This is because it would be difficult to find the original dataset after a long time. Therefore, I want to save it as text code in a list on my web note.

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1) using dput()

First, we can use dput() function.

dput(dataA)

structure(list(season = c(2023, 2023, 2023, 2023, 2023, 2023, 
2023, 2023, 2023, 2023, 2023, 2023, 2023, 2023, 2023, 2023, 2023, 
2023, 2023, 2023, 2023, 2023, 2023, 2023), crop = c("Soybean", 
"Soybean", "Soybean", "Soybean", "Soybean", "Soybean", "Soybean", 
"Soybean", "Soybean", "Soybean", "Soybean", "Soybean", "Soybean", 
"Soybean", "Soybean", "Soybean", "Soybean", "Soybean", "Soybean", 
"Soybean", "Soybean", "Soybean", "Soybean", "Soybean"), plot = c(1, 
1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 5, 6, 
7, 8), treatment = c("tr1", "tr2", "tr3", "tr3", "tr5", "tr1", 
"tr2", "tr3", "tr3", "tr5", "tr1", "tr2", "tr3", "tr3", "tr5", 
"tr1", "tr2", "tr3", "tr3", "tr5", "control", "control", "control", 
"control"), grain_yield = c(32.2, 5, 4.3, 1, 8.7, 25.6, 35.7, 
29.2, 39.9, 20.7, 15.5, 23.2, 44.6, 45, 32.4, 20.5, 35.2, 37.3, 
9.6, 16.8, 103.2, 60.8, 33, 66.2)), class = "data.frame", row.names = c(NA, 
-24L))

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2) using datapasta()

Second, we can use datapasta() function

#install.packages("datapasta")
library(datapasta)

datapasta::df_paste(dataA)

data.frame(
  stringsAsFactors=FALSE,
            season=c(2023,2023,2023,2023,2023,
                     2023,2023,2023,2023,2023,2023,2023,2023,2023,2023,
                     2023,2023,2023,2023,2023,2023,2023,2023,2023),
            crop=c("Soybean","Soybean","Soybean",
                   "Soybean","Soybean","Soybean","Soybean","Soybean",
                   "Soybean","Soybean","Soybean","Soybean","Soybean",
                   "Soybean","Soybean","Soybean","Soybean","Soybean",
                   "Soybean","Soybean","Soybean","Soybean","Soybean",
                   "Soybean"),
            plot=c(1,1,1,1,1,2,2,2,2,2,3,3,3,3,3,4,4,4,4,4,5,6,7,8),
            treatment=c("tr1","tr2","tr3","tr3","tr5","tr1","tr2",
                        "tr3","tr3","tr5","tr1","tr2","tr3","tr3",
                        "tr5","tr1","tr2","tr3","tr3","tr5",
                        "control","control","control","control"),
             grain_yield=c(32.2,5,4.3,1,8.7,25.6,35.7,29.2,39.9,20.7,
                           15.5,23.2,44.6,45,32.4,20.5,35.2,37.3,9.6,
                           16.8,103.2,60.8,33,66.2)
)

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3) using constructive()

This is a great package from https://cynkra.github.io/constructive. The best thing about this package is that the code is simplified by using rep().

#install.packages("remotes")
#install.packages("constructive")
#remotes::install_github("cynkra/constructive")
library(remote)

constructive::construct(dataA)

data.frame(
  season=rep(2023, 24L),
  crop=rep("Soybean", 24L),
  plot=rep(seq(1, 8, by=1), rep(c(5L, 1L), each=4L)),
  treatment=c("tr1", "tr2", "tr3", "tr3", "tr5", "tr1", "tr2",
              "tr3", "tr3", "tr5", "tr1", "tr2", "tr3", "tr3",
              "tr5", "tr1", "tr2", "tr3", "tr3", "tr5", "control",
              "control", "control", "control"),
  grain_yield=c(32.2, 5, 4.3, 1, 8.7, 25.6, 35.7, 29.2, 39.9, 20.7,
                15.5, 23.2, 44.6, 45, 32.4, 20.5, 35.2, 37.3, 9.6,
                16.8, 103.2, 60.8, 33, 66.2)
)

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Reference
https://stackoverflow.com/questions/77834006/how-to-convert-uploaded-data-table-to-data-frame-code-in-r

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Code summary
https://github.com/agronomy4future/r_code/blob/main/How_to_convert_uploaded_data_table_to_data_frame()_code_in_R%3F.ipynb

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