如何读取 r 中的列表列表

Question

我有一个这样的 txt 文件： [[[seller_id","product_id","buyer_id","sale_date","数量","价格"],[7,11,49, "2019-01-21",5,3330],[13,32,6,"2019-02-10",9,1089],[50,47,4,"2019-01-06",1, 1343],[1,22,2,"2019-03-03",9,7677]]

我想通过 R 作为 table 像这样阅读它：

seller_id	product_id	buyer_id	sale_date	quantity	price
7	11	49	2019-01-21	5	3330
13	32	6	2019-02-10	9	1089
50	47	4	2019-01-06	1	1343
1	22	2	2019-03-03	9	7677

如何编写正确的R代码？非常感谢您的宝贵时间。

Answer 1

更简单的选择是 fromJSON

library(jsonlite)
library(janitor)
fromJSON(txt = "file1.txt") %>% 
    as_tibble %>% 
    row_to_names(row_number = 1) %>%
    type.convert(as.is = TRUE)

-输出

# A tibble: 4 x 6
#  seller_id product_id buyer_id sale_date  quantity price
#      <int>      <int>    <int> <chr>         <int> <int>
#1         7         11       49 2019-01-21        5  3330
#2        13         32        6 2019-02-10        9  1089
#3        50         47        4 2019-01-06        1  1343
#4         1         22        2 2019-03-03        9  7677

Answer 2

您需要将 json 从数组解析为数据框。也许是这样的：

# Get string
str <- '[["seller_id","product_id","buyer_id","sale_date","quantity","price"],[7,11,49,"2019-01-21",5,3330],[13,32,6,"2019-02-10",9,1089],[50,47,4,"2019-01-06",1,1343],[1,22,2,"2019-03-03",9,7677]]'

df_list <- jsonlite::parse_json(str)
do.call(rbind, lapply(df_list[-1], function(x) {
  setNames(as.data.frame(x), unlist(df_list[1]))}))
#>   seller_id product_id buyer_id  sale_date quantity price
#> 1         7         11       49 2019-01-21        5  3330
#> 2        13         32        6 2019-02-10        9  1089
#> 3        50         47        4 2019-01-06        1  1343
#> 4         1         22        2 2019-03-03        9  7677

^{由 reprex package (v0.3.0)}

于 2020-12-11 创建

Answer 3

一些基础 R 选项使用：

gsub + read.table

read.table(
  text = gsub('"|\[|\]', "", gsub("\],", "\n", s)),
  sep = ",",
  header = TRUE
)

gsub + read.csv

read.csv(text = gsub('"|\[|\]', "", gsub("\],", "\n", s)))

这给出了

  seller_id product_id buyer_id  sale_date quantity price
1         7         11       49 2019-01-21        5  3330
2        13         32        6 2019-02-10        9  1089
3        50         47        4 2019-01-06        1  1343
4         1         22        2 2019-03-03        9  7677

数据

s <- '[["seller_id","product_id","buyer_id","sale_date","quantity","price"],[7,11,49,"2019-01-21",5,3330],[13,32,6,"2019-02-10",9,1089],[50,47,4,"2019-01-06",1,1343],[1,22,2,"2019-03-03",9,7677]]'

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