R - Yelp 数据业务类别列每个业务有多个类别。想要分成值为 1 和 0 的类别特定列

Question

提前感谢任何愿意为此提供帮助的人。

我使用的是Yelp数据集，我想回答的问题是"which categories are positively correlated with higher stars for X category (Bars for example)"

我遇到的问题是，对于每项业务，每个 businesss_id 的类别都集中在一列和一行中。所以我需要一种方法来分离每个类别，将它们变成列，然后检查原始类别列是否包含为其创建列的类别。

我目前的思路是使用 group_by 和 business_id 然后 unnest_tokens 列，然后 model.matrix() 该列进入我想要的拆分然后将它加入到我正在使用的 df 中。但是我无法让 model.matrix 通过并保持 business_id 连接到每一行。

# an example of what I am using #
df <- 
  data_frame(business_id = c("bus_1",
                             "bus_2", 
                             "bus_3"),
             categories=c("Pizza, Burgers, Caterers",
                          "Pizza, Restaurants, Bars",
                          "American, Barbeque, Restaurants"))

# what I want it to look like #
desired_df <- 
  data_frame(business_id = c("bus_1",
                             "bus_2",
                             "bus_3"),
             categories=c("Pizza, Burgers, Caterers",
                          "Pizza, Restaurants, Bars",
                          "American, Barbeque, Restaurants"),
             Pizza = c(1, 1, 0),
             Burgers = c(1, 0, 0),
             Caterers = c(1, 0, 0),
             Restaurants = c(0, 1, 1),
             Bars = c(0, 1, 0),
             American = c(0, 0, 1),
             Barbeque = c(0, 0, 1))

# where I am stuck #
df %>%
  select(business_id, categories) %>% 
  group_by(business_id) %>% 
  unnest_tokens(categories, categories, token = 'regex', pattern=", ") %>%
  model.matrix(business_id ~ categories, data = .) %>% 
  as_data_frame

编辑：在此 post 和下面的答案之后，我在使用 spread() 时遇到了重复标识符错误。这把我带到了这个帖子 https://github.com/tidyverse/tidyr/issues/426，我的问题的答案是 posted，我在下面重新粘贴了它。

# 用较小的 data.frame #

复制错误

library(tidyverse)
 df <- structure(list(age = c("21", "17", "32", "29", "15"), 
                        gender = structure(c(2L, 1L, 1L, 2L, 2L), .Label = c("Female", "Male"), class = "factor")), 
                   row.names = c(NA, -5L), class = c("tbl_df", "tbl", "data.frame"), .Names = c("age", "gender"))
 df
#> # A tibble: 5 x 2
#>   age   gender
#>   <chr> <fct> 
#> 1 21    Male  
#> 2 17    Female
#> 3 32    Female
#> 4 29    Male  
#> 5 15    Male  

df %>% 
  spread(key=gender, value=age)
#> Error: Duplicate identifiers for rows (2, 3), (1, 4, 5)

#修复问题#

df %>% 
  group_by_at(vars(-age)) %>%  # group by everything other than the value column. 
  mutate(row_id=1:n()) %>% ungroup() %>%  # build group index
  spread(key=gender, value=age) %>%    # spread
  select(-row_id)  # drop the index

#> # A tibble: 3 x 2
#>   Female Male 
#>   <chr>  <chr>
#> 1 17     21   
#> 2 32     29   
#> 3 NA     15

Answer 1

这是一个简单的 tidyverse 解决方案：

library(tidyverse)

df %>% 
  mutate(
    ind = 1,
    tmp = strsplit(categories, ", ")
  ) %>% 
  unnest(tmp) %>% 
  spread(tmp, ind, fill = 0)
## A tibble: 3 x 9
#  business_id categories                      American Barbeque  Bars Burgers Caterers Pizza Restaurants
#  <chr>       <chr>                              <dbl>    <dbl> <dbl>   <dbl>    <dbl> <dbl>       <dbl>
#1 bus_1       Pizza, Burgers, Caterers               0        0     0       1        1     1           0
#2 bus_2       Pizza, Restaurants, Bars               0        0     1       0        0     1           1
#3 bus_3       American, Barbeque, Restaurants        1        1     0       0        0     0           1

Answer 2

基于您对 tidytext::unnest_tokens() 的良好使用，您还可以使用此替代解决方案

library(dplyr)
library(tidyr)
library(tidytext)

df %>%
  select(business_id, categories) %>% 
  group_by(business_id) %>% 
  unnest_tokens(categories, categories, token = 'regex', pattern=", ") %>% 
  mutate(value = 1) %>% 
  spread(categories, value, fill = 0)
# business_id american barbeque  bars burgers caterers pizza restaurants
# <chr>          <dbl>    <dbl> <dbl>   <dbl>    <dbl> <dbl>       <dbl>
# bus_1              0        0     0       1        1     1           0
# bus_2              0        0     1       0        0     1           1
# bus_3              1        1     0       0        0     0           1

R - Yelp 数据业务类别列每个业务有多个类别。想要分成值为 1 和 0 的类别特定列

R - Yelp data Business category column has multiple categories per business. Want to separate into category specific columns with values of 1 and 0

r

dataframe

yelp