pipeline的选择

%>% also works with rlist functions. However, in some cases, the operator may impose conflicting interpretation on . symbol to cause unexpected error.[@Ren2016]

这里会考虑使用pipeR:%>>%:。

JSON格式

In the coming tutorial pages, we will mainly use JSON data to demonstrate the features and examples of rlist package.

[] creates a unnamed node array.
{} creates a named node list.
"key" : value creates a key-value pair where value can be a number, a string, a [] array, or a {} list.

rlist package imports jsonlite package to read/write JSON data.

YAML格式

rlist also imports yaml package to read/write YAML data.

- Name: Ken
  Age: 24
  Interests:
  - reading
  - music
  - movies
  Expertise:
    R: 2
    CSharp: 4
    Python: 3
- Name: James
  Age: 25
  Interests:
  - sports
  - music
  Expertise:
    R: 3
    Java: 2
    Cpp: 5
- Name: Penny
  Age: 24
  Interests:
  - movies
  - reading
  Expertise:
    R: 1
    Cpp: 4
    Python: 2

数据来源于 @Ren2016 https://renkun-ken.github.io/rlist-tutorial/data/sample.yaml 常见于RMarkdown文档的开头申明。

博客可以使用这个来提取yaml数据

举例

library(tidyverse)

## Error in `library()`:
## ! there is no package called 'tidyverse'

library(rlist)

## Error in `library()`:
## ! there is no package called 'rlist'

people <- list.load("data/sample.json")

## Error in `list.load()`:
## ! could not find function "list.load"

str(people)

## Error:
## ! object 'people' not found

NOTE: str() previews the structure of an object. We may use this function more often to avoid verbose representation of list objects.

这个函数展示很不错。

people %>% 
    map(
        ~ list(
            name = .$Name
            ,age = 
                .$Age
            ,range = 
                .$Expertise %>% 
                as.numeric %>% 
                range %>% 
                as.character %>% 
                str_flatten('-')
        )
    ) %>% 
    map(~glue::glue("{.$name}: {.$age} and has {.$range} year experience"))

## Error in `people %>% map(~ list(name = .$Name, age = .$Age, range = .$Expertise %>%
##     as.numeric %>% range %>% as.character %>% str_flatten("-"))) %>% map(~ glue::glue(
##     "{.$name}: {.$age} and has {.$range} year experience"))`:
## ! could not find function "%>%"

这个可以用来出tutorial的题目。

filter

people %>% 
    list.filter(Age >= 25 & "music" %in% Interests) %>% 
    map(~.$Name)

## Error in `people %>% list.filter(Age >= 25 & "music" %in% Interests) %>% map(~ .$Name)`:
## ! could not find function "%>%"

这个还没找好很好的替代方式。

list.find
list.findi
list.first
list.last
list.take
list.skip

太多了，没什么好选择的。

是list.filter 的替代品，只反馈一部分的字段，因为json格式很大时，反馈时间很长。

技术：非结构化数据处理

技术系列导航

pipeline的选择

JSON格式

YAML格式

举例

filter

技术系列导航

技术：非结构化数据处理

技术 系列导航

pipeline的选择

JSON格式

YAML格式

举例

filter

技术 系列导航

技术系列导航

技术系列导航