使用NASA的API检索有关火星天气的信息,我检索了清单列表。在python中,pandas可以很好地格式化数据;但是,我必须在R中编写API。
即使使用jsonlite的fromJSON(x, flatten = TRUE)
函数,这也是R中数据的结构方式。
我想将原始数据构建为类似于熊猫表。
这是我的API代码:
library(httr)
library(jsonlite)
req <- "https://api.nasa.gov/insight_weather/?api_key=&feedtype=json&ver=1.0"
response <- GET(req)
response <- content(response, as="text")
mars <- fromJSON(response, flatten = TRUE)
[API查询返回的信息多于表屏幕快照,但我只专注于返回结构与示例相似的表。如果您想要风速之类的额外信息,则它的结构不同,可能更易于单独解析和合并。
library(jsonlite)
library(purrr)
library(dplyr)
library(tidyr)
req <- "https://api.nasa.gov/insight_weather/?api_key=DEMO_KEY&feedtype=json&ver=1.0"
mars <- fromJSON(req)
map(mars[1:7], ~unlist(.x[1:6]) %>%
bind_rows) %>%
bind_rows(.id = "day") %>%
pivot_longer(cols = grep("\\.", names(.)), names_sep = "\\.", names_to = c(".value", "var"))
# A tibble: 28 x 8
day First_UTC Last_UTC Season var AT HWS PRE
<chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
1 402 2020-01-13T06:24:59Z 2020-01-14T07:04:33Z summer av -65.475 5.364 637.752
2 402 2020-01-13T06:24:59Z 2020-01-14T07:04:33Z summer ct 178174 79226 89083
3 402 2020-01-13T06:24:59Z 2020-01-14T07:04:33Z summer mn -100.044 0.236 618.015
4 402 2020-01-13T06:24:59Z 2020-01-14T07:04:33Z summer mx -16.815 21.146 653.7326
5 403 2020-01-14T07:04:34Z 2020-01-15T07:44:08Z summer av -62.449 5.683 636.87
6 403 2020-01-14T07:04:34Z 2020-01-15T07:44:08Z summer ct 211897 95539 105800
7 403 2020-01-14T07:04:34Z 2020-01-15T07:44:08Z summer mn -101.272 0.205 618.1757
8 403 2020-01-14T07:04:34Z 2020-01-15T07:44:08Z summer mx -16.931 20.986 653.4973
9 404 2020-01-15T07:44:09Z 2020-01-16T08:23:44Z summer av -63.622 5.303 636.148
10 404 2020-01-15T07:44:09Z 2020-01-16T08:23:44Z summer ct 293286 132690 158958
# … with 18 more rows