I need to convert a dataframe to JSON. There are several nested dataframes as variables in the dataframe to convert to JSON.
But, when converting to JSON, I need the data for Values1
described below to be an object (enclosed in {}
only) instead of an array (enclosed in []
).
The code below is a reprex to show my current workflow and problem.
library(dplyr)
library(tidyr)
library(jsonlite)
df1 <- data.frame(name = c("a", "b", "c"),
v = c(1, 2, 3),
w = c(10, 20, 30)) %>%
group_by(name) %>%
nest_legacy(.key = "Values1")
df2 <- data.frame(name = c("a", "b", "c"),
x = c(5, 10, 15),
y = c(100, 200, 300),
z = c(1000, 2000, 3000)) %>%
group_by(name) %>%
nest_legacy(.key = "Values2")
df3 <- df1 %>%
left_join(df2)
json <- toJSON(df3, dataframe = "rows", pretty = TRUE)
json
This is what the json from the above looks like:
> json
[
{
"name": "a",
"Values1": [
{
"v": 1,
"w": 10
}
],
"Values2": [
{
"x": 5,
"y": 100,
"z": 1000
}
]
},
{
"name": "b",
"Values1": [
{
"v": 2,
"w": 20
}
],
"Values2": [
{
"x": 10,
"y": 200,
"z": 2000
}
]
},
{
"name": "c",
"Values1": [
{
"v": 3,
"w": 30
}
],
"Values2": [
{
"x": 15,
"y": 300,
"z": 3000
}
]
}
]
But, this is what I need it to look like:
> json
[
{
"name": "a",
"Values1": {
"v": 1,
"w": 10
},
"Values2": [
{
"x": 5,
"y": 100,
"z": 1000
}
]
},
{
"name": "b",
"Values1": {
"v": 2,
"w": 20
},
"Values2": [
{
"x": 10,
"y": 200,
"z": 2000
}
]
},
{
"name": "c",
"Values1": {
"v": 3,
"w": 30
},
"Values2": [
{
"x": 15,
"y": 300,
"z": 3000
}
]
}
]
Any ideas how to convert Values1
from arrays to objects? They cannot be in arrays as the API does not accept the [
.
I have looked at using unbox()
from jsonlite
but this only works on singletons. I have also tried to construct my final dataframe in various ways.
Any tips/ideas greatly appreciated!
unbox
functionality, but just couldn't figure it out. Thanks for the speedy, succinct reply. – Felton