Is there a json_normalize like feature in Polars?

Question

I went through the entire documentation of Polars but couldn't find anything which could convert nested json into dataframe.

test = {
  "name": "Ravi",
  "Subjects": {
    "Maths": 92,
    "English": 94,
    "Hindi": 98
  }
}

json_normalize in pandas would convert this to a dataframe by naming the columns as name, Subjects.Maths, Subjects.English and Subjects.Hindi. So is this a possibility in Polars? I did try all the functions but it always throws an error as it doesn't undersand the nested structure.

Answer 1

For a simple JSON-like dictionary, you can use a comprehension list to convert the values into list of values.

Below an example:

grades = {
  "name": "Ravi",
  "Subjects": {
    "Maths": 92,
    "English": 94,
    "Hindi": 98
  }}

grades_with_list = {key:[value] for key, value in grades.items()}
pl.DataFrame(grades_with_list)

# Output
shape: (1, 2)
┌──────┬────────────┐
│ name ┆ Subjects   │
│ ---  ┆ ---        │
│ str  ┆ struct[3]  │
╞══════╪════════════╡
│ Ravi ┆ {92,94,98} │
└──────┴────────────┘

# You can also un-nest the Subjets column, to get a separate column for each subject.

pl.DataFrame(grades_with_list).unnest('Subjects')

# Output
shape: (1, 4)
┌──────┬───────┬─────────┬───────┐
│ name ┆ Maths ┆ English ┆ Hindi │
│ ---  ┆ ---   ┆ ---     ┆ ---   │
│ str  ┆ i64   ┆ i64     ┆ i64   │
╞══════╪═══════╪═════════╪═══════╡
│ Ravi ┆ 92    ┆ 94      ┆ 98    │
└──────┴───────┴─────────┴───────┘

Answer 2

A simple version of json_normalize() was added in Polars v1.0

pl.json_normalize(test)

shape: (1, 4)
┌──────┬────────────────┬──────────────────┬────────────────┐
│ name ┆ Subjects.Maths ┆ Subjects.English ┆ Subjects.Hindi │
│ ---  ┆ ---            ┆ ---              ┆ ---            │
│ str  ┆ i64            ┆ i64              ┆ i64            │
╞══════╪════════════════╪══════════════════╪════════════════╡
│ Ravi ┆ 92             ┆ 94               ┆ 98             │
└──────┴────────────────┴──────────────────┴────────────────┘