# DataFrames, best way to import from JSON format file

**URL:** <https://discourse.julialang.org/t/dataframes-best-way-to-import-from-json-format-file/29946>\
**Category:** Data\
**Created:** [October 15, 2019, 2:43pm UTC](https://discourse.julialang.org/t/dataframes-best-way-to-import-from-json-format-file/29946 "2019-10-15T14:43:18Z")\
**Posts on this page:** 7\
**Page:** 1

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**Author:** ![4aHxKzD](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/4ahxkzd/32/10833_2.png) [@4aHxKzD](https://discourse.julialang.org/u/4aHxKzD)\
**Post date:** [October 15, 2019, 2:43pm UTC](https://discourse.julialang.org/t/dataframes-best-way-to-import-from-json-format-file/29946/1 "2019-10-15T14:43:19Z")

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Hi.

I’m coming from Python and would like to know what is the current “standard” on how to import from a JSON file to a DataFrame data structure, i.e., the equivalent to `pandas.read_json()`.

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**Author:** ![ExpandingMan](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/expandingman/32/866_2.png) [@ExpandingMan](https://discourse.julialang.org/u/ExpandingMan)\
**Post date:** [October 15, 2019, 2:58pm UTC](https://discourse.julialang.org/t/dataframes-best-way-to-import-from-json-format-file/29946/2 "2019-10-15T14:58:45Z")

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As far as I know, there isn’t actually a universally standard JSON table format (though I’m sure countless non-standard, or aspiring-to-be-standard formats exist). That said, tables are either dicts of arrays or an array of dicts, so it seems likely that the JSON you’re reading is one of these.

DataFrames implements thte [Tables interface](https://github.com/JuliaData/Tables.jl). The default constructor `DataFrame` therefore supports reading dicts of arrays directly into dataframes. In that case you can just do

```julia
DataFrame(JSON.parse(data))

```

I don’t see any really simple way of reading an array of dicts. You could do

```julia
v = JSON.parse(data)
cols = reduce(∩, keys.(v))
DataFrame((Symbol(c)=>getindex.(v, c) for c ∈ cols)...)

```

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**Author:** ![quinnj](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/quinnj/32/11_2.png) [@quinnj](https://discourse.julialang.org/u/quinnj)\
**Post date:** [October 15, 2019, 3:22pm UTC](https://discourse.julialang.org/t/dataframes-best-way-to-import-from-json-format-file/29946/3 "2019-10-15T15:22:32Z")

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A few of us have been working on [https://github.com/JuliaData/JSONTables.jl](https://github.com/JuliaData/JSONTables.jl), which provides an implementation of the Tables.jl interface to/from JSON via the JSON3.jl package. It’s use is like:

```julia
# turn a json string source into a DataFrame
# json source can be array of objects, or object of arrays
df = DataFrame(jsontable(json_source))

# write out a DataFrame as an array of objects
arraytable(df)

# write out a DataFrame as an object of arrays
objecttable(df)

```

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**Author:** ![jling](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/jling/32/212909_2.png) [@jling](https://discourse.julialang.org/u/jling)\
**Post date:** [October 15, 2019, 6:00pm UTC](https://discourse.julialang.org/t/dataframes-best-way-to-import-from-json-format-file/29946/4 "2019-10-15T18:00:15Z")

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could you elaborate a bit on the relation between JSON and 2 and 3? I know JSON is maintained by a different ‘team’, and what is the long term goal for these three JSON packages?

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**Author:** ![quinnj](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/quinnj/32/11_2.png) [@quinnj](https://discourse.julialang.org/u/quinnj)\
**Post date:** [October 15, 2019, 10:08pm UTC](https://discourse.julialang.org/t/dataframes-best-way-to-import-from-json-format-file/29946/5 "2019-10-15T22:08:04Z")

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Sure, here’s a quick history:

- JSON.jl has been around the longest; takes a very simple, straightforward approach to json parsing/writing, nothing fancy or custom for native Julia objects
- JSON2.jl was started w/ an idea to use generated functions for custom Julia types to generate specialized JSON parsing/writing code that could be much faster than JSON.jl; it was an experiment that worked fairly well, but can incur expensive compilation costs for complex/highly nested objects
- JSON3.jl is a successor of JSON2.jl that took some similar ideas (support for custom object serialization/deserialization), but aims to fix the compilation cost issue by being smarter, and also provides a hybrid lazy parsing approach for generic objects/arrays that is faster than any other solution

I’ll probably deprecate JSON2 at some point, since JSON3.jl is really more of a “breaking release” version of it; there’s also been talk/interest of eventually merging JSON.jl and JSON3.jl, but I’m in favor of letting JSON3.jl bake for a while longer before doing so.

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<div class="post-metadata">

**Author:** ![jling](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/jling/32/212909_2.png) [@jling](https://discourse.julialang.org/u/jling)\
**Post date:** [October 15, 2019, 10:11pm UTC](https://discourse.julialang.org/t/dataframes-best-way-to-import-from-json-format-file/29946/6 "2019-10-15T22:11:04Z")

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> [@quinnj](#):
>
> deprecate JSON2 at some point, since JSON3.jl is really

this would make much sense since you probably don’t want use package name as version # (😉

> [@quinnj](#):
>
> eventually merging JSON.jl and JSON3.jl

this is even better. JSON is somewhat important for Julia’s audience (more than, let’s say, XML, comparable to CSV (IMHO

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<div class="post-metadata">

**Author:** ![4aHxKzD](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/4ahxkzd/32/10833_2.png) [@4aHxKzD](https://discourse.julialang.org/u/4aHxKzD)\
**Post date:** [October 15, 2019, 10:55pm UTC](https://discourse.julialang.org/t/dataframes-best-way-to-import-from-json-format-file/29946/7 "2019-10-15T22:55:03Z")

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@ExpandingMan @quinnj Thank you for your quick replies, you were very helpful.  
I’m going to assume that using `JSONTables` is more generic and the way to go in most situations.