tidyjson (development version)

Add jdouble() and jinteger(). junmber() is aliased to jdouble(), and can still be used, however jdouble() should be preferred as it is less ambiguous.

tidyjson 0.3.1

Add tbl_json methods for join to drop the tbl_json class early. If you need the ..JSON column, ensure to save it with json_get_column() before joining.
Work around an issue with dplyr 1.0.0 and [ not subsetting properly with transmute

Please let us know if you run into any errors of the form

The `[` method for class <tbl_json/tbl_df/tbl/data.frame> must return a data frame with 1 column

We will need to do some more work on how we manage the ..JSON column.

Instead of attr(., "JSON"), the JSON object is now a hidden column (..JSON). To prevent future backwards incompatibilities of this nature, there is now an “extractor” function to pull the raw JSON object off of the tbl_json: json_get(). You can also use json_get_column() to add the raw json onto your tbl_json as a dedicated column
Related to this, selecting a ..JSON column with dplyr::select() will mostly ignore you for complicated reasons. Use json_get_column() if you want to access the raw ..JSON data.
As always, if you want to remove tidyjson “magic”, tibble::as_tibble() will drop the tbl_json class and you are back to normal!

Add a few generics to make behavior generally more consistent: $<-.tbl_json, etc.
Add as_tbl_json as a future replacement for as.tbl_json
Add as_tbl_json.list so that you can more easily parse the JSON outside of tbl_json if you like. Further, this allows tbl_json to work with any arbitrary nested list. (#119)

Add bind_rows() support. Though currently not an S3 implementation, it behaves as much like the dplyr variant as possible, preserving the attr(.,'JSON') components if all components are tbl_json objects. (#58)

“Using Multiple APIs” vignette added to show support for using tidyjson with multiple APIs (#85)
Updated README.md to better explain spread_all() (#92)

Improve compatibility with newer dplyr and tidyr
DROP=TRUE caused an error. Altered behavior to be consistent with tbl_df
Fix spread_all(recursive=FALSE) bug that caused an error (#65)
Alter spread_all() behavior to recursively check for deduplication of names (and thus avoid an error) (#76)
Add named support for the NSE versions of dplyr functions (filter(),mutate(),slice(), etc.) since the SE variants are no longer called behind-the-scenes since dplyr 0.6.0. (#97)
Fix errors with print.tbl_json() when the JSON attribute is missing
Fix json_structure() failure if document.id missing by imputing the missing document.id. (#86)

json_complexity() computes the “complexity” (recursively unlisted length) of JSON data (#5)
json_structure() recursively structures arbitrary JSON data into a single data frame (#2)
json_schema() creates a schema for a JSON document or collection (#12)
is_json functions for testing JSON types, such as is_json_string(), is_json_null() or is_json_object() (#39)
spread_all() spreads all scalar values of a JSON object into new columns (#56)
as.character.tbl_json() converts tbl_json objects back into JSON character strings (#62)
gather_object() replaces gather_keys(), with default column.name of name instead of key (#66). This more closely matches the JSON standard, which refers to objects as name-value pairs, and is now consistent with gather_array().

“Using Multiple APIs” vignette added to show support for using tidyjson with multiple APIs (#85)
Updated README.md to better explain spread_all() (#92)
“Visualizing JSON” vignette for visualizing the structure of complex JSON data, like the companies example (#4)
Significant updates to all documentation and examples for clarity (#42)
Updated “Introduction to tidyjson” vignette to be more concise and use new functionality (#74)

enter_object and the jstring, jnumber and jlogical functions now accept unquoted strings to specify their path (#26)
tbl_json objects now print with a tidy character representation of the JSON attribute (#61)
Use purrr for most list based internal operations (#1)
Use tidyr for gather_array and gather_object functions (#28)
Imported the magrittr %>% operator (#17)
Fixed dplyr::slice() not working correctly with tbl_json objects (#18)
First argument to verbs is .x rather than x to avoid name conflicts in NSE (#23)
Fixed spread_values() to not coerce types (#24)
gather_array() and gather_object() can be called repeatedly in the same pipeline with the same column.name argument, and will simply append an integer identifer to the new columns (#38)