8000 Json normalize nan support by antoineviscardi · Pull Request #25619 · pandas-dev/pandas · GitHub
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Json normalize nan support #25619

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Merged
merged 12 commits into from
Mar 13, 2019
Merged

Json normalize nan support #25619

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daf9d3e
BUG: fixed json_normalize with nullable meta fields (#25468)
antoineviscardi Mar 9, 2019
2cc267c
fixed code style
antoineviscardi Mar 9, 2019
a24a213
modified test to ignore order of columns
antoineviscardi Mar 9, 2019
cf93f8a
fixed change log addition
antoineviscardi Mar 9, 2019
2a8a726
added requested changes
antoineviscardi Mar 10, 2019
dba832c
refactor test_json_normalize_errors
antoineviscardi Mar 10, 2019
5b6a8e7
build expected from list of lists to make order deterministic
antoineviscardi Mar 10, 2019
ba5902e
changed the entry for json_normalize
antoineviscardi Mar 11, 2019
838133a
merger with master
antoineviscardi Mar 11, 2019
4953012
added one-liner
antoineviscardi Mar 13, 2019
b3b744c
resolved merging issue
antoineviscardi Mar 13, 2019
57e5b29
Merge remote-tracking branch 'upstream/master' into json-normalize-na…
antoineviscardi Mar 13, 2019
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fixed change log addition
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@antoineviscardi
antoineviscardi committed Mar 9, 2019
commit cf93f8ae43e8a5c615814d5fff858b346b8202f5
2 changes: 1 addition & 1 deletion doc/source/whatsnew/v0.25.0.rst
8000
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Expand Up @@ -214,7 +214,7 @@ I/O
- Bug in :func:`read_json` for ``orient='table'`` when it tries to infer dtypes by default, which is not applicable as dtypes are already defined in the JSON schema (:issue:`21345`)
- Bug in :func:`read_json` for ``orient='table'`` and float index, as it infers index dtype by default, which is not applicable because index dtype is already defined in the JSON schema (:issue:`25433`)
- Bug in :func:`read_json` for ``orient='table'`` and string of float column names, as it makes a column name type conversion to Timestamp, which is not applicable because column names are already defined in the JSON schema (:issue:`25435`)
- Bug in :func:`json_normalize` for ``errors='ignore'`` and nullable metadata fields, the null values in dataframe were literal nan string and not numpy.nan (:issue:`25468`)
- Bug in :func:`json_normalize` for ``errors='ignore'`` and nullable metadata fields, the missing metadata values in dataframe were filled with the string "nan" instead of ``numpy.nan`` (:issue:`25468`)
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