json_normalize raises TypeError exception · Issue #22706 · pandas-dev/pandas (original) (raw)

Code Sample, a copy-pastable example if possible

from pandas.io.json import json_normalize

d = { 'name': 'alan smith',
'info': { 'phones': [{ 'area': 111, 'number': 2222 }, { 'area': 333, 'number': 4444 }] } } json_normalize(d, record_path=["info", "phones"])

Problem description

The above code throws TypeError exception:

Traceback (most recent call last):
  File ".\test.py", line 15, in <module>
    json_normalize(d, record_path = ["info", "phones"])
  File "C:\Python36\lib\site-packages\pandas\io\json\normalize.py", line 262, in json_normalize
    _recursive_extract(data, record_path, {}, level=0)
  File "C:\Python36\lib\site-packages\pandas\io\json\normalize.py", line 235, in _recursive_extract
    seen_meta, level=level + 1)
  File "C:\Python36\lib\site-packages\pandas\io\json\normalize.py", line 238, in _recursive_extract
    recs = _pull_field(obj, path[0])
  File "C:\Python36\lib\site-packages\pandas\io\json\normalize.py", line 185, in _pull_field
    result = result[spec]
TypeError: string indices must be integers

Expected Output

Output of pd.show_versions()

INSTALLED VERSIONS ------------------ commit: None python: 3.6.4.final.0 python-bits: 64 OS: Windows OS-release: 10 machine: AMD64 processor: Intel64 Family 6 Model 62 Stepping 4, GenuineIntel byteorder: little LC_ALL: None LANG: None LOCALE: None.None

pandas: 0.23.4
pytest: 3.6.2
pip: 18.0
setuptools: 40.2.0
Cython: None
numpy: 1.14.5
scipy: None
pyarrow: None
xarray: None
IPython: 6.3.1
sphinx: 1.5.5
patsy: None
dateutil: 2.7.3
pytz: 2018.5
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: 4.6.0
html5lib: 1.0.1
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None