Description
Pandas version checks
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I have checked that this issue has not already been reported.
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I have confirmed this bug exists on the latest version of pandas.
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I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import pandas as pd
pd.json_normalize(
data=dict(x=[1, 2], y=[]),
record_path='x',
meta=[['y', 'yy']])TypeError: list indices must be integers or slices, not strIssue Description
Hello.
json_normalize is great function. it has feature that allows to coerce errors when provided json structure has some missing keys.
I wish to improve the coercion algorithm.
Expected Behavior
above code should result with {x:[1,2],y:[pd.nan,pd.nan]}.
now it just throws typeError.
I have already made a fix for that, but would be happy to discuss some other improvements before proposing a PR.
Installed Versions
INSTALLED VERSIONS
commit : bdc79c1
python : 3.11.3.final.0
python-bits : 64
OS : Darwin
OS-release : 21.4.0
Version : Darwin Kernel Version 21.4.0: Mon Feb 21 20:36:53 PST 2022; root:xnu-8020.101.4~2/RELEASE_ARM64_T8101
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : None
LOCALE : en_US.UTF-8
pandas : 2.2.1
numpy : 1.26.3
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 68.2.2
pip : 24.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 5.0.1
html5lib : 1.1
pymysql : None
psycopg2 : 2.9.9
jinja2 : 3.1.2
IPython : 8.19.0
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.2
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : 2023.12.2
gcsfs : None
matplotlib : 3.8.2
numba : 0.58.1
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : 1.11.4
sqlalchemy : None
tables : None
tabulate : 0.9.0
xarray : None
xlrd : None
zstandard : 0.22.0
tzdata : 2023.4
qtpy : None
pyqt5 : None