Description
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I have confirmed this bug exists on the latest version of pandas.
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Note: Please read this guide detailing how to provide the necessary information for us to reproduce your bug.
Code Sample, a copy-pastable example
import json
import pandas as pd
body = '''[
{ "c1": 1, "c2": "1.01" },
{ "c1": 2, "c2": "1E-3" },
{ "c1": 3, "c2": "3.03" }
]'''
df1 = pd.read_json(body)
df2 = pd.json_normalize(json.loads(body))
print(df1, "\n\n", df1.dtypes)
print("\n\n", df2, "\n\n", df2.dtypes)Problem description
When creating a dataframe from json string input via json.loads() and pd.json_normalize() float values in scientific notation (e.g. "1E-3") are not parsed as floats. When using pd.read_json() they are parsed correctly.
Output:
c1 c2
0 1 1.010
1 2 0.001
2 3 3.030
c1 int64
c2 float64
dtype: object
c1 c2
0 1 1.01
1 2 1E-3
2 3 3.03
c1 int64
c2 object
dtype: object
Expected Output
c1 c2
0 1 1.010
1 2 0.001
2 3 3.030
c1 int64
c2 float64
dtype: object
c1 c2
0 1 1.010
1 2 0.001
2 3 3.030
c1 int64
c2 float64
dtype: object
Output of pd.show_versions()
INSTALLED VERSIONS
commit : 67a3d42
python : 3.8.5.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.0-1019-gcp
Version : #19-Ubuntu SMP Tue Jun 23 15:46:40 UTC 2020
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : en_US.UTF-8
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.1.4
numpy : 1.19.4
pytz : 2020.4
dateutil : 2.8.1
pip : 20.1.1
setuptools : 47.1.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.3.1
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pyxlsb : None
s3fs : None
scipy : 1.4.1
sqlalchemy : 1.3.19
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None