Description
Code Sample, a copy-pastable example if possible
import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.randint(0,100,size=(100, 4)), columns=list('ABCD'))
df.to_csv("s3://super_dumb_s3_bucket/not_real.csv")
Problem description
If you provide an invalid s3 path (e.g. a bucket that you don't have access to), this command fails silently.
Expected Output
Raise some exception at least.
Output of pd.show_versions()
[paste the output of pd.show_versions()
here below this line]
INSTALLED VERSIONS
commit : None
python : 3.7.2.final.0
python-bits : 64
OS : Linux
OS-release : 4.15.0-88-generic
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : C.UTF-8
LOCALE : en_US.UTF-8
pandas : 0.25.1
numpy : 1.17.0
pytz : 2019.2
dateutil : 2.8.0
pip : 19.0.2
setuptools : 40.8.0
Cython : None
pytest : 3.10.1
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.4.1
html5lib : None
pymysql : None
psycopg2 : 2.8.3 (dt dec pq3 ext lo64)
jinja2 : 2.10.1
IPython : 7.9.0
pandas_datareader: None
bs4 : 4.8.0
bottleneck : None
fastparquet : None
gcsfs : None
lxml.etree : 4.4.1
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
s3fs : None
scipy : 1.3.1
sqlalchemy : None
tables : None
xarray : None
xlrd : None
xlwt : None
xlsxwriter : None