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Thanks @meownoid for the clarification. will update title.
simonjayhawkins
changed the title
BUG: ValueError in read_csv when dtype='string' and parse_dates is present (worked in 0.25)
BUG: ValueError in read_csv when dtype='string' and parse_dates is present
Jul 28, 2020
This bug still stands and the copy-paste-able example still works. If I get up the motivation I might jump in as a contributor and fix it. In the meanwhile, a workaround is to not use the "dtype" keyword. The default actions of pd.read_csv tend to work pretty well. If they don't, you can clean up the dtypes after reading.
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Code Sample, a copy-pastable example
Problem description
ValueError: not all elements from date_cols are numpy arrays
Expected Output
Data frame with all columns as strings except ones specified in parse_dates optional argument.
Output of
pd.show_versions()
INSTALLED VERSIONS
commit : None
python : 3.8.1.final.0
python-bits : 64
OS : Linux
OS-release : 4.15.0-22-generic
machine : x86_64
processor :
byteorder : little
LC_ALL : en_US.UTF-8
LANG : en_US.UTF-8
LOCALE : None.None
pandas : 1.0.1
numpy : 1.18.1
pytz : 2019.3
dateutil : 2.8.1
pip : 20.0.2
setuptools : 46.1.3
Cython : 0.29.15
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.5.0
html5lib : None
pymysql : None
psycopg2 : 2.8.4 (dt dec pq3 ext lo64)
jinja2 : 2.11.2
IPython : 7.13.0
pandas_datareader: None
bs4 : 4.9.0
bottleneck : 1.3.2
fastparquet : None
gcsfs : None
lxml.etree : 4.5.0
matplotlib : 3.1.3
numexpr : 2.7.1
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 0.16.0
pytables : None
pytest : None
pyxlsb : None
s3fs : None
scipy : 1.4.1
sqlalchemy : 1.3.13
tables : None
tabulate : None
xarray : None
xlrd : 1.2.0
xlwt : None
xlsxwriter : None
numba : 0.48.0
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