New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

BUG: Handle large timestamps #1440

Closed
wants to merge 1 commit into
base: master
from

Conversation

Projects
2 participants
@cpcloud
Member

cpcloud commented May 2, 2018

No description provided.

dt.Decimal: 'float64',
dt.Struct: 'object',
}
_ibis_dtypes = toolz.valmap(

This comment has been minimized.

@kszucs

kszucs May 2, 2018

Member

Got nicely symmetric!

df[column] = col.values.astype(pandas_dtype)
elif isinstance(dtype, dt.Timestamp):
# input column has a timezone
timezone = dtype.timezone

This comment has been minimized.

@kszucs

kszucs May 2, 2018

Member

Uhh, this seems complex, there are 5 possible outcomes in case of timestamps.
How about factoring this out with slightly more comments?

@cpcloud cpcloud added this to the 0.14 milestone May 5, 2018

@cpcloud cpcloud added this to To do in BigQuery via automation May 5, 2018

@cpcloud cpcloud self-assigned this May 5, 2018

@cpcloud cpcloud force-pushed the cpcloud:fix-bigquery-large-timestamps branch from ccf6343 to 55731bd May 5, 2018

@cpcloud cpcloud force-pushed the cpcloud:fix-bigquery-large-timestamps branch from 55731bd to 74902a0 May 12, 2018

@cpcloud cpcloud closed this in d61ccb2 May 13, 2018

BigQuery automation moved this from To do to Done May 13, 2018

@cpcloud cpcloud deleted the cpcloud:fix-bigquery-large-timestamps branch May 13, 2018

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment