[jira] [Updated] (ARROW-1989) [Python] Better UX on timestamp conversion to Pandas

2019-06-13 Thread Wes McKinney (JIRA) 


 [ 
https://issues.apache.org/jira/browse/ARROW-1989?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Wes McKinney updated ARROW-1989:

Fix Version/s: (was: 0.14.0)

> [Python] Better UX on timestamp conversion to Pandas
> 
>
> Key: ARROW-1989
> URL: https://issues.apache.org/jira/browse/ARROW-1989
> Project: Apache Arrow
>  Issue Type: Improvement
>  Components: Python
>Reporter: Uwe L. Korn
>Priority: Major
>
> Converting timestamp columns to Pandas, users often have the problem that 
> they have dates that are larger than Pandas can represent with their 
> nanosecond representation. Currently they simply see an Arrow exception and 
> think that this problem is caused by Arrow. We should try to change the error 
> from
> {code}
> ArrowInvalid: Casting from timestamp[ns] to timestamp[us] would lose data: XX
> {code}
> to something along the lines of 
> {code}
> ArrowInvalid: Casting from timestamp[ns] to timestamp[us] would lose data: 
> XX. This conversion is needed as Pandas does only support nanosecond 
> timestamps. Your data is likely out of the range that can be represented with 
> nanosecond resolution.
> {code}



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[jira] [Updated] (ARROW-1989) [Python] Better UX on timestamp conversion to Pandas

2019-03-07 Thread Wes McKinney (JIRA) 


 [ 
https://issues.apache.org/jira/browse/ARROW-1989?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Wes McKinney updated ARROW-1989:

Fix Version/s: (was: 0.13.0)
   0.14.0

> [Python] Better UX on timestamp conversion to Pandas
> 
>
> Key: ARROW-1989
> URL: https://issues.apache.org/jira/browse/ARROW-1989
> Project: Apache Arrow
>  Issue Type: Improvement
>  Components: Python
>Reporter: Uwe L. Korn
>Priority: Major
> Fix For: 0.14.0
>
>
> Converting timestamp columns to Pandas, users often have the problem that 
> they have dates that are larger than Pandas can represent with their 
> nanosecond representation. Currently they simply see an Arrow exception and 
> think that this problem is caused by Arrow. We should try to change the error 
> from
> {code}
> ArrowInvalid: Casting from timestamp[ns] to timestamp[us] would lose data: XX
> {code}
> to something along the lines of 
> {code}
> ArrowInvalid: Casting from timestamp[ns] to timestamp[us] would lose data: 
> XX. This conversion is needed as Pandas does only support nanosecond 
> timestamps. Your data is likely out of the range that can be represented with 
> nanosecond resolution.
> {code}



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[jira] [Updated] (ARROW-1989) [Python] Better UX on timestamp conversion to Pandas

2018-11-19 Thread Wes McKinney (JIRA) 


 [ 
https://issues.apache.org/jira/browse/ARROW-1989?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Wes McKinney updated ARROW-1989:

Fix Version/s: (was: 0.12.0)
   0.13.0

> [Python] Better UX on timestamp conversion to Pandas
> 
>
> Key: ARROW-1989
> URL: https://issues.apache.org/jira/browse/ARROW-1989
> Project: Apache Arrow
>  Issue Type: Improvement
>  Components: Python
>Reporter: Uwe L. Korn
>Priority: Major
> Fix For: 0.13.0
>
>
> Converting timestamp columns to Pandas, users often have the problem that 
> they have dates that are larger than Pandas can represent with their 
> nanosecond representation. Currently they simply see an Arrow exception and 
> think that this problem is caused by Arrow. We should try to change the error 
> from
> {code}
> ArrowInvalid: Casting from timestamp[ns] to timestamp[us] would lose data: XX
> {code}
> to something along the lines of 
> {code}
> ArrowInvalid: Casting from timestamp[ns] to timestamp[us] would lose data: 
> XX. This conversion is needed as Pandas does only support nanosecond 
> timestamps. Your data is likely out of the range that can be represented with 
> nanosecond resolution.
> {code}



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[jira] [Updated] (ARROW-1989) [Python] Better UX on timestamp conversion to Pandas

2018-09-10 Thread Wes McKinney (JIRA) 


 [ 
https://issues.apache.org/jira/browse/ARROW-1989?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Wes McKinney updated ARROW-1989:

Fix Version/s: (was: 0.11.0)
   0.12.0

> [Python] Better UX on timestamp conversion to Pandas
> 
>
> Key: ARROW-1989
> URL: https://issues.apache.org/jira/browse/ARROW-1989
> Project: Apache Arrow
>  Issue Type: Improvement
>  Components: Python
>Reporter: Uwe L. Korn
>Priority: Major
> Fix For: 0.12.0
>
>
> Converting timestamp columns to Pandas, users often have the problem that 
> they have dates that are larger than Pandas can represent with their 
> nanosecond representation. Currently they simply see an Arrow exception and 
> think that this problem is caused by Arrow. We should try to change the error 
> from
> {code}
> ArrowInvalid: Casting from timestamp[ns] to timestamp[us] would lose data: XX
> {code}
> to something along the lines of 
> {code}
> ArrowInvalid: Casting from timestamp[ns] to timestamp[us] would lose data: 
> XX. This conversion is needed as Pandas does only support nanosecond 
> timestamps. Your data is likely out of the range that can be represented with 
> nanosecond resolution.
> {code}



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[jira] [Updated] (ARROW-1989) [Python] Better UX on timestamp conversion to Pandas

2018-06-29 Thread Wes McKinney (JIRA) 


 [ 
https://issues.apache.org/jira/browse/ARROW-1989?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Wes McKinney updated ARROW-1989:

Fix Version/s: (was: 0.10.0)
   0.11.0

> [Python] Better UX on timestamp conversion to Pandas
> 
>
> Key: ARROW-1989
> URL: https://issues.apache.org/jira/browse/ARROW-1989
> Project: Apache Arrow
>  Issue Type: Improvement
>  Components: Python
>Reporter: Uwe L. Korn
>Priority: Major
> Fix For: 0.11.0
>
>
> Converting timestamp columns to Pandas, users often have the problem that 
> they have dates that are larger than Pandas can represent with their 
> nanosecond representation. Currently they simply see an Arrow exception and 
> think that this problem is caused by Arrow. We should try to change the error 
> from
> {code}
> ArrowInvalid: Casting from timestamp[ns] to timestamp[us] would lose data: XX
> {code}
> to something along the lines of 
> {code}
> ArrowInvalid: Casting from timestamp[ns] to timestamp[us] would lose data: 
> XX. This conversion is needed as Pandas does only support nanosecond 
> timestamps. Your data is likely out of the range that can be represented with 
> nanosecond resolution.
> {code}



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[jira] [Updated] (ARROW-1989) [Python] Better UX on timestamp conversion to Pandas

2018-02-21 Thread Wes McKinney (JIRA) 

 [ 
https://issues.apache.org/jira/browse/ARROW-1989?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Wes McKinney updated ARROW-1989:

Fix Version/s: (was: 0.9.0)
   0.10.0

> [Python] Better UX on timestamp conversion to Pandas
> 
>
> Key: ARROW-1989
> URL: https://issues.apache.org/jira/browse/ARROW-1989
> Project: Apache Arrow
>  Issue Type: Improvement
>  Components: Python
>Reporter: Uwe L. Korn
>Priority: Major
> Fix For: 0.10.0
>
>
> Converting timestamp columns to Pandas, users often have the problem that 
> they have dates that are larger than Pandas can represent with their 
> nanosecond representation. Currently they simply see an Arrow exception and 
> think that this problem is caused by Arrow. We should try to change the error 
> from
> {code}
> ArrowInvalid: Casting from timestamp[ns] to timestamp[us] would lose data: XX
> {code}
> to something along the lines of 
> {code}
> ArrowInvalid: Casting from timestamp[ns] to timestamp[us] would lose data: 
> XX. This conversion is needed as Pandas does only support nanosecond 
> timestamps. Your data is likely out of the range that can be represented with 
> nanosecond resolution.
> {code}



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