Title: Support for string[pyarrow] dtype · Issue #954 · googleapis/python-bigquery · GitHub
Open Graph Title: Support for string[pyarrow] dtype · Issue #954 · googleapis/python-bigquery
X Title: Support for string[pyarrow] dtype · Issue #954 · googleapis/python-bigquery
Description: Pandas 1.3 added a new string[pyarrow] dtype which can be considerably more memory-efficient. I'm not sure what all would be involved but obviously it would be nice to support this natively since presumably(?) we already communicate the ...
Open Graph Description: Pandas 1.3 added a new string[pyarrow] dtype which can be considerably more memory-efficient. I'm not sure what all would be involved but obviously it would be nice to support this natively since p...
X Description: Pandas 1.3 added a new string[pyarrow] dtype which can be considerably more memory-efficient. I'm not sure what all would be involved but obviously it would be nice to support this natively sin...
Opengraph URL: https://github.com/googleapis/python-bigquery/issues/954
X: @github
Domain: github.com
{"@context":"https://schema.org","@type":"DiscussionForumPosting","headline":"Support for string[pyarrow] dtype","articleBody":"[Pandas 1.3](https://pandas.pydata.org/pandas-docs/stable/whatsnew/v1.3.0.html#pyarrow-backed-string-data-type) added a new `string[pyarrow]` dtype which can be considerably more [memory-efficient](https://www.youtube.com/watch?v=_zoPmQ6J1aE).\r\n\r\nI'm not sure what all would be involved but obviously it would be nice to support this natively since presumably(?) we already communicate the data in the appropriate format for the pyarrow string type before converting it back to python string objects. Maybe an option like was introduced in #848 for geography types could be used to determine the behavior?","author":{"url":"https://github.com/bnaul","@type":"Person","name":"bnaul"},"datePublished":"2021-09-08T14:16:46.000Z","interactionStatistic":{"@type":"InteractionCounter","interactionType":"https://schema.org/CommentAction","userInteractionCount":9},"url":"https://github.com/954/python-bigquery/issues/954"}
| route-pattern | /_view_fragments/issues/show/:user_id/:repository/:id/issue_layout(.:format) |
| route-controller | voltron_issues_fragments |
| route-action | issue_layout |
| fetch-nonce | v2:069b5330-b92d-c888-a0bc-046fe2dd1c65 |
| current-catalog-service-hash | 81bb79d38c15960b92d99bca9288a9108c7a47b18f2423d0f6438c5b7bcd2114 |
| request-id | 8F44:E21F7:E4CC7F:E9D256:6A4DC1F3 |
| html-safe-nonce | 42218eac07ba9405a1bcf474c7c7b00d815d26b985d2aad632405a1bc6283bef |
| visitor-payload | eyJyZWZlcnJlciI6IiIsInJlcXVlc3RfaWQiOiI4RjQ0OkUyMUY3OkU0Q0M3RjpFOUQyNTY6NkE0REMxRjMiLCJ2aXNpdG9yX2lkIjoiMjc0MTI5NjE1NTg2MjA5MDIyOCIsInJlZ2lvbl9lZGdlIjoic2VhIiwicmVnaW9uX3JlbmRlciI6InNlYSJ9 |
| visitor-hmac | 6b704ed5221f4b8873d397f9ae87e349dbfaad37433fd23bf57b9bdff3cb1e48 |
| hovercard-subject-tag | issue:991192344 |
| github-keyboard-shortcuts | repository,issues,copilot |
| google-site-verification | Apib7-x98H0j5cPqHWwSMm6dNU4GmODRoqxLiDzdx9I |
| octolytics-url | https://collector.github.com/github/collect |
| analytics-location | / |
| fb:app_id | 1401488693436528 |
| apple-itunes-app | app-id=1477376905, app-argument=https://github.com/_view_fragments/issues/show/googleapis/python-bigquery/954/issue_layout |
| twitter:image | https://opengraph.githubassets.com/001644763eef7846d53fcab8fc26151e3250ddf4f04b5c9b8dc2500225cb5625/googleapis/python-bigquery/issues/954 |
| twitter:card | summary_large_image |
| og:image | https://opengraph.githubassets.com/001644763eef7846d53fcab8fc26151e3250ddf4f04b5c9b8dc2500225cb5625/googleapis/python-bigquery/issues/954 |
| og:image:alt | Pandas 1.3 added a new string[pyarrow] dtype which can be considerably more memory-efficient. I'm not sure what all would be involved but obviously it would be nice to support this natively since p... |
| og:image:width | 1200 |
| og:image:height | 600 |
| og:site_name | GitHub |
| og:type | object |
| og:author:username | bnaul |
| hostname | github.com |
| expected-hostname | github.com |
| None | 06b8a6144231bf3a234f1c2e9993861e07ce98a905912b114aa386c2d7e84b33 |
| turbo-cache-control | no-preview |
| go-import | github.com/googleapis/python-bigquery git https://github.com/googleapis/python-bigquery.git |
| octolytics-dimension-user_id | 16785467 |
| octolytics-dimension-user_login | googleapis |
| octolytics-dimension-repository_id | 226992475 |
| octolytics-dimension-repository_nwo | googleapis/python-bigquery |
| octolytics-dimension-repository_public | true |
| octolytics-dimension-repository_is_fork | false |
| octolytics-dimension-repository_network_root_id | 226992475 |
| octolytics-dimension-repository_network_root_nwo | googleapis/python-bigquery |
| turbo-body-classes | logged-out env-production page-responsive |
| disable-turbo | false |
| browser-stats-url | https://api.github.com/_private/browser/stats |
| browser-errors-url | https://api.github.com/_private/browser/errors |
| release | 1d344bdb7547fe6bca17a59bb2b8aac3dc9532a0 |
| ui-target | full |
| theme-color | #1e2327 |
| color-scheme | light dark |
Links:
Viewport: width=device-width