{"action":"created","issue":{"url":"https://api.github.com/repos/pydata/pandas/issues/11304","labels_url":"https://api.github.com/repos/pydata/pandas/issues/11304/labels{/name}","comments_url":"https://api.github.com/repos/pydata/pandas/issues/11304/comments","events_url":"https://api.github.com/repos/pydata/pandas/issues/11304/events","html_url":"https://github.com/pydata/pandas/issues/11304","id":111061362,"number":11304,"title":"Incorrect match for pd.Term with Categorical at read_hdf","user":{"login":"michaelaye","id":69774,"avatar_url":"https://avatars.githubusercontent.com/u/69774?v=3","gravatar_id":"","url":"https://api.github.com/users/michaelaye","html_url":"https://github.com/michaelaye","followers_url":"https://api.github.com/users/michaelaye/followers","following_url":"https://api.github.com/users/michaelaye/following{/other_user}","gists_url":"https://api.github.com/users/michaelaye/gists{/gist_id}","starred_url":"https://api.github.com/users/michaelaye/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/michaelaye/subscriptions","organizations_url":"https://api.github.com/users/michaelaye/orgs","repos_url":"https://api.github.com/users/michaelaye/repos","events_url":"https://api.github.com/users/michaelaye/events{/privacy}","received_events_url":"https://api.github.com/users/michaelaye/received_events","type":"User","site_admin":false},"labels":[{"url":"https://api.github.com/repos/pydata/pandas/labels/IO%20HDF5","name":"IO HDF5","color":"5319e7"}],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":14,"created_at":"2015-10-12T21:40:48Z","updated_at":"2015-10-13T06:14:23Z","closed_at":null,"body":"In below screenshot, I am scanning the database for a categorical called `classification_id` with the value `50ef44b795e6e42cd2000001` but I am getting a data-row where the categorical has the value 50ef44b795e6e42cd6000001`.\r\n\r\nHow is this possible? Note that my list of categorical is huge, more than 4 million entries, with 12 million total rows. (Yes, on average, each classification_id appears 3 times.)\r\n\r\n<img width=\"931\" alt=\"screenshot 2015-10-12 15 31 25\" src=\"https://cloud.githubusercontent.com/assets/69774/10439330/7755e45a-70f6-11e5-9dc6-26ee7359d95a.png\">\r\n\r\nOn a side note: The display of this one row of numpy in the line with `.values` at the end takes a lot of time, possibly due to large size of the Categorical, can that be avoided somehow?\r\n\r\n\r\nHere's my required meta-data for the bug report:\r\npandas Version: 0.17.0\r\n\r\nINSTALLED VERSIONS\r\n------------------\r\ncommit: None\r\npython: 3.4.3.final.0\r\npython-bits: 64\r\nOS: Darwin\r\nOS-release: 14.5.0\r\nmachine: x86_64\r\nprocessor: i386\r\nbyteorder: little\r\nLC_ALL: None\r\nLANG: en_US.UTF-8\r\n\r\npandas: 0.17.0\r\nnose: 1.3.7\r\npip: 7.1.2\r\nsetuptools: 18.3.2\r\nCython: None\r\nnumpy: 1.10.0\r\nscipy: 0.16.0\r\nstatsmodels: None\r\nIPython: 4.1.0-dev\r\nsphinx: None\r\npatsy: None\r\ndateutil: 2.4.2\r\npytz: 2015.6\r\nblosc: None\r\nbottleneck: None\r\ntables: 3.2.2\r\nnumexpr: 2.4.4\r\nmatplotlib: 1.4.3\r\nopenpyxl: None\r\nxlrd: None\r\nxlwt: None\r\nxlsxwriter: None\r\nlxml: None\r\nbs4: None\r\nhtml5lib: None\r\nhttplib2: None\r\napiclient: None\r\nsqlalchemy: 1.0.8\r\npymysql: None\r\npsycopg2: None"},"comment":{"url":"https://api.github.com/repos/pydata/pandas/issues/comments/147616065","html_url":"https://github.com/pydata/pandas/issues/11304#issuecomment-147616065","issue_url":"https://api.github.com/repos/pydata/pandas/issues/11304","id":147616065,"user":{"login":"michaelaye","id":69774,"avatar_url":"https://avatars.githubusercontent.com/u/69774?v=3","gravatar_id":"","url":"https://api.github.com/users/michaelaye","html_url":"https://github.com/michaelaye","followers_url":"https://api.github.com/users/michaelaye/followers","following_url":"https://api.github.com/users/michaelaye/following{/other_user}","gists_url":"https://api.github.com/users/michaelaye/gists{/gist_id}","starred_url":"https://api.github.com/users/michaelaye/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/michaelaye/subscriptions","organizations_url":"https://api.github.com/users/michaelaye/orgs","repos_url":"https://api.github.com/users/michaelaye/repos","events_url":"https://api.github.com/users/michaelaye/events{/privacy}","received_events_url":"https://api.github.com/users/michaelaye/received_events","type":"User","site_admin":false},"created_at":"2015-10-13T06:14:23Z","updated_at":"2015-10-13T06:14:23Z","body":"So, I read in the whole dataframe, as above, it works in memory, and then saved it again, with exactly the same problem. (But, interestingly, half the size of the HDF file?). That should mean, that I'm not doing anything wrong, correct?"}}