{"action":"created","comment":{"url":"https://api.github.com/repos/pandas-dev/pandas/pulls/comments/219704387","pull_request_review_id":157944752,"id":219704387,"node_id":"MDI0OlB1bGxSZXF1ZXN0UmV2aWV3Q29tbWVudDIxOTcwNDM4Nw==","diff_hunk":"@@ -36,114 +36,28 @@\n _shared_docs = dict()\n \n \n-def _get_array_list(arr, others):\n-    \"\"\"\n-    Auxiliary function for :func:`str_cat`\n-\n-    Parameters\n-    ----------\n-    arr : ndarray\n-        The left-most ndarray of the concatenation\n-    others : list, ndarray, Series\n-        The rest of the content to concatenate. If list of list-likes,\n-        all elements must be passable to ``np.asarray``.\n-\n-    Returns\n-    -------\n-    list\n-        List of all necessary arrays\n-    \"\"\"\n-    from pandas.core.series import Series\n-\n-    if len(others) and isinstance(com.values_from_object(others)[0],\n-                                  (list, np.ndarray, Series)):\n-        arrays = [arr] + list(others)\n-    else:\n-        arrays = [arr, others]\n-\n-    return [np.asarray(x, dtype=object) for x in arrays]\n-\n-\n-def str_cat(arr, others=None, sep=None, na_rep=None):\n-    \"\"\"\n+def interleave_sep(all_cols, sep):\n+    '''","path":"pandas/core/strings.py","position":44,"original_position":44,"commit_id":"fcd11b5ed53c82e60e7121f90651fa0d72d908c0","original_commit_id":"fcd11b5ed53c82e60e7121f90651fa0d72d908c0","user":{"login":"jreback","id":953992,"node_id":"MDQ6VXNlcjk1Mzk5Mg==","avatar_url":"https://avatars2.githubusercontent.com/u/953992?v=4","gravatar_id":"","url":"https://api.github.com/users/jreback","html_url":"https://github.com/jreback","followers_url":"https://api.github.com/users/jreback/followers","following_url":"https://api.github.com/users/jreback/following{/other_user}","gists_url":"https://api.github.com/users/jreback/gists{/gist_id}","starred_url":"https://api.github.com/users/jreback/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/jreback/subscriptions","organizations_url":"https://api.github.com/users/jreback/orgs","repos_url":"https://api.github.com/users/jreback/repos","events_url":"https://api.github.com/users/jreback/events{/privacy}","received_events_url":"https://api.github.com/users/jreback/received_events","type":"User","site_admin":false},"body":"use triple-double quotes","created_at":"2018-09-23T16:44:47Z","updated_at":"2018-09-23T16:52:21Z","html_url":"https://github.com/pandas-dev/pandas/pull/22725#discussion_r219704387","pull_request_url":"https://api.github.com/repos/pandas-dev/pandas/pulls/22725","author_association":"CONTRIBUTOR","_links":{"self":{"href":"https://api.github.com/repos/pandas-dev/pandas/pulls/comments/219704387"},"html":{"href":"https://github.com/pandas-dev/pandas/pull/22725#discussion_r219704387"},"pull_request":{"href":"https://api.github.com/repos/pandas-dev/pandas/pulls/22725"}}},"pull_request":{"url":"https://api.github.com/repos/pandas-dev/pandas/pulls/22725","id":215795642,"node_id":"MDExOlB1bGxSZXF1ZXN0MjE1Nzk1NjQy","html_url":"https://github.com/pandas-dev/pandas/pull/22725","diff_url":"https://github.com/pandas-dev/pandas/pull/22725.diff","patch_url":"https://github.com/pandas-dev/pandas/pull/22725.patch","issue_url":"https://api.github.com/repos/pandas-dev/pandas/issues/22725","number":22725,"state":"open","locked":false,"title":"CLN/ERR: str.cat internals","user":{"login":"h-vetinari","id":33685575,"node_id":"MDQ6VXNlcjMzNjg1NTc1","avatar_url":"https://avatars1.githubusercontent.com/u/33685575?v=4","gravatar_id":"","url":"https://api.github.com/users/h-vetinari","html_url":"https://github.com/h-vetinari","followers_url":"https://api.github.com/users/h-vetinari/followers","following_url":"https://api.github.com/users/h-vetinari/following{/other_user}","gists_url":"https://api.github.com/users/h-vetinari/gists{/gist_id}","starred_url":"https://api.github.com/users/h-vetinari/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/h-vetinari/subscriptions","organizations_url":"https://api.github.com/users/h-vetinari/orgs","repos_url":"https://api.github.com/users/h-vetinari/repos","events_url":"https://api.github.com/users/h-vetinari/events{/privacy}","received_events_url":"https://api.github.com/users/h-vetinari/received_events","type":"User","site_admin":false},"body":"This is mainly a clean-up of internal methods for `str.cat` that I didn't want to touch within #20347.\r\n\r\nAs a side benefit of changing the implementation, this also solves #22721. Finally, I've also added a better message for TypeErrors (closes #22722)\r\n\r\n- [x] closes #22721, #22722\r\n- [x] tests modified / passed\r\n- [x] passes `git diff upstream/master -u -- \"*.py\" | flake8 --diff`\r\n- [x] whatsnew entry\r\n\r\nHere's the ASV output (the original implementation of this PR (see first commit) that used more higher-level pandas-functions like `fillna`, `drop_na`, etc. was up to three times slower, so I tweaked it some more, and actually believe that the last solution with `interleave_sep` is the most elegant anyway):\r\n```\r\n       before           after         ratio\r\n     [37455764]       [4d1710f1]\r\n         10.9±1ms         9.11±1ms    ~0.83  strings.Cat.time_cat(0, ',', '-', 0.0)\r\n         9.55±1ms         10.9±0ms    ~1.15  strings.Cat.time_cat(0, ',', '-', 0.001)\r\n         12.5±2ms         14.1±2ms    ~1.12  strings.Cat.time_cat(0, ',', '-', 0.15)\r\n         9.94±1ms       9.23±0.7ms     0.93  strings.Cat.time_cat(0, ',', None, 0.0)\r\n         14.3±2ms         8.68±1ms    ~0.61  strings.Cat.time_cat(0, ',', None, 0.001)\r\n-        13.7±1ms       11.7±0.8ms     0.86  strings.Cat.time_cat(0, ',', None, 0.15)\r\n       9.11±0.7ms         7.81±2ms    ~0.86  strings.Cat.time_cat(0, None, '-', 0.0)\r\n       9.38±0.8ms         10.9±1ms    ~1.17  strings.Cat.time_cat(0, None, '-', 0.001)\r\n         11.4±2ms         10.9±2ms     0.96  strings.Cat.time_cat(0, None, '-', 0.15)\r\n         13.4±2ms       9.38±0.6ms    ~0.70  strings.Cat.time_cat(0, None, None, 0.0)\r\n         9.23±2ms         11.7±1ms    ~1.27  strings.Cat.time_cat(0, None, None, 0.001)\r\n         10.2±2ms         10.9±1ms     1.08  strings.Cat.time_cat(0, None, None, 0.15)\r\n-        70.3±4ms         54.7±4ms     0.78  strings.Cat.time_cat(3, ',', '-', 0.0)\r\n         62.5±4ms        46.9±20ms    ~0.75  strings.Cat.time_cat(3, ',', '-', 0.001)\r\n        93.8±10ms        66.4±10ms    ~0.71  strings.Cat.time_cat(3, ',', '-', 0.15)\r\n         62.5±4ms         62.5±4ms     1.00  strings.Cat.time_cat(3, ',', None, 0.0)\r\n+        46.9±4ms         85.9±4ms     1.83  strings.Cat.time_cat(3, ',', None, 0.001)\r\n         52.1±2ms         50.8±6ms     0.97  strings.Cat.time_cat(3, ',', None, 0.15)\r\n         50.8±8ms         54.7±6ms     1.08  strings.Cat.time_cat(3, None, '-', 0.0)\r\n         54.7±4ms         62.5±4ms    ~1.14  strings.Cat.time_cat(3, None, '-', 0.001)\r\n         62.5±5ms         54.7±3ms    ~0.88  strings.Cat.time_cat(3, None, '-', 0.15)\r\n         46.9±4ms         39.1±0ms    ~0.83  strings.Cat.time_cat(3, None, None, 0.0)\r\n         46.9±8ms         58.6±6ms    ~1.25  strings.Cat.time_cat(3, None, None, 0.001)\r\n         46.9±9ms         54.7±4ms    ~1.17  strings.Cat.time_cat(3, None, None, 0.15)\r\n                                                                  ^  ^     ^     ^\r\n                                                                  |  |     |     |\r\n                                                         other_cols  |   na_rep  |\r\n                                                                     |           |\r\n                                                                    sep        na_frac\r\n```\r\n\r\nThere's a bunch of noise in there, but by and large, things don't look so bad IMO. Especially, when one excludes the not-so-common worst-case scenario of a very small but non-zero amount of NaNs (`na_frac=0.001`):\r\n```\r\n       before           after         ratio\r\n     [37455764]       [4d1710f1]\r\n         10.9±1ms         9.11±1ms    ~0.83  strings.Cat.time_cat(0, ',', '-', 0.0)\r\n         12.5±2ms         14.1±2ms    ~1.12  strings.Cat.time_cat(0, ',', '-', 0.15)\r\n         9.94±1ms       9.23±0.7ms     0.93  strings.Cat.time_cat(0, ',', None, 0.0)\r\n-        13.7±1ms       11.7±0.8ms     0.86  strings.Cat.time_cat(0, ',', None, 0.15)\r\n       9.11±0.7ms         7.81±2ms    ~0.86  strings.Cat.time_cat(0, None, '-', 0.0)\r\n         11.4±2ms         10.9±2ms     0.96  strings.Cat.time_cat(0, None, '-', 0.15)\r\n         13.4±2ms       9.38±0.6ms    ~0.70  strings.Cat.time_cat(0, None, None, 0.0)\r\n         10.2±2ms         10.9±1ms     1.08  strings.Cat.time_cat(0, None, None, 0.15)\r\n-        70.3±4ms         54.7±4ms     0.78  strings.Cat.time_cat(3, ',', '-', 0.0)\r\n         62.5±4ms        46.9±20ms    ~0.75  strings.Cat.time_cat(3, ',', '-', 0.001)\r\n        93.8±10ms        66.4±10ms    ~0.71  strings.Cat.time_cat(3, ',', '-', 0.15)\r\n         62.5±4ms         62.5±4ms     1.00  strings.Cat.time_cat(3, ',', None, 0.0)\r\n         52.1±2ms         50.8±6ms     0.97  strings.Cat.time_cat(3, ',', None, 0.15)\r\n         50.8±8ms         54.7±6ms     1.08  strings.Cat.time_cat(3, None, '-', 0.0)\r\n         62.5±5ms         54.7±3ms    ~0.88  strings.Cat.time_cat(3, None, '-', 0.15)\r\n         46.9±4ms         39.1±0ms    ~0.83  strings.Cat.time_cat(3, None, None, 0.0)\r\n         46.9±9ms         54.7±4ms    ~1.17  strings.Cat.time_cat(3, None, None, 0.15)\r\n                                                                  ^  ^     ^     ^\r\n                                                                  |  |     |     |\r\n                                                         other_cols  |   na_rep  |\r\n                                                                     |           |\r\n                                                                    sep        na_frac\r\n```","created_at":"2018-09-16T00:11:27Z","updated_at":"2018-09-23T16:52:21Z","closed_at":null,"merged_at":null,"merge_commit_sha":"2312b6d2b3a1fbae5463ce5415b7dd489372b194","assignee":null,"assignees":[],"requested_reviewers":[],"requested_teams":[],"labels":[{"id":211029535,"node_id":"MDU6TGFiZWwyMTEwMjk1MzU=","url":"https://api.github.com/repos/pandas-dev/pandas/labels/Clean","name":"Clean","color":"207de5","default":false},{"id":42670965,"node_id":"MDU6TGFiZWw0MjY3MDk2NQ==","url":"https://api.github.com/repos/pandas-dev/pandas/labels/Error%20Reporting","name":"Error 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