{"action":"created","issue":{"url":"https://api.github.com/repos/ecorithm/eco_connect/issues/45","repository_url":"https://api.github.com/repos/ecorithm/eco_connect","labels_url":"https://api.github.com/repos/ecorithm/eco_connect/issues/45/labels{/name}","comments_url":"https://api.github.com/repos/ecorithm/eco_connect/issues/45/comments","events_url":"https://api.github.com/repos/ecorithm/eco_connect/issues/45/events","html_url":"https://github.com/ecorithm/eco_connect/pull/45","id":339817250,"node_id":"MDExOlB1bGxSZXF1ZXN0MjAwMzc2NzI3","number":45,"title":"Scheduled daily dependency update on tuesday","user":{"login":"pyup-bot","id":16239342,"node_id":"MDQ6VXNlcjE2MjM5MzQy","avatar_url":"https://avatars0.githubusercontent.com/u/16239342?v=4","gravatar_id":"","url":"https://api.github.com/users/pyup-bot","html_url":"https://github.com/pyup-bot","followers_url":"https://api.github.com/users/pyup-bot/followers","following_url":"https://api.github.com/users/pyup-bot/following{/other_user}","gists_url":"https://api.github.com/users/pyup-bot/gists{/gist_id}","starred_url":"https://api.github.com/users/pyup-bot/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/pyup-bot/subscriptions","organizations_url":"https://api.github.com/users/pyup-bot/orgs","repos_url":"https://api.github.com/users/pyup-bot/repos","events_url":"https://api.github.com/users/pyup-bot/events{/privacy}","received_events_url":"https://api.github.com/users/pyup-bot/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2018-07-10T12:19:08Z","updated_at":"2018-07-10T12:21:03Z","closed_at":null,"author_association":"CONTRIBUTOR","pull_request":{"url":"https://api.github.com/repos/ecorithm/eco_connect/pulls/45","html_url":"https://github.com/ecorithm/eco_connect/pull/45","diff_url":"https://github.com/ecorithm/eco_connect/pull/45.diff","patch_url":"https://github.com/ecorithm/eco_connect/pull/45.patch"},"body":"\n\n\n\n\n### Update [pandas](https://pypi.org/project/pandas) from **0.23.0** to **0.23.3**.\n\n\n<details>\n  <summary>Changelog</summary>\n  \n  \n   ### 0.23.3\n   ```\n   ----------------------\n\nThis release fixes a build issue with the sdist for Python 3.7 (:issue:`21785`)\nThere are no other changes.\n\n\n.. _whatsnew_0180:\n   ```\n   \n  \n  \n   ### 0.23.2\n   ```\n   ----------------------\n\nThis is a minor bug-fix release in the 0.23.x series and includes some small regression fixes\nand bug fixes. We recommend that all users upgrade to this version.\n\n.. note::\n\n   Pandas 0.23.2 is first pandas release that&#39;s compatible with\n   Python 3.7 (:issue:`20552`)\n\n\n.. contents:: What&#39;s new in v0.23.2\n    :local:\n    :backlinks: none\n\n.. _whatsnew_0232.enhancements:\n\nLogical Reductions over Entire DataFrame\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n:meth:`DataFrame.all` and :meth:`DataFrame.any` now accept ``axis=None`` to reduce over all axes to a scalar (:issue:`19976`)\n\n.. ipython:: python\n\n   df = pd.DataFrame({&quot;A&quot;: [1, 2], &quot;B&quot;: [True, False]})\n   df.all(axis=None)\n\n\nThis also provides compatibility with NumPy 1.15, which now dispatches to ``DataFrame.all``.\nWith NumPy 1.15 and pandas 0.23.1 or earlier, :func:`numpy.all` will no longer reduce over every axis:\n\n.. code-block:: python\n\n   &gt;&gt;&gt;  NumPy 1.15, pandas 0.23.1\n   &gt;&gt;&gt; np.any(pd.DataFrame({&quot;A&quot;: [False], &quot;B&quot;: [False]}))\n   A    False\n   B    False\n   dtype: bool\n\nWith pandas 0.23.2, that will correctly return False, as it did with NumPy &lt; 1.15.\n\n.. ipython:: python\n\n   np.any(pd.DataFrame({&quot;A&quot;: [False], &quot;B&quot;: [False]}))\n\n\n.. _whatsnew_0232.fixed_regressions:\n\nFixed Regressions\n~~~~~~~~~~~~~~~~~\n\n- Fixed regression in :meth:`to_csv` when handling file-like object incorrectly (:issue:`21471`)\n- Re-allowed duplicate level names of a ``MultiIndex``. Accessing a level that has a duplicate name by name still raises an error (:issue:`19029`).\n- Bug in both :meth:`DataFrame.first_valid_index` and :meth:`Series.first_valid_index` raised for a row index having duplicate values (:issue:`21441`)\n- Fixed printing of DataFrames with hierarchical columns with long names (:issue:`21180`)\n- Fixed regression in :meth:`~DataFrame.reindex` and :meth:`~DataFrame.groupby`\n  with a MultiIndex or multiple keys that contains categorical datetime-like values (:issue:`21390`).\n- Fixed regression in unary negative operations with object dtype (:issue:`21380`)\n- Bug in :meth:`Timestamp.ceil` and :meth:`Timestamp.floor` when timestamp is a multiple of the rounding frequency (:issue:`21262`)\n- Fixed regression in :func:`to_clipboard` that defaulted to copying dataframes with space delimited instead of tab delimited (:issue:`21104`)\n\n\nBuild Changes\n~~~~~~~~~~~~~\n\n- The source and binary distributions no longer include test data files, resulting in smaller download sizes. Tests relying on these data files will be skipped when using ``pandas.test()``. (:issue:`19320`)\n\n.. _whatsnew_0232.bug_fixes:\n\nBug Fixes\n~~~~~~~~~\n\n**Conversion**\n\n- Bug in constructing :class:`Index` with an iterator or generator (:issue:`21470`)\n- Bug in :meth:`Series.nlargest` for signed and unsigned integer dtypes when the minimum value is present (:issue:`21426`)\n\n**Indexing**\n\n- Bug in :meth:`Index.get_indexer_non_unique` with categorical key (:issue:`21448`)\n- Bug in comparison operations for :class:`MultiIndex` where error was raised on equality / inequality comparison involving a MultiIndex with ``nlevels == 1`` (:issue:`21149`)\n- Bug in :meth:`DataFrame.drop` behaviour is not consistent for unique and non-unique indexes (:issue:`21494`)\n- Bug in :func:`DataFrame.duplicated` with a large number of columns causing a &#39;maximum recursion depth exceeded&#39; (:issue:`21524`).\n\n**I/O**\n\n- Bug in :func:`read_csv` that caused it to incorrectly raise an error when ``nrows=0``, ``low_memory=True``, and ``index_col`` was not ``None`` (:issue:`21141`)\n- Bug in :func:`json_normalize` when formatting the ``record_prefix`` with integer columns (:issue:`21536`)\n\n**Categorical**\n\n- Bug in rendering :class:`Series` with ``Categorical`` dtype in rare conditions under Python 2.7 (:issue:`21002`)\n\n**Timezones**\n\n- Bug in :class:`Timestamp` and :class:`DatetimeIndex` where passing a :class:`Timestamp` localized after a DST transition would return a datetime before the DST transition (:issue:`20854`)\n- Bug in comparing :class:`DataFrame`s with tz-aware :class:`DatetimeIndex` columns with a DST transition that raised a ``KeyError`` (:issue:`19970`)\n\n**Timedelta**\n\n- Bug in :class:`Timedelta` where non-zero timedeltas shorter than 1 microsecond were considered False (:issue:`21484`)\n\n\n\n.. _whatsnew_050:\n   ```\n   \n  \n  \n   ### 0.23.1\n   ```\n   -----------------------\n\nThis is a minor bug-fix release in the 0.23.x series and includes some small regression fixes\nand bug fixes. We recommend that all users upgrade to this version.\n\n.. contents:: What&#39;s new in v0.23.1\n    :local:\n    :backlinks: none\n\n.. _whatsnew_0231.fixed_regressions:\n\nFixed Regressions\n~~~~~~~~~~~~~~~~~\n\n**Comparing Series with datetime.date**\n\nWe&#39;ve reverted a 0.23.0 change to comparing a :class:`Series` holding datetimes and a ``datetime.date`` object (:issue:`21152`).\nIn pandas 0.22 and earlier, comparing a Series holding datetimes and ``datetime.date`` objects would coerce the ``datetime.date`` to a datetime before comapring.\nThis was inconsistent with Python, NumPy, and :class:`DatetimeIndex`, which never consider a datetime and ``datetime.date`` equal.\n\nIn 0.23.0, we unified operations between DatetimeIndex and Series, and in the process changed comparisons between a Series of datetimes and ``datetime.date`` without warning.\n\nWe&#39;ve temporarily restored the 0.22.0 behavior, so datetimes and dates may again compare equal, but restore the 0.23.0 behavior in a future release.\n\nTo summarize, here&#39;s the behavior in 0.22.0, 0.23.0, 0.23.1:\n\n.. code-block:: python\n\n    0.22.0... Silently coerce the datetime.date\n   &gt;&gt;&gt; Series(pd.date_range(&#39;2017&#39;, periods=2)) == datetime.date(2017, 1, 1)\n   0     True\n   1    False\n   dtype: bool\n\n    0.23.0... Do not coerce the datetime.date\n   &gt;&gt;&gt; Series(pd.date_range(&#39;2017&#39;, periods=2)) == datetime.date(2017, 1, 1)\n   0    False\n   1    False\n   dtype: bool\n\n    0.23.1... Coerce the datetime.date with a warning\n   &gt;&gt;&gt; Series(pd.date_range(&#39;2017&#39;, periods=2)) == datetime.date(2017, 1, 1)\n   /bin/python:1: FutureWarning: Comparing Series of datetimes with &#39;datetime.date&#39;.  Currently, the\n   &#39;datetime.date&#39; is coerced to a datetime. In the future pandas will\n   not coerce, and the values not compare equal to the &#39;datetime.date&#39;.\n   To retain the current behavior, convert the &#39;datetime.date&#39; to a\n   datetime with &#39;pd.Timestamp&#39;.\n     !/bin/python3\n   0     True\n   1    False\n   dtype: bool\n\nIn addition, ordering comparisons will raise a ``TypeError`` in the future.\n\n**Other Fixes**\n\n- Reverted the ability of :func:`~DataFrame.to_sql` to perform multivalue\n  inserts as this caused regression in certain cases (:issue:`21103`).\n  In the future this will be made configurable.\n- Fixed regression in the :attr:`DatetimeIndex.date` and :attr:`DatetimeIndex.time`\n  attributes in case of timezone-aware data: :attr:`DatetimeIndex.time` returned\n  a tz-aware time instead of tz-naive (:issue:`21267`) and :attr:`DatetimeIndex.date`\n  returned incorrect date when the input date has a non-UTC timezone (:issue:`21230`).\n- Fixed regression in :meth:`pandas.io.json.json_normalize` when called with ``None`` values\n  in nested levels in JSON, and to not drop keys with value as `None` (:issue:`21158`, :issue:`21356`).\n- Bug in :meth:`~DataFrame.to_csv` causes encoding error when compression and encoding are specified (:issue:`21241`, :issue:`21118`)\n- Bug preventing pandas from being importable with -OO optimization (:issue:`21071`)\n- Bug in :meth:`Categorical.fillna` incorrectly raising a ``TypeError`` when `value` the individual categories are iterable and `value` is an iterable (:issue:`21097`, :issue:`19788`)\n- Fixed regression in constructors coercing NA values like ``None`` to strings when passing ``dtype=str`` (:issue:`21083`)\n- Regression in :func:`pivot_table` where an ordered ``Categorical`` with missing\n  values for the pivot&#39;s ``index`` would give a mis-aligned result (:issue:`21133`)\n- Fixed regression in merging on boolean index/columns (:issue:`21119`).\n\n.. _whatsnew_0231.performance:\n\nPerformance Improvements\n~~~~~~~~~~~~~~~~~~~~~~~~\n\n- Improved performance of :meth:`CategoricalIndex.is_monotonic_increasing`, :meth:`CategoricalIndex.is_monotonic_decreasing` and :meth:`CategoricalIndex.is_monotonic` (:issue:`21025`)\n- Improved performance of :meth:`CategoricalIndex.is_unique` (:issue:`21107`)\n\n\n.. _whatsnew_0231.bug_fixes:\n\nBug Fixes\n~~~~~~~~~\n\n**Groupby/Resample/Rolling**\n\n- Bug in :func:`DataFrame.agg` where applying multiple aggregation functions to a :class:`DataFrame` with duplicated column names would cause a stack overflow (:issue:`21063`)\n- Bug in :func:`pandas.core.groupby.GroupBy.ffill` and :func:`pandas.core.groupby.GroupBy.bfill` where the fill within a grouping would not always be applied as intended due to the implementations&#39; use of a non-stable sort (:issue:`21207`)\n- Bug in :func:`pandas.core.groupby.GroupBy.rank` where results did not scale to 100% when specifying ``method=&#39;dense&#39;`` and ``pct=True``\n- Bug in :func:`pandas.DataFrame.rolling` and :func:`pandas.Series.rolling` which incorrectly accepted a 0 window size rather than raising (:issue:`21286`)\n\n**Data-type specific**\n\n- Bug in :meth:`Series.str.replace()` where the method throws `TypeError` on Python 3.5.2 (:issue:`21078`)\n- Bug in :class:`Timedelta` where passing a float with a unit would prematurely round the float precision (:issue:`14156`)\n- Bug in :func:`pandas.testing.assert_index_equal` which raised ``AssertionError`` incorrectly, when comparing two :class:`CategoricalIndex` objects with param ``check_categorical=False`` (:issue:`19776`)\n\n**Sparse**\n\n- Bug in :attr:`SparseArray.shape` which previously only returned the shape :attr:`SparseArray.sp_values` (:issue:`21126`)\n\n**Indexing**\n\n- Bug in :meth:`Series.reset_index` where appropriate error was not raised with an invalid level name (:issue:`20925`)\n- Bug in :func:`interval_range` when ``start``/``periods`` or ``end``/``periods`` are specified with float ``start`` or ``end`` (:issue:`21161`)\n- Bug in :meth:`MultiIndex.set_names` where error raised for a ``MultiIndex`` with ``nlevels == 1`` (:issue:`21149`)\n- Bug in :class:`IntervalIndex` constructors where creating an ``IntervalIndex`` from categorical data was not fully supported (:issue:`21243`, :issue:`21253`)\n- Bug in :meth:`MultiIndex.sort_index` which was not guaranteed to sort correctly with ``level=1``; this was also causing data misalignment in particular :meth:`DataFrame.stack` operations (:issue:`20994`, :issue:`20945`, :issue:`21052`)\n\n**Plotting**\n\n- New keywords (sharex, sharey) to turn on/off sharing of x/y-axis by subplots generated with pandas.DataFrame().groupby().boxplot() (:issue:`20968`)\n\n**I/O**\n\n- Bug in IO methods specifying ``compression=&#39;zip&#39;`` which produced uncompressed zip archives (:issue:`17778`, :issue:`21144`)\n- Bug in :meth:`DataFrame.to_stata` which prevented exporting DataFrames to buffers and most file-like objects (:issue:`21041`)\n- Bug in :meth:`read_stata` and :class:`StataReader` which did not correctly decode utf-8 strings on Python 3 from Stata 14 files (dta version 118) (:issue:`21244`)\n- Bug in IO JSON :func:`read_json` reading empty JSON schema with ``orient=&#39;table&#39;`` back to :class:`DataFrame` caused an error (:issue:`21287`)\n\n**Reshaping**\n\n- Bug in :func:`concat` where error was raised in concatenating :class:`Series` with numpy scalar and tuple names (:issue:`21015`)\n- Bug in :func:`concat` warning message providing the wrong guidance for future behavior (:issue:`21101`)\n\n**Other**\n\n- Tab completion on :class:`Index` in IPython no longer outputs deprecation warnings (:issue:`21125`)\n- Bug preventing pandas being used on Windows without C++ redistributable installed (:issue:`21106`)\n\n\n.. _whatsnew_080:\n   ```\n   \n  \n</details>\n\n\n \n\n<details>\n  <summary>Links</summary>\n  \n  - PyPI: https://pypi.org/project/pandas\n  - Changelog: https://pyup.io/changelogs/pandas/\n  - Homepage: http://pandas.pydata.org\n</details>\n\n\n\n\n\n"},"comment":{"url":"https://api.github.com/repos/ecorithm/eco_connect/issues/comments/403802333","html_url":"https://github.com/ecorithm/eco_connect/pull/45#issuecomment-403802333","issue_url":"https://api.github.com/repos/ecorithm/eco_connect/issues/45","id":403802333,"node_id":"MDEyOklzc3VlQ29tbWVudDQwMzgwMjMzMw==","user":{"login":"coveralls","id":2354108,"node_id":"MDQ6VXNlcjIzNTQxMDg=","avatar_url":"https://avatars1.githubusercontent.com/u/2354108?v=4","gravatar_id":"","url":"https://api.github.com/users/coveralls","html_url":"https://github.com/coveralls","followers_url":"https://api.github.com/users/coveralls/followers","following_url":"https://api.github.com/users/coveralls/following{/other_user}","gists_url":"https://api.github.com/users/coveralls/gists{/gist_id}","starred_url":"https://api.github.com/users/coveralls/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/coveralls/subscriptions","organizations_url":"https://api.github.com/users/coveralls/orgs","repos_url":"https://api.github.com/users/coveralls/repos","events_url":"https://api.github.com/users/coveralls/events{/privacy}","received_events_url":"https://api.github.com/users/coveralls/received_events","type":"User","site_admin":false},"created_at":"2018-07-10T12:21:03Z","updated_at":"2018-07-10T12:21:03Z","author_association":"NONE","body":"## Pull Request Test Coverage Report for [Build 150](https://coveralls.io/builds/17912696)\n\n* **0** of **0**   changed or added relevant lines in **0** files are covered.\n* No unchanged relevant lines lost coverage.\n* Overall coverage remained the same at **100.0%**\n\n---\n\n\n\n|  Totals | [![Coverage Status](https://coveralls.io/builds/17912696/badge)](https://coveralls.io/builds/17912696) |\n| :-- | --: |\n| Change from base [Build 66](https://coveralls.io/builds/17150847): |  0.0% |\n| Covered Lines: | 421 |\n| Relevant Lines: | 421 |\n\n---\n##### 💛  - [Coveralls](https://coveralls.io)\n"}}
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