DEPS: drop numpy < 1.12 (#23062)

Author: h-vetinari

ci/azure-macos-35.yaml

@@ -8,10 +8,10 @@ dependencies:
   - html5lib
   - jinja2
   - lxml
-  - matplotlib
+  - matplotlib=2.2.0
   - nomkl
   - numexpr
-  - numpy=1.10.4
+  - numpy=1.12.0
   - openpyxl=2.5.5
   - pytables
   - python=3.5*

ci/azure-windows-27.yaml

@@ -10,7 +10,7 @@ dependencies:
   - html5lib
   - jinja2=2.8
   - lxml
-  - matplotlib
+  - matplotlib=2.0.1
   - numexpr
   - numpy=1.12*
   - openpyxl=2.5.5

ci/azure/macos.yml

@@ -9,7 +9,7 @@ jobs:
   strategy:
     maxParallel: 11
     matrix:
-      py35_np_110:
+      py35_np_120:
         ENV_FILE: ci/azure-macos-35.yaml
         CONDA_PY: "35"
         CONDA_ENV: pandas

ci/azure/windows-py27.yml

@@ -9,7 +9,7 @@ jobs:
   strategy:
     maxParallel: 11
     matrix:
-      py36_np14:
+      py36_np121:
         ENV_FILE: ci/azure-windows-27.yaml
         CONDA_PY: "27"
         CONDA_ENV: pandas

ci/circle-27-compat.yaml

@@ -3,18 +3,18 @@ channels:
   - defaults
   - conda-forge
 dependencies:
-  - bottleneck=1.0.0
+  - bottleneck=1.2.0
   - cython=0.28.2
   - jinja2=2.8
-  - numexpr=2.4.4 # we test that we correctly don't use an unsupported numexpr
-  - numpy=1.9.3
+  - numexpr=2.6.1
+  - numpy=1.12.0
   - openpyxl=2.5.5
   - psycopg2
-  - pytables=3.2.2
+  - pytables=3.4.2
   - python-dateutil=2.5.0
   - python=2.7*
   - pytz=2013b
-  - scipy=0.14.0
+  - scipy=0.18.1
   - sqlalchemy=0.7.8
   - xlrd=0.9.2
   - xlsxwriter=0.5.2

ci/requirements-optional-conda.txt

@@ -1,6 +1,6 @@
 beautifulsoup4>=4.2.1
 blosc
-bottleneck
+bottleneck>=1.2.0
 fastparquet
 feather-format
 gcsfs
@@ -9,17 +9,17 @@ ipython>=5.6.0
 ipykernel
 jinja2
 lxml
-matplotlib
+matplotlib>=2.0.0
 nbsphinx
-numexpr
+numexpr>=2.6.1
 openpyxl=2.5.5
 pyarrow
 pymysql
-pytables
+pytables>=3.4.2
 pytest-cov
 pytest-xdist
 s3fs
-scipy
+scipy>=0.18.1
 seaborn
 sqlalchemy
 statsmodels

ci/requirements-optional-pip.txt

@@ -2,7 +2,7 @@
 # Do not modify directly
 beautifulsoup4>=4.2.1
 blosc
-bottleneck
+bottleneck>=1.2.0
 fastparquet
 feather-format
 gcsfs
@@ -11,17 +11,17 @@ ipython>=5.6.0
 ipykernel
 jinja2
 lxml
-matplotlib
+matplotlib>=2.0.0
 nbsphinx
-numexpr
+numexpr>=2.6.1
 openpyxl==2.5.5
 pyarrow
 pymysql
 tables
 pytest-cov
 pytest-xdist
 s3fs
-scipy
+scipy>=0.18.1
 seaborn
 sqlalchemy
 statsmodels

ci/travis-27-locale.yaml

@@ -3,11 +3,11 @@ channels:
   - defaults
   - conda-forge
 dependencies:
-  - bottleneck=1.0.0
+  - bottleneck=1.2.0
   - cython=0.28.2
   - lxml
-  - matplotlib=1.4.3
-  - numpy=1.9.3
+  - matplotlib=2.0.0
+  - numpy=1.12.0
   - openpyxl=2.4.0
   - python-dateutil
   - python-blosc

ci/travis-27.yaml

@@ -14,7 +14,7 @@ dependencies:
   - jemalloc=4.5.0.post
   - jinja2=2.8
   - lxml
-  - matplotlib
+  - matplotlib=2.2.2
   - mock
   - nomkl
   - numexpr

doc/source/install.rst

@@ -225,7 +225,7 @@ Dependencies
 ------------
 
 * `setuptools <https://setuptools.readthedocs.io/en/latest/>`__: 24.2.0 or higher
-* `NumPy <http://www.numpy.org>`__: 1.9.0 or higher
+* `NumPy <http://www.numpy.org>`__: 1.12.0 or higher
 * `python-dateutil <https://dateutil.readthedocs.io/en/stable/>`__: 2.5.0 or higher
 * `pytz <http://pytz.sourceforge.net/>`__
 
@@ -236,11 +236,11 @@ Recommended Dependencies
 
 * `numexpr <https://github.com/pydata/numexpr>`__: for accelerating certain numerical operations.
   ``numexpr`` uses multiple cores as well as smart chunking and caching to achieve large speedups.
-  If installed, must be Version 2.4.6 or higher.
+  If installed, must be Version 2.6.1 or higher.
 
 * `bottleneck <https://github.com/kwgoodman/bottleneck>`__: for accelerating certain types of ``nan``
   evaluations. ``bottleneck`` uses specialized cython routines to achieve large speedups. If installed,
-  must be Version 1.0.0 or higher.
+  must be Version 1.2.0 or higher.
 
 .. note::
 
@@ -255,9 +255,9 @@ Optional Dependencies
 
 * `Cython <http://www.cython.org>`__: Only necessary to build development
   version. Version 0.28.2 or higher.
-* `SciPy <http://www.scipy.org>`__: miscellaneous statistical functions, Version 0.14.0 or higher
+* `SciPy <http://www.scipy.org>`__: miscellaneous statistical functions, Version 0.18.1 or higher
 * `xarray <http://xarray.pydata.org>`__: pandas like handling for > 2 dims, needed for converting Panels to xarray objects. Version 0.7.0 or higher is recommended.
-* `PyTables <http://www.pytables.org>`__: necessary for HDF5-based storage. Version 3.0.0 or higher required, Version 3.2.1 or higher highly recommended.
+* `PyTables <http://www.pytables.org>`__: necessary for HDF5-based storage, Version 3.4.2 or higher
 * `Feather Format <https://github.com/wesm/feather>`__: necessary for feather-based storage, version 0.3.1 or higher.
 * `Apache Parquet <https://parquet.apache.org/>`__, either `pyarrow <http://arrow.apache.org/docs/python/>`__ (>= 0.4.1) or `fastparquet <https://fastparquet.readthedocs.io/en/latest>`__ (>= 0.0.6) for parquet-based storage. The `snappy <https://pypi.org/project/python-snappy>`__ and `brotli <https://pypi.org/project/brotlipy>`__ are available for compression support.
 * `SQLAlchemy <http://www.sqlalchemy.org>`__: for SQL database support. Version 0.8.1 or higher recommended. Besides SQLAlchemy, you also need a database specific driver. You can find an overview of supported drivers for each SQL dialect in the `SQLAlchemy docs <http://docs.sqlalchemy.org/en/latest/dialects/index.html>`__. Some common drivers are:
@@ -266,7 +266,7 @@ Optional Dependencies
     * `pymysql <https://github.com/PyMySQL/PyMySQL>`__: for MySQL.
     * `SQLite <https://docs.python.org/3/library/sqlite3.html>`__: for SQLite, this is included in Python's standard library by default.
 
-* `matplotlib <http://matplotlib.org/>`__: for plotting, Version 1.4.3 or higher.
+* `matplotlib <http://matplotlib.org/>`__: for plotting, Version 2.0.0 or higher.
 * For Excel I/O:
 
     * `xlrd/xlwt <http://www.python-excel.org/>`__: Excel reading (xlrd) and writing (xlwt)