216,816 research outputs found
pandas-dev/pandas: v1.0.0rc0
No full textThis is the first release candidate for 1.0.0. If all goes well, we'll release pandas 1.0.0 in about two weeks.
Highlights include
A new scalar for missing values
Dedicated extension types for string and
nullable boolean data
Using Numba in rolling.apply
A redesigned website and documentation theme
See the whatsnew for a list of all the
changes.
The release can be installed from PyPI
python -m pip install --upgrade --pre pandas==1.0.0rc0
Or from conda-forge
conda install -c conda-forge/label/dev pandas==1.0.0rc0
Please report any issues with the release candidate on the pandas
issue tracker.
To
elfi-dev/elfi: Release v.0.8.5
No full text<p>0.8.5 (2023-03-07)</p>
<ul>
<li>Fix the option to continue inference in model-based inference</li>
<li>Move classifiers</li>
<li>Fix readthedocs configuration</li>
<li>Update penalty to shrinkage parameter conversion in synthetic likelihood calculation</li>
<li>Update BSL pre sample methods</li>
<li>Update BslSample</li>
<li>Move ROMC tests</li>
<li>Update to numpy 1.24</li>
<li>Update readthedocs configuration</li>
<li>Restrict numpy < 1.24 until codebase has been updated</li>
<li>Update documentation-related files: docs, conf.py and requirements-dev.txt</li>
<li>Update PULL_REQUEST_TEMPLATE.md</li>
<li>Drop tests for py36 and add tests for py39 and py310</li>
<li>Fix couple of minor bugs in <code>ar1</code>-model</li>
<li>Update parent class in BOLFIRE</li>
<li>Fix semiparametric synthetic likelihood with glasso/warton and add tests</li>
<li>Fix plot marginals and remove plot summaries</li>
<li>Fix stochastic volatility example</li>
<li>Improve batch simulations in toad example</li>
<li>Remove synthetic likelihood node and update BSL data collection</li>
<li>Fix M/G/1 example</li>
<li>Fix scratch assay example</li>
<li>Add scratch assay example</li>
<li>Add GP classifier for ratio estimation</li>
<li>Fix multidimensional indexing in daycare example</li>
<li>Add BSL method</li>
</ul>
pandas-dev/pandas: v0.25.2
No full text<p>This is a minor bug-fix release in the 0.25.x series and includes some regression fixes
and bug fixes. We recommend that all users upgrade to this version.</p>
<p>See the full <a href="https://pandas.pydata.org/pandas-docs/version/0.25/whatsnew/v0.25.2.html">whatsnew</a> for a list of all the changes.</p>
<p>The release can be installed with conda from the defaults and conda-forge channels:</p>
<pre><code>conda install pandas
</code></pre>
<p>Or via PyPI:</p>
<pre><code>python3 -m pip install --upgrade pandas
</code></pre>
<p>Please report any issues with the release on the <a href="https://github.com/pandas-dev/pandas/issues">pandas issue tracker</a>.</p>
pandas-dev/pandas: Pandas 1.3.2
No full text<p>This is a patch release in the 1.3.x series and includes some regression fixes and bug fixes. We recommend that all users upgrade to this version.</p>
<p>See the <a href="https://pandas.pydata.org/pandas-docs/version/1.3.2/whatsnew/v1.3.2.html">full whatsnew</a> for a list of all the changes.</p>
<p>The release will be available on the defaults and conda-forge channels:</p>
<pre><code>conda install pandas
</code></pre>
<p>Or via PyPI:</p>
<pre><code>python3 -m pip install --upgrade pandas
</code></pre>
<p>Please report any issues with the release on the <a href="https://github.com/pandas-dev/pandas/issues">pandas issue tracker</a>.</p>
pandas-dev/pandas: Pandas 1.1.5
No full text<p>This is a minor bug-fix release in the 1.1.x series and includes some regression fixes
and bug fixes. We recommend that all users upgrade to this version.</p>
<p>See the <a href="https://pandas.pydata.org/pandas-docs/version/1.1.5/whatsnew/v1.1.5.html">full whatsnew</a> for a list of all the changes.</p>
<p>The release will be available on the defaults and conda-forge channels:</p>
<pre><code>conda install pandas
</code></pre>
<p>Or via PyPI:</p>
<pre><code>python3 -m pip install --upgrade pandas
</code></pre>
<p>Please report any issues with the release on the <a href="https://github.com/pandas-dev/pandas/issues">pandas issue tracker</a>.</p>
pandas-dev/pandas: Pandas 1.4.1
No full text<p>This is the first patch release in the 1.4.x series and includes some regression fixes and bug fixes. We recommend that all users upgrade to this version.</p>
<p>See the <a href="https://pandas.pydata.org/pandas-docs/version/1.4.1/whatsnew/v1.4.1.html">full whatsnew</a> for a list of all the changes.</p>
<p>The release will be available on the defaults and conda-forge channels:</p>
<pre><code>conda install pandas
</code></pre>
<p>Or via PyPI:</p>
<pre><code>python3 -m pip install --upgrade pandas
</code></pre>
<p>Please report any issues with the release on the <a href="https://github.com/pandas-dev/pandas/issues">pandas issue tracker</a>.</p>
pandas-dev/pandas: Pandas 1.0.4
No full text<p>This is a minor bug-fix release in the 1.0.x series and includes some regression fixes
and bug fixes. We recommend that all users upgrade to this version.</p>
<p>See the <a href="https://pandas.pydata.org/docs/whatsnew/v1.0.4.html">full whatsnew</a> for a list of all the changes.</p>
<p>The release will be available on the defaults and conda-forge channels:</p>
<pre><code>conda install pandas
</code></pre>
<p>Or via PyPI:</p>
<pre><code>python3 -m pip install --upgrade pandas
</code></pre>
<p>Please report any issues with the release on the <a href="https://github.com/pandas-dev/pandas/issues">pandas issue tracker</a>.</p>
Development Software 1(EXT YR 2): EDEV 120/EDEV 130, DEV 12EO / DEV 13EO
No full textExamination Development Software 1(EXT YR 2): EDEV 120/EDEV 130, DEV 12EO / DEV 13EO, Nov 201
A comment on Liberalization and food price distribution: ARCH-M evidence from Madagascar (Barrett, 1997)
No full textThis paper revisits that of Barrett, published in Food Po licy in 1997. Even if Barrett resorted to the use of the appropriate methodology, ARCH - M models, it would appear that he misinterpreted its philosophy, just as he misspecified the variance equation of the ARCH. This led him to a spurious modeling at severa l levels, methodological and theoretical. Using food price time series (as Barrett did), we first explain the inconsistencies in Barrett (1997) and then we propose three modeling procedures: that of Engle, Lilien and Robins (1987) and then two others simil ar to Barrett's, but differing by the fact that one is carried out with good identification of the time series data generating process, and the second without. These three models allowed us to apprehend the gap between results of a "correct" ARCH - M model a nd those of Barrett. The interest of this comment on is to highlight few irregularities of drawn conclusions that were subject to economic recommendations at that time, and also that are being largely replicated in agricultural economic papers
L'esaltazione della Dea: un breve approccio al Devī-Māhātmya
No full textIntroduzione al ms. Tessitori e al Devī-Māhātmya
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