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#dask

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Tatu Leppämäki<p>Thank you to <a href="https://mstdn.social/tags/Kone" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Kone</span></a> &amp; Mai and Tor Nessling Foundations for supporting this work. A quantitative work like this would not be possible without a robust suite of FOSS tools. My thanks to the maintainers of <a href="https://mstdn.social/tags/QGIS" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>QGIS</span></a>, <a href="https://mstdn.social/tags/pandas" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>pandas</span></a>, <a href="https://mstdn.social/tags/geopandas" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>geopandas</span></a>, <a href="https://mstdn.social/tags/duckdb" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>duckdb</span></a>, <a href="https://mstdn.social/tags/dask" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>dask</span></a>, <a href="https://mstdn.social/tags/statsmodels" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>statsmodels</span></a>, <a href="https://mstdn.social/tags/jupyter" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>jupyter</span></a> and many more!</p>
Hobson Lane<p><span class="h-card" translate="no"><a href="https://qoto.org/@asm" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>asm</span></a></span> Thank you for introducing me to Xarray (<a href="https://github.com/pydata/xarray" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="">github.com/pydata/xarray</span><span class="invisible"></span></a>) ! Like <a href="https://mstdn.social/tags/Pandas" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Pandas</span></a> but faster simpler and more scalable. It even has labeled dimensions, like a <a href="https://mstdn.social/tags/DataFrame" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DataFrame</span></a>. Looks like it's compatible with <a href="https://mstdn.social/tags/Dask" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Dask</span></a> too. </p><p><a href="https://mstdn.social/tags/numpy" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>numpy</span></a> <a href="https://mstdn.social/tags/BigData" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>BigData</span></a> <a href="https://mstdn.social/tags/WebScale" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>WebScale</span></a> <a href="https://mstdn.social/tags/math" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>math</span></a> <a href="https://mstdn.social/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DeepLearning</span></a> <a href="https://mstdn.social/tags/XArray" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>XArray</span></a> <a href="https://mstdn.social/tags/PyData" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>PyData</span></a> <a href="https://mstdn.social/tags/Python" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Python</span></a> <a href="https://mstdn.social/tags/LinearAlgebra" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LinearAlgebra</span></a></p>
Element 84<p>TOMORROW! E84's own Julia Signell will be representing our team by hosting <a href="https://fosstodon.org/tags/SciPy" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>SciPy</span></a>'s first advanced <a href="https://fosstodon.org/tags/Dask" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Dask</span></a> tutorial. </p><p>The session will cover how to both improve existing code &amp; generate more performant code using Dask.</p><p>More info: <a href="https://cfp.scipy.org/2023/talk/MQQJKG/" rel="nofollow noopener noreferrer" target="_blank"><span class="invisible">https://</span><span class="ellipsis">cfp.scipy.org/2023/talk/MQQJKG</span><span class="invisible">/</span></a> <a href="https://fosstodon.org/tags/SciPy2023" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>SciPy2023</span></a></p>
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