GNU socialtag:chirp.cooleysekula.net,2024-03-29:TagTimeline:pandasNotices tagged with pandasUpdates tagged with pandas on Chirp!!https://chirp.cooleysekula.net/chirp.png2024-03-29T05:39:04+00:00http://activitystrea.ms/schema/1.0/notetag:nu.federati.net,2024-03-21:noticeId=3436254:objectType=noteNew note by lnxw48a1Weird feeling for me: In a few of these #<span class="tag"><a href="https://nu.federati.net/tag/datacamp" rel="tag">DataCamp</a></span> courses, I'm now feeling lost when I'm doing the exercises. I think I need to spin up a separate data analysis project using #<span class="tag"><a href="https://nu.federati.net/tag/rlang" rel="tag">R-Lang</a></span>, or #<span class="tag"><a href="https://nu.federati.net/tag/python" rel="tag">Python</a></span> + #<span class="tag"><a href="https://nu.federati.net/tag/numpy" rel="tag">numpy</a></span> + #<span class="tag"><a href="https://nu.federati.net/tag/pandas" rel="tag">pandas</a></span> or #<span class="tag"><a href="https://nu.federati.net/tag/sql" rel="tag">SQL</a></span> ... or maybe do the same project three ways. <br /> <br /> With SQL, at least, it seems to be an artifact of the way their hands-on code runner works (Displays a short `head` of the relevant tables ... so when you're working on queries, you may not have a direct way to see whether your query does specifically what you expected and intended.) <br /> <br /> With R-Lang, it is just that it isn't always apparent what the language will do. Some things are inexplicably backwards compared to most other languages I've seen, so mentally I tend to go with the wrong choice. Also, the practice question set is too small. I've reached the point where some of the practice exercises are familiar enough that I know which answer to choose immediately without having any understanding of why that is the correct choice.354814http://activitystrea.ms/schema/1.0/post2024-03-21T02:01:33+00:002024-03-21T02:01:33+00:00http://activitystrea.ms/schema/1.0/personhttps://nu.federati.net/user/2lnxw48a1Main account. A GNU+Linux bearing nomad migrating across a Windows-centric desert. I save the world from incompetent headquarters IT folks. I invite comment and discussion, but I dislike arguing .lnxw48a1LinuxWalt (@lnxw48a1) {3EB165E0-5BB1-45D2-9E7D-93B31821F864}Main account. A GNU+Linux bearing nomad migrating across a Windows-centric desert. I save the world from incompetent headquarters IT folks. I invite comment and discussion, but I dislike arguing .{58024A03-1021-499E-B14D-DF4537889BF8}tag:nu.federati.net,2024-03-21:objectType=thread:nonce=9527c1762316e1f5http://activitystrea.ms/schema/1.0/notetag:chirp.cooleysekula.net,2019-03-21:noticeId=264612:objectType=noteNew note by steveFrom ben_j_lindsay <a href="https://twitter.com/ben_j_lindsay" title="https://twitter.com/ben_j_lindsay" class="attachment" id="attachment-56178" rel="nofollow external">https://twitter.com/ben_j_lindsay</a> on Twitter: One of the most underrated #<span class="tag"><a href="https://chirp.cooleysekula.net/tag/pandas" rel="tag">Pandas</a></span> functions in #<span class="tag"><a href="https://chirp.cooleysekula.net/tag/python" rel="tag">Python</a></span> is `.query()`. I use it all the time. data = data.query('age==42') looks so much nicer than: data = data[data['age'] == 42] And it allows chaining like: data = data.query('age >18').query('age < 32')264612http://activitystrea.ms/schema/1.0/post2019-03-21T21:00:51+00:002019-03-21T21:00:51+00:00http://activitystrea.ms/schema/1.0/personhttps://chirp.cooleysekula.net/user/3stevePhysicist, Research Group Manager at SNOLAB, Professor of Physics at Queen's University, dark matter hunter, neutrino watcher, writer, runner, programmer, blogger, sometimes a drummer.steveStephen SekulaPhysicist, Research Group Manager at SNOLAB, Professor of Physics at Queen's University, dark matter hunter, neutrino watcher, writer, runner, programmer, blogger, sometimes a drummer.Sudbury, ON, Canadahomepagehttps://steve.cooleysekula.nettruetag:chirp.cooleysekula.net,2019-03-21:objectType=thread:nonce=bffa6738e62e5665