BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Asia/Kolkata BEGIN:STANDARD DTSTART:19451014T230000 TZOFFSETFROM:+0630 TZOFFSETTO:+0530 TZNAME:IST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20260211T123053Z UID:D81735B3-75AB-4447-84CD-A65039493CF7 DTSTART;TZID=Asia/Kolkata:20251223T103000 DTEND;TZID=Asia/Kolkata:20251223T160000 DESCRIPTION:On 23rd December 2025\, the IEEE Computational Intelligence Soc iety (CIS) Student Branch organized a hands-on workshop on Introduction to NumPy\, Pandas\, and Matplotlib\, aimed at providing students with a foun dational understanding of Python-based data analysis and visualization. Th e session began with an overview of Python’s data ecosystem and the real -world relevance of NumPy\, Pandas\, and Matplotlib. Participants were gui ded through setting up their development environment using Jupyter Noteboo k\, Google Colab\, and Visual Studio Code (VS Code)\, and were introduced to importing libraries and referring to official documentation.\n\nThe wor kshop then focused on NumPy for numerical computation\, where participants learned to create and manipulate 1D and 2D arrays\, generate special arra ys\, and perform core operations such as reshaping\, indexing\, slicing\, broadcasting\, and basic statistical calculations. This was followed by an introduction to Pandas\, covering Series and DataFrames\, data creation f rom multiple sources\, reading external datasets\, and performing initial data exploration.\n\nFurther sessions emphasized data cleaning\, manipulat ion\, and aggregation\, including handling missing values\, filtering and transforming data\, grouping and summarizing datasets\, and integrating mu ltiple datasets using practical examples. The workshop concluded with data visualization using Matplotlib and Pandas\, where participants created an d customized various plots to effectively represent data insights.\n\nOver all\, the workshop successfully provided practical exposure to essential P ython data libraries and tools\, strengthening participants’ understandi ng of data analysis workflows and encouraging further exploration in data- driven applications.\n\nRoom: N401\, Bldg: N-Block\, 12th Main Road\, 27th Cross\,Banashankari 2nd stage\, Bangalore\, Karnataka\, India\, 560070 LOCATION:Room: N401\, Bldg: N-Block\, 12th Main Road\, 27th Cross\,Banashan kari 2nd stage\, Bangalore\, Karnataka\, India\, 560070 ORGANIZER:nagarathna.binu@gmail.com SEQUENCE:16 SUMMARY:Python workshop on NumPy\, Matplotlib and Pandas URL;VALUE=URI:https://events.vtools.ieee.org/m/530647 X-ALT-DESC:Description: <br /><p class="MsoNormal" style="text-align: justi fy\;"><span style="font-size: 12.0pt\; line-height: 107%\; font-family: 'T imes New Roman'\,serif\;">On <strong>23rd December 2025</strong>\, the IEE E Computational Intelligence Society (CIS) Student Branch organized a hand s-on workshop on <strong>Introduction to NumPy\, Pandas\, and Matplotlib</ strong>\, aimed at providing students with a foundational understanding of Python-based data analysis and visualization. The session began with an o verview of Python&rsquo\;s data ecosystem and the real-world relevance of NumPy\, Pandas\, and Matplotlib. Participants were guided through setting up their development environment using <strong>Jupyter Notebook\, Google C olab\, and Visual Studio Code (VS Code)</strong>\, and were introduced to importing libraries and referring to official documentation.</span></p>\n< p class="MsoNormal" style="text-align: justify\;"><span style="font-size: 12.0pt\; line-height: 107%\; font-family: 'Times New Roman'\,serif\;">The workshop then focused on <strong>NumPy for numerical computation</strong>\ , where participants learned to create and manipulate 1D and 2D arrays\, g enerate special arrays\, and perform core operations such as reshaping\, i ndexing\, slicing\, broadcasting\, and basic statistical calculations. Thi s was followed by an introduction to <strong>Pandas</strong>\, covering Se ries and DataFrames\, data creation from multiple sources\, reading extern al datasets\, and performing initial data exploration.</span></p>\n<p clas s="MsoNormal" style="text-align: justify\;"><span style="font-size: 12.0pt \; line-height: 107%\; font-family: 'Times New Roman'\,serif\;">Further se ssions emphasized <strong>data cleaning\, manipulation\, and aggregation</ strong>\, including handling missing values\, filtering and transforming d ata\, grouping and summarizing datasets\, and integrating multiple dataset s using practical examples. The workshop concluded with <strong>data visua lization using Matplotlib and Pandas</strong>\, where participants created and customized various plots to effectively represent data insights.</spa n></p>\n<p class="MsoNormal" style="text-align: justify\;"><span style="fo nt-size: 12.0pt\; line-height: 107%\; font-family: 'Times New Roman'\,seri f\;">Overall\, the workshop successfully provided practical exposure to es sential Python data libraries and tools\, strengthening participants&rsquo \; understanding of data analysis workflows and encouraging further explor ation in data-driven applications.</span></p>\n<p class="MsoNormal" style= "text-align: justify\;"><span style="font-size: 12.0pt\; line-height: 107% \; font-family: 'Times New Roman'\,serif\;"><img src="https://events.vtool s.ieee.org/vtools_ui/media/display/c2b443c4-e305-407d-8d8e-cfa6b965075b">< img src="https://events.vtools.ieee.org/vtools_ui/media/display/b719206f-4 4cc-42af-8f91-4a8a46b2f3f6"></span></p> END:VEVENT END:VCALENDAR