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Positron IDE: Data Analysis with Python in Jupyter Notebooks and Python Script Files (Public Beta)

Timeline --- 00:00 Intro to Positron IDE for data science. 00:15 Focus on Python; other videos cover R. 00:27 Check Python interpreter or environments. 01:10 View environment and interpreter details. 01:23 Switch environments; auto-detects/install dependencies. 01:54 Auto-installs ipykernel if missing. 02:02 Transition between environments. 02:35 Use the new project wizard if needed. 02:45 Create Jupyter notebook or Python project. 03:32 Set up Python environment with Venv or Conda. 04:12 Skip adding new environment; already set up. 04:30 New Notebook vs. New File options. 04:40 Selecting New File lists document options. 05:10 Create Python Notebook on welcome screen. 05:20 Run code immediately in the new notebook. 05:30 Describe code cell execution and output display. 06:03 Cell toolbar actions available. 06:35 Save notebook with Cmd+S (macOS) or Ctrl+S (Windows). 06:55 Create a new folder, save the notebook. 07:25 Saved notebook path and breadcrumb navigation. 08:10 Add code and markdown cells from the toolbar. 09:10 Switch between Python environments and kernels. 10:05 Run cells, view variable values in the session tab. 10:39 Environment issues when switching kernels. 11:09 Variables and data types in the session tab. 11:33 Separation between Jupyter notebook kernel and console. 13:00 Open folder, refresh Positron to execute code. 13:13 Trust authors to allow code execution. 13:57 Set and start interpreter for workspace. 14:14 Reopen notebook, restart kernel, run all cells. 14:45 Hide Explorer tab for more screen space. 15:21 Clear outputs, run cells again. 15:55 Use a pre-made notebook with data analysis code. 16:40 Launch pre-made notebook from Explorer tab. 16:45 Select notebook kernel, start running code. 17:00 Running code updates variables tab with function data. 17:20 Print statements for all cell outputs. 17:47 Keyboard shortcuts for Jupyter Notebook. 18:10 Run cell to download data, clickable URLs. 18:45 Download and access dataset in project directory. 18:55 Use automagic commands to navigate notebook and data. 19:13 Load data into 'penguins' variable, view in session tab. 19:25 Variable viewer details, data frame variables, observations. 20:12 Trigger data viewer inline with %view. 21:33 Interactive data viewer features. 24:07 Actions in data viewer don't affect pandas' data frame. 24:35 Use pandas commands to view data. 24:50 Function help documentation under Help tab. 26:22 Visualization libraries: matplotlib, plotnine, seaborn. 26:45 Use %%capture to suppress output, %pip to install package. 27:48 Interactive visualization libraries: Bokeh, Plotly, Altair. 28:00 Interactivity in Bokeh plot. 28:48 Set render for Plotly plots in Positron. 29:19 Altair for visualization. 29:30 Display summaries. 29:45 Help entry and correlation matrix. 30:10 Handle missing data. 30:30 Create linear regression models with statsmodels, visualize with Seaborn. 31:16 Export notebook to PDF, HTML, Python script. 33:03 Exporting to Python script generates non-runnable script. 33:39 Workable Python script with # %% or line by line execution. 35:04 Console shows Pandas table with HTML formatting. 35:28 Graphs shown in lower right plot window. 36:00 Plot history viewer, navigate previous plot iterations. 36:50 Interactive plots work. 37:23 Final notes. Summary --- We look at the Positron IDE's Python capabilities in terms of data analysis within a Jupyter Notebook and Python Script. We aim to use a pre-existing Python interpreter and associate the code files within a workspace directory. We explore many features from static to interactive plots and using pandas data frames within a notebook and console session. Moreover, we discuss the notebook session being detached from the console session. Links --- Data location: https://github.com/coatless/raw-data/... Relevant script file: https://github.com/coatless-videos/po... Positron Interactive Data Viewer Wiki Page https://github.com/posit-dev/positron... Positron can be obtained from: https://github.com/posit-dev/positron Version information ---- This was demonstrated on: Positron Version: 2024.06.1 (Universal) build 27 Code - OSS Version: 1.90.0 Commit: a893e5b282612ccb2200102957ac38d3c14e5196 Date: 2024-06-26T02:08:06.673Z Electron: 29.4.0 Chromium: 122.0.6261.156 Node.js: 20.9.0 V8: 12.2.281.27-electron.0 OS: Darwin arm64 23.5.0 #positron #posit #rstudio #jupyternotebook #plotnine #seaborn #pandas #plotly #csv