diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..c00f9fa
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,167 @@
+# This file lists the files and folders that should NOT be committed to GitHub.
+
+# Virtual environment
+.venv/
+venv/
+
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
diff --git a/.vscode/settings.json b/.vscode/settings.json
new file mode 100644
index 0000000..6ba1afd
--- /dev/null
+++ b/.vscode/settings.json
@@ -0,0 +1,6 @@
+{
+  "[python]": {
+    "editor.defaultFormatter": "ms-python.black-formatter"
+  },
+  "python.formatting.provider": "none"
+}
\ No newline at end of file
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..15e1ce9
--- /dev/null
+++ b/README.md
@@ -0,0 +1,70 @@
+# Continuous Intelligence and Interactive Analytics - Initial App
+
+- Repository: [cintel-04-reactive](https://github.com/denisecase/cintel-04-reactive)
+- Website: [cintel-04-reactive](https://denisecase.github.io/cintel-04-reactive/)
+- Author: [Denise Case](https://github.com/denisecase)
+
+
+Note: 🚀 Rocket Tips are for learners who want to go beyond the basics. 
+They are NOT required but can improve our workflow, increase productivity, and make things more enjoyable.
+-----
+
+
+## Prerequisites
+
+You'll need the tools installed in 
+
+- [cintel-01-getting-started](https://github.com/denisecase/cintel-01-getting-started)
+- [cintel-02-app](https://github.com/denisecase/cintel-02-app)
+- [cintel-03-data](https://github.com/denisecase/cintel-03-data)
+
+## Sign Up for shinyapps.io (Free Account)
+
+Sign up for a free account on shinyapps.io. 
+I sign in via GitHub for convenience.
+
+## Copy This Repository
+
+Copy this starter repository into your own GitHub account by clicking the 'Fork' button at the top of this page. 
+
+-----
+
+## Customize Your Web App
+
+### Get the Code to your Local Machine
+    
+1. Open VS Code and from the menu, select **View** / **Command Palette**.
+1. Type "Git: Clone" in the command palette and select it.
+1. Enter the URL (web address) of your forked GitHub repository (make sure it contains your GitHub username - not denisecase).
+1. Choose a directory on your local machine (e.g., Documents folder) to store the project.
+1. If prompted, sign in to GitHub from VS Code.
+
+### Make Changes in VS Code
+
+With your respository folder open in VS Code:
+
+1. Click on this README.md file for editing.
+1. Update the README.md file by changing your name in the author link above.
+1. Update the links in the README.md file to your username instead of denisecase.
+
+### Save Your Changes
+
+1. After making changes, you want to send them back to GitHub.
+1. In VS Code, find the "Source Control" icon and click it.
+1. Important: Enter a brief commit message describing your changes.
+1. Change the "Commit" button dropdown to "Commit and Push" to send your changes back to GitHub.
+
+-----
+
+## Reminders
+
+Details matter - check spelling, capitalization, plurals, spacing when things don't match.
+
+## Resources
+
+- [Seaborn](https://seaborn.pydata.org/)
+- [Plotly](https://plotly.com/python/)
+- [Bokeh](https://docs.bokeh.org/en/latest/index.html)
+
+
+- [Seaborn Flights Dataset](https://seaborn.pydata.org/tutorial/data_structure.html)
\ No newline at end of file
diff --git a/REQUIREMENTS.md b/REQUIREMENTS.md
new file mode 100644
index 0000000..a866585
--- /dev/null
+++ b/REQUIREMENTS.md
@@ -0,0 +1,34 @@
+# Python Libraries for Interactive Analytics
+
+This collection includes various Python packages that are used for interactive analytics. Each tool serves a unique purpose and is suitable for different use cases.
+Use your favorites. Try new ones. Share your experiences with the community.
+
+Data Manipulation:
+- **pandas**: A powerful data manipulation library that provides flexible data structures and functions to manipulate structured data. [pandas documentation](https://pandas.pydata.org/)
+
+Excel Library:
+- **openpyxl**: A Python library to read/write Excel 2010 xlsx/xlsm/xltx/xltm files. [openpyxl documentation](https://openpyxl.readthedocs.io/en/stable/)
+
+Template Engine:
+- **jinja2**: A modern and designer-friendly templating language for Python. It is often used to create HTML, XML or other markup formats that are returned to the user via an HTTP request. [jinja2 documentation](https://jinja.palletsprojects.com/)
+
+Data Visualization:
+- **matplotlib**: A data visualization library that provides a MATLAB-like interface for creating plots and charts. [matplotlib dataset list](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.html#module-matplotlib.pyplot)
+- **seaborn**: A data visualization library built on top of matplotlib, providing datasets and high-level statistical graphics. [seaborn dataset list](https://github.com/mwaskom/seaborn-data)
+- **plotnine**: A Python implementation of the R package ggplot2, which is a "grammar of graphics" implementation. It allows you to create complex plots with a few lines of code. [plotnine documentation](https://plotnine.readthedocs.io/en/stable/)
+- **plotly**: A Python graphing library that makes interactive, publication-quality graphs online. It provides a wide range of visualization types and features. [plotly documentation](https://plotly.com/python/)
+- **holoviews**: A Python library that makes data visualization as simple as possible, by automatically connecting data and its graphical representation. [holoviews documentation](http://holoviews.org/)
+- **hvplot**: A high-level plotting API for pandas, dask, xarray, and networkx built on HoloViews. [hvplot documentation](https://hvplot.holoviz.org/)
+
+Interactive Maps:
+- **ipyleaflet**: A Python library for creating interactive maps. It is a Jupyter notebook widget that uses leaflet.js for rendering maps. [ipyleaflet documentation](https://ipyleaflet.readthedocs.io/en/latest/)
+
+Web-based Visualization:
+- **bokeh**: A Python library for creating interactive visualizations and plots, emphasizing web-based, modern, and high-performance output. [bokeh documentation](https://docs.bokeh.org/en/latest/index.html)
+- **jupyter_bokeh**: A Jupyter extension for rendering bokeh content in Jupyter notebook cells. [jupyter_bokeh documentation](https://github.com/bokeh/jupyter_bokeh)
+
+Web Applications:
+- **shiny**: A package in R (with a Python version also available) for creating interactive web applications straight from R and Python. [shiny documentation](https://shiny.rstudio.com/)
+- **shinyswatch**: A package that provides additional themes for Shiny applications. [shinyswatch documentation](https://github.com/Appsilon/shinyswatch)
+- **shinywidgets**: Enhance your Shiny apps with advanced widgets like sliders, checkboxes, etc. [shinywidgets documentation](https://github.com/Appsilon/shiny.widgets)
+- **panel**: A high-level app anddashboarding solution for Python that works well with the PyData ecosystem. It allows you to create interactive dashboards and applications with ease. [panel documentation](https://panel.holoviz.org/)
diff --git a/SHINY.md b/SHINY.md
new file mode 100644
index 0000000..13f982b
--- /dev/null
+++ b/SHINY.md
@@ -0,0 +1,92 @@
+# Interactive Analytics with Shiny
+
+Earlier, you installed Python and verified it with:
+
+```shell
+python --version
+python3 --version
+py --version
+```
+
+Use the command that works instead of `python` in the following instructions. 
+You're encouraged to modify these Markdown (.md) files to reflect the commands that work on your machine. 
+
+## Install and Upgrade Python Tools Globally
+
+Install some additional content into your global Python for best results. 
+open your terminal (PowerShell on Windows, Terminal on Mac/Linux) and
+install these to your default Python using the commands below. 
+
+
+```shell
+python -m pip install --upgrade pip wheel
+python -m pip install --upgrade black ruff pyright
+python -m pip install --upgrade rsconnect-python
+```
+
+You must have reconnect-python installed for the next step.
+
+## Authorize shinyapps.io
+
+Using Chrome (recommended), sign in to your free shinyapps.io account (I use GitHub to sign in.)
+
+1. On the Getting Started page, click on the "Start with Python" tab. 
+1. Click "Show Secret"
+1. Click "Copy to Clipboard". Follow the instructions. Mine said
+1. Hit Ctrl c / ENTER to copy the provided command to the clipboard. 
+1. Open a terminal window. (Terminal on Mac/Linux, PowerShell on Windows).
+1. Click in the terminal window to paste the command and hit ENTER to run it.
+
+![Get the Command to Authorize shinyapps.io](images/GetCommandToAuthorizeShinyAppsdotIO.PNG)
+
+## Create a Virtual Environment
+
+```shell
+python -m venv .venv
+```
+
+When VS Code asks if it should add the new virtual environment, click yes.
+
+
+## Activate the Virtual Environment
+
+- Activate it on Windows: `.venv\Scripts\activate`
+- Activate it on macOS/Linux `source .venv/bin/`
+
+## Install Libaries into Virtual Environment
+
+This gives a good selection of options. You only need to install the ones you use.
+
+```shell
+python -m pip install --upgrade pip wheel shiny shinyswatch 
+python -m pip install --upgrade pandas openpyxl jinja2 matplotlib seaborn plotnine
+python -m pip install --upgrade shinywidgets plotly holoviews panel hvplot ipyleaflet
+python -m pip install --upgrade jupyter_bokeh 
+
+```
+
+OR List your requirements in requirements.txt and install them all at once.
+
+```shell
+python -m pip install --upgrade -r requirements.txt
+```
+
+
+## Run the App
+
+Verify your virtual environment is activated. Run the app. 
+
+```shell
+shiny run --reload app.py
+```
+
+Open the app by following the instructions provided in the terminal. 
+For example, try CRTL CLICK (at the same time) on the URL displayed (http://127.0.0.1:8000).
+
+Hit CTRL c (at the same time) to quit the app. 
+If it won't stop, close the terminal window.
+Reopen the terminal window and be sure the virtual environment is activated
+before running the app again.
+
+
+
diff --git a/app.py b/app.py
new file mode 100644
index 0000000..1efc131
--- /dev/null
+++ b/app.py
@@ -0,0 +1,78 @@
+"""
+Purpose: Use Python to create a continuous intelligence and 
+interactive analytics dashboard using Shiny for Python and 
+interactive charts from Holoviews Bokeh and Plotly Express.
+
+"""
+from shiny import *
+import shinyswatch
+
+from flights_server import get_flights_server_functions
+from flights_ui_inputs import get_flights_sidebar
+from flights_ui_outputs import get_flights_main
+
+from mtcars_server import get_mtcars_server_functions
+from mtcars_ui_inputs import get_mtcars_sidebar
+from mtcars_ui_outputs import get_mtcars_main
+
+from penguins_server import get_penguins_server_functions
+from penguins_ui_inputs import get_penguins_sidebar
+from penguins_ui_outputs import get_penguins_main
+
+from relationships_server import get_relationships_server_functions
+from relationships_ui_inputs import get_relationships_sidebar
+from relationships_ui_outputs import get_relationships_main
+
+from util_logger import setup_logger
+
+logger, logname = setup_logger(__name__)
+
+app_ui = ui.page_navbar(
+    shinyswatch.theme.minty(),
+    ui.nav(
+        "Flights",
+        ui.layout_sidebar(
+            get_flights_sidebar(),
+            get_flights_main(),
+        ),
+    ),
+    ui.nav(
+        "MT_Cars",
+        ui.layout_sidebar(
+            get_mtcars_sidebar(),
+            get_mtcars_main(),
+        ),
+    ),
+    ui.nav(
+        "Penguins",
+        ui.layout_sidebar(
+            get_penguins_sidebar(),
+            get_penguins_main(),
+        ),
+    ),
+    ui.nav(
+        "Relationships",
+        ui.layout_sidebar(
+            get_relationships_sidebar(),
+            get_relationships_main(),
+        ),
+    ),
+
+    ui.nav(ui.a("About", href="https://github.com/denisecase")),
+    ui.nav(ui.a("GitHub", href="https://github.com/denisecase/cintel-04-reactive")),
+    ui.nav(ui.a("App", href="https://denisecase.github.io/cintel-04-reactive/")),
+    ui.nav(ui.a("Examples", href="https://shinylive.io/py/examples/")),
+    ui.nav(ui.a("shinywidgets", href="https://shiny.rstudio.com/py/docs/ipywidgets.html")),
+    title=ui.h1("Case Dashboard"),
+)
+
+
+def server(input, output, session):
+    logger.info("Starting server...")
+    flights_server_functions = get_flights_server_functions(input, output, session)
+    mtcars_server_functions = get_mtcars_server_functions(input, output, session)
+    penguins_server_functions = get_penguins_server_functions(input, output, session)
+    relationships_server_functions = get_relationships_server_functions(input, output, session) 
+
+#app = App(app_ui, server, debug=True)
+app = App(app_ui, server)
diff --git a/app_data.py b/app_data.py
new file mode 100644
index 0000000..683a9c7
--- /dev/null
+++ b/app_data.py
@@ -0,0 +1,42 @@
+'''
+Purpose: Use Python to create local datasets for review.
+
+Once they exist, you don't need to run these, but the examples may be
+useful for creating your own datasets.
+
+You can uncomment the code and add it to your app.py file. 
+After the dataset is created, comment out the code again.
+
+You can also run this file by itself to create datasets.
+
+mtcars.csv - from R mtcars dataset 
+https://shinylive.io/py/examples/#read-local-csv
+
+penguins - from Seaborn penguins dataset
+
+flights - from Seaborn flights dataset
+
+Note: A local csv copy allows review from within VS Code.
+'''
+
+import pandas as pd
+import seaborn as sns
+from bokeh.sampledata.les_mis import data as les_mis_data
+from bokeh.sampledata.movies_data import data as movies_data
+
+
+# penguins = sns.load_dataset("penguins")
+# penguins.to_excel("penguins.xlsx")
+#penguins.to_csv("penguins.csv")
+
+
+# flights = sns.load_dataset("flights")
+# flights.to_excel("flights.xlsx")
+# flights.to_csv("flights.csv")
+
+les_mis = pd.DataFrame(les_mis_data['links'])
+les_mis.to_excel("les_mis.xlsx")
+les_mis.to_csv("les_mis.csv")
+
+
+
diff --git a/flights.csv b/flights.csv
new file mode 100644
index 0000000..a461317
--- /dev/null
+++ b/flights.csv
@@ -0,0 +1,145 @@
+,year,month,passengers
+0,1949,Jan,112
+1,1949,Feb,118
+2,1949,Mar,132
+3,1949,Apr,129
+4,1949,May,121
+5,1949,Jun,135
+6,1949,Jul,148
+7,1949,Aug,148
+8,1949,Sep,136
+9,1949,Oct,119
+10,1949,Nov,104
+11,1949,Dec,118
+12,1950,Jan,115
+13,1950,Feb,126
+14,1950,Mar,141
+15,1950,Apr,135
+16,1950,May,125
+17,1950,Jun,149
+18,1950,Jul,170
+19,1950,Aug,170
+20,1950,Sep,158
+21,1950,Oct,133
+22,1950,Nov,114
+23,1950,Dec,140
+24,1951,Jan,145
+25,1951,Feb,150
+26,1951,Mar,178
+27,1951,Apr,163
+28,1951,May,172
+29,1951,Jun,178
+30,1951,Jul,199
+31,1951,Aug,199
+32,1951,Sep,184
+33,1951,Oct,162
+34,1951,Nov,146
+35,1951,Dec,166
+36,1952,Jan,171
+37,1952,Feb,180
+38,1952,Mar,193
+39,1952,Apr,181
+40,1952,May,183
+41,1952,Jun,218
+42,1952,Jul,230
+43,1952,Aug,242
+44,1952,Sep,209
+45,1952,Oct,191
+46,1952,Nov,172
+47,1952,Dec,194
+48,1953,Jan,196
+49,1953,Feb,196
+50,1953,Mar,236
+51,1953,Apr,235
+52,1953,May,229
+53,1953,Jun,243
+54,1953,Jul,264
+55,1953,Aug,272
+56,1953,Sep,237
+57,1953,Oct,211
+58,1953,Nov,180
+59,1953,Dec,201
+60,1954,Jan,204
+61,1954,Feb,188
+62,1954,Mar,235
+63,1954,Apr,227
+64,1954,May,234
+65,1954,Jun,264
+66,1954,Jul,302
+67,1954,Aug,293
+68,1954,Sep,259
+69,1954,Oct,229
+70,1954,Nov,203
+71,1954,Dec,229
+72,1955,Jan,242
+73,1955,Feb,233
+74,1955,Mar,267
+75,1955,Apr,269
+76,1955,May,270
+77,1955,Jun,315
+78,1955,Jul,364
+79,1955,Aug,347
+80,1955,Sep,312
+81,1955,Oct,274
+82,1955,Nov,237
+83,1955,Dec,278
+84,1956,Jan,284
+85,1956,Feb,277
+86,1956,Mar,317
+87,1956,Apr,313
+88,1956,May,318
+89,1956,Jun,374
+90,1956,Jul,413
+91,1956,Aug,405
+92,1956,Sep,355
+93,1956,Oct,306
+94,1956,Nov,271
+95,1956,Dec,306
+96,1957,Jan,315
+97,1957,Feb,301
+98,1957,Mar,356
+99,1957,Apr,348
+100,1957,May,355
+101,1957,Jun,422
+102,1957,Jul,465
+103,1957,Aug,467
+104,1957,Sep,404
+105,1957,Oct,347
+106,1957,Nov,305
+107,1957,Dec,336
+108,1958,Jan,340
+109,1958,Feb,318
+110,1958,Mar,362
+111,1958,Apr,348
+112,1958,May,363
+113,1958,Jun,435
+114,1958,Jul,491
+115,1958,Aug,505
+116,1958,Sep,404
+117,1958,Oct,359
+118,1958,Nov,310
+119,1958,Dec,337
+120,1959,Jan,360
+121,1959,Feb,342
+122,1959,Mar,406
+123,1959,Apr,396
+124,1959,May,420
+125,1959,Jun,472
+126,1959,Jul,548
+127,1959,Aug,559
+128,1959,Sep,463
+129,1959,Oct,407
+130,1959,Nov,362
+131,1959,Dec,405
+132,1960,Jan,417
+133,1960,Feb,391
+134,1960,Mar,419
+135,1960,Apr,461
+136,1960,May,472
+137,1960,Jun,535
+138,1960,Jul,622
+139,1960,Aug,606
+140,1960,Sep,508
+141,1960,Oct,461
+142,1960,Nov,390
+143,1960,Dec,432
diff --git a/flights.xlsx b/flights.xlsx
new file mode 100644
index 0000000..4c70567
Binary files /dev/null and b/flights.xlsx differ
diff --git a/flights_server.py b/flights_server.py
new file mode 100644
index 0000000..a7e7dbe
--- /dev/null
+++ b/flights_server.py
@@ -0,0 +1,113 @@
+""" 
+Purpose: Provide reactive output for the Flights dataset.
+
+Use inputs from the UI Sidebar to filter the dataset.
+
+Update ouputs in the UI Main Panel.
+
+Matching the IDs in the UI Sidebar and function/ouput names in the UI Main Panel
+to this server code is critical. They are case sensitive and must match exactly.
+
+This example uses dates - arguably the most complex UI input type.
+ - Consider leap years, time changes, daylight savings, etc.
+ - Working with dates is often challenging. 
+ - This example is a good starting point - there are many examples online.
+
+"""
+from shiny import *
+import pandas as pd
+from shinywidgets import render_widget
+import plotly.express as px
+import plotly.graph_objs as go
+
+from util_logger import setup_logger
+logger, logname = setup_logger(__name__)
+
+def get_flights_server_functions(input, output, session):
+
+    original_df = pd.read_excel("flights.xlsx")
+
+    # create new field with year as a string and month together
+    original_df['year-mon'] = original_df['year'].astype(str) + '-' + original_df['month']
+    total_count = len(original_df)
+
+    reactive_df = reactive.Value()
+
+    @reactive.Effect
+    @reactive.event(input.FLIGHTS_DATE_RANGE)
+    def _():
+        ''' Reactive effect to update the filtered dataframe when inputs change.
+        It doesn't need a name, because no one calls it directly.'''
+
+        logger.info("UI inputs changed. Updating flights reactive df")
+
+        df = original_df.copy()
+
+        # first, drop the unnamed index column
+        # axis=1 means drop a column, axis=0 means drop a row
+        df = df.drop(df.columns[0], axis=1)
+
+        # Create a new column using pd.to_datetime() method for filtering
+        year_string = df["year"].astype(str)
+        month_string = df["month"].astype(str)
+        df["Date"] = pd.to_datetime(year_string + "-" + month_string)
+
+        # Convert datetime to just the date, no time (datetime objects have both)
+        df["Date"] = df["Date"].dt.date
+
+        input_range = input.FLIGHTS_DATE_RANGE()
+        input_min = input_range[0]
+        input_max = input_range[1]
+        df = df[(df["Date"] >= input_min) & (df["Date"] <= input_max)]
+
+        #logger.debug(f"filtered flights df: {df}")
+        reactive_df.set(df)
+
+    
+    @output
+    @render.text
+    def flights_record_count_string():
+        logger.debug("Triggered: flights_filter_record_count_string") 
+        filtered_count = len(reactive_df.get())
+        message = f"Showing {filtered_count} of {total_count} records"
+        logger.debug(f"filter message: {message}")
+        return message
+
+    @output
+    @render.table
+    def flights_filtered_table():
+        filtered_df = reactive_df.get()
+        filtered_df.drop(columns=["Date"], inplace=True)
+        return filtered_df
+
+    @output
+    @render_widget
+    def flights_output_widget1():
+        df = reactive_df.get()
+        px_plot = px.scatter(df, 
+            x="year", 
+            y="passengers", 
+            title="Flights Scatter Chart (Plotly Express)",
+            color="month"
+            )
+        return px_plot
+        
+    @output
+    @render_widget
+    def flights_output_widget2():
+        df = reactive_df.get()
+
+        px_plot = px.line(df,
+                  x="year-mon", 
+                  y="passengers",
+                  title="Flights Line Chart (Plotly Express)",
+                  labels={"year-mon": "Year-Mon", "passengers": "Passengers"})
+        return px_plot
+        
+    # return a list of function names for use in reactive outputs
+    return [
+        flights_record_count_string,
+        flights_filtered_table,
+        flights_output_widget1,
+        flights_output_widget2,
+    ]
diff --git a/flights_ui_inputs.py b/flights_ui_inputs.py
new file mode 100644
index 0000000..94127e6
--- /dev/null
+++ b/flights_ui_inputs.py
@@ -0,0 +1,32 @@
+"""
+Purpose: Provide user interaction options for the Flights dataset.
+
+IDs must be unique. They are capitalized in this app for clarity (not typical).
+The IDs are case-sensitive and must match the server code exactly.
+
+We prefaced IDs with the dataset name to avoid naming conflicts.
+
+See
+Example date range at https://shinylive.io/py/examples/#date-range-input
+Function ref at: https://shiny.rstudio.com/py/api/ui.update_date_range.html
+
+
+"""
+from datetime import date
+from shiny import ui
+
+
+def get_flights_sidebar():
+    return ui.panel_sidebar(
+        ui.h2("Flights Interaction"),
+        ui.tags.hr(),
+        ui.input_date_range(
+            "FLIGHTS_DATE_RANGE",
+            "Enter Date Range",
+            start=date(1949, 1, 1),
+            end=date(1960, 12, 31),
+        ),
+        ui.tags.hr(),
+        ui.p("Please be patient. The charts may take a few seconds to load."),
+        ui.tags.hr(),
+    )
diff --git a/flights_ui_outputs.py b/flights_ui_outputs.py
new file mode 100644
index 0000000..58a6954
--- /dev/null
+++ b/flights_ui_outputs.py
@@ -0,0 +1,22 @@
+'''
+Purpose: Display ouput for the Flights dataset.
+'''
+
+from shiny import ui
+from shinywidgets import output_widget
+
+def get_flights_main():
+    return ui.panel_main(
+        ui.h2("Main Panel with Reactive Output"),
+        ui.tags.hr(),
+        ui.tags.section(
+            ui.h3("Filtered Flights: Charts"),
+            output_widget("flights_output_widget1"),
+            output_widget("flights_output_widget2"),
+            ui.tags.hr(),
+            ui.h3("Filtered Flights Table"),
+            ui.output_text("flights_record_count_string"),
+            ui.output_table("flights_filtered_table"),
+            ui.tags.hr(),
+        )
+    )
diff --git a/mtcars.csv b/mtcars.csv
new file mode 100644
index 0000000..2abcf28
--- /dev/null
+++ b/mtcars.csv
@@ -0,0 +1,33 @@
+"mpg","cyl","disp","hp","drat","wt","qsec","vs","am","gear","carb"
+21,6,160,110,3.9,2.62,16.46,0,1,4,4
+21,6,160,110,3.9,2.875,17.02,0,1,4,4
+22.8,4,108,93,3.85,2.32,18.61,1,1,4,1
+21.4,6,258,110,3.08,3.215,19.44,1,0,3,1
+18.7,8,360,175,3.15,3.44,17.02,0,0,3,2
+18.1,6,225,105,2.76,3.46,20.22,1,0,3,1
+14.3,8,360,245,3.21,3.57,15.84,0,0,3,4
+24.4,4,146.7,62,3.69,3.19,20,1,0,4,2
+22.8,4,140.8,95,3.92,3.15,22.9,1,0,4,2
+19.2,6,167.6,123,3.92,3.44,18.3,1,0,4,4
+17.8,6,167.6,123,3.92,3.44,18.9,1,0,4,4
+16.4,8,275.8,180,3.07,4.07,17.4,0,0,3,3
+17.3,8,275.8,180,3.07,3.73,17.6,0,0,3,3
+15.2,8,275.8,180,3.07,3.78,18,0,0,3,3
+10.4,8,472,205,2.93,5.25,17.98,0,0,3,4
+10.4,8,460,215,3,5.424,17.82,0,0,3,4
+14.7,8,440,230,3.23,5.345,17.42,0,0,3,4
+32.4,4,78.7,66,4.08,2.2,19.47,1,1,4,1
+30.4,4,75.7,52,4.93,1.615,18.52,1,1,4,2
+33.9,4,71.1,65,4.22,1.835,19.9,1,1,4,1
+21.5,4,120.1,97,3.7,2.465,20.01,1,0,3,1
+15.5,8,318,150,2.76,3.52,16.87,0,0,3,2
+15.2,8,304,150,3.15,3.435,17.3,0,0,3,2
+13.3,8,350,245,3.73,3.84,15.41,0,0,3,4
+19.2,8,400,175,3.08,3.845,17.05,0,0,3,2
+27.3,4,79,66,4.08,1.935,18.9,1,1,4,1
+26,4,120.3,91,4.43,2.14,16.7,0,1,5,2
+30.4,4,95.1,113,3.77,1.513,16.9,1,1,5,2
+15.8,8,351,264,4.22,3.17,14.5,0,1,5,4
+19.7,6,145,175,3.62,2.77,15.5,0,1,5,6
+15,8,301,335,3.54,3.57,14.6,0,1,5,8
+21.4,4,121,109,4.11,2.78,18.6,1,1,4,2
diff --git a/mtcars_server.py b/mtcars_server.py
new file mode 100644
index 0000000..f349cc1
--- /dev/null
+++ b/mtcars_server.py
@@ -0,0 +1,107 @@
+''' 
+Purpose: Provide reactive output for the MT Cars dataset.
+
+Use inputs from the UI Sidebar to filter the dataset.
+
+Update ouputs in the UI Main Panel.
+
+Matching the IDs in the UI Sidebar and function/ouput names in the UI Main Panel
+to this server code is critical. They are case sensitive and must match exactly.
+
+'''
+
+from shiny import *
+import matplotlib.pyplot as plt
+import pandas as pd
+from bokeh.plotting import figure
+from plotnine import aes, geom_point, ggplot, ggtitle
+from shinywidgets import render_widget
+import plotly.express as px
+import plotly.graph_objs as go
+
+from util_logger import setup_logger
+logger, logname = setup_logger(__name__)
+
+def get_mtcars_server_functions(input, output, session):
+
+    original_df = pd.read_csv("mtcars.csv")
+    total_count = len(original_df)
+
+    reactive_df = reactive.Value()
+
+    @reactive.Effect
+    @reactive.event(input.MTCARS_MPG_RANGE)
+    def _():
+
+        df = original_df.copy()
+
+        input_range = input.MTCARS_MPG_RANGE()
+        input_min = input_range[0]
+        input_max = input_range[1]
+
+        '''
+        Filter the dataframe to just those greater than or equal to the min
+        and less than or equal to the max
+        Note: The ampersand (&) is the Python operator for AND
+        The column name is in quotes and is "mpg".
+        You must be familiar with the dataset to know the column names.
+        '''
+
+        filtered_df = df[(df["mpg"] >= input_min) & (df["mpg"] <= input_max)]
+
+        # Set the reactive value
+        reactive_df.set(filtered_df)
+
+
+    @output
+    @render.text
+    def mtcars_record_count_string():
+        filtered_df = reactive_df.get()
+        filtered_count = len(filtered_df)
+        message = f"Showing {filtered_count} of {total_count} records"
+        logger.debug(f"filter message: {message}")
+        return message
+
+    @output
+    @render.table
+    def mtcars_filtered_table():
+        filtered_df = reactive_df.get()
+        return filtered_df
+
+    @output
+    @render_widget
+    def mtcars_output_widget1():
+        df = reactive_df.get()
+        plotly_express_plot = px.scatter(df, x="mpg", y="hp", color="cyl", size="wt")
+        plotly_express_plot.update_layout(title="MT Cars with Plotly Express")
+        return plotly_express_plot
+    
+    @output
+    @render.plot
+    def mtcars_plot1():
+        df = reactive_df.get()
+        matplotlib_fig, ax = plt.subplots()
+        plt.title("MT Cars with matplotlib")
+        ax.scatter(df["wt"], df["mpg"])
+        return matplotlib_fig
+
+    @output
+    @render.plot
+    def mtcars_plot2():
+        df = reactive_df.get()                  
+        plotnine_plot = (
+            ggplot(df, aes("wt", "mpg"))
+            + geom_point()
+            + ggtitle("MT Cars with plotnine")
+        )
+
+        return plotnine_plot
+
+    # return a list of function names for use in reactive outputs
+    return [
+        mtcars_record_count_string,
+        mtcars_filtered_table,
+        mtcars_output_widget1,
+        mtcars_plot1,
+        mtcars_plot2,
+    ]
diff --git a/mtcars_ui_inputs.py b/mtcars_ui_inputs.py
new file mode 100644
index 0000000..fd7074d
--- /dev/null
+++ b/mtcars_ui_inputs.py
@@ -0,0 +1,46 @@
+"""
+Purpose: Provide user interaction options for the MT Cars dataset.
+
+IDs must be unique. They are capitalized in this app for clarity (not typical).
+The IDs are case-sensitive and must match the server code exactly.
+
+We prefaced IDs with the dataset name to avoid naming conflicts.
+
+"""
+from shiny import ui
+
+
+def get_mtcars_sidebar():
+    return ui.panel_sidebar(
+        ui.h2("MT Cars Interaction"),
+        ui.tags.hr(),
+        ui.input_slider(
+            "MTCARS_MPG_RANGE",
+            "Miles Per Gallon (MPG)",
+            min=10,
+            max=35,
+            value=[10, 35],
+        ),
+        ui.tags.hr(),
+        ui.tags.section(
+            ui.h3("MT Cars Table"),
+            ui.tags.p("Description of each field in the table:"),
+            ui.tags.ul(
+                ui.tags.li("mpg: Miles per Gallon"),
+                ui.tags.li("cyl: Number of cylinders"),
+                ui.tags.li("disp: Displacement (cubic inches)"),
+                ui.tags.li("hp: Gross horsepower"),
+                ui.tags.li("drat: Rear axle ratio"),
+                ui.tags.li("wt: Weight (1,000 lbs)"),
+                ui.tags.li("qsec: 1/4 mile time"),
+                ui.tags.li("vs: V/S (Engine shape; 0 = V-shaped, 1 = Straight)"),
+                ui.tags.li("am: Transmission (0 = Automatic, 1 = Manual)"),
+                ui.tags.li("gear: Number of forward gears"),
+                ui.tags.li("carb: Number of carburetors"),
+            ),
+            ui.output_table("cars_table"),
+        ),
+        ui.tags.hr(),
+        ui.p("Please be patient. The charts may take a few seconds to load."),
+        ui.tags.hr(),
+    )
diff --git a/mtcars_ui_outputs.py b/mtcars_ui_outputs.py
new file mode 100644
index 0000000..95997a9
--- /dev/null
+++ b/mtcars_ui_outputs.py
@@ -0,0 +1,23 @@
+"""
+Purpose: Display ouput for the MT Cars dataset.
+"""
+from shiny import ui
+from shinywidgets import output_widget
+
+
+def get_mtcars_main():
+    return ui.panel_main(
+        ui.h2("Main Panel with Reactive Output"),
+        ui.tags.hr(),
+        ui.tags.section(
+            ui.h3("Filtered Cars: Charts"),
+            output_widget("mtcars_output_widget1"),
+            ui.output_plot("mtcars_plot1"),
+            ui.output_plot("mtcars_plot2"),
+            ui.tags.hr(),
+            ui.h3("Filtered MT Cars Table"),
+            ui.output_text("mtcars_record_count_string"),
+            ui.output_table("mtcars_filtered_table"),
+            ui.tags.hr(),
+        ),
+    )
diff --git a/penguins.csv b/penguins.csv
new file mode 100644
index 0000000..54d30b2
--- /dev/null
+++ b/penguins.csv
@@ -0,0 +1,345 @@
+,species,island,bill_length_mm,bill_depth_mm,flipper_length_mm,body_mass_g,sex
+0,Adelie,Torgersen,39.1,18.7,181.0,3750.0,Male
+1,Adelie,Torgersen,39.5,17.4,186.0,3800.0,Female
+2,Adelie,Torgersen,40.3,18.0,195.0,3250.0,Female
+3,Adelie,Torgersen,,,,,
+4,Adelie,Torgersen,36.7,19.3,193.0,3450.0,Female
+5,Adelie,Torgersen,39.3,20.6,190.0,3650.0,Male
+6,Adelie,Torgersen,38.9,17.8,181.0,3625.0,Female
+7,Adelie,Torgersen,39.2,19.6,195.0,4675.0,Male
+8,Adelie,Torgersen,34.1,18.1,193.0,3475.0,
+9,Adelie,Torgersen,42.0,20.2,190.0,4250.0,
+10,Adelie,Torgersen,37.8,17.1,186.0,3300.0,
+11,Adelie,Torgersen,37.8,17.3,180.0,3700.0,
+12,Adelie,Torgersen,41.1,17.6,182.0,3200.0,Female
+13,Adelie,Torgersen,38.6,21.2,191.0,3800.0,Male
+14,Adelie,Torgersen,34.6,21.1,198.0,4400.0,Male
+15,Adelie,Torgersen,36.6,17.8,185.0,3700.0,Female
+16,Adelie,Torgersen,38.7,19.0,195.0,3450.0,Female
+17,Adelie,Torgersen,42.5,20.7,197.0,4500.0,Male
+18,Adelie,Torgersen,34.4,18.4,184.0,3325.0,Female
+19,Adelie,Torgersen,46.0,21.5,194.0,4200.0,Male
+20,Adelie,Biscoe,37.8,18.3,174.0,3400.0,Female
+21,Adelie,Biscoe,37.7,18.7,180.0,3600.0,Male
+22,Adelie,Biscoe,35.9,19.2,189.0,3800.0,Female
+23,Adelie,Biscoe,38.2,18.1,185.0,3950.0,Male
+24,Adelie,Biscoe,38.8,17.2,180.0,3800.0,Male
+25,Adelie,Biscoe,35.3,18.9,187.0,3800.0,Female
+26,Adelie,Biscoe,40.6,18.6,183.0,3550.0,Male
+27,Adelie,Biscoe,40.5,17.9,187.0,3200.0,Female
+28,Adelie,Biscoe,37.9,18.6,172.0,3150.0,Female
+29,Adelie,Biscoe,40.5,18.9,180.0,3950.0,Male
+30,Adelie,Dream,39.5,16.7,178.0,3250.0,Female
+31,Adelie,Dream,37.2,18.1,178.0,3900.0,Male
+32,Adelie,Dream,39.5,17.8,188.0,3300.0,Female
+33,Adelie,Dream,40.9,18.9,184.0,3900.0,Male
+34,Adelie,Dream,36.4,17.0,195.0,3325.0,Female
+35,Adelie,Dream,39.2,21.1,196.0,4150.0,Male
+36,Adelie,Dream,38.8,20.0,190.0,3950.0,Male
+37,Adelie,Dream,42.2,18.5,180.0,3550.0,Female
+38,Adelie,Dream,37.6,19.3,181.0,3300.0,Female
+39,Adelie,Dream,39.8,19.1,184.0,4650.0,Male
+40,Adelie,Dream,36.5,18.0,182.0,3150.0,Female
+41,Adelie,Dream,40.8,18.4,195.0,3900.0,Male
+42,Adelie,Dream,36.0,18.5,186.0,3100.0,Female
+43,Adelie,Dream,44.1,19.7,196.0,4400.0,Male
+44,Adelie,Dream,37.0,16.9,185.0,3000.0,Female
+45,Adelie,Dream,39.6,18.8,190.0,4600.0,Male
+46,Adelie,Dream,41.1,19.0,182.0,3425.0,Male
+47,Adelie,Dream,37.5,18.9,179.0,2975.0,
+48,Adelie,Dream,36.0,17.9,190.0,3450.0,Female
+49,Adelie,Dream,42.3,21.2,191.0,4150.0,Male
+50,Adelie,Biscoe,39.6,17.7,186.0,3500.0,Female
+51,Adelie,Biscoe,40.1,18.9,188.0,4300.0,Male
+52,Adelie,Biscoe,35.0,17.9,190.0,3450.0,Female
+53,Adelie,Biscoe,42.0,19.5,200.0,4050.0,Male
+54,Adelie,Biscoe,34.5,18.1,187.0,2900.0,Female
+55,Adelie,Biscoe,41.4,18.6,191.0,3700.0,Male
+56,Adelie,Biscoe,39.0,17.5,186.0,3550.0,Female
+57,Adelie,Biscoe,40.6,18.8,193.0,3800.0,Male
+58,Adelie,Biscoe,36.5,16.6,181.0,2850.0,Female
+59,Adelie,Biscoe,37.6,19.1,194.0,3750.0,Male
+60,Adelie,Biscoe,35.7,16.9,185.0,3150.0,Female
+61,Adelie,Biscoe,41.3,21.1,195.0,4400.0,Male
+62,Adelie,Biscoe,37.6,17.0,185.0,3600.0,Female
+63,Adelie,Biscoe,41.1,18.2,192.0,4050.0,Male
+64,Adelie,Biscoe,36.4,17.1,184.0,2850.0,Female
+65,Adelie,Biscoe,41.6,18.0,192.0,3950.0,Male
+66,Adelie,Biscoe,35.5,16.2,195.0,3350.0,Female
+67,Adelie,Biscoe,41.1,19.1,188.0,4100.0,Male
+68,Adelie,Torgersen,35.9,16.6,190.0,3050.0,Female
+69,Adelie,Torgersen,41.8,19.4,198.0,4450.0,Male
+70,Adelie,Torgersen,33.5,19.0,190.0,3600.0,Female
+71,Adelie,Torgersen,39.7,18.4,190.0,3900.0,Male
+72,Adelie,Torgersen,39.6,17.2,196.0,3550.0,Female
+73,Adelie,Torgersen,45.8,18.9,197.0,4150.0,Male
+74,Adelie,Torgersen,35.5,17.5,190.0,3700.0,Female
+75,Adelie,Torgersen,42.8,18.5,195.0,4250.0,Male
+76,Adelie,Torgersen,40.9,16.8,191.0,3700.0,Female
+77,Adelie,Torgersen,37.2,19.4,184.0,3900.0,Male
+78,Adelie,Torgersen,36.2,16.1,187.0,3550.0,Female
+79,Adelie,Torgersen,42.1,19.1,195.0,4000.0,Male
+80,Adelie,Torgersen,34.6,17.2,189.0,3200.0,Female
+81,Adelie,Torgersen,42.9,17.6,196.0,4700.0,Male
+82,Adelie,Torgersen,36.7,18.8,187.0,3800.0,Female
+83,Adelie,Torgersen,35.1,19.4,193.0,4200.0,Male
+84,Adelie,Dream,37.3,17.8,191.0,3350.0,Female
+85,Adelie,Dream,41.3,20.3,194.0,3550.0,Male
+86,Adelie,Dream,36.3,19.5,190.0,3800.0,Male
+87,Adelie,Dream,36.9,18.6,189.0,3500.0,Female
+88,Adelie,Dream,38.3,19.2,189.0,3950.0,Male
+89,Adelie,Dream,38.9,18.8,190.0,3600.0,Female
+90,Adelie,Dream,35.7,18.0,202.0,3550.0,Female
+91,Adelie,Dream,41.1,18.1,205.0,4300.0,Male
+92,Adelie,Dream,34.0,17.1,185.0,3400.0,Female
+93,Adelie,Dream,39.6,18.1,186.0,4450.0,Male
+94,Adelie,Dream,36.2,17.3,187.0,3300.0,Female
+95,Adelie,Dream,40.8,18.9,208.0,4300.0,Male
+96,Adelie,Dream,38.1,18.6,190.0,3700.0,Female
+97,Adelie,Dream,40.3,18.5,196.0,4350.0,Male
+98,Adelie,Dream,33.1,16.1,178.0,2900.0,Female
+99,Adelie,Dream,43.2,18.5,192.0,4100.0,Male
+100,Adelie,Biscoe,35.0,17.9,192.0,3725.0,Female
+101,Adelie,Biscoe,41.0,20.0,203.0,4725.0,Male
+102,Adelie,Biscoe,37.7,16.0,183.0,3075.0,Female
+103,Adelie,Biscoe,37.8,20.0,190.0,4250.0,Male
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diff --git a/penguins.xlsx b/penguins.xlsx
new file mode 100644
index 0000000..dec9dde
Binary files /dev/null and b/penguins.xlsx differ
diff --git a/penguins_server.py b/penguins_server.py
new file mode 100644
index 0000000..62449e2
--- /dev/null
+++ b/penguins_server.py
@@ -0,0 +1,125 @@
+''' 
+Purpose: Provide reactive output for the Penguins dataset.
+
+Use inputs from the UI Sidebar to filter the dataset.
+
+Update ouputs in the UI Main Panel.
+
+Matching the IDs in the UI Sidebar and function/ouput names in the UI Main Panel
+to this server code is critical. They are case sensitive and must match exactly.
+
+'''
+from shiny import *
+import pandas as pd
+from bokeh.plotting import figure
+from shinywidgets import render_widget
+import plotly.express as px
+import plotly.graph_objs as go
+from shinywidgets import render_widget
+import jupyter_bokeh as jbk
+
+from util_logger import setup_logger
+logger, logname = setup_logger(__name__)
+
+def get_penguins_server_functions(input, output, session):
+
+
+    # Local variables just for this function
+    # The original dataset and the total record count
+
+    original_df = pd.read_excel("penguins.xlsx")
+    total_count = len(original_df)
+
+    # Create a reactive value to hold the filtered pandas dataframe
+    reactive_df = reactive.Value()
+
+    # Create a reactive effect to set the reactive value when inputs change
+    # List all the inputs that should trigger this update
+
+    @reactive.Effect
+    @reactive.event(input.PENGUIN_BODY_MASS_RANGE, input.PENGUIN_MAX_BILL,
+                    input.PENGUIN_SPECIES_Adelie, input.PENGUIN_SPECIES_Chinstrap, 
+                    input.PENGUIN_SPECIES_Gentoo, input.PENGUIN_GENDER )
+    def _():        
+        ''' Reactive effect to update the filtered dataframe when inputs change.
+        This is the only way to set a reactive value (after initialization).
+        It doesn't need a name, because no one calls it directly.'''
+
+        logger.info("UI inputs changed. Updating penguins reactive df")
+
+        df = original_df.copy()
+
+        # Body mass is a range
+        input_range = input.PENGUIN_BODY_MASS_RANGE()
+        input_min = input_range[0]
+        input_max = input_range[1]
+        body_mass_filter = (df["body_mass_g"] >= input_min)  & (df["body_mass_g"] <= input_max)
+        df = df[body_mass_filter]
+
+        # Bill length is a max number
+        bill_length_filter = df["bill_length_mm"] <= input.PENGUIN_MAX_BILL()
+        df = df[bill_length_filter]
+
+        # Species is a list of checkboxes (a list of possible values)
+        show_species_list = []
+        if input.PENGUIN_SPECIES_Adelie():
+            show_species_list.append("Adelie")
+        if input.PENGUIN_SPECIES_Chinstrap():
+            show_species_list.append("Chinstrap")
+        if input.PENGUIN_SPECIES_Gentoo():
+            show_species_list.append("Gentoo")
+        show_species_list = show_species_list or ["Adelie", "Chinstrap", "Gentoo"]
+        species_filter = df["species"].isin(show_species_list)
+        df = df[species_filter]
+
+        # Gender is a radio button
+        input_gender = input.PENGUIN_GENDER()
+        gender_dict = {"a": "All", "f": "Female", "m": "Male"}
+        if input_gender != "a":
+            gender_filter = df["sex"] == gender_dict[input_gender]
+            df = df[gender_filter]
+
+        #logger.debug(f"filtered penguins df: {df}")
+        reactive_df.set(df)
+
+
+    @output
+    @render.text
+    def penguins_record_count_string():
+        logger.debug("Triggered: penguins_filter_record_count_string") 
+        filtered_count = len(reactive_df.get())
+        message = f"Showing {filtered_count} of {total_count} records"
+        logger.debug(f"filter message: {message}")
+        return message
+
+    @output
+    @render.table
+    def penguins_filtered_table():
+        filtered_df = reactive_df.get()
+        return filtered_df
+
+    @output
+    @render_widget
+    def penguins_output_widget1():
+        df = reactive_df.get()
+        plotly_plot  = px.scatter(
+          df,
+            x="bill_length_mm",
+            y="body_mass_g",
+            color="species",
+            title="Penguins Plot (Plotly Express))",
+            labels={
+                "bill_length_mm": "Bill Length (mm)",
+                "body_mass_g": "Body Mass (g)"
+            },
+            size_max=8
+        )
+        
+        return plotly_plot
+
+    # return a list of function names for use in reactive outputs
+    return [
+        penguins_record_count_string,
+        penguins_filtered_table,
+        penguins_output_widget1,
+    ]
diff --git a/penguins_ui_inputs.py b/penguins_ui_inputs.py
new file mode 100644
index 0000000..9c71d03
--- /dev/null
+++ b/penguins_ui_inputs.py
@@ -0,0 +1,42 @@
+"""
+Purpose: Provide user interaction options for the Penguins dataset.
+
+Checkboxes should be independent of each other.
+
+Radio buttons should be mutually exclusive.
+
+IDs must be unique. They are capitalized in this app for clarity (not typical).
+The IDs are case-sensitive and must match the server code exactly.
+
+We prefaced IDs with the dataset name to avoid naming conflicts.
+
+"""
+
+from shiny import ui
+
+
+def get_penguins_sidebar():
+    return ui.panel_sidebar(
+        ui.h2("Penguins Interaction"),
+        ui.tags.hr(),
+        ui.input_slider(
+            "PENGUIN_BODY_MASS_RANGE",
+            "Body Mass (g)",
+            min=2700,
+            max=6300,
+            value=[2700, 6300],
+        ),
+        ui.input_numeric("PENGUIN_MAX_BILL", "Max Bill Length (mm):", value=60.0),
+        ui.input_checkbox("PENGUIN_SPECIES_Adelie", "Adelie", value=True),
+        ui.input_checkbox("PENGUIN_SPECIES_Chinstrap", "Chinstrap", value=True),
+        ui.input_checkbox("PENGUIN_SPECIES_Gentoo", "Gentoo", value=True),
+        ui.input_radio_buttons(
+            "PENGUIN_GENDER",
+            "Select Genders",
+            {"a": "All (includes missing values)", "f": "Female", "m": "Male"},
+            selected="a",
+        ),
+        ui.tags.hr(),
+        ui.p("Please be patient. The charts may take a few seconds to load."),
+        ui.tags.hr(),
+    )
diff --git a/penguins_ui_outputs.py b/penguins_ui_outputs.py
new file mode 100644
index 0000000..28b4ae8
--- /dev/null
+++ b/penguins_ui_outputs.py
@@ -0,0 +1,21 @@
+'''
+Purpose: Display ouput for the Penguins dataset.
+'''
+from shiny import ui
+from shinywidgets import output_widget
+
+def get_penguins_main():
+    return ui.panel_main(
+        ui.h2("Main Panel with Reactive Output"),
+        ui.tags.hr(),
+        ui.tags.section(
+            ui.h3("Filtered Penguins: Charts"),
+            output_widget("penguins_output_widget1"),
+            ui.tags.hr(),
+            ui.h3("Filtered Penguins Table"),
+            ui.output_text("penguins_record_count_string"),
+            ui.output_table("penguins_filtered_table"),
+            ui.tags.hr(),
+
+        )
+    )
diff --git a/relationships_server.py b/relationships_server.py
new file mode 100644
index 0000000..e8fde77
--- /dev/null
+++ b/relationships_server.py
@@ -0,0 +1,74 @@
+''' 
+Purpose: Provide reactive output for the relationships dataset.
+
+Use inputs from the UI Sidebar to filter the dataset.
+
+Update ouputs in the UI Main Panel.
+
+See: https://holoviews.org/reference/elements/bokeh/Chord.html
+
+'''
+
+from shiny import *
+import pandas as pd
+import holoviews as hv
+from holoviews import opts, dim
+from bokeh.sampledata.les_mis import data
+import jupyter_bokeh as jbk
+from shinywidgets import render_widget
+
+hv.extension('bokeh')
+
+from util_logger import setup_logger
+logger, logname = setup_logger(__name__)
+
+
+def get_relationships_server_functions(input, output, session):
+    
+    # get a pandas dataframe of the links and the nodes
+    df_links = pd.DataFrame(data['links'])
+    df_nodes = pd.DataFrame(data['nodes'])
+
+    # get a holoviews dataset of nodes. the 'index' column is the node id
+    nodes = hv.Dataset(df_nodes, 'index')
+
+  
+      
+    @output
+    @render_widget
+    def relationships_output_widget1():
+
+      if (input.RELATIONSHIPS_SHOW_TOGGLE()):
+        logger.info("UI inputs changed. Updating relationships output widget2")
+
+        # create a chord diagram from the links and the nodes
+        # value = (5, None) means that only links with a value of 5 or greater will be shown
+        chord = hv.Chord((df_links, nodes)).select(value=(5, None))
+
+        # Set some chart options
+        # Category20 is a color palette
+        # The edge_color is based on the source node
+        # The node_color is based on the index (node id)
+        # The labels are the names of the nodes (from the name column)
+        chord.opts(
+          opts.Chord(
+            cmap='Category20', 
+            edge_cmap='Category20', 
+            edge_color=dim('source').str(), 
+            labels='name', 
+            node_color=dim('index').str(),
+            title='Les Miserables Relationships 5+ (HoloViews Bokeh)',
+            width=800,
+            height=800,
+        ))
+
+        widget = hv.render(chord, backend='bokeh')
+        wrapped_widget = jbk.BokehModel(widget)
+        return wrapped_widget
+      else:
+         return None
+    
+    # return a list of function names for use in reactive outputs
+    return [
+        relationships_output_widget1,
+    ]
diff --git a/relationships_ui_inputs.py b/relationships_ui_inputs.py
new file mode 100644
index 0000000..df71965
--- /dev/null
+++ b/relationships_ui_inputs.py
@@ -0,0 +1,28 @@
+"""
+Purpose: Provide user interaction options for the relationships dataset.
+
+"""
+from shiny import ui
+from htmltools import head_content, HTML
+
+from util_logger import setup_logger
+
+logger, logname = setup_logger(__name__)
+
+bokeh_dependency = None
+try:
+    from bokeh.resources import Resources
+
+    bokeh_dependency = head_content(HTML(Resources(mode="inline").render()))
+except ImportError:
+    logger.warn("Could not import bokeh")
+
+
+def get_relationships_sidebar():
+    return bokeh_dependency, ui.panel_sidebar(
+        ui.h2("Relationships Interaction"),
+        ui.input_switch("RELATIONSHIPS_SHOW_TOGGLE", "Show Charts", value=True),
+        ui.tags.hr(),
+        ui.p("Please be patient. The charts may take a few seconds to load."),
+        ui.tags.hr(),
+    )
diff --git a/relationships_ui_outputs.py b/relationships_ui_outputs.py
new file mode 100644
index 0000000..c53403c
--- /dev/null
+++ b/relationships_ui_outputs.py
@@ -0,0 +1,17 @@
+"""
+Purpose: Display ouput for the relationships dataset.
+"""
+from shiny import ui
+from shinywidgets import output_widget
+
+
+def get_relationships_main():
+    return ui.panel_main(
+        ui.h2("Main Panel with Reactive Output"),
+        ui.tags.hr(),
+        ui.tags.section(
+            ui.h3("Relationships: Charts"),
+            output_widget("relationships_output_widget1"),
+            ui.tags.hr(),
+        ),
+    )
diff --git a/requirements.txt b/requirements.txt
new file mode 100644
index 0000000..a0c4e1f
--- /dev/null
+++ b/requirements.txt
@@ -0,0 +1,15 @@
+shiny 
+shinyswatch 
+pandas 
+openpyxl 
+jinja2 
+matplotlib 
+seaborn 
+plotnine
+shinywidgets 
+plotly 
+holoviews 
+panel 
+hvplot 
+ipyleaflet
+jupyter_bokeh 
\ No newline at end of file
diff --git a/util_logger.py b/util_logger.py
new file mode 100644
index 0000000..7781f96
--- /dev/null
+++ b/util_logger.py
@@ -0,0 +1,85 @@
+"""
+Purpose: Set up logging once and reuse it. 
+
+Author: Denise Case
+
+This file automatically records your work so you don't have to. 
+Analysts and data scientists will work hard once, to be lazy later.
+You should be able to reuse this code without modification.
+You're also welcome to use it as a template for your own logging. 
+
+"""
+
+import logging
+import pathlib
+import platform
+import sys
+import os
+import datetime
+
+def get_source_directory_path(current_file):
+    """Returns the absolute path to this source directory."""
+    dir = os.path.dirname(os.path.abspath(current_file))
+    return dir
+
+def setup_logger(current_file):
+    '''Setup a logger to automatically log useful information.
+      @param current_file: the name of the file reqesting a logger.
+      @returns: the logger object and the name of the logfile.
+    '''
+    logs_dir = pathlib.Path("logs")
+    logs_dir.mkdir(exist_ok=True)
+
+    module_name = pathlib.Path(current_file).stem
+    log_file_name = logs_dir.joinpath(module_name + ".log")
+
+    logger = logging.getLogger(module_name)
+    logger.setLevel(logging.DEBUG)  # Set the root logger level.
+
+    # Create file handler which logs even debug messages.
+    file_handler = logging.FileHandler(log_file_name, "w")
+    file_handler.setLevel(logging.DEBUG)
+
+    # Create console handler with a higher log level.
+    console_handler = logging.StreamHandler()
+    console_handler.setLevel(logging.INFO)
+
+    # Create formatter and add it to the handlers.
+    formatter = logging.Formatter('%(asctime)s.%(name)s.%(levelname)s.%(message)s')
+    file_handler.setFormatter(formatter)
+    console_handler.setFormatter(formatter)
+
+    # Add the handlers to the logger.
+    logger.addHandler(file_handler)
+    logger.addHandler(console_handler)
+
+    divider_string = "============================================================="
+    python_version_string  = platform.python_version()
+    today = datetime.date.today()
+
+    logger.info(divider_string)
+    logger.info(divider_string)
+    logger.info(f"Today is {today} at {datetime.datetime.now().strftime('%I:%M %p')}")
+    logger.info(f"This file is running on: {os.name} {platform.system()} {platform.release()}")
+    logger.info(f"The Python version is: {python_version_string}")
+    logger.info(f"The active conda environment is:  {os.environ.get('CONDA_DEFAULT_ENV') }")
+    logger.info(f"The active pip environment is:    {os.environ.get('PIP_DEFAULT_ENV') }")
+    logger.info(f"The active environment path is:   {sys.prefix}")
+    logger.info(f"The current working directory is: {os.getcwd()}")
+    logger.info(f"This source file is in:           {get_source_directory_path(current_file)}")
+    logger.info(divider_string)
+    logger.info(divider_string)
+
+    return logger, log_file_name
+
+if __name__ == "__main__":
+    logger, logname = setup_logger(__file__)
+    logger.info(f"Starting util_datafun_logger.py")
+    logger.info(f"Information is logged to: logs/{logname}")
+    logger.info(f"Ending util_datafun_logger.py")
+
+    # Use built-in open() function to read log file and print it to the terminal
+    with open(logname, 'r') as file_wrapper:
+        print(file_wrapper.read())
+
+    
\ No newline at end of file