Merge branch 'rebuild-website'

apps/problem-sets/1-getting-started/1.1-data-frame/app.py

@@ -4,6 +4,7 @@
 
 infile = Path(__file__).parent / "simulated-data.csv"
 df = pd.read_csv(infile)
+df = df.drop(columns=["text"])
 
 
 @render.____

apps/problem-sets/1-getting-started/1.3-filter-input/README

@@ -1,3 +1,2 @@
 Add a select input to the app which lets the user select one of the accounts. For reference the account list is:
-`["Berge & Berge",  "Fritsch & Fritsch", "Hintz & Hintz", "Mosciski and Sons", "Wolff Ltd"`
-    ]`
+`["Berge & Berge",  "Fritsch & Fritsch", "Hintz & Hintz", "Mosciski and Sons", "Wolff Ltd"]`

apps/problem-sets/1-getting-started/1.4-filter-connect/app.py

@@ -1,4 +1,4 @@
-from shiny.express import render, ui
+from shiny.express import render, ui, input
 import pandas as pd
 from pathlib import Path
 from data_import import df
@@ -18,5 +18,8 @@
 
 @render.data_frame
 def table():
-    account_counts = df.groupby("sub_account").size().reset_index(name="counts")
+    account_subset = df
+    account_counts = (
+        account_subset.groupby("sub_account").size().reset_index(name="counts")
+    )
     return account_counts

apps/problem-sets/1-getting-started/1.7-add-plot/app-solution.py

@@ -16,15 +16,6 @@
 )
 
 
-@render.data_frame
-def table():
-    account_subset = df[df["account"] == input.account()]
-    account_counts = (
-        account_subset.groupby("sub_account").size().reset_index(name="counts")
-    )
-    return account_counts
-
-
 @render_plotly
 def precision_recall_plot():
     account_subset = df[df["account"] == input.account()]

apps/problem-sets/3-reactivity/3.2-stacking-reactives/README

@@ -1,5 +1,5 @@
 We have a second sidebad input which allows the user to filter the dataset by the number of characters in the `text` field.
 Add a second reactive calculation to the app which filters the `account_data()` reactive.
 
-For `input.chars()` returns a tuple with the lower and upper range of a value, and you can filter the data frame with:
+For reference `input.chars()` returns a tuple with the lower and upper range of a value, and you can filter the data frame with:
 `df[df["text"].str.len().between(*input.chars()]`.

apps/problem-sets/3-reactivity/3.2-stacking-reactives/app-solution.py

@@ -12,7 +12,7 @@ def account_data():
 
 @reactive.calc()
 def character_filter():
-    return account_data()[(account_data()["text"].str.len().between(*input.chars()))]
+    return account_data()[account_data()["text"].str.len().between(*input.chars())]
 
 
 with ui.sidebar():

apps/problem-sets/3-reactivity/3.2-stacking-reactives/app.py

@@ -4,6 +4,12 @@
 from plots import plot_auc_curve, plot_precision_recall_curve, plot_score_distribution
 from shinywidgets import render_plotly
 
+
+@reactive.calc
+def account_data():
+    return df[df["account"] == input.account()]
+
+
 with ui.sidebar():
     ui.input_select(
         "account",
@@ -32,14 +38,11 @@
 
         @render_plotly
         def metric():
-            account_subset = df[df["account"] == input.account()]
             if input.metric() == "ROC Curve":
-                return plot_auc_curve(
-                    account_subset, "is_electronics", "training_score"
-                )
+                return plot_auc_curve(account_data, "is_electronics", "training_score")
             else:
                 return plot_precision_recall_curve(
-                    account_subset, "is_electronics", "training_score"
+                    account_data(), "is_electronics", "training_score"
                 )
 
         ui.input_select("metric", "Metric", choices=["ROC Curve", "Precision Recall"])
@@ -49,5 +52,4 @@ def metric():
 
         @render_plotly
         def score_dist():
-            account_subset = df[df["account"] == input.account()]
-            return plot_score_distribution(account_subset)
+            return plot_score_distribution(account_data())

exercises/1-hello-world.qmd

@@ -11,7 +11,6 @@ from helpers import problem_tabs
 
 ```
 
-# Exercise 1.0 - Hello World
 
 ```{python}
 # | echo: false

helpers.py

@@ -124,8 +124,11 @@ def find_problem_set_folder(base_path, target_path):
 
     path = find_problem_set_folder("apps/problem-sets", folder_name)
 
+    formatted_title = "## " + folder_name.replace("-", " ").title()
+
     block = QuartoPrint(
         [
+            formatted_title,
             "::::: {.column-screen-inset}",
             "::: {.panel-tabset}",
             "## Goal",