Final tidy

vizro-core/examples/visual-vocabulary/pages/__init__.py

@@ -0,0 +1 @@
+# TODO: eventually deduplicate page generation into a function rather than copying and pasting across files?

vizro-core/examples/visual-vocabulary/pages/_pages_utils.py

@@ -45,7 +45,7 @@ def make_code_clipboard_from_py_file(filepath: str, mode="vizro"):
     example_code = (Path(__file__).parents[1] / "pages/examples" / filepath).read_text()
 
     if mode == "vizro":
-        example_code = VIZRO_CODE_TEMPLATE.format(title="Title", example_code=example_code)
+        example_code = VIZRO_CODE_TEMPLATE.format(example_code=example_code)
     else:
         replacements = {"import vizro.plotly.express as px": "import plotly.express as px", '@capture("graph")': ""}
         for old_code, new_code in replacements.items():
@@ -59,82 +59,3 @@ def make_code_clipboard_from_py_file(filepath: str, mode="vizro"):
 
 
 PAGE_GRID = [[0, 0, 0, 0, 0, 0, 0]] * 2 + [[1, 1, 1, 1, 2, 2, 2]] * 5
-
-# DATA --------------------------------------------------------------
-gapminder = px.data.gapminder()
-iris = px.data.iris()
-stocks = px.data.stocks()
-tips = px.data.tips()
-wind = px.data.wind()
-ages = pd.DataFrame(
-    {
-        "Age": ["0-19", "20-29", "30-39", "40-49", "50-59", ">=60"],
-        "Male": [800, 2000, 4200, 5000, 2100, 800],
-        "Female": [1000, 3000, 3500, 3800, 3600, 700],
-    }
-)
-sankey_data = pd.DataFrame(
-    {
-        "Origin": [0, 1, 0, 2, 3, 3],
-        "Destination": [2, 3, 3, 4, 4, 5],
-        "Value": [8, 4, 2, 8, 4, 2],
-    }
-)
-
-funnel_data = pd.DataFrame(
-    {"Stage": ["Leads", "Sales calls", "Follow-up", "Conversion", "Sales"], "Value": [10, 7, 4, 2, 1]}
-)
-
-stepped_line_data = pd.DataFrame(
-    {
-        "year": [1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003],
-        "rate": [0.10, 0.12, 0.15, 0.13, 0.14, 0.13, 0.14, 0.16, 0.15],
-    }
-)
-
-
-carshare = px.data.carshare()
-
-tasks = pd.DataFrame(
-    [
-        {"Task": "Job A", "Start": "2009-01-01", "Finish": "2009-02-28"},
-        {"Task": "Job B", "Start": "2009-03-05", "Finish": "2009-04-15"},
-        {"Task": "Job C", "Start": "2009-02-20", "Finish": "2009-05-30"},
-    ]
-)
-
-waterfall_data = pd.DataFrame(
-    {
-        "x": ["Sales", "Consulting", "Net revenue", "Purchases", "Other expenses", "Profit before tax"],
-        "y": [60, 80, 0, -40, -20, 0],
-        "measure": ["relative", "relative", "total", "relative", "relative", "total"],
-    }
-)
-
-pastries = pd.DataFrame(
-    {
-        "pastry": [
-            "Scones",
-            "Bagels",
-            "Muffins",
-            "Cakes",
-            "Donuts",
-            "Cookies",
-            "Croissants",
-            "Eclairs",
-        ],
-        "Profit Ratio": [-0.10, -0.05, 0.10, 0.05, 0.15, -0.08, 0.08, -0.12],
-        "Strongly Disagree": [20, 30, 10, 5, 15, 5, 10, 25],
-        "Disagree": [30, 25, 20, 10, 20, 10, 15, 30],
-        "Agree": [30, 25, 40, 40, 45, 40, 40, 25],
-        "Strongly Agree": [20, 20, 30, 45, 20, 45, 35, 20],
-    }
-)
-
-salaries = pd.DataFrame(
-    {
-        "Job": ["Developer", "Analyst", "Manager", "Specialist"],
-        "Min": [60000, 55000, 70000, 50000],
-        "Max": [130000, 110000, 96400, 80000],
-    }
-)

vizro-core/examples/visual-vocabulary/pages/examples/column_and_line.py

@@ -33,6 +33,6 @@ def column_and_line(
     return fig
 
 
-gapminder = px.data.gapminder()
+gapminder = px.data.gapminder().query("country == 'Vietnam'")
 
-fig = column_and_line(gapminder.query("country == 'Vietnam'"), y_column="gdpPercap", y_line="lifeExp", x="year")
+fig = column_and_line(gapminder, y_column="gdpPercap", y_line="lifeExp", x="year")

vizro-core/examples/visual-vocabulary/pages/examples/treemap.py

@@ -1,7 +1,5 @@
 import vizro.plotly.express as px
 
-gapminder = px.data.gapminder()
+gapminder = px.data.gapminder().query("year == 2007")
 
-fig = px.treemap(
-    gapminder.query("year == 2007"), path=[px.Constant("world"), "continent", "country"], values="pop", color="lifeExp"
-)
+fig = px.treemap(gapminder, path=[px.Constant("world"), "continent", "country"], values="pop", color="lifeExp")