Last updates

README.md

@@ -1,4 +1,4 @@
-# Chart gallery dashboard
+# Vizro - Visual vocabulary
 
 This dashboard shows a gallery of charts. It includes guidance on when to use each chart type and sample Python code
 to create them using [Plotly](https://plotly.com/python/) and [Vizro](https://github.com/mckinsey/vizro).
@@ -98,6 +98,6 @@ To contribute a chart, follow the steps below:
 
 ## How to run the example locally
 
-1. If you have `hatch` set up, run the example with the command `hatch run example _chart-gallery`.
+1. If you have `hatch` set up, run the example with the command `hatch run example _visual-vocabulary`.
    Otherwise, with a virtual Python environment activated, run `pip install -r requirements.txt` and then `python app.py`.
 2. You should now be able to access the app locally via http://127.0.0.1:8050/.

app.py

@@ -1,4 +1,4 @@
-"""App configuration for chart gallery dashboard."""
+"""App configuration for dashboard."""
 
 from typing import List, Union
 

custom_charts.py

@@ -136,8 +136,8 @@ def categorical_column(data_frame: pd.DataFrame, x: str, y: str):
     """Creates a column chart where the x-axis values are converted to category type."""
     fig = px.bar(
         data_frame,
-        y=y,
         x=x,
+        y=y,
     )
     # So ticks are aligned with bars when xaxes values are numbers (e.g. years)
     fig.update_xaxes(type="category")

pages/_pages_utils.py

@@ -1,5 +1,6 @@
 """Contains reusable data sets and constants."""
 
+import logging
 from pathlib import Path
 
 import black
@@ -7,6 +8,9 @@ import pandas as pd
 import vizro.plotly.express as px
 from custom_components import CodeClipboard
 
+# To disable logging info messages caused by black.format_str: https://github.com/psf/black/issues/2058
+logging.getLogger("blib2to3").setLevel(logging.ERROR)
+
 
 def make_code_clipboard_from_py_file(filepath: str):
     # Black doesn't yet have a Python API, so format_str might not work at some point in the future.

pages/examples/time_column.py

@@ -11,8 +11,8 @@ gapminder = px.data.gapminder()
 def categorical_column(data_frame: pd.DataFrame, x: str, y: str):
     fig = px.bar(
         data_frame,
-        y=y,
         x=x,
+        y=y,
     )
     # So ticks are aligned with bars when xaxes values are numbers (e.g. years)
     fig.update_xaxes(type="category")