Some cleanup

pola-rs · Jan 29, 2024 · 8ff4f78 · 8ff4f78
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diff --git a/docs/src/python/user-guide/misc/visualization.py b/docs/src/python/user-guide/misc/visualization.py
@@ -1,29 +1,26 @@
-# --8<-- [start:setup]
-import base64
-
-# --8<-- [end:setup]
 # --8<-- [start:dataframe]
-
 import polars as pl
 
-url = "docs/data/iris.csv"
+path = "docs/data/iris.csv"
 
+df = pl.scan_csv(path).group_by("species").agg(pl.col("petal_length").mean()).collect()
+print(df)
+# --8<-- [end:dataframe]
 
-iris_agg_df = (
-    pl.scan_csv(url)
-    .group_by("species")
-    .agg(
-        pl.col("petal_length").mean(),
-    )
-    .collect()
+"""
+# --8<-- [start:hvplot_show_plot]
+df.plot.bar(
+    x="species",
+    y="petal_length",
+    width=650,
 )
-
-# --8<-- [end:dataframe]
+# --8<-- [end:hvplot_show_plot]
+"""
 
 # --8<-- [start:hvplot_make_plot]
 import hvplot
 
-plot = iris_agg_df.plot.bar(
+plot = df.plot.bar(
     x="species",
     y="petal_length",
     width=650,
@@ -32,66 +29,71 @@
 with open("docs/images/hvplot_bar.html", "r") as f:
     chart_html = f.read()
     print(f"{chart_html}")
-
 # --8<-- [end:hvplot_make_plot]
+
 """
-# --8<-- [start:hvplot_show_plot]
-iris_agg_df.plot.bar(
-    x="species",
-    y="petal_length",
-    width=650,
-)
-# --8<-- [end:hvplot_show_plot]
-"""
+# --8<-- [start:matplotlib_show_plot]
+import matplotlib.pyplot as plt
 
+plt.bar(x=df["species"], height=df["petal_length"])
+# --8<-- [end:matplotlib_show_plot]
+"""
 
 # --8<-- [start:matplotlib_make_plot]
+import base64
+
 import matplotlib.pyplot as plt
 
-plt.bar(x=iris_agg_df["species"], height=iris_agg_df["petal_length"])
+plt.bar(x=df["species"], height=df["petal_length"])
 plt.savefig("docs/images/matplotlib_bar.png")
 with open("docs/images/matplotlib_bar.png", "rb") as f:
     png = base64.b64encode(f.read()).decode()
     print(f'<img src="data:image/png;base64, {png}"/>')
-
 # --8<-- [end:matplotlib_make_plot]
-"""
-# --8<-- [start:matplotlib_show_plot]
-import matplotlib.pyplot as plt
 
-plt.bar(x=iris_agg_df["species"], height=iris_agg_df["petal_length"])
-# --8<-- [end:matplotlib_show_plot]
 """
+# --8<-- [start:seaborn_show_plot]
+import seaborn as sns
+sns.barplot(
+    df,
+    x="species",
+    y="petal_length",
+)
+# --8<-- [end:seaborn_show_plot]
+"""
+
 # --8<-- [start:seaborn_make_plot]
 import seaborn as sns
 
 sns.barplot(
-    iris_agg_df,
+    df,
     x="species",
     y="petal_length",
 )
 plt.savefig("docs/images/seaborn_bar.png")
 with open("docs/images/seaborn_bar.png", "rb") as f:
     png = base64.b64encode(f.read()).decode()
     print(f'<img src="data:image/png;base64, {png}"/>')
-
 # --8<-- [end:seaborn_make_plot]
+
 """
-# --8<-- [start:seaborn_show_plot]
-import seaborn as sns
-sns.barplot(
-    iris_agg_df,
+# --8<-- [start:plotly_show_plot]
+import plotly.express as px
+
+px.bar(
+    df,
     x="species",
     y="petal_length",
+    width=400,
 )
-# --8<-- [end:seaborn_show_plot]
+# --8<-- [end:plotly_show_plot]
 """
 
 # --8<-- [start:plotly_make_plot]
 import plotly.express as px
 
 fig = px.bar(
-    iris_agg_df,
+    df,
     x="species",
     y="petal_length",
     width=650,
@@ -100,25 +102,21 @@
 with open("docs/images/plotly_bar.html", "r") as f:
     chart_html = f.read()
     print(f"{chart_html}")
-
 # --8<-- [end:plotly_make_plot]
+
 """
-# --8<-- [start:plotly_show_plot]
-import plotly.express as px
-px.bar(
-    iris_agg_df,
-    x="species",
-    y="petal_length",
-    width=400,
-)
-# --8<-- [end:plotly_show_plot]
+# --8<-- [start:altair_show_plot]
+import altair as alt
+
+alt.Chart(df, width=700).mark_bar().encode(x="species:N", y="petal_length:Q")
+# --8<-- [end:altair_show_plot]
 """
-# --8<-- [start:altair_make_plot]
 
+# --8<-- [start:altair_make_plot]
 import altair as alt
 
 chart = (
-    alt.Chart(iris_agg_df, width=600)
+    alt.Chart(df, width=600)
     .mark_bar()
     .encode(
         x="species:N",
@@ -129,19 +127,4 @@
 with open("docs/images/altair_bar.html", "r") as f:
     chart_html = f.read()
     print(f"{chart_html}")
-
 # --8<-- [end:altair_make_plot]
-
-"""
-# --8<-- [start:altair_show_plot]
-import altair as alt
-
-alt.Chart(iris_agg_df, width=700)
-.mark_bar()
-.encode(
-    x="species:N",
-    y="petal_length:Q",
-)
-
-# --8<-- [end:altair_show_plot]
-"""
diff --git a/docs/user-guide/misc/visualization.md b/docs/user-guide/misc/visualization.md
@@ -2,23 +2,17 @@
 
 Data in a Polars `DataFrame` can be visualized using common visualization libraries.
 
-<div style="display:none">
-```python exec="on" result="text" session="user-guide/misc/visualization"
---8<-- "python/user-guide/misc/visualization.py:setup"
-```
-</div>
-
 We illustrate plotting capabilities using the Iris dataset. We scan a CSV and then do a group-by on the `species` column and get the mean of the `petal_length`.
 
 {{code_block('user-guide/misc/visualization','dataframe',[])}}
 
-```python exec="on" session="user-guide/misc/visualization"
+```python exec="on" result="text" session="user-guide/misc/visualization"
 --8<-- "python/user-guide/misc/visualization.py:dataframe"
 ```
 
 ## Built-in plotting with hvPlot
 
-Polars has a `plot` method to create interactive plots using hvPlot.
+Polars has a `plot` method to create interactive plots using [hvPlot](https://hvplot.holoviz.org/).
 
 {{code_block('user-guide/misc/visualization','hvplot_show_plot',[])}}
 
@@ -39,7 +33,7 @@ data without null values.
 
 ## Seaborn, Plotly & Altair
 
-Seaborn, Plotly & Altair can accept a Polars `DataFrame` by leveraging the [dataframe interchange protocol](https://data-apis.org/dataframe-api/), which offers zero-copy-conversion where possible.
+[Seaborn](https://seaborn.pydata.org/), [Plotly](https://plotly.com/) & [Altair](https://altair-viz.github.io/) can accept a Polars `DataFrame` by leveraging the [dataframe interchange protocol](https://data-apis.org/dataframe-api/), which offers zero-copy conversion where possible.
 
 ### Seaborn