Scratch work for creating graphs for presentations

tmp_graph.py

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+import altair as alt
+from altair import datum
+
+import pandas as pd
+
+data = [
+    ["fiona", 232, "FlatGeobuf"],
+    ["pyogrio", 108, "FlatGeobuf"],
+    ["GeoArrow", 10, "FlatGeobuf"],
+    ["fiona", 227, "GeoPackage"],
+    ["pyogrio", 103, "GeoPackage"],
+    ["GeoArrow", 10, "GeoPackage"],
+]
+
+# Create the pandas DataFrame
+df = pd.DataFrame(data, columns=["Method", "Read time (s)", "File Format"])
+
+gp_chart = (
+    alt.Chart(df)
+    .mark_bar()
+    .encode(
+        alt.X("Read time (s)"),
+        alt.Y("File Format", axis=alt.Axis(grid=True)),
+        alt.Color("Method"),
+        yOffset="Method",
+    )
+)
+gp_chart = gp_chart.properties(
+    title="Reading geospatial data to a GeoPandas GeoDataFrame",
+    # width=alt.Step(80),  # Adjust the width of bars if needed
+)
+
+gp_chart
+gp_chart.save("chart.png", ppi=200, scale_factor=10)
+!pip install vl-convert-python
+
+
+
+# Example data
+data = pd.DataFrame({"Category": ["A", "B", "C", "D"], "Value": [20, 35, 30, 25]})
+
+# Create the Altair chart
+chart = alt.Chart(data).mark_bar().encode(x="Category", y="Value")
+
+# Optionally, add titles and adjust appearance
+chart = chart.properties(
+    title="Bar Chart Example",
+    width=alt.Step(80),  # Adjust the width of bars if needed
+)
+
+# Show the chart
+chart

tmp_line_graph.py

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+import altair as alt
+from vega_datasets import data
+
+source = data.stocks()
+
+source
+
+alt.Chart(source).mark_line().encode(
+    x="date:T",
+    y="price:Q",
+    color="symbol:N",
+)
+
+import pandas as pd
+
+data = [
+    ["ipyleaflet", 10_000, 1.16],
+    ["ipyleaflet", 50_000, 5.3],
+    ["ipyleaflet", 100_000, 12.4],
+    ["ipyleaflet", 150_000, 17.43],
+    ["ipyleaflet", 200_000, 24.84],
+    ["ipyleaflet", 300_000, 50.29],
+    ["pydeck", 10_000, 0.96],
+    ["pydeck", 50_000, 3.75],
+    ["pydeck", 100_000, 6.52],
+    ["pydeck", 250_000, 17.79],
+    ["pydeck", 500_000, 35.63],
+    ["pydeck", 750_000, 55.1],
+    ["pydeck", 1_000_000, 74.25],
+    ["lonboard", 100_000, 0.55],
+    ["lonboard", 500_000, 0.71],
+    ["lonboard", 1_000_000, 0.92],
+    ["lonboard", 2_000_000, 1.25],
+    ["lonboard", 3_000_000, 1.67],
+    ["lonboard", 5_000_000, 3.32],
+    ["lonboard", 7_500_000, 4.33],
+    ["lonboard", 10_000_000, 5.61],
+    ["lonboard", 15_000_000, 7.95],
+]
+
+columns = ["Library", "# of rows", "Render time (s)"]
+df = pd.DataFrame(data, columns=columns)
+
+color_scale = alt.Scale(
+    domain=["ipyleaflet", "pydeck"],  # , "lonboard"],
+    range=["#4e79a7", "#f28e2b"],  # , "#59A14F"],
+)
+
+
+chart = (
+    alt.Chart(df)
+    .mark_line()
+    .encode(
+        x=f"{columns[1]}:Q",
+        y=f"{columns[2]}:Q",
+        color=alt.Color(shorthand=f"{columns[0]}:N", scale=color_scale),
+    )
+)
+chart = chart.properties(
+    title="Time to render interactive map by number of points",
+    # width=alt.Step(80),  # Adjust the width of bars if needed
+)
+chart
+# chart.save("ipyleaflet.png", ppi=200, scale_factor=10)
+chart.save("ipyleaflet_pydeck.png", ppi=200, scale_factor=10)
+# !pip install vl-convert-python