Prerelease 1.48.0: Apps (#1317)

* Use numpy Generator instance in app examples

* Apps for 1.48.0 features

* Bump streamlit version

Author: sfc-gh-dmatthews

pyproject.toml

@@ -0,0 +1,2 @@
+[tool.black]
+line-length = 79

python/api-examples-source/charts.altair_selections.py

@@ -1,15 +1,9 @@
-import streamlit as st
-import pandas as pd
-import numpy as np
 import altair as alt
+import pandas as pd
+import streamlit as st
+from numpy.random import default_rng as rng
 
-
-@st.cache_data
-def load_data():
-    return pd.DataFrame(np.random.randn(20, 3), columns=["a", "b", "c"])
-
-
-df = load_data()
+df = pd.DataFrame(rng(0).standard_normal((20, 3)), columns=["a", "b", "c"])
 
 point_selector = alt.selection_point("point_selection")
 interval_selector = alt.selection_interval("interval_selection")
@@ -22,7 +16,9 @@ def load_data():
         size="c",
         color="c",
         tooltip=["a", "b", "c"],
-        fillOpacity=alt.condition(point_selector, alt.value(1), alt.value(0.3)),
+        fillOpacity=alt.condition(
+            point_selector, alt.value(1), alt.value(0.3)
+        ),
     )
     .add_params(point_selector, interval_selector)
 )

python/api-examples-source/charts.area_chart.py

@@ -1,14 +1,7 @@
-import numpy as np
 import pandas as pd
 import streamlit as st
+from numpy.random import default_rng as rng
 
+df = pd.DataFrame(rng(0).standard_normal((20, 3)), columns=["a", "b", "c"])
 
-@st.cache_data
-def load_data():
-    df = pd.DataFrame(np.random.randn(20, 3), columns=["a", "b", "c"])
-    return df
-
-
-chart_data = load_data()
-
-st.area_chart(chart_data)
+st.area_chart(df)

python/api-examples-source/charts.area_chart1.py

@@ -1,20 +1,13 @@
-import numpy as np
 import pandas as pd
 import streamlit as st
+from numpy.random import default_rng as rng
 
+df = pd.DataFrame(
+    {
+        "col1": list(range(20)) * 3,
+        "col2": rng(0).standard_normal(60),
+        "col3": ["a"] * 20 + ["b"] * 20 + ["c"] * 20,
+    }
+)
 
-@st.cache_data
-def load_data():
-    df = pd.DataFrame(
-        {
-            "col1": np.random.randn(20),
-            "col2": np.random.randn(20),
-            "col3": np.random.choice(["A", "B", "C"], 20),
-        }
-    )
-    return df
-
-
-chart_data = load_data()
-
-st.area_chart(chart_data, x="col1", y="col2", color="col3")
+st.area_chart(df, x="col1", y="col2", color="col3")

python/api-examples-source/charts.area_chart2.py

@@ -1,16 +1,18 @@
-import numpy as np
 import pandas as pd
 import streamlit as st
+from numpy.random import default_rng as rng
 
-
-@st.cache_data
-def load_data():
-    df = pd.DataFrame(np.random.randn(20, 3), columns=["col1", "col2", "col3"])
-    return df
-
-
-chart_data = load_data()
+df = pd.DataFrame(
+    {
+        "col1": list(range(20)),
+        "col2": rng(0).standard_normal(20),
+        "col3": rng(1).standard_normal(20),
+    }
+)
 
 st.area_chart(
-    chart_data, x="col1", y=["col2", "col3"], color=["#FF0000", "#0000FF"]  # Optional
+    df,
+    x="col1",
+    y=["col2", "col3"],
+    color=["#FF000080", "#0000FF80"],
 )

python/api-examples-source/charts.area_chart_steamgraph.py

@@ -1,6 +1,6 @@
 import streamlit as st
 from vega_datasets import data
 
-source = data.unemployment_across_industries()
+df = data.unemployment_across_industries()
 
-st.area_chart(source, x="date", y="count", color="series", stack="center")
+st.area_chart(df, x="date", y="count", color="series", stack="center")

python/api-examples-source/charts.bar_chart.py

@@ -1,14 +1,7 @@
-import numpy as np
 import pandas as pd
 import streamlit as st
+from numpy.random import default_rng as rng
 
+df = pd.DataFrame(rng(0).standard_normal((20, 3)), columns=["a", "b", "c"])
 
-@st.cache_data
-def load_data():
-    df = pd.DataFrame(np.random.randn(20, 3), columns=["a", "b", "c"])
-    return df
-
-
-chart_data = load_data()
-
-st.bar_chart(chart_data)
+st.bar_chart(df)

python/api-examples-source/charts.bar_chart1.py

@@ -1,20 +1,13 @@
-import numpy as np
 import pandas as pd
 import streamlit as st
+from numpy.random import default_rng as rng
 
+df = pd.DataFrame(
+    {
+        "col1": list(range(20)) * 3,
+        "col2": rng(0).standard_normal(60),
+        "col3": ["a"] * 20 + ["b"] * 20 + ["c"] * 20,
+    }
+)
 
-@st.cache_data
-def load_data():
-    df = pd.DataFrame(
-        {
-            "col1": list(range(20)) * 3,
-            "col2": np.random.randn(60),
-            "col3": ["A"] * 20 + ["B"] * 20 + ["C"] * 20,
-        }
-    )
-    return df
-
-
-chart_data = load_data()
-
-st.bar_chart(chart_data, x="col1", y="col2", color="col3")
+st.bar_chart(df, x="col1", y="col2", color="col3")

python/api-examples-source/charts.bar_chart2.py

@@ -1,22 +1,18 @@
-import numpy as np
 import pandas as pd
 import streamlit as st
+from numpy.random import default_rng as rng
 
-
-@st.cache_data
-def load_data():
-    df = pd.DataFrame(
-        {
-            "col1": list(range(20)),
-            "col2": np.random.randn(20),
-            "col3": np.random.randn(20),
-        }
-    )
-    return df
-
-
-chart_data = load_data()
+df = pd.DataFrame(
+    {
+        "col1": list(range(20)),
+        "col2": rng(0).standard_normal(20),
+        "col3": rng(1).standard_normal(20),
+    }
+)
 
 st.bar_chart(
-    chart_data, x="col1", y=["col2", "col3"], color=["#FF0000", "#0000FF"]  # Optional
+    df,
+    x="col1",
+    y=["col2", "col3"],
+    color=["#FF0000", "#0000FF"],
 )

python/api-examples-source/charts.bar_chart_horizontal.py

@@ -1,10 +1,6 @@
 import streamlit as st
 from vega_datasets import data
 
-@st.cache_data
-def get_data():
-    return data.barley()
-
-source = get_data()
+source = data.barley()
 
 st.bar_chart(source, x="variety", y="yield", color="site", horizontal=True)