Add top-5-income-share-streamlit (#107)

* Add top-5-income-share-streamlit
* Use example category

---------

Co-authored-by: Jordan Jensen <[email protected]>

Author: cgraham-rs

.github/workflows/extensions.yml

@@ -45,6 +45,7 @@ jobs:
             fastapitableau-example: extensions/fastapitableau-example/**
             portfolio-report: extensions/portfolio-report/**
             quarto-script-r: extensions/quarto-script-r/**
+            top-5-income-share-streamlit: extensions/top-5-income-share-streamlit/**
             usage-metrics-dashboard: extensions/usage-metrics-dashboard/**
 
   # Runs for each extension that has changed from `simple-extension-changes`

extensions/top-5-income-share-streamlit/README.md

@@ -0,0 +1,15 @@
+# Top 5% income share
+
+## About this example
+
+A Streamlit application makes it easy to transform your analysis into an interactive dashboard using Python so users can ask and answer questions in real-time, without having to touch any code.
+
+
+## Learn more
+
+* [Streamlit Getting Started Guide](https://docs.streamlit.io/en/latest/getting_started.html)
+* [User Guide: Streamlit](https://docs.posit.co/connect/user/streamlit/)
+
+## Requirements
+
+* Python version 3.9 or higher

extensions/top-5-income-share-streamlit/app.py

@@ -0,0 +1,56 @@
+import os.path
+
+import altair as alt
+import pandas as pd
+import streamlit as st
+
+HERE = os.path.dirname(os.path.abspath(__file__))
+
+st.title("Top 5%" " income share")
+st.markdown("Share of income received by the richest 5%" " of the population.")
+DATA = os.path.join(HERE, "data.csv")
+
+
+@st.cache_data
+def load_data(nrows):
+    return pd.read_csv("./data.csv", nrows=nrows)
+
+
+data_load_state = st.text("Loading data...")
+data = load_data(10000)
+data_load_state.text("")
+
+countries = st.multiselect(
+    "Countries",
+    list(sorted({d for d in data["Entity"]})),
+    default=["Australia", "China", "Germany", "Japan", "United States"],
+)
+earliest_year = data["Year"].min()
+latest_year = data["Year"].max()
+min_year, max_year = st.slider(
+    "Year Range",
+    min_value=int(earliest_year),
+    max_value=int(latest_year),
+    value=[int(earliest_year), int(latest_year)],
+)
+filtered_data = data[data["Entity"].isin(countries)]
+filtered_data = filtered_data[filtered_data["Year"] >= min_year]
+filtered_data = filtered_data[filtered_data["Year"] <= max_year]
+
+chart = (
+    alt.Chart(filtered_data)
+    .mark_line()
+    .encode(
+        x=alt.X("Year", axis=alt.Axis(format="d")),
+        y=alt.Y("Percent", axis=alt.Axis(format="~s")),
+        color="Entity",
+        strokeDash="Entity",
+    )
+)
+st.altair_chart(chart, use_container_width=True)
+
+if st.checkbox("Show raw data"):
+    st.subheader("Raw data")
+    st.write(filtered_data)
+
+st.markdown("Source: <https://ourworldindata.org/grapher/top-5-income-share>")