Create Child Mortality vs Daily Income.py (#3)

- Create Child Mortality vs Daily Income.py (d1a7338220465be5b579d574330ec6236ffea742)


Co-authored-by: Ji Eun Kim <jieunk3@users.noreply.huggingface.co>

pages/Child Mortality vs Daily Income.py

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+import streamlit as st
+import pandas as pd
+import altair as alt
+
+income_df = pd.read_csv('https://huggingface.co/spaces/jiyachachan/fp2/resolve/main/mincpcap_cppp.csv')
+mortality_df = pd.read_csv('https://huggingface.co/spaces/jiyachachan/fp2/resolve/main/child_mortality_0_5_year_olds_dying_per_1000_born.csv')
+
+income_long = pd.melt(income_df, id_vars=['country'], var_name='year', value_name='income')
+mortality_long = pd.melt(mortality_df, id_vars=['country'], var_name='year', value_name='mortality')
+
+income_long['year'] = income_long['year'].astype(int)
+mortality_long['year'] = mortality_long['year'].astype(int)
+
+yay = pd.merge(income_long, mortality_long, on=['country', 'year'])
+
+yer = yay.dropna()
+yer = yer[yer["year"] <= 2024]
+
+st.title("Child Mortality vs Daily Income")
+
+filtered_yer = yer[yer["year"] == yeyear]
+
+scatter_plot = alt.Chart(filtered_yer).mark_circle(size=60).encode(
+    x=alt.X('income', title='Daily Income (USD)', scale=alt.Scale(type='log')),
+    y=alt.Y('mortality', title='Child Mortality (per 1,000)'),
+    color='country',
+    tooltip=['country', 'year', 'income', 'mortality']
+).properties(
+    width=700,
+    height=500,
+    title=f"Child Mortality vs Daily Income in {yeyear}"
+)
+
+st.altair_chart(scatter_plot, use_container_width=True)
+
+st.text("The interactive scatterplot above displays Child Mortality versus Daily Income from 24 countries. The interactive slider allows the user to choose a year where the earliest year is 1800 and the maximum year is 2024. The x-axis is represented by daily income (USD) set to a logarithmic scale for better visualization of larger income ranges, and the y-axis is represented by child mortality (per 1,000). Each country is assigned a unique color and we incorporate a hover tooltip to show the country, year, income, and mortality rate for a specific data point.")