Code Editor for app.py

import streamlit as st
import pandas as pd
import altair as alt

# Create sample data for leatherback turtles across populations
data = {
    'Population': ['Western Pacific', 'Eastern Pacific', 'Atlantic', 'Indian Ocean'] * 3,
    'Sex': ['Female', 'Female', 'Female', 'Female', 
            'Male', 'Male', 'Male', 'Male',
            'Unknown', 'Unknown', 'Unknown', 'Unknown'],
    'Carapace_Length_cm': [159, 145, 152, 147,
                          142, 138, 145, 140,
                          150, 142, 148, 143],
    'Standard_Deviation': [12, 10, 11, 9,
                          8, 7, 9, 8,
                          10, 9, 10, 8]
}

df = pd.DataFrame(data)

st.title('Global Leatherback Turtle Sizes by Population and Sex')
st.markdown('''
This visualization shows the average carapace (shell) length of leatherback turtles
across different populations and sexes. Error bars represent standard deviation.
''')

# Create an error bar chart using Altair
chart = alt.Chart(df).mark_bar().encode(
    x=alt.X('Population:N', title='Population'),
    y=alt.Y('Carapace_Length_cm:Q', title='Carapace Length (cm)'),
    color='Sex:N',
    column=alt.Column('Sex:N', title=None)
).properties(
    width=200
)

error_bars = alt.Chart(df).mark_errorbar().encode(
    x=alt.X('Population:N'),
    y=alt.Y('Carapace_Length_cm:Q', 
            scale=alt.Scale(zero=False),
            title='Carapace Length (cm)'),
    yError='Standard_Deviation:Q',
    color='Sex:N',
    column=alt.Column('Sex:N', title=None)
)

final_chart = (chart + error_bars).properties(
    title='Leatherback Turtle Sizes Across Populations'
)

st.altair_chart(final_chart, use_container_width=True)

# Display the raw data in a table
st.subheader('Raw Data')
st.dataframe(df)