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import streamlit as st
import pandas as pd
import plotly.express as px
import csv
import base64
# Default data for top two corporations per state
corporations_data = {
'Minnesota': [('CorpA', 100), ('CorpB', 50)],
'California': [('TechCorp', 300), ('HealthCorp', 200)],
# Add more states and corporations as needed
}
# Function to create a CSV file from the corporations_data dictionary
def create_csv():
csv_file = 'corporations_data.csv'
with open(csv_file, 'w', newline='') as file:
writer = csv.writer(file)
writer.writerow(['State', 'Corporation', 'Revenue'])
for state, data in corporations_data.items():
for corp, revenue in data:
writer.writerow([state, corp, revenue])
return csv_file
# Function to download CSV
def download_csv(file_name):
with open(file_name, 'r') as file:
csv_data = file.read()
b64 = base64.b64encode(csv_data.encode()).decode()
href = f'<a href="data:file/csv;base64,{b64}" download="{file_name}">Download CSV File 📥</a>'
return href
# Function to plot the map
def plot_map(data):
fig = px.choropleth(locations=data['State'], locationmode="USA-states", color=data['Revenue'],
scope="usa", title="Top Corporations by State in the United States",
hover_name=data['Corporation'], hover_data=['Revenue'])
return fig
# Create CSV from default data
csv_file = create_csv()
# Streamlit app
st.title('Top Corporations by State in the United States')
# Upload CSV
uploaded_files = st.file_uploader("Choose a CSV file", accept_multiple_files=True, type="csv")
# If files are uploaded, use them to generate maps
if uploaded_files:
for uploaded_file in uploaded_files:
data = pd.read_csv(uploaded_file)
st.write(f"Map for {uploaded_file.name}")
st.plotly_chart(plot_map(data))
else:
# Use default data
data = pd.read_csv(csv_file)
st.plotly_chart(plot_map(data))
# Download CSV
st.markdown(download_csv(csv_file), unsafe_allow_html=True)
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