initial commit

.gitignore

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+venv/
+dataset.py

app.py

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+import streamlit as st
+import pandas as pd
+import kagglehub
+import zipfile
+import os
+
+st.title('Dashboard de Venture Capital')
+st.markdown('Demo portafolio de Machine Learning y Venture Capital')
+
+# Download latest version
+path = kagglehub.dataset_download("sashakorovkina/4808-techstars-backed-companies-in-2024", path="./datasets/")
+
+# # Unzip the dataset (if compressed)
+# with zipfile.ZipFile(path, 'r') as zip_ref:
+#     zip_ref.extractall("./datasets")
+
+# Load CSV into a DataFrame
+csv_path = "./datasets/sashakorovkina/4808-techstars-backed-companies-in-2024.csv"
+df = pd.read_csv(csv_path)
+
+# Display DataFrame in Streamlit
+st.write(df.head())
+
+
+# Sidebar and Filter
+st.sidebar.write("Opciones para Filtro")

requirements.txt

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+streamlit
+kagglehub