Upload 3_DataGen.py

pages/3_DataGen.py

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+import streamlit as st
+import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+from io import BytesIO
+
+# Title of the App
+st.title("Random Data Generator")
+
+# Sidebar for User Inputs
+st.sidebar.header("Settings")
+
+# Distribution Selector
+distribution = st.sidebar.selectbox(
+"Select a Distribution",
+["Uniform", "Bernoulli", "Gaussian", "Discrete"]
+)
+
+# Number of Data Points
+n_points = st.sidebar.number_input(
+"Number of Data Points", min_value=1, max_value=1000000, value=1000, step=1000
+)
+
+# Parameters for Distributions
+if distribution == "Uniform":
+    low = st.sidebar.number_input("Lower Bound", value=0.0)
+    high = st.sidebar.number_input("Upper Bound", value=1.0)
+    data = np.random.uniform(low, high, n_points)
+
+elif distribution == "Bernoulli":
+    p = st.sidebar.slider("Probability (p)", min_value=0.0, max_value=1.0, value=0.5)
+    data = np.random.binomial(1, p, n_points)
+
+elif distribution == "Gaussian":
+    mean = st.sidebar.number_input("Mean", value=0.0)
+    std_dev = st.sidebar.number_input("Standard Deviation", value=1.0)
+    data = np.random.normal(mean, std_dev, n_points)
+
+elif distribution == "Discrete":
+    low = st.sidebar.number_input("Lower Bound", value=0)
+    high = st.sidebar.number_input("Upper Bound", value=10)
+    data = np.random.randint(low, high + 1, n_points)
+
+
+# Visualization
+st.write("### Visualization")
+fig, ax = plt.subplots()
+ax.hist(data, bins=30, alpha=0.75, color="skyblue", edgecolor="black")
+ax.set_title(f"Histogram of {distribution} Distribution")
+ax.set_xlabel("Value")
+ax.set_ylabel("Frequency")
+st.pyplot(fig)
+
+
+# Display the Generated Data
+st.write(f"### {distribution} Distribution - {n_points} Points")
+df = pd.DataFrame(data, columns=["Value"])
+st.dataframe(df)
+
+with st.sidebar:
+    # Download the Data
+    st.write("### Download Data")
+    csv = df.to_csv(index=False).encode("utf-8")
+    st.download_button(
+    label="Download CSV",
+    data=csv,
+    file_name=f"{distribution}_data.csv",
+    mime="text/csv",
+    )