app.py

import streamlit as st
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

# Sidebar
st.sidebar.header("Select Visualization")
plot_type = st.sidebar.selectbox("Choose a plot type", ("Heatmap", "3D Heatmap", "Contour", "Quiver", "Contourf", "Streamplot", "Hexbin", "Eventplot", "Tricontour", "Triplot"))

# Load Data
# data = pd.read_csv("healthcare_treatments.csv")

# Define Functions for each plot type
def heatmap():
    fig, ax = plt.subplots()
    ax.set_title("Top Health Care Treatments")
    heatmap_data = np.random.rand(10, 10)
    im = ax.imshow(heatmap_data, cmap="YlOrRd")
    plt.colorbar(im, ax=ax)
    st.pyplot(fig)

def heatmap_3d():
    fig = plt.figure()
    ax = fig.add_subplot(111, projection='3d')
    ax.set_title("Top Health Care Treatments")
    x, y = np.meshgrid(range(10), range(10))
    z = np.random.rand(10, 10)
    ax.plot_surface(x, y, z, cmap="YlOrRd")
    st.pyplot(fig)

def contour():
    fig, ax = plt.subplots()
    ax.set_title("Top Health Care Treatments")
    x = np.linspace(-3, 3, 100)
    y = np.linspace(-3, 3, 100)
    X, Y = np.meshgrid(x, y)
    Z = np.sin(np.sqrt(X**2 + Y**2))
    ax.contour(X, Y, Z, cmap="YlOrRd")
    st.pyplot(fig)

def quiver():
    fig, ax = plt.subplots()
    ax.set_title("Top Health Care Treatments")
    x = np.arange(-2, 2, 0.2)
    y = np.arange(-2, 2, 0.2)
    X, Y = np.meshgrid(x, y)
    U = np.cos(X)
    V = np.sin(Y)
    ax.quiver(X, Y, U, V)
    st.pyplot(fig)

def contourf():
    fig, ax = plt.subplots()
    ax.set_title("Top Health Care Treatments")
    x = np.linspace(-3, 3, 100)
    y = np.linspace(-3, 3, 100)
    X, Y = np.meshgrid(x, y)
    Z = np.sin(np.sqrt(X**2 + Y**2))
    ax.contourf(X, Y, Z, cmap="YlOrRd")
    st.pyplot(fig)

def streamplot():
    fig, ax = plt.subplots()
    ax.set_title("Top Health Care Treatments")
    x, y = np.linspace(-3, 3, 100), np.linspace(-3, 3, 100)
    X, Y = np.meshgrid(x, y)
    U = -1 - X**2 + Y
    V = 1 + X - Y**2
    ax.streamplot(X, Y, U, V, density=[0.5, 1], cmap="YlOrRd")
    st.pyplot(fig)

def hexbin():
    fig, ax = plt.subplots()
    ax.set_title("Top Health Care Treatments")
    x = np.random.normal(0, 1, 1000)
    y = np.random.normal(0, 1, 1000)
    ax.hexbin(x, y, gridsize=20, cmap="YlOrRd")
    st.pyplot(fig)

def eventplot():
    fig, ax = plt.subplots()
    ax.set_title("Top Health Care Treatments")
    data = np.random.rand(10, 10) > 0.5
    ax.eventplot(np.where(data))
    st.pyplot(fig)

def tricontour():
    fig, ax = plt.subplots()
    ax.set_title("Top Health Care Treatments")
    x = np.random.rand(10)
    y = np.random.rand(10)
    z = np.random.rand(10)
    ax.tricontour(x, y, z, cmap="YlOrRd")
    st.pyplot(fig)

def triplot():
    fig, ax = plt.subplots()
    ax.set_title("Top Health Care Treatments")
    x = np.random.rand(10)
    y = np.random.rand(10)
    tri = np.random.randint(0, 10, (10, 3))
    ax.triplot(x, y, tri)
    st.pyplot(fig)

def voxel():
    fig = plt.figure()
    ax = fig.gca(projection='3d')
    ax.set_title("Top Health Care Treatments")
    x, y, z = np.indices((8, 8, 8))
    voxels = (x < 4) & (y < 4) & (z < 4)
    ax.voxels(voxels, facecolors='YlOrRd', edgecolor='k')
    st.pyplot(fig)

st.title("Top Health Care Treatments Visualizations")

if plot_type == "Heatmap":
    heatmap()
elif plot_type == "3D Heatmap":
    heatmap_3d()
elif plot_type == "Contour":
    contour()
elif plot_type == "Quiver":
    quiver()
elif plot_type == "Contourf":
    contourf()
elif plot_type == "Streamplot":
    streamplot()
elif plot_type == "Hexbin":
    hexbin()
elif plot_type == "Eventplot":
    eventplot()
elif plot_type == "Tricontour":
    tricontour()
elif plot_type == "Triplot":
    triplot()