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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() |