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#!/usr/bin/env python3 | |
# -*- coding: utf-8 -*- | |
""" | |
@author: hamzafarooq@ MABA CLASS | |
""" | |
import streamlit as st | |
import pandas as pd | |
import plotly.express as px | |
st.title("Uma") | |
st.markdown("This is a demo Streamlit app.") | |
st.markdown("My name is UN, hello world!..") | |
st.markdown("This is v2") | |
def load_data(): | |
df = pd.read_csv("https://datahub.io/machine-learning/iris/r/iris.csv") | |
return(df) | |
def run(): | |
st.subheader("Iris Data Loaded into a Pandas Dataframe.") | |
df = load_data() | |
disp_head = st.sidebar.radio('Select DataFrame Display Option:',('Head', 'All'),index=0) | |
#Multi-Select | |
#sel_plot_cols = st.sidebar.multiselect("Select Columns For Scatter Plot",df.columns.to_list()[0:4],df.columns.to_list()[0:2]) | |
#Select Box | |
#x_plot = st.sidebar.selectbox("Select X-axis Column For Scatter Plot",df.columns.to_list()[0:4],index=0) | |
#y_plot = st.sidebar.selectbox("Select Y-axis Column For Scatter Plot",df.columns.to_list()[0:4],index=1) | |
if disp_head=="Head": | |
st.dataframe(df.head()) | |
else: | |
st.dataframe(df) | |
#st.table(df) | |
#st.write(df) | |
#Scatter Plot | |
fig = px.scatter(df, x=df["sepallength"], y=df["sepalwidth"], color="class", | |
size='petallength', hover_data=['petalwidth']) | |
fig.update_layout({ | |
'plot_bgcolor': 'rgba(0, 0, 0, 0)'}) | |
fig.update_xaxes(showgrid=True, gridwidth=1, gridcolor='lightgray') | |
fig.update_yaxes(showgrid=True, gridwidth=1, gridcolor='lightgray') | |
st.write("\n") | |
st.subheader("Scatter Plot") | |
st.plotly_chart(fig, use_container_width=True) | |
#Add images | |
#images = ["<image_url>"] | |
#st.image(images, width=600,use_container_width=True, caption=["Iris Flower"]) | |
if __name__ == '__main__': | |
run() | |