auto-ml / app.py
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Update app.py
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import streamlit as st
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
# Load the Iris dataset
iris_df = sns.load_dataset('iris')
# Sidebar for file upload and dataset selection
st.sidebar.title('Upload CSV File')
uploaded_file = st.sidebar.file_uploader("Choose a CSV file", type=['csv'])
if uploaded_file is not None:
# Read the uploaded file
custom_df = pd.read_csv(uploaded_file)
# Display the uploaded dataset
st.write('**Uploaded Dataset:**')
st.write(custom_df.head())
# Sidebar for plot selection
plot_type = st.sidebar.selectbox('Select Plot Type', ['Histogram', 'Scatter Plot'])
if plot_type == 'Histogram':
# Sidebar for selecting column
selected_column = st.sidebar.selectbox('Select Column for Histogram', custom_df.columns)
# Plot histogram
plt.figure(figsize=(8, 6))
sns.histplot(custom_df[selected_column])
st.pyplot()
elif plot_type == 'Scatter Plot':
# Sidebar for selecting columns
x_axis = st.sidebar.selectbox('Select X-Axis Column', custom_df.columns)
y_axis = st.sidebar.selectbox('Select Y-Axis Column', custom_df.columns)
# Plot scatter plot
plt.figure(figsize=(8, 6))
sns.scatterplot(x=x_axis, y=y_axis, data=custom_df)
st.pyplot()
else:
# Display the default dataset
st.write('**Default Dataset (Iris):**')
st.write(iris_df.head())
# Sidebar for plot selection
plot_type = st.sidebar.selectbox('Select Plot Type', ['Histogram', 'Scatter Plot'])
if plot_type == 'Histogram':
# Sidebar for selecting column
selected_column = st.sidebar.selectbox('Select Column for Histogram', iris_df.columns)
# Plot histogram
plt.figure(figsize=(8, 6))
sns.histplot(iris_df[selected_column])
st.pyplot()
elif plot_type == 'Scatter Plot':
# Sidebar for selecting columns
x_axis = st.sidebar.selectbox('Select X-Axis Column', iris_df.columns)
y_axis = st.sidebar.selectbox('Select Y-Axis Column', iris_df.columns)
# Plot scatter plot
plt.figure(figsize=(8, 6))
sns.scatterplot(x=x_axis, y=y_axis, data=iris_df)
st.pyplot()