Upload app.py

app.py

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+import streamlit as st
+import seaborn as sns
+import matplotlib.pyplot as plt
+
+# Load datasets names
+dataset_names = sns.get_dataset_names()
+
+# Sidebar for user inputs
+st.sidebar.header('User Input Features')
+selected_dataset = st.sidebar.selectbox('Select a dataset', dataset_names)
+
+# Load the selected dataset
+data = sns.load_dataset(selected_dataset)
+
+# Select plot
+plot_types = ['scatterplot', 'lineplot', 'histplot', 'boxplot', 'violinplot',
+              'barplot', 'countplot', 'pairplot', 'heatmap', 'jointplot', 'kdeplot']
+plot_type = st.sidebar.selectbox('Select the type of plot', plot_types)
+
+# Options for different plots
+if plot_type in ['scatterplot', 'lineplot', 'barplot', 'countplot']:
+    x_var = st.sidebar.selectbox('Choose X variable', data.columns)
+    y_var = st.sidebar.selectbox('Choose Y variable', data.columns if plot_type != 'countplot' else ['None'])
+    hue_var = st.sidebar.selectbox('Hue (optional)', ['None'] + list(data.columns), index=0)
+elif plot_type in ['histplot', 'boxplot', 'violinplot', 'kdeplot']:
+    x_var = st.sidebar.selectbox('Choose variable', data.columns)
+    hue_var = st.sidebar.selectbox('Hue (optional)', ['None'] + list(data.columns), index=0)
+elif plot_type == 'jointplot':
+    x_var = st.sidebar.selectbox('Choose X variable', data.columns)
+    y_var = st.sidebar.selectbox('Choose Y variable', data.columns)
+elif plot_type == 'pairplot':
+    hue_var = st.sidebar.selectbox('Hue (optional for pairplot)', ['None'] + list(data.columns), index=0)
+elif plot_type == 'heatmap':
+    # Typically used for correlation matrices or pivot tables
+    st.write("Heatmap will display correlation matrix for numerical data.")
+
+# Handle hue
+hue = None if hue_var == 'None' else hue_var
+
+# Main area
+st.title('Seaborn Plot Viewer')
+
+# Generate plot based on the type
+fig, ax = plt.subplots()
+
+if plot_type == 'scatterplot':
+    sns.scatterplot(data=data, x=x_var, y=y_var, hue=hue, ax=ax)
+elif plot_type == 'lineplot':
+    sns.lineplot(data=data, x=x_var, y=y_var, hue=hue, ax=ax)
+elif plot_type == 'histplot':
+    sns.histplot(data=data, x=x_var, hue=hue, ax=ax)
+elif plot_type == 'boxplot':
+    sns.boxplot(data=data, x=x_var, hue=hue, ax=ax)
+elif plot_type == 'violinplot':
+    sns.violinplot(data=data, x=x_var, hue=hue, ax=ax)
+elif plot_type == 'barplot':
+    sns.barplot(data=data, x=x_var, y=y_var, hue=hue, ax=ax)
+elif plot_type == 'countplot':
+    sns.countplot(data=data, x=x_var, hue=hue, ax=ax)
+elif plot_type == 'pairplot':
+    if hue:
+        sns.pairplot(data=data, hue=hue)
+    else:
+        sns.pairplot(data=data)
+    st.pyplot()
+    st.stop()
+elif plot_type == 'heatmap':
+    corr = data.corr()
+    sns.heatmap(corr, annot=True, cmap='coolwarm', ax=ax)
+elif plot_type == 'jointplot':
+    sns.jointplot(data=data, x=x_var, y=y_var, kind='scatter')
+    st.pyplot()
+    st.stop()
+elif plot_type == 'kdeplot':
+    sns.kdeplot(data=data, x=x_var, hue=hue, ax=ax)
+
+st.pyplot(fig)