EDA_App.py

import streamlit as st
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt


def plot_categorical_cols(
    df,
    categorical_cols,
    target_col,
    plot_type='countplot',
    figsize=(6, 3),
    rotation=45,
    palette=None,
    show_labels=False,
    label_type='count'):
    
    for col in categorical_cols:
        plt.figure(figsize=figsize)

        if plot_type == 'countplot':
            ax = sns.countplot(data=df, x=col, hue=target_col, palette=palette)
        elif plot_type == 'barplot':
            temp = df.groupby([col, target_col]).size().reset_index(name='count')
            ax = sns.barplot(data=temp, x=col, y='count', hue=target_col, palette=palette)
        elif plot_type == 'violinplot':
            ax = sns.violinplot(data=df, x=col, y=target_col, palette=palette)
        elif plot_type == 'boxplot':
            ax = sns.boxplot(data=df, x=col, y=target_col, palette=palette)
        else:
            st.warning(f"Plot type '{plot_type}' not supported.")
            continue

        if show_labels and hasattr(ax, 'containers'):
            for p in ax.containers:
                labels = []
                for bar in p:
                    height = bar.get_height()
                    if height == 0:
                        labels.append("")
                        continue
                    if label_type == 'count':
                        labels.append(f'{int(height)}')
                    elif label_type == 'percent':
                        total = len(df)
                        percent = 100 * height / total
                        labels.append(f'{percent:.1f}%')
                    else:
                        labels.append(f'{int(height)}')
                ax.bar_label(p, labels=labels, label_type='edge', padding=2,
                             fontsize=8, color='black', weight='bold')
        plt.title(f"{col} vs {target_col}", weight='bold', fontsize=13, color='black')
        plt.xlabel(col, weight='bold')
        plt.ylabel(target_col, weight='bold')
        plt.xticks(rotation=rotation)
        plt.tight_layout()
        st.pyplot(plt.gcf())
        plt.close()



st.set_page_config(page_title="EDA App ", layout="wide",page_icon=":bar_chart:")
st.title("Exporatory Data Analysis (EDA) App")
fileuploaded= st.file_uploader("Upload your data file", type=["csv", "xlsx"])
if fileuploaded is not None:
    if fileuploaded.name.endswith('.csv'):
        df = pd.read_csv(fileuploaded)
    elif fileuploaded.name.endswith('.xlsx'):
        df = pd.read_excel(fileuploaded)
    else:
        st.error("Unsupported file format. Please upload a CSV or Excel file.")
        df = None

    if df is not None:
        st.write("Data uploaded successfully!")
        st.subheader("Data Preview")
        st.write("Slider to choose the number of rows to display")
        value = st.slider("Number of rows to display", min_value=1, max_value=min(100, len(df)), value=10)
        st.dataframe(df.head(value))
        st.subheader("Column Selection")
        columns = df.columns.tolist()
        selected_columns = st.multiselect("Select columns to display", options=columns, default=columns[:1])
        if selected_columns:
            st.dataframe(df[selected_columns].head())  # Display selected columns

        # Filtering data
        st.subheader("Data Filtering")
        filter_column = st.selectbox("Select column to filter", options=columns)
        unique_values = df[filter_column].dropna().unique()
        filter_value = st.selectbox("Enter value to filter by", options=unique_values, index=0)
        if filter_value:
            filtered_df = df[df[filter_column].astype(str).str.contains(str(filter_value), na=False)]
            st.write("Filtered Data:")
            st.dataframe(filtered_df)

        st.write("Choose the type of EDA")
        EDA_type = st.selectbox("Select EDA Type", ["Descriptive", "Exploratory", "Visual"])
        if st.button("Run EDA"):
            if EDA_type == "Descriptive":
                st.write("Descriptive EDA selected. Displaying basic statistics and data types.")
                st.subheader("Data Summary")
                st.write(df.describe())
                st.write("Data Types:", df.dtypes)
                st.write("Data Shape:", df.shape)
                st.write("Columns:", df.columns.tolist())
            elif EDA_type == "Exploratory":
                st.write("Exploratory EDA selected. Displaying unique values and missing values.")
                st.write("Unique Values:", df.nunique())
                st.write("Missing Values:", df.isnull().sum())
            elif EDA_type == "Visual":
                st.write("Visual EDA selected. Displaying plots and charts.")
                st.subheader("Data Visualization")
                st.write("Choose the type of Columns to visualize")
                col_type = st.selectbox("Select Column Type", ["Numerical", "Categorical"])
                st.write("Plot type")
                plot_type = st.selectbox("Select Plot Type", ["Count Plot", "Bar Plot", "Violin Plot", "Box Plot"])
                if col_type == "Numerical":
                    st.write("Displaying numerical columns")
                    numerical_cols = df.select_dtypes(include=[np.number]).columns.tolist()
                    categorical_cols = df.select_dtypes(include=[object]).columns.tolist()
                    st.write("Numerical Columns:", numerical_cols)
                    x_axis = st.selectbox("Select X-axis for plot", options=numerical_cols)
                    y_axis = st.selectbox("Select Y-axis for plot", options=numerical_cols + categorical_cols)
                    if x_axis and y_axis:
                        fig, ax = plt.subplots(figsize=(6, 3))
                        if plot_type == "Box Plot":
                            sns.boxplot(data=df, x=x_axis, y=y_axis, ax=ax)
                        elif plot_type == "Violin Plot":
                            sns.violinplot(data=df, x=x_axis, y=y_axis, ax=ax)
                        elif plot_type == "Bar Plot":
                            sns.barplot(data=df, x=x_axis, y=y_axis, ax=ax)
                        elif plot_type == "Count Plot":
                            sns.countplot(data=df, x=x_axis, ax=ax)
                        ax.set_title(f"{x_axis} vs {y_axis}")
                        st.pyplot(fig)
                        plt.close(fig)
                elif col_type == "Categorical":
                    st.write("Displaying categorical columns")
                    categorical_cols = df.select_dtypes(include=[object]).columns.tolist()
                    st.write("Categorical Columns:", categorical_cols)
                    # Let user select one or more categorical columns
                    selected_cats = st.multiselect("Select categorical columns to plot", options=categorical_cols, default=categorical_cols[:1])
                    y_axis = st.selectbox("Select Target column (for hue)", options=categorical_cols)
                    # Map plot_type to function argument
                    plot_type_map = {
                        "Count Plot": "countplot",
                        "Bar Plot": "barplot",
                        "Violin Plot": "violinplot",
                        "Box Plot": "boxplot"
                    }
                    label_type_map = {
                        "Count Plot": "count",
                        "Bar Plot": "count",
                        "Violin Plot": "count",
                        "Box Plot": "count"
                    }
                    plot_categorical_cols(
                        df,
                        selected_cats,
                        target_col=y_axis,
                        plot_type=plot_type_map.get(plot_type, "countplot"),
                        figsize=(6, 3),
                        rotation=45,
                        palette=None,
                        show_labels=True,
                        label_type=label_type_map.get(plot_type, "count")
                    )
                else:
                    st.error("Please select a valid column type and plot type.")
else:
    st.write("Please upload a data file to get started.")





st.markdown("""
<div style="text-align: center;">
    <h3>Contact Us</h3>
    <p>If you have any questions or feedback, please contact us at <a href="mailto:asadalich56@gmail.com">
     <span style="vertical-align:middle; color:#C1A9A9; font-weight:bold; font-size:18px;">Contact</span> </a> </p>
</div>
<br>
""", unsafe_allow_html=True)
# Display three social links in a row with icons
col_link1, col_link2, col_link3 = st.columns(3)
with col_link1:
    st.markdown(
        '''
        <div style="display: flex; justify-content: center;">
            <a href="https://datz-asadanalyst.github.io/" target="_blank" style="text-decoration:none;">
                <img src="https://img.icons8.com/ios-filled/32/000000/domain.png" style="vertical-align:middle; margin-right:8px;"/>
                <span style="vertical-align:middle; color:#00B8A9; font-weight:bold; font-size:18px;">Website</span>
            </a>
        </div>
        ''',
        unsafe_allow_html=True
    )
with col_link2:
    st.markdown(
        '''
        <div style="display: flex; justify-content: center;">
            <a href="https://www.linkedin.com/in/datz-asad-analyst56" target="_blank" style="text-decoration:none;">
                <img src="https://img.icons8.com/ios-filled/32/000000/linkedin.png" style="vertical-align:middle; margin-right:8px;"/>
                <span style="vertical-align:middle; color:#00B8A9; font-weight:bold; font-size:18px;">LinkedIn</span>
            </a>
        </div>
        ''',
        unsafe_allow_html=True
    )
with col_link3:
    st.markdown(
        '''
        <div style="display: flex; justify-content: center;">
            <a href="https://github.com/Datz-AsadAnalyst" target="_blank" style="text-decoration:none;">
                <img src="https://img.icons8.com/ios-filled/32/000000/github.png" style="vertical-align:middle; margin-right:8px;"/>
                <span style="vertical-align:middle;color:#00B8A9; font-weight:bold; font-size:18px;">GitHub</span>
            </a>
        </div>
        ''',
        unsafe_allow_html=True
    )

st.markdown("---")  
st.markdown(""" 
<div style="text-align: center;">
    <div style="font-size: 16px; color: #888;">
        <p>Made with ❤️ by Asad In Data</p>
        <p> © 2025 EDA App. All rights reserved.</p>
    </div>
</div>
""", unsafe_allow_html=True)