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+Streamlit Dynamic Filters
+Streamlit Dynamic Filters is a Python library that brings advanced, dynamic filtering capabilities to Streamlit applications. It allows users to easily filter data based on multiple criteria with filters that automatically update to reflect the current state of the data.
+
+Installation
+bash
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+pip install streamlit-dynamic-filters
+Usage
+Basic Example
+Here's a simple example to get started with Streamlit Dynamic Filters:
+
+python
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+import streamlit as st
+import pandas as pd
+from streamlit_dynamic_filters import DynamicFilters
+
+# Sample data
+data = {
+    'Category': ['Fruit', 'Vegetable', 'Fruit', 'Vegetable'],
+    'Item': ['Apple', 'Carrot', 'Banana', 'Broccoli']
+}
+df = pd.DataFrame(data)
+
+# Initialize DynamicFilters
+dynamic_filters = DynamicFilters(df, ['Category', 'Item'])
+
+# Display the filters and the dataframe
+dynamic_filters.display_filters()
+dynamic_filters.display_df()
+Advanced Usage
+Hierarchical Filtering
+For hierarchical data (e.g., Country > State > City), use DynamicFiltersHierarchical:
+
+python
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+from streamlit_dynamic_filters import DynamicFiltersHierarchical
+
+# Assuming df is a DataFrame with hierarchical data
+dynamic_filters = DynamicFiltersHierarchical(df, ['Country', 'State', 'City'])
+dynamic_filters.display_filters()
+dynamic_filters.display_df()
+Filters in Sidebar
+Place filters in the sidebar:
+
+python
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+dynamic_filters.display_filters(location='sidebar')
+Customizing Number of Columns
+Display filters in multiple columns:
+
+python
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+dynamic_filters.display_filters(location='columns', num_columns=2)
+Contributing
+Contributions to the streamlit-dynamic-filters library are welcome. Please follow the standard fork, branch, and pull request workflow.
+
+License
+This project is licensed under the MIT License.
+
+Support
+For support and questions, please open an issue in the GitHub repository.