Custom component to create dynamic multiselect filters in Streamlit. The filters apply to a dataframe and adjust their values based on the user selection (similar to Google Sheets slicers or Only Relevant Values in Tableau).
Basic documentation is available at https://arsentievalex.github.io/streamlit-dynamic-filters/
How to install and use the package:
-
Install the package using pip:
pip install streamlit-dynamic-filters -
Import the
DynamicFiltersclass:from streamlit_dynamic_filters import DynamicFilters -
Create an instance of the
DynamicFiltersclass and pass the dataframe and the list of fields that will serve as filters:dynamic_filters = DynamicFilters(df, filters=['col1', 'col2', 'col3', 'col4']) -
Display the filters in your app:
dynamic_filters.display_filters() -
Display the filtered dataframe:
dynamic_filters.display_df()
import streamlit as st
import pandas as pd
from streamlit_dynamic_filters import DynamicFilters
data = {
'region': ['North America', 'North America', 'Europe', 'Oceania',
'North America', 'North America', 'Europe', 'Oceania',
'North America', 'North America', 'Europe', 'Oceania'],
'country': ['USA', 'Canada', 'UK', 'Australia',
'USA', 'Canada', 'UK', 'Australia',
'USA', 'Canada', 'UK', 'Australia'],
'city': ['New York', 'Toronto', 'London', 'Sydney',
'New York', 'Toronto', 'London', 'Sydney',
'New York', 'Toronto', 'London', 'Sydney'],
'district': ['Manhattan', 'Downtown', 'Westminster', 'CBD',
'Brooklyn', 'Midtown', 'Kensington', 'Circular Quay',
'Queens', 'Uptown', 'Camden', 'Bondi']
}
df = pd.DataFrame(data)
dynamic_filters = DynamicFilters(df, filters=['region', 'country', 'city', 'district'])
with st.sidebar:
st.write("Apply filters in any order 👇")
dynamic_filters.display_filters(location='sidebar')
dynamic_filters.display_df()
Demo GIF:
import streamlit as st
import pandas as pd
from streamlit_dynamic_filters import DynamicFilters
data = {
'region': ['North America', 'North America', 'Europe', 'Oceania',
'North America', 'North America', 'Europe', 'Oceania',
'North America', 'North America', 'Europe', 'Oceania'],
'country': ['USA', 'Canada', 'UK', 'Australia',
'USA', 'Canada', 'UK', 'Australia',
'USA', 'Canada', 'UK', 'Australia'],
'city': ['New York', 'Toronto', 'London', 'Sydney',
'New York', 'Toronto', 'London', 'Sydney',
'New York', 'Toronto', 'London', 'Sydney'],
'district': ['Manhattan', 'Downtown', 'Westminster', 'CBD',
'Brooklyn', 'Midtown', 'Kensington', 'Circular Quay',
'Queens', 'Uptown', 'Camden', 'Bondi']
}
df = pd.DataFrame(data)
dynamic_filters = DynamicFilters(df, filters=['region', 'country', 'city', 'district'])
st.write("Apply filters in any order 👇")
dynamic_filters.display_filters(location='columns', num_columns=2, gap='large')
dynamic_filters.display_df()
Demo GIF:
