streamlit-dynamic-filters


Namestreamlit-dynamic-filters JSON
Version 0.1.9 PyPI version JSON
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home_pagehttps://github.com/arsentievalex/streamlit-dynamic-filters
SummaryDynamic multiselect filters for Streamlit
upload_time2024-08-02 11:36:34
maintainerNone
docs_urlNone
authorOleksandr Arsentiev
requires_pythonNone
licenseMIT
keywords streamlit custom component
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            # Dynamic Multi Select Filters for Streamlit
[![Open Demo App](https://static.streamlit.io/badges/streamlit_badge_black_white.svg)](https://dynamic-filters-demo.streamlit.app/)

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/](https://arsentievalex.github.io/streamlit-dynamic-filters/)

How to install and use the package:
1. Install the package using [pip](https://pypi.org/project/streamlit-dynamic-filters/):
    ```pip install streamlit-dynamic-filters```
2. Import the `DynamicFilters` class:
    ```from streamlit_dynamic_filters import DynamicFilters```
3. Create an instance of the `DynamicFilters` class and pass the dataframe and the list of fields that will serve as filters:

    ```dynamic_filters = DynamicFilters(df, filters=['col1', 'col2', 'col3', 'col4'])```
4. Display the filters in your app:
    ```dynamic_filters.display_filters()```
5. Display the filtered dataframe:
    ```dynamic_filters.display_df()```


#### Sample usage with sidebar filters:

```
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:
<img src="https://i.postimg.cc/x1zDwgwh/dynamic-filters-demo-1.gif"/>   

#### Sample usage with columns:

```
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:
<img src="https://i.postimg.cc/gkLTjjg6/dynamic-filters-demo-2.gif"/>   



## 0.1.9 - 2nd August 2024
### Added
- Key for each elements in filters, so that multiple DynamicFilters can be used in one app (contribution by @vikashgraja)
- reset_filters function (contribution by @ragchuck)


## 0.1.6 - 27th March 2024
### Added
- Sorted alphabetically filter labels


## 0.1.5 - 28th December 2023
### Added by kzielins <Krzysztof Zielinski> kzislinsk@gmail.com
- Hierarchical filter selectors
- Independent filters with diffrent sessions name


## 0.1.3 - 28th September 2023
### Added
- Ability to specify filter location in display_filters(). The filters can be either displayed in sidebar, main area or columns.
- Error handling of invalid arguments in display_filters().

### Changed
- Renamed filter_except() to filter_df(). The function returns a filtered df.

### Fixed
- The StreamlitApiException that occured when selected values did not exist in the dataset.
- Possibility to have more than one filter

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    "description": "# Dynamic Multi Select Filters for Streamlit\n[![Open Demo App](https://static.streamlit.io/badges/streamlit_badge_black_white.svg)](https://dynamic-filters-demo.streamlit.app/)\n\nCustom component to create dynamic multiselect filters in Streamlit. \nThe 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). \n\nBasic documentation is available at [https://arsentievalex.github.io/streamlit-dynamic-filters/](https://arsentievalex.github.io/streamlit-dynamic-filters/)\n\nHow to install and use the package:\n1. Install the package using [pip](https://pypi.org/project/streamlit-dynamic-filters/):\n    ```pip install streamlit-dynamic-filters```\n2. Import the `DynamicFilters` class:\n    ```from streamlit_dynamic_filters import DynamicFilters```\n3. Create an instance of the `DynamicFilters` class and pass the dataframe and the list of fields that will serve as filters:\n\n    ```dynamic_filters = DynamicFilters(df, filters=['col1', 'col2', 'col3', 'col4'])```\n4. Display the filters in your app:\n    ```dynamic_filters.display_filters()```\n5. Display the filtered dataframe:\n    ```dynamic_filters.display_df()```\n\n\n#### Sample usage with sidebar filters:\n\n```\nimport streamlit as st\nimport pandas as pd\nfrom streamlit_dynamic_filters import DynamicFilters\n\ndata = {\n    'region': ['North America', 'North America', 'Europe', 'Oceania',\n               'North America', 'North America', 'Europe', 'Oceania',\n               'North America', 'North America', 'Europe', 'Oceania'],\n    'country': ['USA', 'Canada', 'UK', 'Australia',\n                'USA', 'Canada', 'UK', 'Australia',\n                'USA', 'Canada', 'UK', 'Australia'],\n    'city': ['New York', 'Toronto', 'London', 'Sydney',\n             'New York', 'Toronto', 'London', 'Sydney',\n             'New York', 'Toronto', 'London', 'Sydney'],\n    'district': ['Manhattan', 'Downtown', 'Westminster', 'CBD',\n                 'Brooklyn', 'Midtown', 'Kensington', 'Circular Quay',\n                 'Queens', 'Uptown', 'Camden', 'Bondi']\n}\n\ndf = pd.DataFrame(data)\n\ndynamic_filters = DynamicFilters(df, filters=['region', 'country', 'city', 'district'])\n\nwith st.sidebar:\n    st.write(\"Apply filters in any order \ud83d\udc47\")\n\ndynamic_filters.display_filters(location='sidebar')\n\ndynamic_filters.display_df()\n```\n\nDemo GIF:\n<img src=\"https://i.postimg.cc/x1zDwgwh/dynamic-filters-demo-1.gif\"/>   \n\n#### Sample usage with columns:\n\n```\nimport streamlit as st\nimport pandas as pd\nfrom streamlit_dynamic_filters import DynamicFilters\n\ndata = {\n    'region': ['North America', 'North America', 'Europe', 'Oceania',\n               'North America', 'North America', 'Europe', 'Oceania',\n               'North America', 'North America', 'Europe', 'Oceania'],\n    'country': ['USA', 'Canada', 'UK', 'Australia',\n                'USA', 'Canada', 'UK', 'Australia',\n                'USA', 'Canada', 'UK', 'Australia'],\n    'city': ['New York', 'Toronto', 'London', 'Sydney',\n             'New York', 'Toronto', 'London', 'Sydney',\n             'New York', 'Toronto', 'London', 'Sydney'],\n    'district': ['Manhattan', 'Downtown', 'Westminster', 'CBD',\n                 'Brooklyn', 'Midtown', 'Kensington', 'Circular Quay',\n                 'Queens', 'Uptown', 'Camden', 'Bondi']\n}\n\ndf = pd.DataFrame(data)\n\ndynamic_filters = DynamicFilters(df, filters=['region', 'country', 'city', 'district'])\n\nst.write(\"Apply filters in any order \ud83d\udc47\")\n\ndynamic_filters.display_filters(location='columns', num_columns=2, gap='large')\n\ndynamic_filters.display_df()\n```\n\nDemo GIF:\n<img src=\"https://i.postimg.cc/gkLTjjg6/dynamic-filters-demo-2.gif\"/>   \n\n\n\n## 0.1.9 - 2nd August 2024\n### Added\n- Key for each elements in filters, so that multiple DynamicFilters can be used in one app (contribution by @vikashgraja)\n- reset_filters function (contribution by @ragchuck)\n\n\n## 0.1.6 - 27th March 2024\n### Added\n- Sorted alphabetically filter labels\n\n\n## 0.1.5 - 28th December 2023\n### Added by kzielins <Krzysztof Zielinski> kzislinsk@gmail.com\n- Hierarchical filter selectors\n- Independent filters with diffrent sessions name\n\n\n## 0.1.3 - 28th September 2023\n### Added\n- Ability to specify filter location in display_filters(). The filters can be either displayed in sidebar, main area or columns.\n- Error handling of invalid arguments in display_filters().\n\n### Changed\n- Renamed filter_except() to filter_df(). The function returns a filtered df.\n\n### Fixed\n- The StreamlitApiException that occured when selected values did not exist in the dataset.\n- Possibility to have more than one filter \n",
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Oleksandr Arsentiev
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