[](https://kaggle-data-connector.streamlit.app/)
Custom component that allows to import Kaggle datasets to Streamlit apps.
[Kaggle](https://www.kaggle.com/) is the world's largest data science community. It enables users to explore and analyze a wide variety of public datasets.
This app demonstrates a simple `KaggleDatasetConnection` which was built by extending the
[built-in BaseConnection](https://docs.streamlit.io/library/api-reference/connections/st.connections.experimentalbaseconnection)
You can view the connection source code
[here](https://github.com/arsentievalex/kaggle-streamlit-data-connector/blob/main/connection.py).
While Kaggle offers datasets in different formats, this connector ONLY supports CSV files.
A user can connect to a Kaggle dataset by providing the dataset path and filename.
The path is the part of the dataset URL after the domain name, the structure is following: username/dataset-name.
For example, for the dataset https://www.kaggle.com/shivamb/netflix-shows, the path is `shivamb/netflix-shows`,
and the file name is `netflix_titles.csv`.
Using this example, the code to connect to the dataset would look like this:
```
from st_kaggle_connector import KaggleDatasetConnection
import streamlit as st
conn = st.connection("kaggle_datasets", type=KaggleDatasetConnection)
df = conn.get(path='shivamb/netflix-shows', filename='netflix_titles.csv', ttl=3600)
```
KaggleDatasetConnection` class assumes that you have secrets set up in the following format:
```
[connections.kaggle_datasets]
KAGGLE_USERNAME = "insert your Kaggle username"
KAGGLE_KEY = "insert your Kaggle API key"
```
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"description": "[](https://kaggle-data-connector.streamlit.app/)\r\n\r\nCustom component that allows to import Kaggle datasets to Streamlit apps.\r\n\r\n[Kaggle](https://www.kaggle.com/) is the world's largest data science community. It enables users to explore and analyze a wide variety of public datasets.\r\nThis app demonstrates a simple `KaggleDatasetConnection` which was built by extending the \r\n[built-in BaseConnection](https://docs.streamlit.io/library/api-reference/connections/st.connections.experimentalbaseconnection)\r\nYou can view the connection source code\r\n[here](https://github.com/arsentievalex/kaggle-streamlit-data-connector/blob/main/connection.py).\r\n\r\nWhile Kaggle offers datasets in different formats, this connector ONLY supports CSV files.\r\n\r\nA user can connect to a Kaggle dataset by providing the dataset path and filename.\r\nThe path is the part of the dataset URL after the domain name, the structure is following: username/dataset-name.\r\nFor example, for the dataset https://www.kaggle.com/shivamb/netflix-shows, the path is `shivamb/netflix-shows`,\r\nand the file name is `netflix_titles.csv`.\r\n\r\nUsing this example, the code to connect to the dataset would look like this:\r\n\r\n```\r\nfrom st_kaggle_connector import KaggleDatasetConnection\r\nimport streamlit as st\r\n\r\nconn = st.connection(\"kaggle_datasets\", type=KaggleDatasetConnection)\r\ndf = conn.get(path='shivamb/netflix-shows', filename='netflix_titles.csv', ttl=3600)\r\n```\r\n\r\nKaggleDatasetConnection` class assumes that you have secrets set up in the following format:\r\n\r\n```\r\n[connections.kaggle_datasets]\r\n KAGGLE_USERNAME = \"insert your Kaggle username\"\r\n KAGGLE_KEY = \"insert your Kaggle API key\"\r\n```\r\n\r\n\r\n",
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