Askdata's mission is to make data meaningful for everyone, unlocking personal and business productivity.
📒 Docs | Usage, Guides, API documentation ... |
💻 Access Akdata | Start using Askdata signing-in or registering |
🎨 Key components | Overview of core concepts |
👀 Getting Started | Basic explanation of concepts, options and usage |
🎓 Tutorials | Jupyter/Colab Notebooks & Scripts |
🔭 Roadmap | Public roadmap of Askdata |
❤️ Contributing | We welcome all contributions! |
Askdata is a platform that allows users to interact with data through natural language, thus making accessing data as simple as searching for a restaurant on Google. Askdata makes its technology available to large national and international customers and is supported by Y Combinator, the prestigious Californian accelerator.
Askdata is a platform designed to enable anyone, regardless of the level of technical knowledge, to harness the power of data (big and small). Users leverage Askdata to explore, query, visualize, and share data from any data source. Our work enables anybody in business teams to use the data. Every day, thousands of users around the world use Askdata to share insights and make data-driven decisions.
This repository contains examples of Askdata usage in serving different types of data.
pip install askdata
or
pip install -r requirements.txt
Lets handle our authenticaton
from askdata import Askdata
askdata = Askdata()
Once your insert your account and password you're all set
#get one agent
df = askdata.get("sales by countries", workspace="sales_demo")
df
# Load the list of the agents connected to your account as a pandas dataframe
askdata.save(df, dataset_name='My Dataset Name',workspace="my_workspace")
Check the following tutorial, to learn more about Askdata end-to-end.