pd-auto-ml 0.3.0

Pd auto_ml provides a pandas dataframe accessor to allow using dataframes with MindsDB (either the local native library or a local or remote mindsdb server)

Python MindsDB SDK

It enables you to connect to a midnsDB server and use it in a similar way to mindsb_native.

Install

pip install mindsdb-client

example of usage

from mindsdb_client import MindsDB

# connect
mdb = MindsDB(server='https://mindsdb.com', params={'email': '[e-mail]', 'password': 'secret'})

# upload datasource
mdb.datasources.add('rentals_ds', path='home_rentals.csv')

# create a new predictor and learn to predict
predictor = mdb.predictors.learn(
    name='home_rentals_price',
    data_source_name='rentals_ds',
    to_predict=['rental_price']
)

# predict
result = predictor.predict({'number_of_rooms': '2','number_of_bathrooms': '1', 'sqft': '1190'})

tests

Before run tests, change SERVER and CREDENTIAL constants in tests/test.py to relevant. After run python3 tests/test.py
Test file - is a place where you can find some examples of api usage.

API Reference

class MindsDB(server: str, params: dict)

class DataSources()

class DataSource()

class Predictors()

class Predictor()

class Proxy()