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A Python package for interacting with the thaink2 analytics APIs

Project description

th2analytics

PyPI version
License: MIT
Python Versions

th2analytics is a Python library that provides a simple and efficient wrapper for interacting with the thaink2 analytics APIs. It enables users to generate future forecasts rapidly while adapting to various types of data.


Features

  • Generate forecasts quickly using an intuitive interface.
  • Supports multiple forecasting models like ARIMA, XGBOOST, Random, and others.
  • Customizable parameters for forecast horizon, grouping, and target variables.
  • Lightweight and easy to integrate into existing workflows.

Installation

Install the package using pip:

pip install th2analytics

A bearer token is needed in order to perform the API request, use the following url to generate a valid token https:\opensource.thaink2.com\app\th2token

from th2analytics.forecasting import ForecastingAPI
import numpy as np
import pandas as pd

api_token = "************" # get your token here: https:\\opensource.thaink2.com\app\th2token


# Initialize the API wrapper
api = ForecastingAPI(
    base_url = "https://apis-dev.thaink2.fr/",
    api_token = api_token
)

np.random.seed(42)
dates = pd.date_range(start='2022-01-01', periods=100, freq='D')
values = np.random.randn(100).cumsum()
# Create a DataFrame from the generated data
input_data = pd.DataFrame({'date': dates, 'value': values})
# Generate the forecast
forecast = api.th2forecast_api(
    actuals = input_data,
    fcast_horizon = 30,
    group_target = None,
    target_var = "value",
    date_var = "date",
    models_list = ["xgboost"]
)
# Print the forecast

forecast_df = pd.json_normalize(forecast)
print(forecast_df)

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