Quick Start

1. Install the SDK

pip install datfid

2. Get Your API Key

You need an API token to use the SDK. Getting one is free and takes about 15 minutes.

Fill out a short form and the DATFID team will respond within 15 minutes with your personal token. See Get Your API Key for details.

3. Initialize the Client

import pandas as pd
from datfid import DATFIDClient

client = DATFIDClient(token="your_DATFID_token")

Sample Datasets

Ready-to-use sample data is available on GitHub: DATFID sample-datasets repo

4. Fit a Model

Load your panel data and fit an interpretable model. DATFID will return a formula with coefficients that explain the relationships in your data.

df = pd.read_excel("your_data.xlsx")

result = client.fit_model(
    df=df,
    id_col="Product",
    time_col="Time",
    y="Revenue",
    current_features="all",
    filter_by_significance=True
)

5. Generate Forecasts

Load a forecast file that defines which entities and time periods to predict, then run the forecast.

df_forecast = pd.read_excel("your_forecast_data.xlsx")

forecast = client.forecast_model(df_forecast=df_forecast)

Next Steps

• → Python SDK Reference — full parameter reference for fit_model() and forecast_model()
• → REST API Reference — use DATFID via HTTP endpoints
• → Use Case Examples — see real results with sample datasets