Usage Guide

There are multiple ways to use PyDaddy, and this page gives an overview of all of them.

PyDaddy on Google Colab

The easiest way to get started with PyDaddy is using Google Colaboratory (also called Colab). Colab is a free Jupyter notebook environment, by Google, hosted entirely in the cloud. You can run PyDaddy on Google Colab notebooks, without having to install anything on your system. The tutorial notebooks have links to open them directly on Colab. (Note that you will need a Google login.)

To use PyDaddy from any Colab notebook, enter the following line to a cell and run it. This command sets up PyDaddy on the notebook’s environment.

%pip install git+


To upload your data files to the Colab notebook, click the ‘Files’ icon on the sidebar, and then click the ‘Upload to session storage’ icon.


All files and data will be lost when you disconnect from the notebook. Make sure you download and save any relevant anaysis results.

One-line operation

Once PyDaddy is installed on your machine, it can be invoked from the command-line using the single-command mode. This mode runs all relevant analysis on a specified data file, and generates a single HTML report with all the analysis results.


If you installed PyDaddy in a separate conda environment, activate that environment before continuing.

To use PyDaddy in this mode, use the following command:

pydaddy <file-name> --column_format xyt

Replace <file-name> with the name of the CSV file containing the data to be analyzed. The CSV file should contain the one or two data columns and one optional time-stamp column. The columns could be in any order; and the column order can be speficied using the --column_format option as shown above. (For example, if the time-stamp column comes first followed by the x and y columns, the column format should be txy.) If time-stamp column is not present, the sampling interval can be provided using the -t option.

For more details about other options and flags, use

pydaddy --help


Ideally, the one-line functionality should be used only for a quick preliminary analysis. In particular, the results of the function fitting may not be optimal and may contain spurious terms. For best results, use PyDaddy within a notebook or script to fine-tune the estimation procedure (see the advanced function fitting tutorial).

Python Interface


If you installed PyDaddy in a separate conda environment, activate that environment before continuing.

For full control over the estimation procedure, you can use PyDaddy through Python scripts or notebooks. To use PyDaddy in an Jupyter notebook, start a Jupyter notebook server using the following command:

jupyter notebook

Create a new notebook and import PyDaddy as follows.

import pydaddy

You should be able to use all features of PyDaddy in the notebook. See the tutorials or package documentation for more details on available functionality.