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ydata-synthetic is available through PyPi, allowing an easy process of installation and integration with the data science programing environments (Google Colab, Jupyter Notebooks, Visual Studio Code, PyCharm) and stack (pandas, numpy, scikit-learn).

Installing the package

Currently, the package supports python versions over 3.9, and can be installed in Windows, Linux or MacOS operating systems.

Prior to the package installation, it is recommended the creation of a virtual or conda environment:

conda create -n synth-env python=3.10
conda activate synth-env

The above command creates and activates a new environment called "synth-env" with Python version 3.10.X. In the new environment, you can then install ydata-synthetic:

pip install ydata-synthetic==1.1.0

Installing ydata-synthetic 5min – Step-by-step installation guide

Using Google Colab

To install inside a Google Colab notebook, you can use the following:

!pip install ydata-synthetic==1.1.0

Make sure your Google Colab is running Python versions >=3.9, <3.11. Learn how to configure Python versions on Google Colab here.

Installing the Streamlit App

Since version 1.0.0, the ydata-synthetic includes a GUI experience provided by a Streamlit app. The UI supports the data synthesization process from reading the data to profiling the synthetic data generation, and can be installed as follows:

pip install "ydata-synthetic[streamlit]"

Note that Jupyter or Colab Notebooks are not yet supported, so use it in your Python environment.