Installation Guide for Pydata-visualizer

This guide provides detailed instructions for installing Pydata-visualizer in various environments.

Requirements

Python 3.8 or higher
pip (Python package installer)

Basic Installation

The simplest way to install Pydata-visualizer is using pip:

pip install pydata-visualizer

This will install the library and all its dependencies.

Installation Options

Install from PyPI with all extras

For a complete installation with all optional features:

pip install "pydata-visualizer[complete]"

Install from GitHub

To install the latest development version:

pip install git+https://github.com/Adi-Deshmukh/Pydata-visualizer.git

Local Development Installation

For development purposes, you can install the package in editable mode:

git clone https://github.com/Adi-Deshmukh/Pydata-visualizer.git
cd Pydata-visualizer
pip install -e .

Environment-specific Instructions

Conda Environment

# Create a new conda environment
conda create -n data-viz python=3.10
conda activate data-viz

# Install the package
pip install pydata-visualizer

Virtual Environment (venv)

# Create a virtual environment
python -m venv data_viz_env
source data_viz_env/bin/activate  # On Windows: data_viz_env\Scripts\activate

# Install the package
pip install pydata-visualizer

Jupyter Notebook

If you’re using Jupyter Notebook, you can install the package and use it in your notebooks:

pip install pydata-visualizer

# Then in your notebook:
# import pandas as pd
# from data_visualizer.profiler import AnalysisReport
# ...

Troubleshooting

Missing Dependencies

If you encounter errors related to missing dependencies, try installing them explicitly:

pip install pandas matplotlib seaborn numpy scipy jinja2 visions pydantic colorama tqdm imagehash wordcloud plotly shapely

Matplotlib Backend Issues

If you encounter issues with matplotlib visualizations, you may need to set a non-interactive backend:

import matplotlib
matplotlib.use('Agg')  # Set before importing pyplot

Installation in Restricted Environments

In environments with restricted permissions:

pip install --user pydata-visualizer

Verifying Installation

You can verify that the installation was successful by running:

import data_visualizer
print(data_visualizer.__version__)  # Should print the installed version

Dependencies

The following dependencies will be automatically installed:

imagehash
Jinja2
matplotlib
numpy
pandas
pydantic
scipy
seaborn
shapely
visions
tqdm
colorama
wordcloud
plotly

Upgrading

To upgrade to the latest version:

pip install --upgrade pydata-visualizer

Uninstallation

To remove the package:

pip uninstall pydata-visualizer