ComfyUI-Data-Analysis

ComfyUI-Data-Analysis is a custom module for analyzing data using Pandas and Matplotlib within ComfyUI.

Currently, it supports the following nodes:

Loading CSV as a DataFrame
Selecting a subset of columns from a DataFrame
Selecting a subset of rows from a DataFrame by specifying a filter condition
Sorting a DataFrame by a column
Displaying the content of a DataFrame
Extracting the first part of a DataFrame
Joining two DataFrames (inner, left, right, outer joins)
Outputting statistics of a DataFrame (e.g., standard deviation)
Line plot
Scatter plot
Bar chart

You can connect these nodes to conduct complex analysis in an intuitive graphical way.
You can also use other Comfy custom nodes to fit your needs (e.g., combining images).

These custom nodes aim to make data exploration and analysis more efficient and enjoyable.

Installation

Note: GPU is not required to run this custom module.

Installation via ComfyUI Manager

Press Manager button on the top menu bar to display ComfyUI Manager Menu.
Click Custom Node Manager.
In the search field, enter Data analysis.
"ComfyUI-Data-Analysis" should be displayed. Select Install.
Restart ComfyUI.
Reload browser page.

Installation via git

Navigate to the custom_nodes directory within your ComfyUI installation.
Run the following command:
```
git clone https://github.com/HowToSD/ComfyUI-Data-Analysis.git
```
This will create a new subdirectory ComfyUI-Data-Analysis.
Rename the folder name from ComfyUI-Data-Analysis to data-analysis. If you skip this, example workflows will not work as those flows use this folder name.
Check if your ComfyUI environment already has pandas and matplotlib. If not, install them using pip.
```
pip install -r requirements.txt
```
Refer to requirements.txt for the right versions.
Start ComfyUI.

Troubleshooting for installation

This custom node module requires pandas and matplotlib, which are not included in the default ComfyUI installation. If you install this module using ComfyUI Manager, these packages should be installed automatically. However, if installation fails, refer to the pandas and matplotlib documentation for manual installation.

How to Use

Refer to User's Guide

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