dataframeviewer 1.7.0

PyQt5 application to visualize pandas DataFrames

Overview

The DataFrameViewer application is a Qt Python application to view, edit, plot, and filter data from various file types.

The DataFrameViewer utilizes the pandas module along with the Qt for Python module to provide a familiar spreadsheet-like GUI for any type of data that can be stored in a pandas DataFrame.

The intention of this application is to provide a high-performance, cross-platform application to review and analyze data. The DataFrameViewer provides a faster and more optimized alternative for viewing and plotting data files in a table format as opposed to other applications such as Microsoft Excel or OpenOffice.

Supported Input Formats

Note: Input formats are automatically recognized based on the
filename.

The Data Viewer currently supports the following input formats:

• CSV (comma-delimited, tab-delimited)

• TXT (plain-text files)

• JSON (Javascript Object Notation)

• PICKLE (Python Pickle Format)

• XLSX (Microsoft Excel or OpenOffice files)

• HDF5 (Hierachical Data Format)

Supported Operating Systems

The following operating systems have been tested and confirmed to operate the application nominally:

• Windows 10

• MacOS Version 11.2 (Big Sur) using Apple M1

• Linux (CentOS, Ubuntu)

Other operating systems are untested but will likely function if they are supported by the Qt for Python version documented in requirements.txt

Setup Instructions

Dependencies

• pandas

• numpy

• PyQt5

• openpyxl

• matplotlib

• QDarkStyle

Application Setup / Installation

Note: If you are using an Anaconda installation, you can skip these setup steps and proceed directly to the Starting the Application section.

The recommended setup method is to use an isolated installation via the virtualenv module.

virtualenv installation on Windows:

virtualenv venv
source venv/Scripts/activate
pip install dataframeviewer

virtualenv installation on MacOS / Linux:

virtualenv venv
source venv/bin/activate
pip install dataframeviewer

Local installation (on any platform):

pip install dataframeviewer

Starting the Application

Run as a module

python -m dataframeviewer

Run with sample data

python -m dataframeviewer --example

Run with input file(s)

python -m dataframeviewer -f file1.csv file2.csv ...

To show the full command line option list

python -m dataframeviewer --help

See the User Manual for application usage instructions.