dataframeviewer 1.6.11

PyQt5 application to visualize pandas DataFrames

# Python Data Viewer Application

## Overview

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

The Data Viewer 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 Data Viewer 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)

### 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

The following dependencies are required to run the data viewer application.

> Note: See [requirements.txt](requirements.txt) for the full dependency list including module versions.

• Python (Version 3.6 or greater)

• pandas

• numpy

• PyQt5

• openpyxl

• matplotlib

• QDarkStyle

### Application Setup / Installation

The Data Viewer uses pip to manage it’s dependencies and can be setup using the commands below from the base directory of this repository.

> Note: If you are using an Anaconda installation, you can skip these setup steps and proceed directly to the the [Running the Application](#running-the-application) section.

#### Using a Python Virtual Environment (Recommended setup method)

> Windows (Git Bash)

`bash virtualenv venv source venv/Scripts/activate pip install dataframeviewer `

> MacOS / Linux

`bash virtualenv venv source venv/bin/activate pip install dataframeviewer `

#### Installing locally

> Note: The commands below can be used in Linux, MacOS, or Windows (Powershell, Git Bash, Cygwin, or WSL)

`bash pip install dataframeviewer `

## Running the Application

> Run as a module

`bash python -m dataframeviewer `

> Run with sample data

`bash python -m dataframeviewer --example `

> Run with input file(s)

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

> Show full command line option list

`bash python -m dataframeviewer --help `

> If using Anaconda 3 on windows with Git Bash installed, you can use the [run.sh](run.sh) script.

`bash ./run.sh `