A simple graphical tabular data viewer
Project description
gtabview: a simple graphical tabular data viewer
Graphical counterpart to tabview, a simple tabular data viewer that can be used both stand-alone and as a Python module for various files and Python/Pandas/NumPy data structures.
Stand-alone usage
gtabview reads most text tabular data formats automatically:
gtabview data.csv gtabview data.txt
If xlrd is installed, Excel files can be read directly:
gtabview file.xls[x]
When Blaze is also installed, any Blaze source can be used by specifying a supported URI on the command line:
gtabview file://dataset.hdf5 gtabview file://dataset.json gtabview sqlite://file.db::table gtabview postgresql://host.domain/db_name::table
The database URL syntax is inherited from SQLAlchemy, so refer to SQLAlchemy’s database URLs for a detailed reference.
Usage as a module
gtabview.view() can be used to display simple Python types directly in tabulated form:
from gtabview import view
# view a file
view("/path/to/file")
# view a list
view([1, 2, 3])
# view a dict (by columns)
view({'a': [1, 2, 3], 'b': [4, 5, 6], 'c': [7, 8, 9]})
# view a dict (by rows)
view({'a': [1, 2, 3], 'b': [4, 5, 6], 'c': [7, 8, 9]}, transpose=True)
# view a simple list of lists
view([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
# view a simple list of lists (with headers)
view([['a', 'b', 'c'], [1, 2, 3], [4, 5, 6], [7, 8, 9]], hdr_rows=1)
gtabview includes native support for NumPy and all features of Pandas’ DataFrames, such as MultiIndexes and level names:
from gtabview import view
# numpy arrays up to two dimensions are supported
import numpy as np
view(np.array([[1, 2, 3], [4, 5, 6]]))
# view a DataFrame/Series/Panel
import pandas as pd
df = pd.DataFrame([[1, 2, 3], [4, 5, 6]],
columns=['a', 'b', 'c'], index=['x', 'y'])
view(df)
Blaze can also be used directly as a data source, either explicitly or implicitly through an URI:
from gtabview import view
import blaze as bz
iris = bz.Data('sqlite:///blaze/examples/data/iris.db::iris')
view(iris)
view('postgresql://user:pass@host.domain:port/db_name::table')
gtabview is designed to integrate correctly with matplotlib. If you’re using gtabview with matplotlib either directly or indirectly (for example, using the Pandas visualization API or Seaborn), be sure to include matplotlib first to correctly initialize gtabview.
gtabview will also use matplotlib’s interactive setting to determine the default behavior of the data window: when interactive, calls to view() will not block, and will keep recycling the same window.
Requirements and installation
gtabview is available directly on the Python Package Index.
gtabview requires:
Python 2 or Python 3
PyQt4 or PySide
setuptools and setuptools-git (install-only).
Under Debian/Ubuntu, install the required dependencies with:
sudo apt-get install python python-qt4 sudo apt-get install python-setuptools python-setuptools-git
Then download and install simply via pip:
pip install gtabview
Install xlrd if reading Excel files directly is desired, and optionally Blaze for interacting with other/scientific data formats:
pip install xlrd pip install blaze
License
Latest release notes
Improved column auto-sizing.
NaNs (as None) are now also displayed as empty cells.
Empty structures no longer cause view() to fail.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.