_____         ______  ______        _________
__  /_______ ____  /_ ___  /_ _____ ______  /
_  __/_  __ `/__  __ \__  __ \_  _ \_  __  / 
/ /_  / /_/ / _  /_/ /_  /_/ //  __// /_/ /  
\__/  \__,_/  /_.___/ /_.___/ \___/ \__,_/   

Tabbed is under active documentation-driven development.

Tabbed is a format-agnostic tabular dataset library, written in Python. It is a full python module which doubles as a CLI application for quick dataset conversions.

Formats supported:

• JSON
• YAML
• Excel
• CSV
• CDL
• HTML

Please note that tabbed purposefully excludes XML support. It always will.

Features

Convert data formats via API:

tabbed.import(filename='data.csv').export('data.json')

Convert data formats via CLI:

tabbed data.csv data.json

Populate fresh data files:

headers = ('first_name', 'last_name', 'gpa')

data = [
	('John', 'Adams', 4.0),
	('George', 'Washington', 2.6),
	('Henry', 'Ford', 2.3)
]

data = tabbed.Data(*data, headers=headers)

# Establish file location and save
data.save('test.xls')

Intelligently add new rows:

data.addRow('Bob', 'Dylan')
# >>> Warning: Existing column count is 3

print data.headers
# >>> ('first_name', 'last_name', 'gpa')

Slice rows:

print data[0:1]
# >>> [('John', 'Adams', 4.0), ('George', 'Washington', 2.6)]

Slice columns by header:

print data['first_name']
# >>> ['John', 'George', 'Henry']

Manipulate rows by index:

data.delRow(0)
print data[0:1]
# >>> [('George', 'Washington', 2.6), ('Henry', 'Ford', 2.3)]

# Update saved file
data.save()

Export to various formats:

# Save copy as CSV
data.export('backup.csv')