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Kenneth Reitz
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@@ -30,11 +30,11 @@ A :class:`Dataset <tablib.Dataset>` is nothing more than what its name implies
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Creating your own instance of the :class:`tablib.Dataset` object is simple. ::
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data = tablib.Dataset()
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You can now start filling this :class:`Dataset <tablib.Dataset>` object with data.
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.. admonition:: Example Context
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From here on out, if you see ``data``, assume that it's a fresh :class:`Dataset <tablib.Dataset>` object.
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@@ -52,7 +52,7 @@ Let's say you want to collect a simple list of names. ::
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for name in names:
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# split name appropriately
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fname, lname = name.split()
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# add names to Dataset
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data.append([fname, lname])
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@@ -76,19 +76,19 @@ Now our data looks a little different. ::
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>>> data.dict
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[{'Last Name': 'Reitz', 'First Name': 'Kenneth'}, {'Last Name': 'Monke', 'First Name': 'Bessie'}]
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--------------
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Adding Columns
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Adding Columns
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--------------
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Now that we have a basic :class:`Dataset` in place, let's add a column of **ages** to it. ::
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data.append(col=[22, 20], header='Age')
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Let's view the data now. ::
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>>> data.dict
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@@ -106,8 +106,8 @@ Tablib's killer feature is the ability to export your :class:`Dataset` objects i
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**Comma-Separated Values** ::
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>>> data.csv
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Last Name,First Name,Age
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Reitz,Kenneth,22
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Last Name,First Name,Age
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Reitz,Kenneth,22
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Monke,Bessie,20
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**JavaScript Object Notation** ::
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@@ -121,7 +121,7 @@ Tablib's killer feature is the ability to export your :class:`Dataset` objects i
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>>> data.yaml
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- {Age: 22, First Name: Kenneth, Last Name: Reitz}
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- {Age: 20, First Name: Bessie, Last Name: Monke}
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**Microsoft Excel** ::
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@@ -190,11 +190,11 @@ Thanks to Josh Ourisman, Tablib now supports adding dynamic columns. A dynamic c
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Let's add a dynamic column to our :class:`Dataset` object. In this example, we have a function that generates a random grade for our students. ::
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import random
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def random_grade(row):
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"""Returns a random integer for entry."""
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return (random.randint(60,100)/100.0)
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data.append(col=[random_grade], header='Grade')
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Let's have a look at our data. ::
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@@ -209,7 +209,7 @@ Let's remove that column. ::
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>>> del data['Grade']
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When you add a dynamic column, the first argument that is passed in to the given callable is the current data row. You can use this to perform calculations against your data row.
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When you add a dynamic column, the first argument that is passed in to the given callable is the current data row. You can use this to perform calculations against your data row.
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For example, we can use the data available in the row to guess the gender of a student. ::
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@@ -217,9 +217,9 @@ For example, we can use the data available in the row to guess the gender of a s
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"""Calculates gender of given student data row."""
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m_names = ('Kenneth', 'Mike', 'Yuri')
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f_names = ('Bessie', 'Samantha', 'Heather')
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name = row[0]
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if name in m_names:
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return 'Male'
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elif name in f_names:
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@@ -243,8 +243,8 @@ Filtering Datasets with Tags
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.. versionadded:: 0.9.0
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When constructing a :class:`Dataset` object, you can add tags to rows by specifying the ``tags`` parameter.
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This allows you to filter your :class:`Dataset` later. This can be useful so separate rows of data based on
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When constructing a :class:`Dataset` object, you can add tags to rows by specifying the ``tags`` parameter.
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This allows you to filter your :class:`Dataset` later. This can be useful so separate rows of data based on
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arbitrary criteria (*e.g.* origin) that you don't want to include in your :class:`Dataset`.
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Let's tag some students. ::
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@@ -266,10 +266,10 @@ It's that simple. The original :class:`Dataset` is untouched.
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Excel Workbook With Multiple Sheets
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------------------------------------
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------------------------------------
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When dealing with a large number of :class:`Datasets <Dataset>` in spreadsheet format, it's quite common to group multiple spreadsheets into a single Excel file, known as a Workbook. Tablib makes it extremely easy to build workbooks with the handy, :class:`Databook` class.
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Let's say we have 3 different :class:`Datasets <Dataset>`. All we have to do is add then to a :class:`Databook` object... ::
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@@ -287,15 +287,15 @@ The resulting **students.xls** file will contain a separate spreadsheet for each
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Make sure to open the output file in binary mode.
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.. _seperators:
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.. _separators:
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----------
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Seperators
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Separators
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----------
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.. versionadded:: 0.8.2
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When, it's often useful to create a blank row containing information on the upcoming data. So,
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When, it's often useful to create a blank row containing information on the upcoming data. So,
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@@ -305,24 +305,24 @@ When, it's often useful to create a blank row containing information on the upco
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('11/24/09', 'Math 101 Mid-term Exam', 56.),
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('05/24/10', 'Math 101 Final Exam', 62.)
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]
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suzie_tests = [
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('11/24/09', 'Math 101 Mid-term Exam', 56.),
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('05/24/10', 'Math 101 Final Exam', 62.)
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]
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# Create new dataset
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tests = tablib.Dataset()
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tests.headers = ['Date', 'Test Name', 'Grade']
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# Daniel's Tests
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tests.append_seperator('Daniel\'s Scores')
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tests.append_separator('Daniel\'s Scores')
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for test_row in daniel_tests:
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tests.append(test_row)
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# Susie's Tests
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tests.append_seperator('Susie\'s Scores')
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tests.append_separator('Susie\'s Scores')
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for test_row in suzie_tests:
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tests.append(test_row)
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@@ -331,7 +331,7 @@ When, it's often useful to create a blank row containing information on the upco
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with open('grades.xls', 'wb') as f:
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f.write(tests.xls)
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The resulting **tests.xls** will have the following layout:
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The resulting **tests.xls** will have the following layout:
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Daniel's Scores:
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@@ -347,7 +347,7 @@ The resulting **tests.xls** will have the following layout:
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.. admonition:: Format Support
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At this time, only :class:`Excel <Dataset.xls>` output supports separators.
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----
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Now, go check out the :ref:`API Documentation <api>` or begin :ref:`Tablib Development <development>`.
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