Emulate Excel

One of agate’s most powerful assets is that instead of a wimpy “formula” language, you have the entire Python language at your disposal. Here are examples of how to translate a few common Excel operations.

Simple formulas

If you need to simulate a simple Excel formula you can use the Formula class to apply an arbitrary function.


=($A1 + $B1) / $C1


def f(row):
    return (row['a'] + row['b']) / row['c']

new_table = table.compute([
    ('new_column', Formula(f))

If this still isn’t enough flexibility, you can also create your own subclass of Computation.


number_type = agate.Number()

def five_year_total(row):
    columns = ('2009', '2010', '2011', '2012', '2013')

    return sum(tuple(row[c] for c in columns)]

formula = agate.Formula(number_type, five_year_total)

new_table = table.compute([
    ('five_year_total', formula)


new_table = table.compute([
    ('name_stripped', Formula(text_type, lambda r: r['name'].strip()))


new_table = table.compute([
    ('full_name', Formula(text_type, lambda r: '%(first_name)s %(middle_name)s %(last_name)s' % r))


new_table = table.compute([
    ('mvp_candidate', Formula(boolean_type, lambda r: row['batting_average'] > 0.3))


states = {
    'AL': 'Alabama',
    'AK': 'Alaska',
    'AZ': 'Arizona',

new_table = table.compute([
    ('mvp_candidate', Formula(text_type, lambda r: states[row['state_abbr']]))

Pivot tables

You can emulate most of the functionality of Excel’s pivot tables using the TableSet.aggregate() method.

jobs = employees.group_by('job_title')
summary = jobs.aggregate([
    ('employee_count', agate.Length())
    ('salary_mean', agate.Mean('salary')),
    ('salary_median', agate.Median('salary'))

The resulting summary table will have four columns: job_title, employee_count, salary_mean and salary_median.