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A Python data analysis library that is optimized for humans instead of machines.

Home Page: https://agate.readthedocs.io

License: MIT License

Python 77.55% Jupyter Notebook 22.45%

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agate's Issues

Cookbook: filter to 90th percentile

Py3 support

Memoize instantiated Columns

NumberColumn.quintiles

Return a list of quintiles for the given column.

Table.filter and Table.reject should take test funcs, not lists

This should be standard... maybe support both?

Cookbook: filter by glob

DateColumn

See https://github.com/onyxfish/csvkit/blob/master/csvkit/typeinference.py#L126

Cookbook: using with csvkit

Table.group

Should output an dict of tables

Should take a function name that returns a grouping key

Column.any

Column.map API isn't consistent

Should probably just drop this now that Table.compute is in?

TimeColumn

See #7

Cookbook: filter to values within a range

NumberColumn.percentiles

Return an list of percentiles for a given column.

Column.variance

Cookbook: levenshtein

Combine Table.where with levenshtein algorithm. Maybe this one? https://pypi.python.org/pypi/python-Levenshtein/0.11.2

BooleanColumn

See https://github.com/onyxfish/csvkit/blob/master/csvkit/typeinference.py#L54

Table.join

Table.remove_column

Should have a way to create a new table from a subset of columns of an existing table. What is the API for this? What is it called? subset? part? subtable?

Table.find

Find the first row that satisfies the criteria

Cookbook: write a table back out to a CSV

Table.merge

Like Table.join (#11) but for rows.

Column.count

Count instances of a value

DateTimeColumn

See #7

Table.rank

Table.rank(self, func)

func returns a value, these values are compared to generate a rank IntColumn.

Optional sort_by_rank param?

Tests for IntColumn.stdev and FloatColumn.stdev

Table.init: validate dimensions of rows, names and types

NumberColumn.quartiles

Return a list of quartiles for the given column.

Cookbook: filter by regex

Tests failing due to float precision issues

FAIL: test_median (tests.test_columns.TestFloatColumn)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/Users/onyxfish/src/journalism/tests/test_columns.py", line 191, in test_median
    self.assertEqual(self.table.columns['two'].median(), 2.805)
AssertionError: 2.8049999999999997 != 2.805

======================================================================
FAIL: test_sum (tests.test_columns.TestFloatColumn)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/Users/onyxfish/src/journalism/tests/test_columns.py", line 177, in test_sum
    self.assertEqual(self.table.columns['two'].sum(), 10.71)
AssertionError: 10.709999999999999 != 10.71

Cookbook: emulating vlookup

Eliminate duplicative column index lookups

Since tables are immutable this can be cached:

i = self._table._column_names.index(self._k)

Cookbook: emulating pivot table

Cookbook: emulating Excel formulas

Table.compute

Cookbook section of docs

Column.some(func)

Returns true if any value in the column passes a truth test

Column.frequency

Stubbed as freq, but should be spelled. Returns a dict, I guess? Or a Table?

Memoize data access functions in Column

_data, _data_without_nulls, _data_sorted

Reminder: tables are immutable so we can cache this indefinately

Table.percent_change

Compute percent change between two columns into another

Cookbook: round a column to n decimal places

Table.compute_column(func)

Iterate over the table and compute a new column based existing columns

What to call this?

Cookbook: generate a histogram

Cookbook: loading a csv

Append columns to Table

How should this work? Operator overloading? Function call? What sort of validation do we need?

Tests for Column.cast

Support variable-length rows

csvkit does this by return None when a key is outside the row range, which seems sound

Multi-column sort

Column.all

Beg, borrow and steal from latimes-calculate

http://latimes-calculate.readthedocs.org/en/latest/

Most of these probably don't make sense, but a few, like Benford's would be a good fit

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