pygrinder

library0.7pypypi✓ verified 87d ago

A Python toolkit for introducing missing values into datasets under various missingness mechanisms (MCAR, MAR, MNAR) and patterns (point, sequential, block). Current version: 0.7. Requires Python >=3.8. Released quarterly.

data ai-ml

pip install pygrinder

github ↗package ↗homepage ↗docs ↗

INSTALL

IMPORT

SIG · PYGRINDER

pygrinder

datapythonv0.7

Install

81.7s avg

Import

12845ms

Disk

5248MB

Pass rate

4/ 10

Env Coverage4 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.7 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

glibc

py 3.10

✕ build_error

✓ 90.3s

py 3.11

✕ build_error

✓ 87.3s

py 3.12

✕ build_error

✓ 77s

py 3.13

✕ build_error

✓ 72.3s

py 3.9

✕ build_error

✕ timeout

5248MB installed

● package 5248MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

mcar

✓ from pygrinder import mcar

Earlier versions (pre-0.4) returned masks; now returns only corrupted data.

mar_logistic

✓ from pygrinder import mar_logistic

Renamed from mar_logistic (always existed).

mnar_x

✓ from pygrinder import mnar_x

Renamed from mnar_x (always existed).

mnar_t

✓ from pygrinder import mnar_t

Renamed from mnar_t (always existed).

mnar_nonuniform

✓ from pygrinder import mnar_nonuniform

Added in v0.7, replaces mnar_num.

seq_missing

✓ from pygrinder import seq_missing

Added in v0.6.

block_missing

✓ from pygrinder import block_missing

Added in v0.6.

rdo

✓ from pygrinder import rdo

Added in v0.5.

fill_and_get_mask

✓ from pygrinder import fill_and_get_mask

Added in v0.4.

little_mcar_test

✓ from pygrinder import little_mcar_test

Added in v0.2.

calc_missing_rate

✓ from pygrinder import calc_missing_rate

✗ from pygrinder import calc_misssing_rate

Typo in v0.6.1 used 'calc_misssing_rate' (extra 's'), corrected to 'calc_missing_rate' from v0.6.2 onwards.

Basic usage: create MCAR missingness, then fill NaNs and get mask.

import numpy as np from pygrinder import mcar, fill_and_get_mask X = np.random.randn(100, 10) corrupted_X = mcar(X, rate=0.2) X_filled, mask = fill_and_get_mask(corrupted_X, fill_value=0) print(f"Original shape: {X.shape}, missing rate: {1 - mask.mean():.2f}")

Debug

Known issues

breakingIn v0.4, all missingness-creating functions (mcar, mar_logistic, mnar_x, mnar_t) changed to return only the corrupted data (with NaN), not a tuple (X_intact, X, mask). Use fill_and_get_mask to get the mask.

fix

Update code: data = mcar(X, rate=0.2) instead of X_intact, data, mask = mcar(X, rate=0.2). Use fill_and_get_mask(data) to get mask.

affects: <0.4

deprecatedIn v0.7, mnar_num has been renamed to mnar_nonuniform. The old name mnar_num is removed.

fix

Replace mnar_num with mnar_nonuniform.

affects: <=0.6.4

gotchaFunctions seq_missing and block_missing require seq_len argument; setting seq_len equal to n_steps can cause an empty step_idx list bug (fixed in v0.6.4). Verify that seq_len < n_steps to avoid errors.

fix

Upgrade to >=0.6.4 or ensure seq_len < n_steps.

affects: <=0.6.3

gotchaMar_logistic had a bug in argument order (v0.6.2 and earlier) that could produce incorrect missingness. Fixed in v0.6.3.

fix

Upgrade to >=0.6.3.

affects: <=0.6.2

deprecatedIn v0.4, the parameter 'return_masks' was available to return masks alongside corrupted data; it was removed in later versions. Use fill_and_get_mask instead.

fix

Switch to fill_and_get_mask to retrieve the mask.

affects: 0.3-0.4

Errors

Common errors & fixes

AttributeError: module 'pygrinder' has no attribute 'calc_misssing_rate'

Typo in function name; the correct name is calc_missing_rate (single 's' after 'miss').

fix

Use from pygrinder import calc_missing_rate

TypeError: mcar() got multiple values for argument 'rate'

Passing both positional and keyword argument for 'rate', or duplicate keyword.

fix

Call mcar(X, rate=0.2) with only one rate specification.

ValueError: seq_len must be less than n_steps

In seq_missing, seq_len equals or exceeds the number of time steps, causing an empty index list.

fix

Set seq_len < n_steps, or upgrade to pygrinder >=0.6.4 where this condition is handled.

Upgrade

Version history

0.7latest on PyPI · released Feb 3, 2025

Audit

Dependencies

numpyrequiredCore dependency for array operations

torchrequiredUsed for random number generation and tensor operations

Agent activity

9 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/WenjieDu/PyGrinder ↗

packagehttps://pypi.org/project/pygrinder/ ↗

homepagehttps://pypots.com ↗

docshttps://docs.pypots.com ↗