impyute
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eltonlaw
Data imputations library to preprocess datasets with missing data
Slightly relax line lengths, and clean up some of the outstanding issues with linting.
See discussion in: https://github.com/eltonlaw/impyute/issues/64
Create a function named `randc` to generate a dataset of categorical variables with missingness. Follow the general form of `randu` & `randn`, witht he following arguments: - `nlevels`: Number of...
In the first case, an `UnboundLocalError` occurs because `data` is not assigned based on the current `if/else` criteria. Add an `else` clause and `raise BadInputError` accompanied by a more informative...
Complete `mnar` method in the `Corruptor` class. Simplified, MNAR (Missing Not at Random) is a type of missingness in which the probability of a value being missing is conditional (in...
Complete `mar` method in the `Corruptor` class. Simplified, MAR (Missing at Random) is a type of missingness in which the probability of a value being missing is conditional only on...
## todo 1. `Dockerfile.pybase` builds the `eltonlaw/pybase` image which sets up the python environments. Add stuff to install pypy here. 2. `Dockerfile` builds the `impyute` image which installs dev requirements...
Side issue of #54 Data properties (shape, data type, distribution etc.)
