spam-classifier
/
venv
/lib
/python3.11
/site-packages
/pandas
/tests
/arrays
/floating
/conftest.py
| import numpy as np | |
| import pytest | |
| import pandas as pd | |
| from pandas.core.arrays.floating import ( | |
| Float32Dtype, | |
| Float64Dtype, | |
| ) | |
| def dtype(request): | |
| """Parametrized fixture returning a float 'dtype'""" | |
| return request.param() | |
| def data(dtype): | |
| """Fixture returning 'data' array according to parametrized float 'dtype'""" | |
| return pd.array( | |
| list(np.arange(0.1, 0.9, 0.1)) | |
| + [pd.NA] | |
| + list(np.arange(1, 9.8, 0.1)) | |
| + [pd.NA] | |
| + [9.9, 10.0], | |
| dtype=dtype, | |
| ) | |
| def data_missing(dtype): | |
| """ | |
| Fixture returning array with missing data according to parametrized float | |
| 'dtype'. | |
| """ | |
| return pd.array([np.nan, 0.1], dtype=dtype) | |
| def all_data(request, data, data_missing): | |
| """Parametrized fixture returning 'data' or 'data_missing' float arrays. | |
| Used to test dtype conversion with and without missing values. | |
| """ | |
| if request.param == "data": | |
| return data | |
| elif request.param == "data_missing": | |
| return data_missing | |