Closed jreback closed 5 years ago
@jreback Is this still relevant? If so, I'd like to help with it!
sure spitting of big test modules is always welcome
@jreback I've made an attempt at categorizing the tests for the sparse series only so far:
Tests in sparse.test_series.py
Test Category
TestSparseSeries
test_constructor_dict_input constructors
test_constructor_dict_order constructors
test_constructor_dtype constructors
test_iteration_and_str sparse
test_construct_DataFrame_with_sp_series constructors
test_constructor_preserve_attr constructors
test_series_density sparse
test_sparse_to_dense sparse
test_to_dense_fill_value missing
test_dense_to_sparse sparse
test_to_dense_preserve_name api
test_constructor constructors
test_constructor_scalar constructors
test_constructor_ndarray constructors
test_constructor_nonnan constructors
test_constructor_empty constructors
test_copy_astype dtypes
test_shape api
test_astype dtypes
test_astype_all dtypes
test_kind sparse
test_to_frame io
test_pickle io
test_getitem indexing
test_get_get_value indexing
test_set_value indexing
test_getitem_slice indexing
test_take indexing
test_numpy_take indexing
test_setitem indexing
test_setslice indexing
test_operators operators
test_binary_operators operators
test_unary_operators operators
test_abs operators
test_reindex indexing
test_sparse_reindex indexing
test_repr repr
test_iter api
test_truncate api
test_fillna missing
test_reductions apply
test_dropna missing
test_homogenize sparse
test_fill_value_corner missing
test_fill_value_when_combine_const missing
test_shift api
test_shift_nan missing
test_shift_dtype dtypes
test_shift_dtype_fill_value missing
test_combine_first api
test_memory_usage_deep sparse
TestSparseHandlingMultiIndexes
test_to_sparse_preserve_multiindex_names_columns indexing
test_round_trip_preserve_multiindex_names indexing
TestSparseSeriesScipyInteraction
test_to_coo_text_names_integer_row_levels_nosort coo
test_to_coo_text_names_integer_row_levels_sort coo
test_to_coo_text_names_text_row_levels_nosort_col_level_single coo
test_to_coo_integer_names_integer_row_levels_nosort coo
test_to_coo_text_names_text_row_levels_nosort coo
test_to_coo_bad_partition_nonnull_intersection coo
test_to_coo_bad_partition_small_union coo
test_to_coo_nlevels_less_than_two coo
test_to_coo_bad_ilevel coo
test_to_coo_duplicate_index_entries coo
test_from_coo_dense_index coo
test_from_coo_nodense_index coo
test_from_coo_long_repr coo
test_concat concat
test_concat_axis1 concat
test_concat_different_fill concat
test_concat_axis1_different_fill concat
test_concat_different_kind concat
test_concat_sparse_dense concat
test_value_counts analytics
test_value_counts_dup analytics
test_value_counts_int analytics
test_isna missing
test_notna missing
TestSparseSeriesAnalytics
test_cumsum analytics
test_numpy_cumsum analytics
test_numpy_func_call analytics
test_deprecated_numpy_func_call analytics
test_deprecated_reindex_axis analytics
With this I've introduced two new categories as I felt these were necessary, given that some of the tests were very specific. These two are sparse
and coo
, where sparse
is for new properties/features that the sparse series introduce and coo
is for SciPy's coordinate format matrices (there are a bunch of tests that are specifically related to this).
Let me know what you think of this categorization, if it looks good I'll start splitting the tests and put up a PR.
https://github.com/pandas-dev/pandas/pull/18968
sets up a really basic structure. ideally split out tests from tests_series and test_frame, in a similar manner to how we do
pandas/tests/frame
andpandas/tests/series
.