def test_agg_apply_axis_names(axis, func, op):
eval_general(
*create_test_dfs(test_data["int_data"]),
lambda df: getattr(df, op)(func, axis),
)
def test_min_max_mean(data, axis, skipna, numeric_only, is_transposed, method):
eval_general(
*create_test_dfs(data),
lambda df: getattr((df.T if is_transposed else df), method)
(axis=axis, skipna=skipna, numeric_only=numeric_only),
)
def test_all_any(data, axis, skipna, is_transposed, method):
eval_general(
*create_test_dfs(data),
lambda df: getattr((df.T if is_transposed else df), method)
(axis=axis, skipna=skipna, bool_only=None),
)
def test_describe(data, percentiles):
eval_general(
*create_test_dfs(data),
lambda df: df.describe(percentiles=percentiles),
)
def test_idxmin_idxmax(data, axis, skipna, is_transposed, method):
eval_general(
*create_test_dfs(data),
lambda df: getattr((df.T if is_transposed else df), method)
(axis=axis, skipna=skipna),
)
def test_diff(axis, periods):
eval_general(
*create_test_dfs(test_data["float_nan_data"]),
lambda df: df.diff(axis=axis, periods=periods),
)
def test_count(data, axis):
eval_general(
*create_test_dfs(data),
lambda df: df.count(axis=axis),
)
def test_reduction_specific(fn, numeric_only):
eval_general(
*create_test_dfs(test_data_diff_dtype),
lambda df: getattr(df, fn)(numeric_only=numeric_only),
)
def test_median_skew_transposed(axis, method):
eval_general(
*create_test_dfs(test_data["int_data"]),
lambda df: getattr(df.T, method)(axis=axis),
)
def test_to_string(data):
eval_general(
*create_test_dfs(data),
lambda df: df.to_string(),
)
def test_sum_prod_specific(fn, min_count, numeric_only):
eval_general(
*create_test_dfs(test_data_diff_dtype),
lambda df: getattr(df, fn)
(min_count=min_count, numeric_only=numeric_only),
)
def test_to_records(request, data):
eval_general(
*create_test_dfs(data),
lambda df: df.dropna().to_records(),
)
def test_dropna_subset_error(data, axis, subset):
eval_general(*create_test_dfs(data),
lambda df: df.dropna(axis=axis, subset=subset))
def test___hash__():
data = test_data_values[0]
pandas_df = pandas.DataFrame(data)
modin_df = pd.DataFrame(data)
eval_general(modin_df, pandas_df, lambda df: hash(df))
def test_std_var_transposed(axis, ddof, method):
eval_general(
*create_test_dfs(test_data["int_data"]),
lambda df: getattr(df.T, method)(axis=axis, ddof=ddof),
)
def test_median_skew_std_var_rank_sem_specific(numeric_only, method):
eval_general(
*create_test_dfs(test_data_diff_dtype),
lambda df: getattr(df, method)(numeric_only=numeric_only),
)
def test_cummin_cummax_int_and_float(axis, method):
data = {"col1": list(range(1000)), "col2": [i * 0.1 for i in range(1000)]}
eval_general(*create_test_dfs(data), lambda df: getattr(df, method)
(axis=axis))
def test_cumprod_cummin_cummax_cumsum(axis, skipna, method):
eval_general(
*create_test_dfs(test_data["float_nan_data"]),
lambda df: getattr(df, method)(axis=axis, skipna=skipna),
)
def test_diff_transposed(axis):
eval_general(
*create_test_dfs(test_data["int_data"]),
lambda df: df.T.diff(axis=axis),
)
def test_rank_transposed(axis, na_option):
eval_general(
*create_test_dfs(test_data["int_data"]),
lambda df: df.rank(axis=axis, na_option=na_option),
)
def test_count_specific(numeric_only):
eval_general(
*create_test_dfs(test_data_diff_dtype),
lambda df: df.count(numeric_only=numeric_only),
)
def test_cumprod_cummin_cummax_cumsum_transposed(axis, method):
eval_general(
*create_test_dfs(test_data["int_data"]),
lambda df: getattr(df.T, method)(axis=axis),
)
def test_describe_specific(exclude, include):
eval_general(
*create_test_dfs(test_data_diff_dtype),
lambda df: df.drop("str_col", axis=1).describe(exclude=exclude,
include=include),
)
def test_sem_float_nan_only(skipna, ddof):
eval_general(
*create_test_dfs(test_data["float_nan_data"]),
lambda df: df.sem(skipna=skipna, ddof=ddof),
)
def test_memory_usage(data, index):
eval_general(*create_test_dfs(data),
lambda df: df.memory_usage(index=index))
def test_sem_int_only(axis, ddof):
eval_general(
*create_test_dfs(test_data["int_data"]),
lambda df: df.sem(axis=axis, ddof=ddof),
)
def test_sum_specific(min_count, numeric_only):
eval_general(
*create_test_dfs(test_data_diff_dtype),
lambda df: df.sum(min_count=min_count, numeric_only=numeric_only),
)
def test_std_var_rank(axis, skipna, method):
eval_general(
*create_test_dfs(test_data["float_nan_data"]),
lambda df: getattr(df, method)(axis=axis, skipna=skipna),
)
def test_all_any_specific(bool_only, method):
eval_general(
*create_test_dfs(test_data_diff_dtype),
lambda df: getattr(df, method)(bool_only=bool_only),
)
def test_agg_apply(axis, func, op):
eval_general(
*create_test_dfs(test_data["float_nan_data"]),
lambda df: getattr(df, op)(func, axis),
)