def test_binning_multiindex(): global iris grouped = iris.groupby('species') agg = grouped.agg(['min', 'max', 'mean']) bins = { ('sepal_length', 'mean'): { 'method': 'quantile', 'count': 4, 'palette': 'green' }, ('petal_length', 'min'): { 'method': 'interval', 'count': 4, 'palette': 'blue' }, ('petal_length', 'max'): { 'method': 'interval', 'count': 4, 'palette': 'red' } } output_json = df_to_json(agg, bins=bins) assert output_json dt = loads(output_json) assert_standard_props(dt) meta_cols = dt['meta'].get('columns') assert 'sepal_length|mean' in meta_cols['bins'] assert 'petal_length|min' in meta_cols['bins'] assert 'petal_length|max' in meta_cols['bins']
def test_multiindex_df_to_json(): global iris grouped = iris.groupby('species') agg = grouped.agg(['min', 'max', 'mean']) output_json = df_to_json(agg) assert output_json assert_standard_props(loads(output_json))
def test_nestedRowsColumns_yesColouring(): bins = { ('sepal_length', 'min'): { 'method': 'interval', 'count': 5, 'palette': 'Greens' } } js = df_to_json(gdf_columns_rows, bins=bins) with open('nestedRowsColumns_yesColoring.json', 'w') as f: f.write(js)
def test_simple_yesColouring(): bins = { 'sepal_length': { 'method': 'interval', 'count': 5, 'palette': 'Greens' } } js = df_to_json(df, bins=bins) with open('simple_yesColoring.json', 'w') as f: f.write(js)
def test_filter_simple(): global iris filterFields = ['sepal_length', 'petal_length'] output_json = df_to_json(iris, filterFields=filterFields) assert output_json df = loads(output_json) m = df['meta'] assert m['filterFields'] == filterFields
def test_filter_multiindex(): global iris grouped = iris.groupby('species') agg = grouped.agg(['min', 'max', 'mean']) filterFields = [('sepal_length', 'mean'), ('petal_length', 'min')] output_json = df_to_json(agg, filterFields=filterFields) assert output_json df = loads(output_json) m = df['meta'] print(m) fields_from_JSON = [] for f in m['filterFields']: fields_from_JSON.append(tuple(f.split("|")) if "|" in f else f) assert fields_from_JSON == filterFields
def test_binning_simple(): global iris bins = dict(sepal_length={ 'method': 'quantile', 'count': 4, 'palette': 'green' }, petal_length={ 'method': 'interval', 'count': 4, 'palette': 'magma' }) output_json = df_to_json(iris, bins=bins) assert output_json assert_standard_props(loads(output_json))
def test_simple_df_to_json(): global iris output_json = df_to_json(iris) assert output_json assert_standard_props(loads(output_json))
def test_nestedColumns_filterFields(): filterFields = [('sepal_length', 'min')] js = df_to_json(gdf_columns, filterFields=filterFields) with open('nestedColumns_filterFields.json', 'w') as f: f.write(js)
def test_simple_filterFields(): filterFields = ['sepal_length'] js = df_to_json(df, filterFields=filterFields) with open('simple_filterFields.json', 'w') as f: f.write(js)
def test_nestedRowsColumns_noColouring(): js = df_to_json(gdf_columns_rows) with open('nestedRowsColumns_noColoring.json', 'w') as f: f.write(js)
def test_simple_noColouring(): js = df_to_json(df) with open('simple_noColoring.json', 'w') as f: f.write(js)