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)