def test_dataframe_index_name(dataframe):
# Setting a custom index name
dataframe.index.name = "custom_index"
grid = DataGrid(dataframe)
# Making sure no value is set for index_name
assert grid._index_name is None
# Checking index name matches DataFrame retrieved from grid
data = grid.get_visible_data()
assert data.index.name == "custom_index"
def test_selections(clear: bool, dataframe: pd.DataFrame) -> None:
grid = DataGrid(dataframe, selection_mode="cell", editable=True)
grid.select(1, 0, 2, 1) # Select 1A to 2B
if clear:
grid.clear_selection()
assert grid.selected_cells == []
else:
assert grid.selected_cells == [
{
"c": 0,
"r": 1
},
{
"c": 1,
"r": 1
},
{
"c": 0,
"r": 2
},
{
"c": 1,
"r": 2
},
]
def test_default_dataframe_index(dataframe):
# Setting a custom index name
grid = DataGrid(dataframe)
# Making sure index_name is set
assert grid._index_name is None
# Generate primary key schema object
index_key = grid.get_dataframe_index(dataframe)
data_obj = grid.generate_data_object(dataframe, "ipydguuid", index_key)
# Default and unused keys should not be in schema
assert "key" in data_obj["schema"]["primaryKey"]
def test_user_defined_index_name(dataframe):
# Setting a custom index name
dataframe.index.name = "unused_index"
grid = DataGrid(dataframe, index_name="custom_index")
# Making sure index_name is set
assert grid._index_name is not None
# Checking index name matches DataFrame retrieved from grid
index_key = grid.get_dataframe_index(dataframe)
data_obj = grid.generate_data_object(dataframe, "ipydguuid", index_key)
# Default and unused keys should not be in schema
assert "key" not in data_obj["schema"]["primaryKey"]
assert "unused_index" not in data_obj["schema"]["primaryKey"]
# User defined key should be in primary key schema
assert "custom_index" in data_obj["schema"]["primaryKey"]
def plot_tabular(df: pd.DataFrame, opts: ComputeOpts) -> DataGrid:
renderer = TextRenderer(
format=',') if not opts.normalize else TextRenderer(format=',.4f')
grid = DataGrid(
df,
base_row_size=30,
selection_mode="cell",
editable=False,
base_column_size=80,
# layout={'height': '200px'}
renderers={
c: renderer
for c in df.columns if c not in TEMPORAL_GROUP_BY
},
)
grid.transform([{"type": "sort", "columnIndex": 0, "desc": False}])
grid.auto_fit_params = {"area": "all", "padding": 40, "numCols": 1}
grid.auto_fit_columns = True
return grid
def display_grid(data: Union[dict, pd.DataFrame], **opts) -> DataGrid:
column_formats: dict = opts.get('column_formats', {})
renderers = {
c: TextRenderer(format=column_formats[c])
if c in column_formats else TextRenderer()
for c in data.columns
}
grid = DataGrid(
data,
base_row_size=30,
selection_mode="cell",
editable=False,
base_column_size=80,
# layout={'height': '200px'}
renderers=renderers,
)
grid.transform([{"type": "sort", "columnIndex": 0, "desc": False}])
grid.auto_fit_params = {"area": "all", "padding": 40, "numCols": 1}
grid.auto_fit_columns = True
return grid
def test_data_setter(dataframe) -> None:
grid = DataGrid(dataframe)
new_df = pd.DataFrame(data={"A": [0, 0, 0], "B": [4, 5, 6]})
grid.data = new_df
assert grid.data.equals(new_df)
def test_data_getter(dataframe) -> None:
grid = DataGrid(dataframe)
assert grid.data.equals(dataframe)
def datagrid(dataframe) -> None:
return DataGrid(dataframe)