dosubot[bot] commented on issue #30270:
URL: https://github.com/apache/superset/issues/30270#issuecomment-2349717211
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To address the issue of radar charts incorrectly visualizing `NULL` values
as `0`, you need to modify the `transformProps` function to handle `NULL`
values properly. Specifically, ensure that `NULL` values are not included in
the `value` array for each data point. Here’s how you can do it:
```ts
data.forEach(datum => {
const joinedName = extractGroupbyLabel({
datum,
groupby: groupbyLabels,
coltypeMapping,
timeFormatter: getTimeFormatter(dateFormat),
});
// map(joined_name: [columnLabel_1, columnLabel_2, ...])
columnsLabelMap.set(
joinedName,
groupbyLabels.map(col => datum[col] as string),
);
// put max value of series into metricLabelAndMaxValueMap
// eslint-disable-next-line no-restricted-syntax
for (const [metricLabel, value] of Object.entries(datum)) {
if (metricLabelAndMaxValueMap.has(metricLabel)) {
metricLabelAndMaxValueMap.set(
metricLabel,
Math.max(
value as number,
ensureIsInt(
metricLabelAndMaxValueMap.get(metricLabel),
Number.MIN_SAFE_INTEGER,
),
),
);
} else {
metricLabelAndMaxValueMap.set(metricLabel, value as number);
}
}
const isFiltered =
filterState.selectedValues &&
!filterState.selectedValues.includes(joinedName);
// generate transformedData
transformedData.push({
value: metricLabels.map(metricLabel => datum[metricLabel] !== null ?
datum[metricLabel] : undefined),
name: joinedName,
itemStyle: {
color: colorFn(joinedName, sliceId, colorScheme),
opacity: isFiltered
? OpacityEnum.Transparent
: OpacityEnum.NonTransparent,
},
lineStyle: {
opacity: isFiltered
? OpacityEnum.SemiTransparent
: OpacityEnum.NonTransparent,
},
label: {
show: showLabels,
position: labelPosition,
formatter,
},
} as RadarSeriesDataItemOption);
});
```
This modification ensures that `NULL` values are replaced with `undefined`,
preventing the radar chart from drawing a line to the axis containing the
missing data point
<sup>[[1]](https://github.com/apache/superset/blob/master/superset-frontend/plugins/plugin-chart-echarts/src/Radar/transformProps.ts)</sup>.
Additionally, there is an existing test for radar charts that include `NULL`
values, which can help ensure your changes work correctly:
```python
def test_pivot_df_complex_null_values():
"""
Pivot table when a column, rows and 2 metrics are selected.
"""
df = pd.DataFrame.from_dict(
{
"state": {
0: None,
1: None,
2: None,
3: None,
4: None,
5: None,
6: None,
7: None,
8: None,
9: None,
10: None,
11: None,
},
"gender": {
0: "girl",
1: "boy",
2: "girl",
3: "girl",
4: "girl",
5: "girl",
6: "boy",
7: "girl",
8: "girl",
9: "boy",
10: "boy",
11: "girl",
},
"name": {
0: "Amy",
1: "Edward",
2: "Sophia",
3: "Amy",
4: "Cindy",
5: "Dawn",
6: "Edward",
7: "Sophia",
8: "Dawn",
9: "Tony",
10: "Tony",
11: "Cindy",
},
"SUM(num)": {
0: 45426,
1: 31290,
2: 18859,
3: 14740,
4: 14149,
5: 11403,
6: 9395,
7: 7181,
8: 5089,
9: 3765,
10: 2673,
11: 1218,
},
"MAX(num)": {
0: 2227,
1: 1280,
2: 2588,
3: 854,
4: 842,
5: 1157,
6: 389,
7: 1187,
8: 461,
9: 598,
10: 247,
11: 217,
},
}
)
assert (
df.to_markdown()
== """
```
<sup>[[2]](https://github.com/apache/superset/blob/master/tests/unit_tests/charts/test_post_processing.py)</sup>
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