示例：NaN 检测和移除

使用 markNaN 函数将数据集中的离群值标记为 NaN (非数字)。使用 IsNaN、matchNaN 和 filterNaN 函数管理 NaN。

1. 读取包含最近三个世纪记录的太阳黑子数量的文件，并绘制数据图像。

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2. 使用 ThreeSigma 函数来查找离群值的索引。

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离群值是下列年份中所记录的太阳黑子的数量：

3. 使用 markNaN 函数将数据第一列中的离群值标记为 NaN。

数据替换为 NaN 表明已进行测量，但可在处理之前将包含 NaN 的行过滤掉。

4. 使用 matchNaN 函数来查找被标记为 NaN 的点的索引。

257 行和 278 行中的数据已被替换为内置常数NaN：

5. 使用 IsNaN 函数来检查年份 1957 在 Data 和 MarkedData 数据集中是否被标记为 NaN。

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6. 绘制新数据集的图像，并将其与旧数据集的进行对比。

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原始数据集中的离群值并没有以蓝色突出显示，这是由于绘图跳过了在 MarkedData 数据集中记录的 NaN。

7. 使用 filterNaN 函数过滤矩阵 MarkedData 集来移除包含 NaN 的行。

8. 使用 rows 函数来计算 Data 和 FilteredData 集的行数。

FilteredData 中的行数已减少 2。

9. 使用 mean 函数来计算 MarkedData 和 FilteredData 集的均值。

可以收集 FilteredData 数据集的统计信息，而对 MarkedData 数据集则不可以。