private[this] def extractNumericStatistics()

in src/main/scala/com/amazon/deequ/profiles/ColumnProfiler.scala [465:545]
69 lines of code
23 McCabe index (conditional complexity)

  private[this] def extractNumericStatistics(results: AnalyzerContext): NumericColumnStatistics = {

    val means = results.metricMap
      .collect { case (analyzer: Mean, metric: DoubleMetric) =>
        metric.value match {
          case Success(metricValue) => Some(analyzer.column -> metricValue)
          case _ => None
        }
      }
      .flatten
      .toMap

    val stdDevs = results.metricMap
      .collect { case (analyzer: StandardDeviation, metric: DoubleMetric) =>
        metric.value match {
          case Success(metricValue) => Some(analyzer.column -> metricValue)
          case _ => None
        }
      }
      .flatten
      .toMap

    val maxima = results.metricMap
      .collect { case (analyzer: Maximum, metric: DoubleMetric) =>
        metric.value match {
          case Success(metricValue) => Some(analyzer.column -> metricValue)
          case _ => None
        }
      }
      .flatten
      .toMap

    val minima = results.metricMap
      .collect { case (analyzer: Minimum, metric: DoubleMetric) =>
        metric.value match {
          case Success(metricValue) => Some(analyzer.column -> metricValue)
          case _ => None
        }
      }
      .flatten
      .toMap

    val sums = results.metricMap
      .collect { case (analyzer: Sum, metric: DoubleMetric) =>
        metric.value match {
          case Success(metricValue) => Some(analyzer.column -> metricValue)
          case _ => None
        }
      }
      .flatten
      .toMap


    val kll = results.metricMap
      .collect { case (analyzer: KLLSketch, metric: KLLMetric) if metric.value.isSuccess =>
        metric.value match {
          case Success(bucketDistribution) =>
            Some(analyzer.column -> bucketDistribution)
          case _ => None
        }
      }
      .flatten
      .toMap

    val approxPercentiles = results.metricMap
      .collect {  case (analyzer: KLLSketch, metric: KLLMetric) =>
        metric.value match {
          case Success(bucketDistribution) =>

            val percentiles = bucketDistribution.computePercentiles()

            Some(analyzer.column -> percentiles.toSeq.sorted)
          case _ => None
        }
      }
      .flatten
      .toMap


    NumericColumnStatistics(means, stdDevs, minima, maxima, sums, kll, approxPercentiles)
  }