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Aprende Challenge: Find Outliers in Sales Data | Data Quality Essentials
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bookChallenge: Find Outliers in Sales Data

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You will use the 1.5 * IQR rule to detect outliers in a vector of sales figures. Outliers can sometimes signal data entry errors or rare but valid events.

  • Calculate the first quartile (q1) and third quartile (q3) of the sales vector.
  • Compute the interquartile range (iqr) as q3 - q1.
  • Determine the lower and upper bounds for outliers using the 1.5 * IQR rule.
  • Identify the indices and values of any sales figures below the lower bound or above the upper bound.
  • Return a list with two elements: indices (the positions of outliers in the original vector) and values (the outlier sales figures).

Solución

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Sección 3. Capítulo 4
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bookChallenge: Find Outliers in Sales Data

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Tarea

Swipe to start coding

You will use the 1.5 * IQR rule to detect outliers in a vector of sales figures. Outliers can sometimes signal data entry errors or rare but valid events.

  • Calculate the first quartile (q1) and third quartile (q3) of the sales vector.
  • Compute the interquartile range (iqr) as q3 - q1.
  • Determine the lower and upper bounds for outliers using the 1.5 * IQR rule.
  • Identify the indices and values of any sales figures below the lower bound or above the upper bound.
  • Return a list with two elements: indices (the positions of outliers in the original vector) and values (the outlier sales figures).

Solución

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¿Todo estuvo claro?

¿Cómo podemos mejorarlo?

¡Gracias por tus comentarios!

Sección 3. Capítulo 4
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single

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