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Column Null Ratio: Provides the percentage of null values within a column Column Pattern: Generates regular expressions for a percentage of rows within a table This can be used to identify the number of different formats within a column for things like phone number, postal codes, and Social Security numbers For example, if profiling a ZIP code column, you may be interested in how many entries have the expanded ZIP code format (with four extra digits) The likely regular expressions might be \d{5}-\d{4}, \d{5}, and \d{9} Getting an expression like \d{15} would cause you to want to do further research Column Statistics: Provides statistical values for the selected column, such as standard deviation, minimum, maximum, or average For example, this could be used to do bounds checks for test scores, where no score should be less than 0 percent or greater than 100 percent.

Use the animation objects that support keyframes such as the ColorAnimationUsingKeyFrames, DoubleAnimationUsingKeyFrames, PointAnimationUsingKeyFrames, and ObjectAnimationUsingKeyFrames classes to create more realistic effects.

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You could also use this profile to check date ranges during a data warehouse load For example, you probably wouldn t expect an active employee to have a start date greater than the current date Column Value Distribution: Provides all the distinct values within the column along with their percentage distribution If you were profiling a column that contained US states, then you would expect 50 or 54 distinct state values, depending on what is considered a state If you received 70 distinct state values, then obviously there would be a data-quality problem The Data Profiling task provides the following data profiles for multiple columns: Candidate Key: Indicates whether a particular column, or set of columns, can be used as a key or an approximate key Functional Dependency: Provides an indication of the dependency of one column on another.

We covered the basics of animation in Recipe 3-11 In 1, Recipe 1-5, we explained how to create keyframe animations as part of the Expression Blend walkthrough In this recipe, we dive deeper into keyframe animations and explore animating multiple controls and properties in the same Storyboard, configuring the interpolation type for the animation, and easing in, easing out, or accelerating portions of the overall animation for fine-tuned control Just as in Recipe 3-11, keyframe animations work on certain types, including Color, Double, Point, and Object with the corresponding keyframe class of ColorAnimationUsingKeyFrames, DoubleAnimationUsingKeyFrames, PointAnimationUsingKeyFrames, and ObjectAnimationUsingKeyFrames Each of these classes includes a KeyFrames collection containing keyframe objects that correspond to the type being animated, with an additional wrinkle of the algorithm used to interpolate between keyframes The available interpolation options are linear, discrete, and splined Linear interpolation animates at a constant rate for the duration of the segment.

Figure 6-5. Pie chart visualizations with small pie slices or a large number of slices can hamper visual analysis. Following are some of the challenges of using pie chart visualizations: The slices of a pie chart must add up to 100 percent. By definition, a pie (circle) cannot represent more than 100 percent correctly. However, software charting solutions are often forgiving, and this causes designers to improperly expose the dynamic data in a pie chart. For example, a 50 percent pie slice that represents a 120 percent total is going to take less than half of the area (which is clearly incorrect visually). Very small slices can be hard to see in a pie chart. Small slices can make it frustrating for the user to get additional information or perform an action (e.g., hovering to see a tool tip or clicking for drill-down). Large number of slices can degrade analysis and cause annotations (labels) to overlap. Pie charts rely on colors to clearly identify slices. If there are a large number of slices or a color cannot be used (e.g., when printing to paper), this will negate using a color-based legend. Furthermore, the color requirement could cause problems for users that are color-blind.

For example, if there is a product category and product subcategory relationship, this profile can determine whether a particular subcategory exists only within the product category It wouldn t be expected that the subcategory exists within many product categories Value Inclusion: Indicates the overlap between a set of columns Continuing with the previous example, when profiling the product subcategory column within the product table, all values should exist within the product subcategory table..

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