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1: Aggregation
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2: Grouping With Dictionaries
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3: Grouping in Pandas
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4: Category Type
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5: Grouping by Multiple Columns
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6: Multiple Aggregations
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7: Named Aggregations
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8: Custom Aggregations
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9: Pivot Tables
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10: Pivot Table Aggregations
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11: Star Schema
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12: Grain Validation
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13: Fixing Grain Violations
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14: Building a Data Model
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Raw data is usually rows of individual events: one order, one click, one transaction. Business questions, on the other hand, are usually about summaries.
You don't answer these by reading individual rows, but rather by aggregating: grouping rows together and calculating summary statistics. Common aggregations include:
Aggregations take you from 10,000 "raw" order rows to 50 category-level summaries.