Pivot for Trend Identification

Demonstrate how you would use a pivot table to identify trends in this provided dataset.

Use the provided OpenX ad-performance tables and return one row for every listed channel, including channels without activity. Compare January, February, and March 2025 totals to classify the overall trend from January to March.

Output

1. One row per channel, ordered alphabetically with null channel names last.
2. Columns: channel_name, january_impressions, february_impressions, march_impressions, and trend.
3. trend must be Increasing, Declining, or Stable.

Output details

• Treat each month as including its first date and excluding the first date of the following month.
• Treat NULL impressions values as 0 when calculating monthly totals.
• Classify trend by comparing March with January: greater is Increasing, lower is Declining, and equal is Stable.
• Retain separate rows for distinct channels even when their channel_name values are identical or NULL.