我正在整理一个包含我们的日历数据和相关指标的表格。我应该注意，我们目前有一个非常定制的零售日历，大致基于4-5-4零售版本。因此，如果看起来有些怪异，那就是原因（例如：19年3月31日被归类为4月19日）
这是一个样本
| day | day_of_wk | day_of_mnth | day_of_qtr | day_of_yr | wk | wk_of_mnth | wk_of_yr | mnth | mnth_of_yr | qtr_of_yr | _yr |
+---------+-----------+-------------+------------+-----------+---------+------------+----------+--------+------------+-----------+------+
| 4/1/18 | 1 | 1 | 1 | 92 | 4/1/18 | 1 | 14 | 4/1/18 | 4 | 2 | 2018 |
| 4/2/18 | 2 | 2 | 2 | 93 | 4/1/18 | 1 | 14 | 4/1/18 | 4 | 2 | 2018 |
| 4/3/18 | 3 | 3 | 3 | 94 | 4/1/18 | 1 | 14 | 4/1/18 | 4 | 2 | 2018 |
| 4/4/18 | 4 | 4 | 4 | 95 | 4/1/18 | 1 | 14 | 4/1/18 | 4 | 2 | 2018 |
| 4/5/18 | 5 | 5 | 5 | 96 | 4/1/18 | 1 | 14 | 4/1/18 | 4 | 2 | 2018 |
| 4/6/18 | 6 | 6 | 6 | 97 | 4/1/18 | 1 | 14 | 4/1/18 | 4 | 2 | 2018 |
| 4/7/18 | 7 | 7 | 7 | 98 | 4/1/18 | 1 | 14 | 4/1/18 | 4 | 2 | 2018 |
| 4/8/18 | 1 | 8 | 8 | 99 | 4/8/18 | 2 | 15 | 4/1/18 | 4 | 2 | 2018 |
| 4/9/18 | 2 | 9 | 9 | 100 | 4/8/18 | 2 | 15 | 4/1/18 | 4 | 2 | 2018 |
| 4/10/18 | 3 | 10 | 10 | 101 | 4/8/18 | 2 | 15 | 4/1/18 | 4 | 2 | 2018 |
| 4/11/18 | 4 | 11 | 11 | 102 | 4/8/18 | 2 | 15 | 4/1/18 | 4 | 2 | 2018 |
| 4/12/18 | 5 | 12 | 12 | 103 | 4/8/18 | 2 | 15 | 4/1/18 | 4 | 2 | 2018 |
| 4/13/18 | 6 | 13 | 13 | 104 | 4/8/18 | 2 | 15 | 4/1/18 | 4 | 2 | 2018 |
| 4/14/18 | 7 | 14 | 14 | 105 | 4/8/18 | 2 | 15 | 4/1/18 | 4 | 2 | 2018 |
| 4/15/18 | 1 | 15 | 15 | 106 | 4/15/18 | 3 | 16 | 4/1/18 | 4 | 2 | 2018 |
| 4/16/18 | 2 | 16 | 16 | 107 | 4/15/18 | 3 | 16 | 4/1/18 | 4 | 2 | 2018 |
| 4/17/18 | 3 | 17 | 17 | 108 | 4/15/18 | 3 | 16 | 4/1/18 | 4 | 2 | 2018 |
| 4/18/18 | 4 | 18 | 18 | 109 | 4/15/18 | 3 | 16 | 4/1/18 | 4 | 2 | 2018 |
| 4/19/18 | 5 | 19 | 19 | 110 | 4/15/18 | 3 | 16 | 4/1/18 | 4 | 2 | 2018 |
| 4/20/18 | 6 | 20 | 20 | 111 | 4/15/18 | 3 | 16 | 4/1/18 | 4 | 2 | 2018 |
| 4/21/18 | 7 | 21 | 21 | 112 | 4/15/18 | 3 | 16 | 4/1/18 | 4 | 2 | 2018 |
| 4/22/18 | 1 | 22 | 22 | 113 | 4/22/18 | 4 | 17 | 4/1/18 | 4 | 2 | 2018 |
| 4/23/18 | 2 | 23 | 23 | 114 | 4/22/18 | 4 | 17 | 4/1/18 | 4 | 2 | 2018 |
| 4/24/18 | 3 | 24 | 24 | 115 | 4/22/18 | 4 | 17 | 4/1/18 | 4 | 2 | 2018 |
| 4/25/18 | 4 | 25 | 25 | 116 | 4/22/18 | 4 | 17 | 4/1/18 | 4 | 2 | 2018 |
| 4/26/18 | 5 | 26 | 26 | 117 | 4/22/18 | 4 | 17 | 4/1/18 | 4 | 2 | 2018 |
| 4/27/18 | 6 | 27 | 27 | 118 | 4/22/18 | 4 | 17 | 4/1/18 | 4 | 2 | 2018 |
| 4/28/18 | 7 | 28 | 28 | 119 | 4/22/18 | 4 | 17 | 4/1/18 | 4 | 2 | 2018 |
| 3/31/19 | 1 | 1 | 1 | 92 | 3/31/19 | 1 | 14 | 4/1/19 | 4 | 2 | 2019 |
| 4/1/19 | 2 | 2 | 2 | 93 | 3/31/19 | 1 | 14 | 4/1/19 | 4 | 2 | 2019 |
| 4/2/19 | 3 | 3 | 3 | 94 | 3/31/19 | 1 | 14 | 4/1/19 | 4 | 2 | 2019 |
| 4/3/19 | 4 | 4 | 4 | 95 | 3/31/19 | 1 | 14 | 4/1/19 | 4 | 2 | 2019 |
| 4/4/19 | 5 | 5 | 5 | 96 | 3/31/19 | 1 | 14 | 4/1/19 | 4 | 2 | 2019 |
| 4/5/19 | 6 | 6 | 6 | 97 | 3/31/19 | 1 | 14 | 4/1/19 | 4 | 2 | 2019 |
| 4/6/19 | 7 | 7 | 7 | 98 | 3/31/19 | 1 | 14 | 4/1/19 | 4 | 2 | 2019 |
| 4/7/19 | 1 | 8 | 8 | 99 | 4/7/19 | 2 | 15 | 4/1/19 | 4 | 2 | 2019 |
| 4/8/19 | 2 | 9 | 9 | 100 | 4/7/19 | 2 | 15 | 4/1/19 | 4 | 2 | 2019 |
| 4/9/19 | 3 | 10 | 10 | 101 | 4/7/19 | 2 | 15 | 4/1/19 | 4 | 2 | 2019 |
| 4/10/19 | 4 | 11 | 11 | 102 | 4/7/19 | 2 | 15 | 4/1/19 | 4 | 2 | 2019 |
| 4/11/19 | 5 | 12 | 12 | 103 | 4/7/19 | 2 | 15 | 4/1/19 | 4 | 2 | 2019 |
| 4/12/19 | 6 | 13 | 13 | 104 | 4/7/19 | 2 | 15 | 4/1/19 | 4 | 2 | 2019 |
| 4/13/19 | 7 | 14 | 14 | 105 | 4/7/19 | 2 | 15 | 4/1/19 | 4 | 2 | 2019 |
| 4/14/19 | 1 | 15 | 15 | 106 | 4/14/19 | 3 | 16 | 4/1/19 | 4 | 2 | 2019 |
| 4/15/19 | 2 | 16 | 16 | 107 | 4/14/19 | 3 | 16 | 4/1/19 | 4 | 2 | 2019 |
| 4/16/19 | 3 | 17 | 17 | 108 | 4/14/19 | 3 | 16 | 4/1/19 | 4 | 2 | 2019 |
| 4/17/19 | 4 | 18 | 18 | 109 | 4/14/19 | 3 | 16 | 4/1/19 | 4 | 2 | 2019 |
| 4/18/19 | 5 | 19 | 19 | 110 | 4/14/19 | 3 | 16 | 4/1/19 | 4 | 2 | 2019 |
| 4/19/19 | 6 | 20 | 20 | 111 | 4/14/19 | 3 | 16 | 4/1/19 | 4 | 2 | 2019 |
| 4/20/19 | 7 | 21 | 21 | 112 | 4/14/19 | 3 | 16 | 4/1/19 | 4 | 2 | 2019 |
| 4/21/19 | 1 | 22 | 22 | 113 | 4/21/19 | 4 | 17 | 4/1/19 | 4 | 2 | 2019 |
| 4/22/19 | 2 | 23 | 23 | 114 | 4/21/19 | 4 | 17 | 4/1/19 | 4 | 2 | 2019 |
| 4/23/19 | 3 | 24 | 24 | 115 | 4/21/19 | 4 | 17 | 4/1/19 | 4 | 2 | 2019 |
| 4/24/19 | 4 | 25 | 25 | 116 | 4/21/19 | 4 | 17 | 4/1/19 | 4 | 2 | 2019 |
| 4/25/19 | 5 | 26 | 26 | 117 | 4/21/19 | 4 | 17 | 4/1/19 | 4 | 2 | 2019 |
| 4/26/19 | 6 | 27 | 27 | 118 | 4/21/19 | 4 | 17 | 4/1/19 | 4 | 2 | 2019 |
| 4/27/19 | 7 | 28 | 28 | 119 | 4/21/19 | 4 | 17 | 4/1/19 | 4 | 2 | 2019 |
我正在尝试创建一个识别表
使用day_of_yr字段，去年这一天的匹配日期是什么（例如：今天是19年4月11日，而去年的相应日期实际上是18年4月12日，因为{{ 1}}是103）？昨天也一样
哪些天对应于本周以及去年的这一周
什么日子对应于本月和去年的这个月
什么日期对应于去年第二季度的当前季度
最终输出看起来像
day_of_yr这将创建新的列，所以如果我想看看我们如何比较本周与去年的销售额，我可以进行过滤