I have the following dataset with 21 columns - 19 variables and Month and Date as date type columns.
The aim is to analyze how correlation change over time calculating a daily correlation between variables summarized in one month. For example, see this "monthly correlation" over time. (X-axis as month type)
+------------+---------+-----+-----+--------+---------+-------------+
| Date | Month | AOV | ASP | Clicks | Traffic | Impressions |
+------------+---------+-----+-----+--------+---------+-------------+
| 2017-01-01 | 2017-01 | 50 | 6 | 700 | 10000 | 4500 |
+------------+---------+-----+-----+--------+---------+-------------+
| 2017-01-02 | 2017-01 | 55 | 7 | 800 | 20000 | 4600 |
+------------+---------+-----+-----+--------+---------+-------------+
| 2017-02 | 2017-02 | 58 | 8 | 700 | 4599 | 2300 |
+------------+---------+-----+-----+--------+---------+-------------+
At the moment I have the following code but I only can compare two variables at the same time
ddply(corr,"Month",summarise,corr=cor(AOV,ASP))
I get the table below
+---------+------------+
| Month | corr |
+---------+------------+
| 2017-1 | 0.4958738 |
+---------+------------+
| 2017-10 | 0.8527522 |
+---------+------------+
| 2017-11 | -0.2751771 |
+---------+------------+
| 2017-12 | NA |
+---------+------------+
| 2017-2 | 0.6596346 |
+---------+------------+
| 2017-3 | 0.6399969 |
+---------+------------+
| 2017-4 | 0.7926245 |
+---------+------------+
| 2017-5 | 0.6429613 |
+---------+------------+
| 2017-6 | 0.3824414 |
+---------+------------+
| 2017-7 | 0.9154873 |
+---------+------------+
| 2017-8 | 0.7235767 |
+---------+------------+
| 2017-9 | 0.8264006 |
+---------+------------+
I have been using combn to create the combinations set but I'm not quite sure how to use it with ddply. I get 171 combinations in pairs.
combn(corr,2,simplify = F)
