Capturing high collinearity in statsmodel : I was trying to solve a problem that asked me to assess whether the digital advertising campaign is successful in driving volume sales.

Because we only have limited impression data, I have filled 0 in impression for those that are nan. 

The data is on a weekly basis and it looks like this:
[![enter image description here][1]][1]

Then I did a scatterplot for impression and volume:
[![enter image description here][2]][2]

However when I try to regression using impression as x and volume as y in statsmodel it gives me collearity warning but I 'm only using impression as x variables. The code I'm using is the following:
[![enter image description here][3]][3]

And it gives me the following result:
[![enter image description here][4]][4]
[![enter image description here][5]][5]

Could anyone help me to figure out?? I'm really confused since I only have one x, there shouldn't be any collearity.

  [1]: https://i.stack.imgur.com/vEU1y.png
  [2]: https://i.stack.imgur.com/S3IE1.png
  [3]: https://i.stack.imgur.com/B9xiO.png
  [4]: https://i.stack.imgur.com/h3E1b.png
  [5]: https://i.stack.imgur.com/X5bKD.png