# Significance test for multiple Spearman Rank Correlations

I have data for a TV show that runs on multiple days. I know many viewers came from a certain channel. So on day 1 there might for example be 30 viewers coming from channel 1 and 20 viewers coming from channel 2. On day two 10 viewers come from channel 1 and 5 from channel 3 etc. (This is just an illustration, there are a lot more channels). I want to know if the rank of the incoming channels is stable. I therefore paired up the shows on consecutive days and ran a Spearman Rank Correlation. Using scipy I also get the p-values for those correlations.

I want to make a statement over the set of those shows. I do not want to look at one pair, but at all the pairs of shows. I would like to be able to say "We reject the null hypothesis that the rank correlation for consecutive days is 0 with a confidence level of X". So how do I do this for a set of p-values?

One idea I had was that I could make a summary statistic for the p-values. Say for example Y percent of the p-values are smaller than 0.05, or take the average p-value. But I don't know what the correct way to go about this is.