How find seasonals patterns that had more than x% rate of success in a time serie - R

data = data['1990::2019'] head(data) KO.Open KO.High KO.Low KO.Close KO.Volume KO.Adjusted 1990-01-02 1.045447 1.055597 1.038680 1.055597 12128000 1.055597 1990-01-03 1.053904 1.053904 1.036988 1.040371 12976000 1.040371 1990-01-04 1.040372 1.042064 1.021764 1.035297 7841600 1.035297 1990-01-05 1.035296 1.045446 1.025146 1.026838 8305600 1.026838 1990-01-08 1.026839 1.048830 1.023455 1.048830 10064000 1.048830 1990-01-09 1.048829 1.052213 1.035296 1.040371 7419200 1.040371 tail(data) KO.Open KO.High KO.Low KO.Close KO.Volume KO.Adjusted 2019-12-23 54.52184 54.75975 54.36323 54.43262 9300800 54.43262 2019-12-24 54.32358 54.52184 54.16497 54.23436 3359300 54.23436 2019-12-26 54.44254 54.54167 54.31367 54.54167 6228500 54.54167 2019-12-27 54.53175 54.96793 54.52184 54.86880 6895500 54.86880 2019-12-30 54.70028 54.90845 54.58132 54.78949 6431700 54.78949 2019-12-31 54.72010 54.89854 54.50202 54.86880 7982600 54.86880

As I mentioned in the title, I am looking for some R code that finds seasonal patterns in a time series with the option of setup or input the rate of success as a kind of filter. The minimum time= a week and max time infinite. This example is the time series from 1990 to 2019 and despite I can have the seasonal plot and some other information I am not even remotely of finding a code that returns what I am looking for (I am so newbie). I look to have some details as weel like the % return for each seasonal pattern found and the total average as well. But this maybe I manage to do it in the future. I really appreciate if somebody could help in some way with this matter. Thank you in advance