How to automate ANOVA in Python
I am not sure ANOVA is the best and easiest way to find correlation between these categorical features and your target. You may see this great post where they propose many other methods along with ANOVA. If you persist to use ANOVA test or Kruskal-Wallis H Test, you need to know how it works to give you that notion of correlation (variation of variance among groups of categoricals). It is nicely explained in that post:


  ANOVA estimates the variance of the continuous variable that can be
  explained through the categorical variable. One need to group the
  continuous variable using the categorical variable, measure the
  variance in each group and comparing it to the overall variance of the
  continuous variable. If the variance after grouping falls down
  significantly, it means that the categorical variable can explain most
  of the variance of the continuous variable and so the two variables
  likely have a strong association. If the variables have no
  correlation, then the variance in the groups is expected to be similar
  to the original variance.


Once you understand how it works, implementing it and automating it is not difficult. In fact scipy and statsmodels have ANOVA. Check this post out, where they demonstrate in details how to perform ANOVA test on an actual dataset and estimate the correlation between categorical variable and continuous target. It is just a matter of putting these pieces together and change a bit to make it work for your own dataframe.