Fisher's exact test is designed for tables when sample sizes are small or expected counts are low.
It keeps the row and column totals fixed, then compares the observed table to all equally margined tables that are at least as rare.
If the p-value is less than or equal to your chosen significance level , the data provide evidence against the null hypothesis of no association.
A large p-value does not prove independence. It only means the observed table is not unusual enough, under the null model, to reject it.
Estimate Cramer's V from observed category pairs, inspect the contingency heatmap, and interpret the association strength on the same screen.
Easily perform a Chi-Square Test for Independence online.
Run an exact binomial test, compare observed and hypothesized proportions, and inspect the tail probability on the distribution.