Show ONLY correlation that exceeds a certain threshold and in which correlations are significant ( p-value less than 0.05 ) on heatmap

Question

I've seen post How can we show ONLY features that are correlated over a certain threshold in a heatmap?

that shows only correlations that exceed a certain threshold on a heatmap

with the following piece of code

components = list()
visited = set()
print(newdf.columns)
for col in newdf.columns:
    if col in visited:
        continue

    component = set([col, ])
    just_visited = [col, ]
    visited.add(col)
    while just_visited:
        c = just_visited.pop(0)
        for idx, val in corr[c].items():
            if abs(val) > 0.999 and idx not in visited:
                just_visited.append(idx)
                visited.add(idx)
                component.add(idx)
    components.append(component)

for component in components:
    plt.figure(figsize=(12,8))
    sns.heatmap(corr.loc[component, component], cmap="Reds")

My question is how do u include only features with correlations that exceed a certain threshold and in which their correlations are significant ( p-values less than 0.05 ) on a heatmap?