Difference between map, applymap and apply methods in Pandas

Question

Can you tell me when to use these vectorization methods with basic examples?

I see that map is a Series method whereas the rest are

Answer 1

My understanding:

From the function point of view:

If the function has variables that need to compare within a column/ row, use apply.

e.g.: lambda x: x.max()-x.mean().

If the function is to be applied to each element:

1> If a column/row is located, use apply

2> If apply to entire dataframe, use applymap

majority = lambda x : x > 17
df2['legal_drinker'] = df2['age'].apply(majority)

def times10(x):
  if type(x) is int:
    x *= 10 
  return x
df2.applymap(times10)