map() is a Python built in that lets you apply or "map" a function to each element in a list or iterable object. map() is one of the most useful Python built in functions for data analytics, since you will often be working with large sequence data types that need to be transformed in various ways.

Code used in the video:

# Map lets you apply a function to each element of a list

power_level_list = [1000, 4000, 16000, 150, 9001, 1500]

def greater_than_9000(x):
if x ＞ 9000:
return True
return False

mapped = map(greater_than_9000, power_level_list)

print(mapped)

# Print each mapping

for m in mapped:
print(m)

# Extract mapping into new list

mapped_list = [*map(greater_than_9000, power_level_list)]

mapped_list

# Use map with a lambda function

[*map(lambda x: x ＞ 9000, power_level_list)]

* Note: YouTube does not allow greater than or less than symbols in the text description, so the code above will not be exactly the same as the code shown in the video! I will use Unicode large ＜ and ＞ symbols in place of the standard sized ones. .

Videos on Pandas map() operations:

How To Use apply() In Pandas (Python)
https://www.youtube.com/watch?v=smPLY_5gVv4&ab_channel=DataDaft

How To Use applymap() In Pandas (Python)
https://www.youtube.com/watch?v=azF6O_mzaCI&ab_channel=DataDaft