What is the difference between list comprehension and lambda?

The difference between Lambdas and List Comprehension. List Comprehension is used to create lists, Lambdas are functions that can process like other functions and thus return values or list.

Can we use lambda in list comprehension?

The lambdas in the list comprehension are a closure over the scope of this comprehension. A lexical closure, so they refer to the i via reference, and not its value when they were evaluated!

Are list comprehensions slow?

List comprehensions are faster than for loops to create lists. But, this is because we are creating a list by appending new elements to it at each iteration. This is slow. Side note: It would even be worse if it was a Numpy Array and not a list.

Is pandas apply faster than list comprehension?

Using List comprehensions is way faster than a normal for loop. Reason which is given for this is that there is no need of append in list comprehensions, which is understandable.

What is the difference between list and list comprehension?

So what’s the difference between Generator Expressions and List Comprehensions? The generator yields one item at a time and generates item only when in demand. Whereas, in a list comprehension, Python reserves memory for the whole list. Thus we can say that the generator expressions are memory efficient than the lists.

Is apply Lambda faster than for loop Python?

apply is not faster in itself but it has advantages when used in combination with DataFrames. This depends on the content of the apply expression. If it can be executed in Cython space, apply is much faster (which is the case here). We can use apply with a Lambda function.

How do I speed up pandas apply function?

You can speed up the execution even faster by using another trick: making your pandas’ dataframes lighter by using more efficent data types. As we know that df only contains integers from 1 to 10, we can then reduce the data type from 64 bits to 16 bits.