This cheat sheet includes basic python required for data analysis excluding pandas, numpy & other libraries

👉 List comprehensions: List comprehension offers a shorter syntax when you want to create a new list based on the values of an existing list.

Example:
Based on a list of fruits, you want a new list, containing only the fruits with the letter "a" in the name.
Without list comprehension you will have to write a for statement with a conditional test inside:

fruits = ["apple", "banana", "cherry", "kiwi", "mango"]
newlist = []

for x in fruits:
  if "a" in x:
    newlist.append(x)

print(newlist)

With list comprehension you can do all that with only one line of code:

fruits = ["apple", "banana", "cherry", "kiwi", "mango"]

newlist = [x for x in fruits if "a" in x]

print(newlist)

Syntax:
newlist = [expression for item in iterable if condition == True]

The return value is a new list, leaving the old list unchanged.

The condition is like a filter that only accepts the items that valuate to True. The condition is optional and can be omitted.
The iterable can be any iterable object, like a list, tuple, set etc.
The expression is the current item in the iteration, but it is also the outcome, which you can manipulate before it ends up like a list item in the new list.

Python Lambda:
A lambda function is a small anonymous function.
A lambda function can take any number of arguments, but can only have one expression.

lambda arguments : expression

The expression is executed and the result is returned.

Use lambda functions when an anonymous function is required for a short period of time.

Example:

Add 10 to argument a, and return the result:

x = lambda a : a + 10
print(x(5))

Output will be 15

Python Generators
In Python, a generator is a function that returns an iterator that produces a sequence of values when iterated over.
Generators are useful when we want to produce a large sequence of values, but we don't want to store all of them in memory at once.

There is a lot of complexity in creating iteration in Python; we need to implement iter() and next() method to keep track of internal states.
It is a lengthy process to create iterators. That's why the generator plays an essential role in simplifying this process. If there is no value found in iteration, it raises StopIteration exception.

🔹 Statistics in Python

Python Variables: How to Define/Declare String Variable Types

What is a Variable in Python?
A Python variable is a reserved memory location to store values. In other words, a variable in a python program gives data to the computer for processing.

Python Variable Types
Every value in Python has a datatype. Different data types in Python are Numbers, List, Tuple, Strings, Dictionary, etc. Variables in Python can be declared by any name or even alphabets like a, aa, abc, etc.

How to Declare and use a Variable
Let see an example. We will define variable in Python and declare it as “a” and print it.

1 a=100
2 print (a)

Big Data Analytics_ A Hands-On Approach ( PDFDrive ).pdf