Anaconda

Anaconda is a free and open-source (you can view the source code) package of the Python and R programming languages for scientific computing. It is the starting point for data analysts + scientists around the world.

If you’re just starting out on your data journey, we highly recommend starting with Anaconda.

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Abs (Absolute Value)

Abs stands for “absolute value.” This means the distance a number or vector is away from the origin or 0. The result is always positive.

Ex: abs(4) = 4, abs(-3) = 3

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Append

Append is used when you need to add items to a list in python. This is a very common operation, not just in Python, but also in every other programming language

my_list.append(new_item)

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Argument

Arguments are the information that is passed into a function. Arguments and the word ‘parameter’ can be used interchangeably.

def my_function(argument1, argument2):
  # Do soething

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Assert

Assert in real life means “to state or declare.” In Python, assert is used when debugging code. You present a statement to assert, and if it is true, then your code will pass. If not, then a AssertionError will be raised.

x = "DataIndy"

# If the condition you pass returns True, then nothing happens:
assert x == "DataIndy"

# If the condition you pass condition returns False
# AssertionError is raised:
assert x == "Lake Tahoe Trees"

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Assigning A Variable

Assigning a variable means to either 1) create a variable and give it a value or 2) update a variables value. Either way, you’re setting the value of a variable.

In python this is done via a single equals (“=”) sign.

# Assign the value 3 to variable x
x = 3

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Block

In Python, a block refers to a “block of code.” This is a piece of code that is generally part of a function, class, or loop.

An easy way to tell which blocks of code exist are through the code indents. Lines that are on the same indent (and not interrupted by other lines not on the same indent) are part of the same code block.

for i in range(5):
  print (i) # This is a single line and code block

def my_func():
  print (i)
  print (y)
# Above we have a code block with two lines

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Callable

Simply, a ‘callable’ is something that can be called. This is either a class with a __call__ method, or else a function. Most commonly you’ll be able to tell which items are callables by looking at the open/closed parentheses “()”

It is also a python keyword callable(your_item) will return True if your_item is able to be called

my_func() # Callable

class Counter:
    def __init__(self, value = 0):
        self.n = 0

    def __call__(self): # Makes a class callable
        self.n += 1
        return self.n

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Class

Python is an Object Oriented Programing (OOP) Language. This means that a large amount of code is done using classes. Classes are uses to keep related items together.

Say you had 5 students, and they each had 5 properties (age, grade, hometown, test score 1, test score 2). The class-less way to do this would be by creating 25 variables (5 students * 5 properties).

However with classes, you’re able to create a “Student Class” which has 5 properties. Think of this as a template that is able to hold information.

class Student:
    def __init__(self, age, grade, hometown, test1, test2):
        self.age = age
        self.grade = grade
        self.hometown = hometown
        self.test1 = test1
        self.test2 = test2

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Conditional

Python is able to check a condition and change the behavior of a program depending on certain outcomes.

For example, if you wanted to create a program that printed “mow the lawn” IF it was sunny, then you would be running that code based off of a condition.

The main conditional in python is the if...else statement.

if is_sunny: # Conditional
  print ("Mow the lawn") # Run if True
else:
  print ("Wait till the sun comes out") # Run if False

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Continue

The python keyword continue will skip to the next item in your loop. This is used when working with for and while loops.

For example, if you wanted to print the numbers 1 through 5, but skip 3, then you could execute continue if the number is three.

for i in range(5):
  if i == 3:
    continue
  else:
    print (i)

Continue is cousins with break and pass

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Def

defis the command that starts a function or method in python. It is short for define.

def my_function():
  print ("This is my function")

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Dictionary

A dictionary is a type of data in python. Its identifying characteristic is the key:value data structure and it’s curly brackets.

Dictionaries are especially useful when you want to quickly look up an item, and return another. Similar to a vlookup in Excel

my_dict = {
    'key1' : 'value1',
    'key2' : 'value2',
    'key3' : 'value3',
}

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Double Underscore (Dunder)

Dunders or Double Unders (Underscores) or Magic Methods are special methods within python. They are denoted by the preceeding and trailing double underscores “__”

Common examples include __init__, __len__, __name__. They are mainly used within classes.

if __name__ = '__main__':
  my_program()

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Exploratory Data Analysis (EDA)

EDA is the process of getting intimate with your data. In all seriousness, it’s the act of getting to know your data from a foundational level.

How many rows are there? Columns? What are the value distributions like? How many unqiue values are there?

EDA is as much of an art as it is a science. You’ll find out paths you’d like to explore later on!

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Exception

Python throws errors. This means it will return an error if it doesn’t understand something. Exceptions are expected errors.

These are not the worse thing in the world because you can account for them without breaking your program. In order to do this, you’ll need to do exception handling or simply, making sure you account for errors.

To do exception handling, you need to use the try…except statements.

try:
	x = int(input("Please enter a number: "))
	break
except ValueError:
	print("Oops!  That was no valid number.  Try again...")

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Float

Python has many datatypes. The float datatype represents a number with decimal points.

The close, more well-rounded, sister of the float is the int. You won’t think about floats too often…until they cause you data type errors and you’ll need to debug.

x = 5.6
print (type(x))
>>> <class 'float'>

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For Loop

Python’s For Loop will iterate through an iterable and process each item. The command reads almost like a regular sentence.

“For each item in the whole. Do something with each item”

for name in ["Bob", "Sally", "Frank"]:
  print (name)

>>> "Bob"
>>> "Sally"
>>> "Frank"

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Generator

Generators are a special type of memory efficient function. They are especially useful when working with large data sets. They are an advanced Python topic, so use at your own caution!

# Generator function for an infinite sequence
def my_generator():
    x = 0
    while True:
        yield x
        x += 1

next(g)
>>> 0
next(g)
>>> 1

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Immutable

Immutable means that your data object can not be edited after you create it. Common immutable objects are int, string, and tuples.

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Import

In order to get other packages and libraries in your script, you’ll need to import them. Import does what it sounds like, imports other things into your code. You can use a ‘nickname’ for you package if you specify an ‘as’ + name afterward.

import pandas as pd
pd.do_something()

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Indent

An indent in python is like an indent within general writing. You use an indent when you want to group code together. For example, everything below a for loop that is indented once will be executed with the loop.

for i in range (5):
    print (i) # This line is indented once
    print ("This is my loop") # This line is also indented once
    print () # Finally, this line is also indented
print ("Ended Loop") # This line is back to 0 indents

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Int

In python, an int is a datatype, or a specific type of data. An int is a number without a decimal point. It’s close cousin the float is also a data type, but it has decimal point specification.

x = 5
print (type(x))
>>> <class 'int'>

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IPython

An old word for the program that provided data analysis notebooks (Ex: IPython Notebooks). This has since been more generally rebranded as “Juptyer”

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Iterable

An iterable is anything you’re able to ‘iterate’ through. Or simply, you can traverse the items in an object one by one. The most common example of an iterator in Python is the list.

# This list is an iterable
my_list = [1,2,3,4,6]
for i in my_list:
    print (i)
>>> 1
>>> 2
>>> 3
>>> 4
>>> 6

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Jupyter

Project Jupyter creates Data Analysis and Data Science notebooks. The project is an evolution of the previously (and still currently) very popular. Ipython Notebooks.

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