Probability & Sample Distribution Conditional Probabilities You’re testing for a disease and advertising that the test is 99% accurate: if you have the disease, you will test positive 99% of the time, if you don’t have the disease, you will test negative 99% of the time. Let’s say that 1% of all people have the […]
Author: Stefan
Python – Statistics – EDA
Exploratory Data Analysis Descriptive Statistics Working with categorical data Relationship between two variables Descriptive Statistics what it sound like help you describe the data with numerical calculations or plots many types – focus on most common ones : measures of centrality – measures of variability Measures of centrality Mean The mean is the average, which […]
SQL – Basic SQL on one table
SQL BASICs Order of SQL Operations FROM –> table selectopn WHERE –> row(s) selection GROUP BY –> rows grouping by column Aggregations on columns –> in SELECT or ORDER BY HAVING –> in case you have to select on an aggregated value WINDOW functions –> operations on a selection of rows SELECT –> column selection […]
Python – Object Oriented Programming – Design Inheritance & Properties
Best Practices Designing for Inheritance and Polymorphism Polymorphism Interface
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# Withdraw amount from each account in list_of_accounts def batch_withdraw(list_of_accounts, amount): for acct in list_of_accounts: acct.withdraw(amount) b, c, s = BankAccount(1000), CheckingAccount(2000), SavingsAccount(3000) batch_withdraw([b,c,s]) # uses bankaccount.withdraw, checking, Savings |
batch_withdraw() doesn’t need to check the object to know which withdraw() to call Liskov substitution principle Base class should be interchangeable with any of its subclasses without altering any properties of the program Wherever BankAccout woorks –> CheckingAccount should work as well Syntactically function […]
Python – Object Oriented Programming – Exceptions
Integration with Python Operator overloading : comparison Object equality
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class Customer: def __init__(self, name, balance): self.name, self.balance = name, balance cust1 = Customer("John Fisher", 2100) cust2 = Customer("John Fisher", 2100) cust1 == cust2 > False |
Variables are references
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class Customer: def __init__(self, name, balance, id): self.name, self.balance = name, balance self.id = id cust1 = Customer("John Fisher", 2100, 123) cust2 = Customer("John Fisher", 2100, 123) cust1 == cust2 > False print(cust1) <__main__.Customer at 0x16549e8e78> print(cust2) <__main__.Customer at 0x16549e7e51> |
Due to the fact how the objects and variables representing them are stored printing the value of the (customer) object –> prints the memory allocation chunk the value = reference to the memory chunk ))> so when comparing we are […]
Python – Object Oriented Programming – Class Inheritance
Inheritance and Polymorphism Instance and Class Data Core Principles of OOP Inheritance Extending functionality of existing code Polymorphism Creating an unified interface Encapsulation Bundling of data and Methods Instance-level data
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class Employee: def __init__(self, name, salary): self.name = name self.salary = salary emp1 = Employee("Theo Mill", 50000) emp2 = Employee("Martina Kosova", 65000) |
name , salary are instance attributes self binds to an instance Class-level data
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class MyClass: # Define a class attribute CLASS_ATTR_NAME = attr_value |
data shared among all instances of a class define class […]
Python – Object Oriented Programming – Classes and Objects
Object Oriented Programming – Intro What’s OOP ? Procedural vs Object Oriented Procedural programming : sequential coding OK for Data Analysis Object Oriented Coding as interaction for object Frameworks and tools usability Terminology Object = state + behaviour ==> a FIlou a dog has 4 legs and a tail, and can bark and fetch a […]
Python Basics – Boolean Operations
Boolean Operations Boolean logic consists of operations done between True and False values : and ( logical conjunction) or ( logical disjunction) not ( logical negation ) Object Evaluation Evaluates as False Constants : False and None Numeric zero : 0 and 0.0 Lengths of zero : “” and [] Evaluates as True everything else […]
Python Basics – Comparison Operators
Comparison Operators Equality : == , != Order: < , > , <= , >= Assignment Operator Assignment : =
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13 == 13 > True count = 13 print(count) > 13 |
Equality Comparisons datetimes numbers ( float / int ) dictionaries strings …
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# Comparing dictionaries d1 = {'high':56.78,'low':33.24,'closing':56.77} d2 = {'high':56.78,'low':33.24,'closing':56.77} print(d1 == d2) > True d1 = {'high':56.78,'low':33.24,'closing':56.77} d2 = {'high':56.78,'low':33.24,'closing':46.01} print(d1 == d2) > False |
Comparing different types
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# Comparing int vs float print(3 == 3.0) > True # comparing int vs string print(3 == '3') > False |
Not equal operator
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print(3 != 4) > True print( 3 != 3) > False |
Order operators Less than < Less than or equal <= Greater than > Greater than […]
Python Basics – Dictionary
Dictionaries Lists
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my_list = ['a','b','c','d'] # index 0 1 2 3 my_list[0] > 'a' my_list.index['c'] > 2 |
Intro
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Keys Values ---- ------ Firm Code FRD Process Date 10/14/2019 CUSIP 13246879 |
Representation of a dictionary = { ‘key-1’ : ‘value-1’ , ‘key-2’ : ‘value-2’ , ‘key-3’ : ‘value-3’ , ‘key-4’ : ‘value-4’ } Creation
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# Create an empty dict my_dict = {} my_dict > {} # native tickersymbols = {'AAPL':'Apple', 'F':'Ford', 'XON':'Exxon'} > {'AAPL': 'Apple', 'F': 'Ford', 'XON': 'Exxon'} # OR by lists tickersymbols = dict([['AAPL','Apple'],['F','Ford'],['XON','Exxon']]) > {'AAPL': 'Apple', 'F': 'Ford', 'XON': 'Exxon'} |
Handling a dictionary
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# Adding tickersymbols['TSLA'] = 'Tesla' tickersymbols > {'AAPL': 'Apple', 'F': 'Ford', 'XON': 'Exxon', 'TSLA': 'Tesla'} # Update tickersymbols['TSLA'] = 'Tesla_Inc' tickersymbols > {'AAPL': 'Apple', 'F': 'Ford', 'XON': 'Exxon', 'TSLA': 'Tesla_Inc'} # Deleting an entry del(tickersymbols['F']) tickersymbols > {'AAPL': 'Apple', 'XON': 'Exxon', 'TSLA': 'Tesla_Inc'} |
Accessing
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# Entry in dict tickersymbols['XON'] > 'Exxon' # No entry in dict tickersymbols['IBM'] > KeyError: 'IBM' # Second method tickersymbols.get('XON') > 'Exxon' tickersymbols.get('IBM') > (nothing) tickersymbols.get('IBM','Missing ticker') > 'Missing ticker' |
Examples
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from datetime import datetime, timedelta alphabet_hist = {datetime.datetime(2019, 7, 30, 0, 0): 1228, datetime.datetime(2019, 7, 31, 0, 0): 1218.2, datetime.datetime(2019, 8, 1, 0, 0): 1211.78, datetime.datetime(2019, 8, 2, 0, 0): 1196.32} closing_price_date = datetime.datetime(2019, 8, 2, 0, 0) # Closing price for day before day_before_closing_price_date = closing_price_date - timedelta(days=1) # Safely print closing price day before or None if it's missing print(alphabet_hist.get(day_before_closing_price_date)) > 1211.78 # Get day eight weeks in future future_closing_price_date = closing_price_date + timedelta(weeks=8) # Safely get value for the future date or the string 'Missing' print(alphabet_hist.get(future_closing_price_date, 'Missing')) > Missing # Print with key print(alphabet_hist) > {datetime.datetime(2019, 8, 2, 0, 0): 1196.32, datetime.datetime(2019, 8, 1, 0, 0): 1211.78, datetime.datetime(2019, 7, 31, 0, 0): 1218.2, datetime.datetime(2019, 7, 30, 0, 0): 1228} # Remove entry del(alphabet_hist[closing_price_date]) # Print with key deleted print(alphabet_hist) > {datetime.datetime(2019, 8, 1, 0, 0): 1211.78, datetime.datetime(2019, 7, 31, 0, 0): 1218.2, datetime.datetime(2019, 7, 30, 0, 0): 1228} |