toolbox.py

import os
import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

data = pd.read_csv('input/pokemon.csv')

#define function
def tuble_ex():
    """ return defined t tuble"""
    t = (1,2,3)
    return t
a,b,c = tuble_ex()
print(a,b,c)

#Scope
# guess print what
x = 2
def f():
    x = 3
    return x
print(x)      # x = 2 global scope
print(f())    # x = 3 local scope

# How can we learn what is built in scope
import builtins
#print(dir(builtins))


#Nested functions
#nested function
def square():
    """ return square of value """
    def add():
        """ add two local variable """
        x = 2
        y = 3
        z = x + y
        return z
    return add()**2
print(square())

#Default and Flexible Arguments
# default arguments
def f(a, b = 1, c = 2):
    y = a + b + c
    return y
print(f(5))
# what if we want to change default arguments
print(f(5,4,3))

# flexible arguments *args
def f(*args):
    for i in args:
        print(i)
f(1)
print("")
f(1,2,3,4)
# flexible arguments **kwargs that is dictionary
def f(**kwargs):
    """ print key and value of dictionary"""
    for key, value in kwargs.items():               # If you do not understand this part turn for loop part and look at dictionary in for loop
        print(key, " ", value)
f(country = 'spain', capital = 'madrid', population = 123456)

# lambda function
square = lambda x: x**2     # where x is name of argument
print(square(4))
tot = lambda x,y,z: x+y+z   # where x,y,z are names of arguments
print(tot(1,2,3))

#Anonymous functions
number_list = [1,2,3]
y = map(lambda x:x**2,number_list)
print(list(y))

# iteration example
name = "ronaldo"
it = iter(name)
print(next(it))    # print next iteration
print(*it)         # print remaining iteration

# zip example
list1 = [1,2,3,4]
list2 = [5,6,7,8]
z = zip(list1,list2)
print(z)
z_list = list(z)
print(z_list)

#un zip
un_zip = zip(*z_list)
un_list1,un_list2 = list(un_zip) # unzip returns tuble
print(un_list1)
print(un_list2)
print(type(un_list2))

# Example of list comprehension
num1 = [1,2,3]
num2 = [i + 1 for i in num1 ]
print(num2)

# Conditionals on iterable
num1 = [5,10,15]
num2 = [i**2 if i == 10 else i-5 if i < 7 else i+5 for i in num1]
print(num2)


# lets return pokemon csv and make one more list comprehension example
# lets classify pokemons whether they have high or low speed. Our threshold is average speed.
threshold = sum(data.Speed)/len(data.Speed)
data["speed_level"] = ["high" if i > threshold else "low" for i in data.Speed]
data.loc[:10,["speed_level","Speed"]] # we will learn loc more detailed later