https://www.anaconda.com/download/
download 3.6
https://conda.io/docs/user-guide/tasks/manage-environments.html
conda env create -f environment.yml
activate pyfinance
jupyter notebook
http://localhost:8888/?token=8353cd76ab1525e6aab4b0cf408cac74bf56a05589c68e71
Shift + enter : run
Shift + Tab : doc
define x='12'
x. +tab see all method
name="greg"
print("hi, {}".format(name))
number=12
print("hi, {}, no {}".format(name,number))
print("hi, {x}, {y}".format(y=x,x=no))
#nested list
nested =[1,2,["a","b"]]
#dictionary
d={'key':10, 'key2':'2nd'}
d['key2']
#tuple (can't change items)
t=(1,2,3)
#set
set([1,1])
import math
(1==1) and not (1==2)
# if and else has to on the same column, elif
if 1==2:
print('hi')
elif 2==2:
print('2')
else:
print('3')
#for
seq=[1,2,3,4,5]
for jelly in seq:
print(jelly)
#while
i=1
while(i<5):
print('i={}'.format(i))
i=i+1
#range
range(5)
for i in range(0,20,2):
print(i)
#function
def mF():
print("hi")
def mF(p):
print(p)
def mF(p='default'):
print(p)
def mF(p='default'):
return(p)
#lambda
lambda var:var*2
seq=[1,2,3]
list(map(lambda var:var*2,seq))
def is_even(num):
return num%2 ==0
list(filter(is_even,seq))
list(filter(lambda num:num%2==0,seq))
#method
st.lower
st.upper
tweet=" go sp #cool"
tweet,split()
tweet.split('#')[1]
mylist=[1,2,3,4]
mylist.pop()
mylist.pop(1)
2 in mylist
Exercise
prince ** 0.5
import math
math.sqrt(price)
#task 2
stock_index[2:]
task#3
print("the {} is at {}".format(stock_index,price))
task#4
stock_info.keys()
stock_info['sp500']['yesterday']
stock_info['info'][1][2]
task#5
def source_finder(p):
return p.split("--")[-1]
def price_finder(p):
return 'price' in p.lower()
task#6
def count_price(s):
count = 0
for word in s.lower().split():
if 'price' in word:
count = count + 1
return count
def count_price(s)
return s.lower().count('price')
task#7
def avg_price(s):
return sum(s)/len(s)
