Wrapping up

Intermediate Python for Finance

Kennedy Behrman

Data Engineer, Author, Founder

Chapter 1

  • Representing time

datetime

  • Mapping data

dict()

Intermediate Python for Finance

Chapter 2

  • Comparison operators

< <= > >=

  • Equality operators

== !=

  • Boolean operators

and or not

  • If statements
if a < b:
   print(a)
  • Loops
while a < b:
     a = a + 1
for a in c:
    print(a)
Intermediate Python for Finance

Chapter 3

  • Creating a DataFrame
DataFrame(data=data)
pd.read_csv('/data.csv')
  • Accessing data
stocks.loc['a', 'Values']
stocks.iloc[2:22, 12]
  • Aggregating, summarizing
stocks.mean()
stocks.median()
  • Extending, manipulating
pce['PCESV'] = pcesv
gdp.apply(np.sum, axis=1)
Intermediate Python for Finance

Chapter 4

  • Peeking
aapl.head()
aapl.tail()
aapl.describe()
  • Filtering
mask = prices.High > 216
prices.loc[mask]
  • Plotting
exxon.plot(x='Date', 
           y='High' )
Intermediate Python for Finance

Congratulations!

Intermediate Python for Finance

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