Select stocks and get data from Yahoo! Finance

Importing and Managing Financial Data in Python

Stefan Jansen

Instructor

Select stocks based on criteria

Use the listing information to select specific stocks
As criteria:
- Stock Exchange
- Sector or Industry
- IPO Year
- Market Capitalization

Get ticker for largest company

nyse = pd.read_excel('listings.xlsx',sheet_name='nyse', na_values='n/a')
nyse = nyse.sort_values('Market Capitalization', ascending=False)

nyse[['Stock Symbol', 'Company Name']].head(3)

     Stock Symbol             Company Name
1586          JNJ        Johnson & Johnson
1125          XOM  Exxon Mobil Corporation
1548          JPM    J P Morgan Chase & Co

largest_by_market_cap = nyse.iloc[0]  # 1st row

largest_by_market_cap['Stock Symbol'] # Select row label

'JNJ'

Get ticker for largest company

nyse = nyse.set_index('Stock Symbol') # Stock ticker as index
nyse.info()

Index: 3147 entries, JNJ to EAE
Data columns (total 6 columns):
 #   Column                 Non-Null Count  Dtype  
 --  ------                 --------------  -----  
 0   Company Name           3147 non-null   object 
 1   Last Sale              3079 non-null   float64
 2   Market Capitalization  3147 non-null   float64
...

nyse['Market Capitalization'].idxmax() # Index of max value

'JNJ'

Get ticker for largest tech company

nyse['Sector'].unique() # Unique values as numpy array

array(['Technology', 'Health Care', ...], dtype=object)

tech = nyse.loc[nyse.Sector == 'Technology']
tech['Company Name'].head(2)

Stock Symbol                        Company Name            
ORCL                          Oracle Corporation
TSM           Taiwan Semiconductor Manufacturing

nyse.loc[nyse.Sector=='Technology', 'Market Capitalization'].idxmax()

'ORCL'

Get data for largest tech company with 2017 IPO

ticker = nyse.loc[(nyse.Sector=='Technology') & (nyse['IPO Year']==2017), 
                 'Market Capitalization'].idxmax()

data = DataReader(ticker, 'yahoo') # Start: 2010/1/1
data = data.loc[:, ['Close', 'Volume']]

Visualize price and volume on two axes

import matplotlib.pyplot as plt
data.plot(title=ticker, secondary_y='Volume')
plt.tight_layout(); plt.show()

Let's practice!

Importing and Managing Financial Data in Python