Statement of Completion#72f5af10
LI WEISHENG has successfully completed this project.
Intro to Pandas for Data Analysis
easy
Series Practice with S&P Companies' Market Cap
Resolution
Activities
Project.ipynb
Take a look at the raw data:¶
Company stock symbols
In [27]:
!head sp500-symbols.csv
Name,Symbol 3M Company,MMM A.O. Smith Corp,AOS Abbott Laboratories,ABT AbbVie Inc.,ABBV Accenture plc,ACN Activision Blizzard,ATVI Acuity Brands Inc,AYI Adobe Systems Inc,ADBE Advance Auto Parts,AAP
Market cap raw data:
In [16]:
!head sp500-marketcap.csv
Name,Market Cap 3M Company,138721055226 A.O. Smith Corp,10783419933 Abbott Laboratories,102121042306 AbbVie Inc.,181386347059 Accenture plc,98765855553 Activision Blizzard,52518668144 Acuity Brands Inc,6242377704 Adobe Systems Inc,94550214268 Advance Auto Parts,8123611867
In [1]:
import pandas as pd
In [21]:
market_cap = pd.read_csv("sp500-marketcap.csv", index_col="Symbol")['Market Cap']
market_cap.head()
Out[21]:
Symbol MMM 138721055226 AOS 10783419933 ABT 102121042306 ABBV 181386347059 ACN 98765855553 Name: Market Cap, dtype: int64
In [24]:
What's the name of the series contained in the market_cap variable?
Out[24]:
Name 3M Company MMM A.O. Smith Corp AOS Abbott Laboratories ABT AbbVie Inc. ABBV Accenture plc ACN Name: Symbol, dtype: object
Basic Series Attributes¶
1. Name of the market_cap Series¶
In [6]:
import pandas as pd
df = pd.read_csv('sp500-marketcap.csv')
df.columns
market_cap = pd.read_csv('sp500-marketcap.csv', index_col='Symbol')['Market Cap']
market_cap.name
Out[6]:
'Market Cap'
2. Name of the symbols Series¶
In [9]:
import pandas as pd
df = pd.read_csv('sp500-symbols.csv')
df.columns
symbols = pd.read_csv('sp500-symbols.csv', index_col='Name')['Symbol']
symbols.name
Out[9]:
'Symbol'
3. What's the dtype of market_cap¶
In [12]:
import pandas as pd
df = pd.read_csv('sp500-marketcap.csv')
df['Market Cap'].dtype
Out[12]:
dtype('int64')
4. What's the dtype of symbols¶
In [15]:
import pandas as pd
df = pd.read_csv('sp500-marketcap.csv')
df['Symbol'].dtype
Out[15]:
dtype('O')
5. How many elements do the series have?¶
In [18]:
import pandas as pd
df = pd.read_csv('sp500-marketcap.csv')
df.columns
market_cap = pd.read_csv('sp500-marketcap.csv', index_col='Symbol')['Market Cap']
market_cap.shape
Out[18]:
(505,)
6. What's the minimum value for Market Cap?¶
In [21]:
import pandas as pd
#df = pd.read_csv('sp500-marketcap.csv')
#df.columns
market_cap = pd.read_csv('sp500-marketcap.csv', index_col='Symbol')['Market Cap']
market_cap.min()
Out[21]:
2626102121
7. What's the maximum value for Market Cap?¶
In [22]:
import pandas as pd
#df = pd.read_csv('sp500-marketcap.csv')
#df.columns
market_cap = pd.read_csv('sp500-marketcap.csv', index_col='Symbol')['Market Cap']
market_cap.max()
Out[22]:
809508034020
8. What's the average Market Cap?¶
In [23]:
import pandas as pd
#df = pd.read_csv('sp500-marketcap.csv')
#df.columns
market_cap = pd.read_csv('sp500-marketcap.csv', index_col='Symbol')['Market Cap']
market_cap.mean()
Out[23]:
49239436929.50495
9. What's the median Market Cap?¶
In [24]:
import pandas as pd
#df = pd.read_csv('sp500-marketcap.csv')
#df.columns
market_cap = pd.read_csv('sp500-marketcap.csv', index_col='Symbol')['Market Cap']
market_cap.median()
Out[24]:
21400952517.0
Selection and Indexing¶
In [50]:
market_cap.head()
Out[50]:
Symbol MMM 138721055226 AOS 10783419933 ABT 102121042306 ABBV 181386347059 ACN 98765855553 Name: Market Cap, dtype: int64
10. What's the symbol of Oracle Corp.?¶
In [1]:
import pandas as pd
df = pd.read_csv('sp500-symbols.csv')
df.columns
symbols = pd.read_csv('sp500-symbols.csv', index_col='Name')['Symbol']
symbols.loc['Oracle Corp.']
Out[1]:
'ORCL'
11. What's the Market Cap of Oracle Corp.?¶
In [4]:
import pandas as pd
market_cap = pd.read_csv('sp500-marketcap.csv', index_col='Symbol')['Market Cap']
market_cap.loc['ORCL']
Out[4]:
202302349740
12. What's the Market Cap of Wal-Mart Stores?¶
In [5]:
import pandas as pd
symbols = pd.read_csv('sp500-symbols.csv', index_col='Name')['Symbol']
market_cap = pd.read_csv('sp500-marketcap.csv',index_col='Symbol')['Market Cap']
market_cap.loc[symbols.loc['Wal-Mart Stores']]
Out[5]:
304680931618
13. What's the symbol of the 129th company?¶
In [13]:
import pandas as pd
symbols = pd.read_csv('sp500-symbols.csv', index_col='Name')['Symbol']
symbols.iloc[128]
Out[13]:
'STZ'
14. What's the Market Cap of the 88th company in symbols?¶
In [19]:
import pandas as pd
symbols = pd.read_csv('sp500-symbols.csv', index_col='Name')['Symbol']
c88th = symbols.iloc[87]
market_cap = pd.read_csv('sp500-marketcap.csv',index_col='Symbol')['Market Cap']
market_cap.loc[c88th]
Out[19]:
13467193376
15. Create a new series only with FAANG Stocks¶
In [ ]:
faang_market_cap = ...
In [6]:
import pandas as pd
#symbols = pd.read_csv('sp500-symbols.csv',index_col='Name')['Symbol']
#symbols[["Amazon.com Inc", "Apple Inc.", "Microsoft Corp.", "Alphabet Inc Class A", "Facebook, Inc.", "Netflix Inc.", ]]
market_cap = pd.read_csv('sp500-marketcap.csv',index_col='Symbol')['Market Cap']
faang_market_cap = market_cap[['AMZN','AAPL','MSFT','GOOGL','FB','NFLX']]
faang_market_cap = market_cap[symbols[["Amazon.com Inc", "Apple Inc.", "Microsoft Corp.", "Alphabet Inc Class A", "Facebook, Inc.", "Netflix Inc."]]]
16. Select the market cap of companies in position 1st, 100th, 200th, etc.¶
In [14]:
import pandas as pd
market_cap = pd.read_csv('sp500-marketcap.csv',index_col='Symbol')['Market Cap']
position_companies = market_cap.iloc[[0,99,199,299,399,499]]
position_companies
Out[14]:
Symbol MMM 138721055226 CTL 18237196861 FL 5819080328 MAT 5843402350 ROP 27247789759 XL 10753423590 Name: Market Cap, dtype: int64
Sorting Series¶
17. What's the 4th company sorted lexicographically by their symbol?¶
In [22]:
import pandas as pd
symbols = pd.read_csv('sp500-symbols.csv', index_col='Name')['Symbol']
symbols_sorted = symbols.sort_values(ascending = True)
symbols_sorted.index[3]
#symbols_sorted.iloc[3]
Out[22]:
'Apple Inc.'
18. What's the Market Cap of the 7th company (in descending order)?¶
In [29]:
import pandas as pd
market_cap = pd.read_csv('sp500-marketcap.csv',index_col='Symbol')['Market Cap']
position_companies = market_cap.sort_index(ascending = False)
position_companies.head(7)
Out[29]:
Symbol ZTS 35991109776 ZION 10670678640 ZBH 24454698119 YUM 27003303098 XYL 12915021000 XRX 7938833340 XRAY 13390513478 Name: Market Cap, dtype: int64
In [ ]:
