選股並從 Yahoo! Finance 取得資料

在 Python 中匯入與管理財務資料

Stefan Jansen

Instructor

依條件選股

用清單資訊篩選特定股票
篩選條件：
- 交易所
- 產業或子產業
- IPO 年份
- 市值

取得最大公司的代號

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'

取得最大公司的代號

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'

取得最大科技公司的代號

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'

取得 2017 年 IPO 的最大科技公司資料

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']]

以雙軸視覺化收盤價與成交量

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

醜陋的圖表

一起來練習吧！

在 Python 中匯入與管理財務資料