筛选数据

Python 金融进阶

Kennedy Behrman

Data Engineer, Author, Founder

数据介绍

prices.head()
Python 金融进阶

数据介绍

prices.head()
Date Symbol High
0 2020-04-03 AAPL 245.70
1 2020-04-02 AAPL 245.15
2 2020-04-01 AAPL 248.72
3 2020-03-31 AAPL 262.49
4 2020-03-30 AAPL 255.52
Python 金融进阶

数据介绍

prices.describe()
Python 金融进阶

数据介绍

prices.describe()
High
count 378.000000
mean 881.593138
std 720.771922
min 227.490000
max 2185.950000
Python 金融进阶

数据介绍

prices.describe(include='object')
Symbol
count 378
unique 3
top AMZN
freq 126
Python 金融进阶

比较运算符

< <= > >= == !=

Python 金融进阶

列比较

prices.High > 2160
Python 金融进阶

列比较

prices.High > 2160
0      False
1      False
2      False
3      False
4      False
       ...  
374    False
375    False
376    False
377    False
Python 金融进阶

列比较

prices.Symbol == 'AAPL'
Python 金融进阶

列比较

prices.Symbol == 'AAPL'
0       True
1       True
2       True
3       True
4       True
       ...  
374    False
375    False
376    False
377    False
Python 金融进阶

按股票代码筛选

mask_symbol = prices.Symbol == 'AAPL'
aapl = prices.loc[mask_symbol]
Python 金融进阶

按股票代码筛选

mask_symbol = prices.Symbol == 'AAPL'
aapl = prices.loc[mask_symbol]
aapl.describe(include='object')
Symbol
count 126
unique 1
top AAPL
freq 126
Python 金融进阶

按价格筛选

mask_high = prices.High > 2160
big_price = prices.loc[mask_high]
Python 金融进阶

按价格筛选

big_price.describe()
High
count 6.000000
mean 2177.406567
std 7.999334
min 2166.070000
max 2185.95000
Python 金融进阶

Pandas 布尔运算符

  • &
  • |
  • ~
Python 金融进阶

组合条件

mask_prices = prices['Symbol'] != 'AMZN'
mask_date = historical_highs['Date'] > datetime(2020, 4, 1)
mask_amzn = mask_prices & mask_date
prices.loc[mask_amzn]
Python 金融进阶

组合条件

Date Symbol High
0 2020-04-03 AAPL 245.7000
1 2020-04-02 AAPL 245.1500
252 2020-04-03 TSLA 515.4900
253 2020-04-02 TSLA 494.2599
Python 金融进阶

Vamos praticar!

Python 金融进阶

Preparing Video For Download...