在数据框中将字符转换为数值 [英] Converting characters to numerical values in a dataframe

问题描述

我有一个称为"XLK"的df:

I have a df called 'XLK':

       Market Cap   PE  
AAN     3.25B      23.6 
AAPL    819.30B    18.44    
ACFN    6.18M      2.1  
ACIW    2.63B      103.15   

我只希望市值大于1亿，所以预期输出为:

I just want the market cap for values > 100 million, so expected output is:

       Market Cap   PE  
AAN     3.25B      23.6 
AAPL    819.30B    18.44    
ACIW    2.63B      103.15   

我尝试将字母转换为适当的0失败了:

I've tried converting the letters to the appropriate 0's with no success:

XLK['Market Cap'].replace('M','000000')
XLK.drop[XLK_quote['Market Cap'] < '100M'].index

推荐答案

将replace与regex=True结合使用，并使用模拟科学计数法的替换字符串.然后使用astype(float)或pd.to_numeric.

Use replace with regex=True and use replacement strings that emulate scientific notation. Then use astype(float) or pd.to_numeric.

df[df.Market_Cap.replace(dict(B='E9', M='E6'), regex=True).astype(float) >= 100E6]

     Market_Cap      PE
AAN       3.25B   23.60
AAPL    819.30B   18.44
ACIW      2.63B  103.15

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等价

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Equivalently

dct = dict(B='E9', M='E6')
num = pd.to_numeric(df.Market_Cap.replace(dct, regex=True), 'coerce')
df[num >= 100E6]

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