要计算列值的方差,请使用var()方法。首先,导入所需的 Pandas 库 -
import pandas as pd
创建一个包含两列的 DataFrame -
dataFrame1 = pd.DataFrame( { "Car": ['BMW', 'Lexus', 'Audi', 'Tesla', 'Bentley', 'Jaguar'], "Units": [100, 150, 110, 80, 110, 90] } )
使用var()函数查找“单位”列值的方差-
print"Variance of Units column from DataFrame1 = ",dataFrame1['Units'].var()
以同样的方式,我们计算了第二个DataFrame的方差。
以下是完整的代码 -
import pandas as pd # Create DataFrame1 dataFrame1 = pd.DataFrame( { "Car": ['BMW', 'Lexus', 'Audi', 'Tesla', 'Bentley', 'Jaguar'], "Units": [100, 150, 110, 80, 110, 90] } ) print"DataFrame1 ...\n",dataFrame1 # Finding Variance of "Units" column values print"Variance of Units column from DataFrame1 = ",dataFrame1['Units'].var() # Create DataFrame2 dataFrame2 = pd.DataFrame( { "Product": ['TV', 'PenDrive', 'HeadPhone', 'EarPhone', 'HDD', 'SSD'], "Price": [8000, 500, 3000, 1500, 3000, 4000] } ) print"\nDataFrame2 ...\n",dataFrame2 # Finding Variance of "Price" column values print"Variance of Price column from DataFrame2 = ",dataFrame2['Price'].var()输出结果
这将产生以下输出 -
DataFrame1 ... Car Units 0 BMW 100 1 Lexus 150 2 Audi 110 3 Tesla 80 4 Bentley 110 5 Jaguar 90 Variance of Units column from DataFrame1 = 586.666666667 DataFrame2 ... Price Product 0 8000 TV 1 500 PenDrive 2 3000 HeadPhone 3 1500 EarPhone 4 3000 HDD 5 4000 SSD Variance of Price column from DataFrame2 = 6766666.66667