Python Pandas - 查找两个 DataFrame 之间的不常见行
要查找两个DataFrame之间的不常见行,请使用concat()方法。让我们首先使用别名导入所需的库-
import pandas as pd
创建具有两列的DataFrame1-
dataFrame1 = pd.DataFrame( { "Car": ['BMW', 'Lexus', 'Audi', 'Tesla', 'Bentley', 'Jaguar'], "Reg_Price": [1000, 1500, 1100, 800, 1100, 900] } )
创建具有两列的DataFrame2-
dataFrame2 = pd.DataFrame( { "Car": ['BMW', 'Lexus', 'Audi', 'Tesla', 'Bentley', 'Jaguar'], "Reg_Price": [1000, 1300, 1000, 800, 1100, 800] } )
在两个DataFrame之间查找不常见的行并连接结果-
print"\nUncommon rows between two DataFrames...\n",pd.concat([dataFrame1,dataFrame2]).drop_duplicates(keep=False)
示例
以下是代码-
import pandas as pd #创建DataFrame1 dataFrame1 = pd.DataFrame( { "Car": ['BMW', 'Lexus', 'Audi', 'Tesla', 'Bentley', 'Jaguar'], "Reg_Price": [1000, 1500, 1100, 800, 1100, 900] } ) print"DataFrame1 ...\n",dataFrame1 #创建DataFrame2 dataFrame2 = pd.DataFrame( { "Car": ['BMW', 'Lexus', 'Audi', 'Tesla', 'Bentley', 'Jaguar'], "Reg_Price": [1000, 1300, 1000, 800, 1100, 800] } ) print"\nDataFrame2 ...\n",dataFrame2 #在两个DataFrame之间找到不常见的行并连接结果 print"\nUncommon rows between two DataFrames...\n",pd.concat([dataFrame1,dataFrame2]).drop_duplicates(keep=False)输出结果
这将产生以下输出-
DataFrame1 ... Car Reg_Price 0 BMW 1000 1 Lexus 1500 2 Audi 1100 3 Tesla 800 4 Bentley 1100 5 Jaguar 900 DataFrame2 ... Car Reg_Price 0 BMW 1000 1 Lexus 1300 2 Audi 1000 3 Tesla 800 4 Bentley 1100 5 Jaguar 800 Uncommon rows between two DataFrames... Car Reg_Price 1 Lexus 1500 2 Audi 1100 5 Jaguar 900 1 Lexus 1300 2 Audi 1000 5 Jaguar 800