将 Pandas DataFrame 与公共列合并
要将两个具有公共列的PandasDataFrame合并,请使用该merge()函数并将ON参数设置为列名。
首先,让我们使用别名导入pandas库-
import pandas as pd
让我们创造1日数据框-
dataFrame1 = pd.DataFrame( { "Car": ['BMW', 'Lexus', 'Audi', 'Mustang', 'Bentley', 'Jaguar'],"Units": [100, 150, 110, 80, 110, 90] } )
接下来,创建第二个DataFrame-
dataFrame2 = pd.DataFrame( { "Car": ['BMW', 'Lexus', 'Audi', 'Mustang', 'Mercedes', 'Jaguar'],"Reg_Price": [7000, 1500, 5000, 8000, 9000, 6000] } )
现在,将两个DataFrame与列“Car”合并-
mergedRes = pd.merge(dataFrame1, dataFrame2, on ='Car')
示例
以下是完整的代码-
import pandas as pd # Create DataFrame1 dataFrame1 = pd.DataFrame( { "Car": ['BMW', 'Lexus', 'Audi', 'Mustang', 'Bentley', 'Jaguar'],"Units": [100, 150, 110, 80, 110, 90] } ) print"DataFrame1 ...\n",dataFrame1 # Create DataFrame2 dataFrame2 = pd.DataFrame( { "Car": ['BMW', 'Lexus', 'Audi', 'Mustang', 'Mercedes', 'Jaguar'],"Reg_Price": [7000, 1500, 5000, 8000, 9000, 6000] } ) print"\nDataFrame2 ...\n",dataFrame2 # merge DataFrames with common column Car mergedRes = pd.merge(dataFrame1, dataFrame2, on ='Car') print"\nMerged data frame with common column...\n", mergedRes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 Mustang 80 4 Bentley 110 5 Jaguar 90 DataFrame2 ... Car Reg_Price 0 BMW 7000 1 Lexus 1500 2 Audi 5000 3 Mustang 8000 4 Mercedes 9000 5 Jaguar 6000 Merged data frame with common column... Car Units Reg_Price 0 BMW 100 7000 1 Lexus 150 1500 2 Audi 110 5000 3 Mustang 80 8000 4 Jaguar 90 6000