如何对 Pandas DataFrame 的值进行分组
为了GROUPBY值数,使用groupby(),size()和unstack()熊猫数据帧的方法。首先,创建一个包含3列的DataFrame-
dataFrame = pd.DataFrame({ 'Product Category': ['Computer', 'Mobile Phone', 'Electronics', 'Electronics', 'Computer', 'Mobile Phone'],'Product Name': ['Keyboard', 'Charger', 'SmartTV', 'Camera', 'Graphic Card', 'Earphone'],'Quantity': [10, 50, 10, 20, 25, 50]})
现在,groupby值使用groupby()方法计数。对于计数,请使用size()和unstack()。该unstack()出栏标签的一个新的水平-
dataFrame = dataFrame.groupby(['Product Category', 'Product Name', 'Quantity']).size().unstack(fill_value=0)
示例
以下是完整的代码-
import pandas as pd # create a dataframe with 3 columns dataFrame = pd.DataFrame({ 'Product Category': ['Computer', 'Mobile Phone', 'Electronics', 'Electronics', 'Computer', 'Mobile Phone'],'Product Name': ['Keyboard', 'Charger', 'SmartTV', 'Camera', 'Graphic Card', 'Earphone'],'Quantity': [10, 50, 10, 20, 25, 50]}) # dataframe print"Dataframe...\n",dataFrame # count and unstack dataFrame = dataFrame.groupby(['Product Category', 'Product Name', 'Quantity']).size().unstack(fill_value=0) print"\nResultant DataFrame...\n",dataFrame输出结果
这将产生以下输出-
Dataframe... Product Category Product Name Quantity 0 Computer Keyboard 10 1 Mobile Phone Charger 50 2 Electronics SmartTV 10 3 Electronics Camera 20 4 Computer Graphic Card 25 5 Mobile Phone Earphone 50 Resultant DataFrame... Quantity 10 20 25 50 Product Category Product Name Computer Graphic Card 0 0 1 0 Keyboard 1 0 0 0 Electronics Camera 0 1 0 0 SmartTV 1 0 0 0 Mobile Phone Charger 0 0 0 1 Earphone 0 0 0 1