Example #7Source File: test_pivot.py From vnpy_crypto with MIT License 6 votes def test_pivot_multi_functions(self): f = lambda func: pivot_table(self.data, values=['D', 'E'], index=['A', 'B'], columns='C', aggfunc=func) result = f([np.mean, np.std]) means = f(np...
Example 5:构造出一个以大分类为列,小分类为行的销量数据。 它的代码是这样的 Result = pd.pivot_table(Table, index = 'category_name', columns = 'commodity_code', aggfunc = np.sum, fill_value = 0) ''' Result: order_id commodity_code S1 S11 S2 S3 S5 S9 category_name 食品0 8 0 0 ...
# 文件模板# pivot_table_example.pyimportpandasaspd data={'日期':['2023-01-01','2023-01-01','2023-01-02','2023-01-02'],'类别':['A','B','A','B'],'值':[10,20,30,40]}df=pd.DataFrame(data)defgenerate_pivot(df):returndf.pivot_table(index='日期',columns='类别',values='...
We learned that thepivot_tablefunction in Pandas allows us to create pivot tables by specifying the data, values, index, columns, and aggregation function. We also saw an example of how to create a pivot table to summarize the sales and profit for each product and region combination. Pivot ...
This first example aggregates values by taking the sum. >>> table = pd.pivot_table(df, values='D', index=['A', 'B'], ... columns=['C'], aggfunc=np.sum) >>> table C large small A B bar one 4.0 5.0 two 7.0 6.0
pivot_table 和groupby 都用于聚合数据框。区别仅在于结果的形状。 Using pd.pivot_table(df, index=["a"], columns=["b"], values=["c"], aggfunc=np.sum) a table is created where a is on the row axis, b is on the column axis, and the values are the sum of c。 例子: df = pd....
数据透视表（Pivot Table）import pandas as pd# 假设df是从Excel读取的数据df = pd.read_excel('sales_data.xlsx')# 创建数据透视表pivot_table = pd.pivot_table(df, values='Sales', index=['Manager'], columns=['Product'], aggfunc=np.sum, fill_value=0)# 输出到新的Excel文件pivot_table.to...
titanic.pivot_table('survived', ['sex', age], 'class') we can do the same game with the columns; let’s add info on the fare paid usingpd.qcutto automatically compute quantiles: fare = pd.qcut(titanic['fare'], 2) titanic.pivot_table('survived', ['sex', age], [fare, 'class'...
机器学习的过程中很多时候需要用到类似透视表的功能。Pandas提供了pivot和pivot_table实现透视表功能。相对比而言,pivot_table更加强大,在实现透视表的时候可以进行聚类等操作.../pandas.pivot_table.html 官方给的几个例子: This first example aggregatesvaluesby takingthesum. Wecanalso fill missingvalues ...
Example of pandas.DataFrame.pivot_table() Method # Importing pandas packageimportpandasaspd# Creating a Dictionaryd={'A': ['Amit','Amit','Ashish','Ashish'],'B': ['Bablu','Bablu','Bobby','Bhanu'],'C': ['Chetan','Chirag','Chiranjeev','Chetna'] }# Creating a DataFramedf=pd.DataFr...