如何使用 Pandas 在Python中创建数据透视表？

数据透视表是一个统计表，它汇总了像大数据集这样的大量表。它是数据处理的一部分。数据透视表中的摘要可能包括平均值、中位数、总和或其他统计项。数据透视表最初与 MS Excel 相关联，但我们可以使用 Pandas 使用 dataframe.pivot() 方法在Python中创建数据透视表。

Syntax : dataframe.pivot(self, index=None, columns=None, values=None, aggfunc)

Parameters –
index: Column for making new frame’s index.
columns: Column for new frame’s columns.
values: Column(s) for populating new frame’s values.
aggfunc: function, list of functions, dict, default numpy.mean

示例 1：
让我们首先创建一个包含水果销售的数据框。

# importing pandas
import pandas as pd
  
# creating dataframe
df = pd.DataFrame({'Product' : ['Carrots', 'Broccoli', 'Banana', 'Banana',
                                'Beans', 'Orange', 'Broccoli', 'Banana'],
                   'Category' : ['Vegetable', 'Vegetable', 'Fruit', 'Fruit',
                                 'Vegetable', 'Fruit', 'Vegetable', 'Fruit'],
                   'Quantity' : [8, 5, 3, 4, 5, 9, 11, 8],
                   'Amount' : [270, 239, 617, 384, 626, 610, 62, 90]})
df

输出：

获取每个产品的总销售额

# creating pivot table of total sales
# product-wise aggfunc = 'sum' will 
# allow you to obtain the sum of sales
# each product
pivot = df.pivot_table(index =['Product'],
                       values =['Amount'],
                       aggfunc ='sum')
print(pivot)

输出：

获取每个类别的总销售额

# creating pivot table of total 
# sales category-wise aggfunc = 'sum'
# will allow you to obtain the sum of
# sales each product
pivot = df.pivot_table(index =['Category'], 
                       values =['Amount'], 
                       aggfunc ='sum')
print(pivot)

输出：

获取按类别和产品的总销售额

# creating pivot table of sales
# by product and category both
# aggfunc = 'sum' will allow you
# to obtain the sum of sales each
# product
pivot = df.pivot_table(index =['Product', 'Category'], 
                       values =['Amount'], aggfunc ='sum')
print (pivot)

输出 -

按类别获取平均、中位数、最低销售额

# creating pivot table of Mean, Median,
# Minimum sale by category aggfunc = {'median',
# 'mean', 'min'} will get median, mean and 
# minimum of sales respectively
pivot = df.pivot_table(index =['Category'], values =['Amount'], 
                       aggfunc ={'median', 'mean', 'min'})
print (pivot)

输出 -

按产品获取均值、中值、最低销售额

# creating pivot table of Mean, Median,
# Minimum sale by product aggfunc = {'median',
# 'mean', 'min'} will get median, mean and
# minimum of sales respectively
pivot = df.pivot_table(index =['Product'], values =['Amount'],
                       aggfunc ={'median', 'mean', 'min'})
print (pivot)

输出：