熊猫数据框如何根据日期移动行

编程问答 2022-08-16

问题描述

我正在尝试评估促销活动对客户的影响。目的是从提供促销的时间点评估收入。但是，促销是针对不同地点的不同客户提供的。如何将数据重新排列到Month 0，Month 1，Month 2，Month 3。 Month 0是客户首次获得促销的月份。

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解决方法

使用以下自我解释代码，您可以获得所需的输出：

# Create DataFrame
import pandas as pd
df = pd.DataFrame({"Account":[1,2,3,4,5,6],\
"May-18":[181,166,221,158,210,159],\
"Jun-18":[178,222,230,189,219,200],\
"Jul-18":[184,207,175,167,201,204],\
"Aug-18":[161,174,178,233,223,\
"Sep-18":[218,209,165,204,225],\
"Oct-18":[199,206,205,196,212,205],\
"Nov-18":[231,218,234,235],\
"Dec-18":[173,\
"Promotion Month":["Sep-18","Aug-18","Jul-18","May-18","Jun-18"]})
df = df.set_index("Account")
cols = ["May-18","Jun-18","Sep-18","Oct-18","Nov-18","Dec-18","Promotion Month"]
df = df[cols]

# Define function to select the four months after promotion
def selectMonths(row):
    cols = df.columns.to_list()
    colMonth0 = cols.index(row["Promotion Month"])
    colsOut = cols[colMonth0:colMonth0+4]
    out = pd.Series(row[colsOut].to_list())
    return out

# Apply the function and set the index and columns of output DataFrame
out = df.apply(selectMonths,axis=1)
out.index = df.index
out.columns=["Month 0","Month 1","Month 2","Month 3"]

那么您得到的输出是：

>>> out
         Month 0  Month 1  Month 2  Month 3
Account                                    
1            218      199      231      173
2            174      209      206      196
3            175      178      165      205
4            158      189      167      233
5            223      204      212      234
6            200      204      204      225
dataframepandaspandaspython-datetime