[英]How to calculate revenue by month between years in python?
The columns in the below dataset will represent:以下数据集中的列将代表:
A: Date contract opened; A: 合约开仓日期;
B: Date contract stops; B:合约停止日期;
C: Unique account ID against which contract associated (can have multiple contracts live against one ID) C:与合约关联的唯一账户 ID(可以有多个合约针对一个 ID 生效)
D: Monthly revenue for contract period - for simplicity, assume revenue generated from first month contract assumed up to month before the date the contract closes D:合同期间的每月收入——为简单起见,假设从第一个月合同产生的收入假设到合同结束前一个月
Start Date contract end date Unique Account Field MRR
1/2/2013 1/2/2015 50e55 195.00
1/2/2013 1/2/2014 4ee75 50.00
1/2/2013 1/2/2014 4f031 75.00
1/2/2013 1/2/2016 4c3b2 133.00
1/2/2013 1/2/2016 49ec8 132.00
1/3/2013 1/3/2014 49fc8 59.00
1/4/2013 1/4/2015 49wc8 87.00
12/27/2013 12/27/2014 50bf7 190.00
12/27/2013 12/27/2014 49cc8 179.00
12/27/2013 12/27/2014 49wc8 147.00
etc....
I would like to calculate the following:我想计算以下内容:
1.How much revenue was generated by month between Jan-2013 and Dec-2014? 1. 2013 年 1 月至 2014 年 12 月期间每月产生了多少收入?
2.How many active contracts (generated revenue in that month) were there by month between Jan-2013 and Dec-2014? 2. 2013 年 1 月至 2014 年 12 月期间,按月有多少活跃合约(当月产生的收入)?
3.How many active accounts (generated revenue from at least one contract) were there by month between Jan-2013 and Dec-2014? 3. 2013 年 1 月至 2014 年 12 月期间,每月有多少活跃账户(从至少一份合同产生的收入)?
I tried the below code: I was able to use sum() to get the revenues, but I'm not sure what to do beyond this.我尝试了下面的代码:我能够使用 sum() 来获得收入,但我不确定除此之外还能做什么。
from datetime import date
df['date'] = pd.to_datetime(df['Start Date'])
df.groupby(df['Start Date'].dt.strftime('%B'))['MRR'].sum().sort_values()
Result I got from the above code:我从上面的代码得到的结果:
Start Date
February 221744
January 241268
July 245811
August 247413
April 249702
March 251219
June 251494
May 259149
September 263395
October 293990
November 296590
December 311659
I need to calculate the above following.我需要计算以下内容。 How can I achieve this in python?
如何在 python 中实现这一点?
Maybe you want something like this?也许你想要这样的东西?
date_range = (df['date'] >= "2013-01-01") & (df['date'] <= "2014-12-31")
df[date_range].groupby(df['date'].dt.strftime('%B')).agg(
MRR=('MRR', 'sum'),
Contracts=('date', 'count'),
Accounts=('Unique Account Field', 'nunique')
)
Output:- Output:-
MRR Contracts Accounts
date
December 516.0 3 3
January 731.0 7 7
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