有条件地对 pandas 数据框执行计算 [英] Conditionally perform calculation on pandas dataframe

问题描述

time_period    total_cost    total_revenue
7days          150           250
14days         350           600
30days         900           750
7days          180           400
14days         430           620

鉴于此数据，我想将total_cost和total_revenue列转换为给定时间段内的平均值.我认为这会起作用:

Given this data, I want to convert the total_cost and total_revenue columns into averages for their given time period. I thought this would work:

df[['total_cost','total_revenue']][df.time_period]=="7days"]=df[['total_cost','total_revenue']][df.time_period]=="7days"]/7

但是它返回的数据帧保持不变.

But it returns the dataframe unchanged.

推荐答案

我相信您正在对数据框的副本进行操作.我认为您应该使用apply:

I believe that you are operating on copies of the dataframe. I think you should use apply:

from StringIO import StringIO
import pandas
datastring = StringIO("""\
time_period    total_cost    total_revenue
7days          150           250
14days         350           600
30days         900           750
7days          180           400
14days         430           620
""")

data = pandas.read_table(datastring, sep='\s\s+')

data['total_cost_avg'] = data.apply(
    lambda row: row['total_cost'] / float(row['time_period'][:-4]), 
    axis=1
)

给我:

  time_period  total_cost  total_revenue  total_cost_avg
0       7days         150            250       21.428571
1      14days         350            600       25.000000
2      30days         900            750       30.000000
3       7days         180            400       25.714286
4      14days         430            620       30.714286

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