Question

根据公司的不同，我拥有具有30-35列和50-1500行数据的excel文件。有问题的列如下；使用了剩余退款。这三列由其他列的计算组成。

USED是GAL的每一行的总和，因此excel计算如下：以= W2开始，然后下一行是W2 + W3，然后是W3 + W4，依此类推

剩余已分配使用

退款是GAL * CREDIT

这样的事情是否可能，目前，我正在excel中进行所有计算，这很耗时，经过一番研究，我发现编写一些代码来自动化它会更容易。感谢任何帮助，即使只是一栏的计算

我一直在网上寻找一些想法，认为熊猫是最好的选择，但是如果有其他建议的话，我会敞开心

import pandas as pd
filename = home/itdept/Documents/BestWines.xlsx
df = pd.read_excel(filename)
df['Refund'] = df['QUANTITY IN GAL']*df['CBMA Credit']
df.head(5)
df.to_excel("path to save")

这是我在第一列中想到的：退款，我不确定如何/是否可以将所有其他列也合并到代码中

Answer 1

"""importing packages to be used in our code"""
import pandas as pd
from pandas import ExcelWriter
from pandas import ExcelFile


"""importing excel content to df DataFrame"""
df = pd.read_excel('sflowone.xlsx', sheetname='Sheet1')

""" we will use LIST for updating (USED)coloumn"""
newlist = []        # created empty list

x=int(0)            # created a variable which will take all values of "GAL"
for value in df["GAL"]: # FOR LOOP will run for every value in "GAL" and takes data in "value"
    x = value + x       # add all earliear entries of "GAL"
    newlist.append(x)   # here we append the new values of x inside empty list
df.drop("USED",axis=1,inplace= True)  # deleted the "USED" column if exist before updating.
df.insert(3,"USED",newlist)     # inserted updated "USED" column with newlist in index number "3" 


"""Updating (REMAIN) and  (REFUND)"""
df ["REMAIN"]= df["ASSIGNED"]- df["USED"]
df ["REFUND"]= df["GAL"]* df["CREDIT"]

""" Visualising first 5 entries"""
df.head(5)
""" saving to Excel sheet """
df.to_excel("sflowfinal.xlsx")


"""CODE IS TESTED AND RUNNING, for query please reply"""

Answer 2

考虑Series.cumsum的累计金额：

df['USED'] = df['GAL'].cumsum()

从那里，任何基本的算术运算（例如减法和乘法）都可以直接在列上运行：

# SUBTRACTION
df['REMAIN'] = df['ASSIGNED'] - df['USED']

# MULTIPLICATION
df['REFUND'] = df['QUANTITY IN GAL'] * df['CBMA Credit']

或它们的功能形式sub和mul（以及其他类似的运算符）：

# SUBTRACTION
df['REMAIN'] = df['ASSIGNED'].sub(df['USED'])

# MULTIPLICATION
df['REFUND'] = df['QUANTITY IN GAL'].mul(df['CBMA Credit'])

总而言之，请考虑assign作为一个简洁的陈述：

import pandas as pd

filename = "home/itdept/Documents/BestWines.xlsx"
df = (pd.read_excel(filename)
        .assign(USED = lambda x: x['GAL'].cumsum(),
                REMAIN = lambda x: x['ASSIGNED'].sub(x['USED']),
                REFUND = lambda x: x['QUANTITY IN GAL'].mul(x['CBMA Credit'])
               )
     )

df.head(5)
df.to_excel("path to save")

计算现有的新列

2 个答案: