如何在python中将pandas数据框的值放入for循环中? [英] How to put values of pandas dataframe into a for loop in python?

问题描述

这是Python API Connection程序的一部分

这是DataFrame示例

This is a part of a Python API Connection program

Here is the DataFrame Sample

      Region  Sector  Brand ID  Start Date
7188  US      41      40000     2006-03-06
7189  US      41      40345     2017-11-06
7190  US      41      40123     2019-01-12
7191  US      42      40145     2001-02-06
7192  US      42      40185     2013-03-16

以下是工作功能，它是API python程序的一部分，通常采用固定的参数值，即；区域，部门，品牌ID，开始日期，结束日期="05-04-2020"，计分=总计".(结束日期和计分是固定值，其余的都在不断变化).

Here is the working function as a part of API python program which usually takes a fixed parameter values i.e; Region, Sector, Brand ID, Start Date, End Date="05-04-2020", Scoring ="total".(End Date and Scoring are fixed values, rest of them are keep changing).

#This code is working if manually enter
#details of a Dataframe one by one which is inefficient.
#This code generates me a URL of a dataset using the parameters

querySingleBrandTimeline('db.csv', {'region':'us','sector':'41', 'brand_id':'40000', 'scoring':'total', 'start_date':'2006-03-06','end_date':'2020-03-31'})

我想要实现的是一个for循环，该循环从pandas DtaFrame中获取值并将其相应地放入函数参数中.

What I am trying to achieve is a for loop which takes values from the pandas DtaFrame and put it in the function parameters accordingly.

这是我尝试过的示例代码:

Here is the sample code i've tried:

for id in US['Sector']:
  for brandid in US['Brand ID']:
    querySingleBrandTimeline('db.csv', {'region':{}.format(US['Region']),'sector':{}.format(US['Category ID']), 'brand_id':{}.format(US['Brand ID']), 'scoring':'total'}, 'start_date':{}.format{US['Start Date']},'end_date':'2020-03-31'})

我不太确定如何动态地将DataFrame的值传递给函数

I'm quite not sure how to pass values of the DataFrame to the function dynamically

推荐答案

使用iterrows()按行迭代数据框.我相信您的数据框名称是美国.然后:

Iterate the dataframe by rows using iterrows(). I believe your dataframe name is US. Then:

for(index, row_data) in US.iterrows():
        querySingleBrandTimeline('db.csv', {'region':{}.format(row_data['Region']),'sector':{}.format(row_data['Category ID']), 'brand_id':{}.format(row_data['Brand ID']), 'scoring':'total'}, 'start_date':{}.format{row_data['Start Date']},'end_date':'2020-03-31'})

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