如何在Pandas中基于搜索子字符串创建规则集以将值分配给特定列？ [英] How can i create a ruleset to assign values to specific columns, based on searching substrings, in Pandas?

问题描述

我是Python（和Pandas库）的新手，需要在其中重新创建一些SQL代码。

I am a complete newbie to Python (and Pandas library) and need to recreate some SQL code in it.

我的任务非常简单，我有几列，我需要搜索它们的特定字符串，如果它们存在，则将值放在类别​​列中。

My task is quite simple of the face of it, I have a few columns, and i need to search them for specific strings, and if they exist then a value is placed in category columns.

例如

import pandas as pd

phone_ds= [('IPHONE_3UK_CONTRACT', 968), ('IPHONE_O2_SIMONLY', 155), ('ANDROID_3UK_PAYG', 77), , ('ANDROID_VODAF_CONTRACT', 973)]

a = pd.DataFrame(data=phone_ds, columns=['Names', 'qty'])

def f(a):
    if a['Names'].str.contains('3UK'):
        company = 'Three'
    if a['Names'].str.contains('iPhone'):
        OS = 'iOS'
.
.
.
etc

是否有比列出if语句更好（更有效）的方法？

Is there a better (more efficient) way than listing if statements?

我如何将结果添加到新列中？

How would i go about adding the results into new columns?

谢谢

推荐答案

找到了一种方法，但不确定它是否最有效。如果它遵循我上面发布的相同逻辑，如果它将创建一个带有规则的函数。规则将在预定义的搜索词列表中查找，然后为规则创建一个新列。

Found a way to do this, but not sure if it is most efficient. If would follow the same logic as i posted above, if that it would create a function with rules. The rules would look in a list of pre-defined search words, then create a new column for the rules.

每列都需要自己的功能，所以要添加3电话，承运人，合同类型的列，我创建了3个功能。

Each column would require its own function, so to add 3 columns for Phone, Carrier, Contract Type, i created 3 functions.

如下所示：

android_phones = ['samsung','xperia','google']

iphone= ['iphone','apple']


def OS_rules(raw_Df):
    val=''  

    if any(word in raw_Df['Names'].lower() for word in android_phones):
        val='android'
    elif any(word in raw_Df['Names'].lower() for word in iphone):
        val='iPhone'        
    else: val = 'Handset' 

    return val


df.loc[:,'OS_Type']=df.apply(OS_rules,axis=1)

这篇关于如何在Pandas中基于搜索子字符串创建规则集以将值分配给特定列？的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！