我在使用FuzzyWuzzy库将所有结果存储到数据框列中时遇到了挑战(我猜测它可能需要循环?)我一直在挠头在这一整天,现在我想看看你们中是否有人可以帮我解决这个问题!会非常有帮助!
作为我尝试做的一个例子,这里有2个数据框表......
主表
+----+-----------------+
| ID | ITEM |
+----+-----------------+
| | |
| 1 | Pepperoni Pizza |
| | |
| 2 | Cheese Pizza |
| | |
| 3 | Chicken Salad |
| | |
| 4 | Plain Salad |
+----+-----------------+
查找表
+--------------+---+
| LOOKUP VALUE | - |
+--------------+---+
| | |
| Cheese | - |
| | |
| Salad | - |
+--------------+---+
本质上,我试图将查找表的值用于Master表中的整个值列表,并将结果存储在第三个表中。
以下是我希望最终输出看起来......
+--------------+----------------------------+-------------------+
| LOOKUP VALUE | MATCHED VALUES | MATCHED VALUE IDS |
+--------------+----------------------------+-------------------+
| | | |
| Cheese | Cheese Pizza | 2 |
| | | |
| Salad | Chicken Salad, Plain Salad | 3,4 |
+--------------+----------------------------+-------------------+
我知道模糊Wuzzy的基础知识,这里是我的开始:
from fuzzywuzzy import fuzz
from fuzzywuzzy import process
choices = ["Pepperoni Pizza","Cheese Pizza","Chicken Salad", "Plain Salad"]
process.extract("salad",choices,limit=2)
输出 = [(' Chicken Salad',90),(' Plain Salad',90)]
很好,但是如何系统地执行此操作,针对主表中的所有值运行所有查找值?
非常感谢您阅读我!
答案 0 :(得分:3)
在DataFrame中存储列表不是一个好主意,我建议将每个匹配存储在DataFrame中。这是代码:
from fuzzywuzzy import fuzz
from fuzzywuzzy import process
import pandas as pd
import io
master = pd.read_csv(io.StringIO("""ID,ITEM
1,Pepperoni Pizza
2,Cheese Pizza
3,Chicken Salad
4,Plain Salad"""))
lookups = ["Cheese", "Salad"]
choices = master.set_index("ID").ITEM.to_dict()
res = [(lookup,) + item for lookup in lookups for item in process.extract(lookup, choices,limit=2)]
df = pd.DataFrame(res, columns=["lookup", "matched", "score", "id"])
df
输出:
lookup matched score id
0 Cheese Cheese Pizza 90 2
1 Cheese Chicken Salad 45 3
2 Salad Chicken Salad 90 3
3 Salad Plain Salad 90 4
基本上,我从choices
创建一个master
dict进行匹配,然后循环lookups
并将结果存储为列表。并最终将列表转换为DataFrame。