如何使用来自另一个数据帧的部分匹配过滤数据帧

问题描述

我有两个数据帧，我想使用其中一个数据帧来过滤另一个数据帧，并创建一个新的数据帧。两个数据帧具有包含类似信息的列，但不是精确匹配。我一直在尝试使用 str.contains 但到目前为止我一直得到 TypeError：'Series'对象是可变的，因此他们不能哈希当我尝试。这里是我的数据框架和我试过的代码示例。

I have two dataframe and I want to use one of the dataframes to filter the other and make a new dataframe. The two dataframes have a column with similar information but it is not an exact match. I have been trying to use str.contains but so far I keep getting TypeError: 'Series' objects are mutable, thus they cannot be hashed when I try. Here is a sample of my dataframes and the code I have tried.

promoter = pd.read_csv('promoter_coordinate.csv')
print(promoter.head())

AssociatedGeneName            B      C    D E                                   F
            plexB_1  NC_004353.3  64381  - Drosophila melanogaster (Fruit fly)  region
               ci_1  NC_004353.3  76925  - Drosophila melanogaster (Fruit fly)  region
             RS3A_1  NC_004353.3  87829  - Drosophila melanogaster (Fruit fly)  region
              pan_1  NC_004353.3  89986  + Drosophila melanogaster (Fruit fly)  region
              pan_2  NC_004353.3  90281  + Drosophila melanogaster (Fruit fly)  region

data = pd.read_csv('FBgn with gene name.csv')
print(data.head())
Gene AssociatedGeneName   FBgn Number     timepoint
CG10002        fkh        FBgn0000659          2
CG10002        fkh        FBgn0000659          2
CG10002        fkh        FBgn0000659          2
CG10002        fkh        FBgn0000659          2
CG10006    CG10006        FBgn0036461          2

x = promoter[promoter['AssociatedGeneName'].str.contains(data['AssociatedGeneName'])]

两个列表的头没有匹配，但基本上理想的结果将是类似于以下，其中名为AssociatedGeneName的两列将被比较。

The heads of both list don't have a match but basically the ideal outcome would be something similar to the following, where the two columns that are named 'AssociatedGeneName' would be compared.

AssociatedGeneName            B      C    D  E                                    F
             fkh_1  NT_033777.2  24410805 -  Drosophila melanogaster (Fruit fly)  region

本质上我想要一个数据框架中的所有值在启动子部分匹配 data ['AssociatedGeneName']中的值如果有人可以指出正确的方向，我将不胜感激。我相对较新的编码，我一直在使用python和pandas，并宁愿继续使用python来解决这个问题。这是我不断得到的错误。

Essentially I want a dataframe with all of the values in promoter that have a partial match to the values in data['AssociatedGeneName'] If someone could point me the right direction I would be grateful. I am relatively new to coding, I have been using python and pandas and would prefer to keep using python to solve this problem. Here is the error I keep getting.

x = promoter[promoter['AssociatedGeneName'].str.contains(data['AssociatedGeneName'])]

Traceback (most recent call last):
  File "<pyshell#15>", line 1, in <module>
    x = promoter[promoter['AssociatedGeneName'].str.contains(data['Associated Gene Name'])]
  File "C:\Python34\lib\site-packages\pandas\core\strings.py", line 1226, in contains
na=na, regex=regex)
  File "C:\Python34\lib\site-packages\pandas\core\strings.py", line 203, in str_contains
regex = re.compile(pat, flags=flags)
  File "C:\Python34\lib\re.py", line 219, in compile
return _compile(pattern, flags)
  File "C:\Python34\lib\re.py", line 278, in _compile
return _cache[type(pattern), pattern, flags]
  File "C:\Python34\lib\site-packages\pandas\core\generic.py", line 663, in __hash__
    ' hashed'.format(self.__class__.__name__))
TypeError: 'Series' objects are mutable, thus they cannot be hashed




推荐答案

首先创建一个函数，检查启动符的值是否与 data 这将检查数据中的每个值

First create a function that checks if values from promoter has a partial match from data this will check for each value in data

def contain_partial(x , y = data.AssociatedGeneName):
        res = []
        for z in y:
            res.append(z in x)
        return res

这将是函数的结果

contains = promoter.AssociatedGeneName.apply(contain_partial)


$ b b

然后在结束检查如果至少一个值是真的然后返回true和过滤
启动

promoter[contains.apply(any)]

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