Question

我有两个csv文件，它们都包含两列。

第一个具有产品ID，第二个具有序列号。

我需要查找第一个csv中的所有序列号，并在第二个csv上查找匹配项。结果报告将在单独的列中显示匹配的序列号以及每个csv的相应产品ID 我试图修改下面的代码，没有运气。

你会怎么做？

import pandas as pd
    A=set(pd.read_csv("c1.csv", index_col=False, header=None)[0]) #reads the csv, takes only the first column and creates a set out of it.
    B=set(pd.read_csv("c2.csv", index_col=False, header=None)[0]) #same here
    print(A-B) #set A - set B gives back everything thats only in A.
    print(B-A) # same here, other way around.

Answer 1

我认为你需要merge：

A = pd.DataFrame({'product id':   [1455,5452,3775],
                    'serial number':[44,55,66]})

print (A)

B = pd.DataFrame({'product id':   [7000,2000,1000],
                    'serial number':[44,55,77]})

print (B)

print (pd.merge(A, B, on='serial number'))
   product id_x  serial number  product id_y
0          1455             44          7000
1          5452             55          2000

Answer 2

试试这个：

A = pd.read_csv("c1.csv", header=None, usecols=[0], names=['col']).drop_duplicates()
B = pd.read_csv("c2.csv", header=None, usecols=[0], names=['col']).drop_duplicates()
# A - B
pd.merge(A, B, on='col', how='left', indicator=True).query("_merge == 'left_only'")
# B - A
pd.merge(A, B, on='col', how='right', indicator=True).query("_merge == 'right_only'")

Answer 3

您可以将df转换为集合，在比较数据时忽略索引，然后使用set symmetric_difference

ds1 = set([ tuple(values) for values in df1.values.tolist()])
ds2 = set([ tuple(values) for values in df2.values.tolist()])

ds1.symmetric_difference(ds2)
print df1 ,'\n\n'
print df2,'\n\n'

print pd.DataFrame(list(ds1.difference(ds2))),'\n\n'
print pd.DataFrame(list(ds2.difference(ds1))),'\n\n'

df1

id  Name  score isEnrolled               Comment
0  111  Jack   2.17       True  He was late to class
1  112  Nick   1.11      False             Graduated
2  113   Zoe   4.12       True                   NaN

df2

    id  Name  score isEnrolled               Comment
0  111  Jack   2.17       True  He was late to class
1  112  Nick   1.21      False             Graduated
2  113   Zoe   4.12      False           On vacation

输出

     0     1     2      3          4
0  113   Zoe  4.12   True        NaN
1  112  Nick  1.11  False  Graduated 


     0     1     2      3            4
0  113   Zoe  4.12  False  On vacation
1  112  Nick  1.21  False    Graduated

Answer 4

first_one=pd.read_csv(file_path)
//same way for second_one
// if product_id is the first column then its location would be at '0'
len_=len(first_one)
i=0
while(len_!=0)
{
if(first_one[i]==second_one[i])
{
//it is a match do whatever you want with this matched data
i=i-1;
}
len_=len_-1;
}

比较两个csv文件与python pandas

4 个答案: