使用 python 返回 excel 中两个不同文件中两列之间的差异

Question

我有两个 csv 文件，其中有一个名为 'Name' 的公共列。文件 2 将不断更新并在列中随机添加新值。我如何编写脚本来比较两列并找到差异，而不管新值在 file2 中的位置如何。

只有当新值在列的末尾而不是在列中随机出现时，其他解决方案才会发现差异。

我试过的代码（只输出列底部的新值，而不是随机出现在列中的时候）：

df1 = pd.read_csv('file1.csv')
df2 = pd.read_csv('file2.csv')

new_df = (df1[['Name']].merge(df2[['Name']],on='Name',how = 'outer',indicator = True)
                       .query("_merge != 'both'")
                       .drop('_merge',axis = 1))

new_df.to_csv('file4.csv')

文件 1:

Name     
gfd454
3v4fd
th678iy

文件 2:

Name     
gfd454
fght45
3v4fd
th678iy

输出应该是：

Name
fght45

Answer 1

使用左侧的文件 2 进行左连接。之后，提取不匹配的 NaN 行。

Answer 2

如果您只想检查一列，您可以通过比较两个列表来尝试：

list1=df1['Name'].tolist()
list2=df2['Name'].tolist()
s = set(list1)
diff = [x for x in list2 if x not in s]

Answer 3

# df1 original dataframe of File_1 data
df1 = pd.DataFrame({'Name':[ 'gfd454' , '3v4fd', 'th678iy']})

# df2 dataframe of changing File_2 data
df2 = pd.DataFrame({'Name':[ 'gfd454' , 'abcde', 'fght45', '3v4fd', 'abcde' ,'th678iy', 'abcde']})

# Assuming df1 comprises distinct elements and doesn't change, and that
# df2 contains all elements of df1 and more (the new updates) 
# df2 may have duplicates like 'abcde'

# Drop duplicates in df2, if df1 has duplicates also drop it first
# ``keep = first`` : Drop duplicates except for the first occurrence.
df2.drop_duplicates(keep='first', inplace=True)
print(df2)

# pandas.concat adds elements of df2 to df1, even if it already exists in df1
df_concat = pd.concat([df1,df2], join='outer', ignore_index = True)
print(df_concat)

# now drop the duplicates between df1, df2
df_diff = df_concat .drop_duplicates(keep=False)
print(df_diff)

现在，问题在于您必须确保 df1-df2 = {}，即 df1 是 df2

的子集

使用 python 返回 excel 中两个不同文件中两列之间的差异

Returning differences between two columns in two different files in excel using python

python

csv

concat

pandas

difference