Question

我有两个数据帧。我想看看另一个数据帧中是否存在特定的行（完整的）。来自df_subset的示例行：

id    category    value    date
1     A           10       01-01-15
3     C           10       03-01-15

另一个df_full：

id    category    value    date
1     A           10       01-01-15
2     B           10       02-01-15
3     C           10       03-01-15
4     D           16       04-01-15

有没有办法检查一个数据帧的行是否存在于另一个数据帧中？这样的事情（显然这不起作用）：df_subset in df_full，存在吗？

> True

Answer 1

我认为你可以merge使用内部联接（默认情况下）与DataFrame.equals进行比较，以便与df_subset进行比较：

print (pd.merge(df_subset,df).equals(df_subset))
True

Answer 2

您可以使用merge(..., indicator=True)方法：

In [14]: pd.merge(df1, df2, indicator=True, how='outer')
Out[14]:
   id category  value      date      _merge
0   1        A     10  01-01-15        both
1   3        C     10  03-01-15        both
2   2        B     10  02-01-15  right_only
3   4        D     16  04-01-15  right_only

Answer 3

使用numpy

(df_subset.values[:, None] == df_full.values).all(2).any(1).all()

True

<强> 定时

解释

# using [:, None] to extend into new dimension at
# take advantage of broadcasting
a1 = df_subset.values[:, None] == df_full.values

     # ━> third dimension ━>
     # ━━━━> axis=2 ━━━>
# 1st dim
---->[[[ True  True  True  True]   # │
       [False False  True False]   # │ second dimension
       [False False  True False]   # │ axis=1
       [False False False False]]  # ↓

 # axis=0
 ---->[[False False  True False]   # │ 
       [False False  True False]   # │ second dimension
       [ True  True  True  True]   # │ axis=1
       [False False False False]]] # ↓

# first row of subset with each row of full 
[[[ True  True  True  True]  <-- This one is true for all 
  [False False  True False]
  [False False  True False]
  [False False False False]]

# second row of subset with each row of full 
 [[False False  True False] 
  [False False  True False]
  [ True  True  True  True]  <-- This one is true for all
  [False False False False]]]

a2 = a1.all(2)

#   ┌─ first row of subset all equal
[[ True False False False]
 [False False  True False]]
#               └─ second row of subset all equal

a3 = a2.any(1)

#  ┌─ first row of subset matched at least one row of full
[ True  True]
#        └─ second row of subset matched at least one row of full

a3.all()

True

df_subset所有行都在df_full

检查另一个数据帧中是否存在多行

3 个答案: