# Finding intersection of two rows in Pandas using an index

2 answers

Pandas indexes have an intersection method that you can use. If you have two series, `s1`

and `s2`

, then

```
s1.index.intersection(s2.index)
```

gives the index values ββthat are in `s1`

both `s2`

.

You can then use this index list to view the corresponding elements of the series. For example:

```
>>> ixs = s1.index.intersection(s2.index)
>>> s1[ixs]
# view of s1 with only the indexes also found in s2 appears here
```

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Both of my data are increasing, so I wrote a function to get the indices, then filtered the data based on their indices.

```
np.shape(data1) # (1330, 8)
np.shape(data2) # (2490, 9)
index_1, index_2 = overlap(data1, data2)
data1 = data1[index1]
data2 = data2[index2]
np.shape(data1) # (540, 8)
np.shape(data2) # (540, 9)
def overlap(data1, data2):
'''both data is assumed to be incrementing'''
mask1 = np.array([False] * len(data1))
mask2 = np.array([False] * len(data2))
idx_1 = 0
idx_2 = 0
while idx_1 < len(data1) and idx_2 < len(data2):
if data1[idx_1] < data2[idx_2]:
mask1[idx_1] = False
mask2[idx_2] = False
idx_1 += 1
elif data1[idx_1] > data2[idx_2]:
mask1[idx_1] = False
mask2[idx_2] = False
idx_2 += 1
else:
mask1[idx_1] = True
mask2[idx_2] = True
idx_1 += 1
idx_2 += 1
return mask1, mask2
```

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