# Dealing with delayed measurements in (Geo)Pandas

Yesterday, I learned about a cool use case in data-driven agriculture that requires dealing with delayed measurements. As Bert mentions, for example, potatoes end up in the machines and are counted a few seconds after they’re actually taken out of the ground:

Therefore, in order to accurately map yield, we need to take this temporal offset into account.

We need to make sure that time and location stay untouched, but need to shift the potato count value. To support this use case, I’ve implemented `apply_offset_seconds()` for trajectories in movingpandas:

```    def apply_offset_seconds(self, column, offset):
self.df[column] = self.df[column].shift(offset, freq='1s')
```

The following test illustrates its use: you can see how the value column is shifted by 120 second. Geometry and time remain unchanged but the value column is shifted accordingly. In this test, we look at the row with index 2 which we access using iloc[2]:

```    def test_offset_seconds(self):
df = pd.DataFrame([
{'geometry': Point(0, 0), 't': datetime(2018, 1, 1, 12, 0, 0), 'value': 1},
{'geometry': Point(-6, 10), 't': datetime(2018, 1, 1, 12, 1, 0), 'value': 2},
{'geometry': Point(6, 6), 't': datetime(2018, 1, 1, 12, 2, 0), 'value': 3},
{'geometry': Point(6, 12), 't': datetime(2018, 1, 1, 12, 3, 0), 'value':4},
{'geometry': Point(6, 18), 't': datetime(2018, 1, 1, 12, 4, 0), 'value':5}
]).set_index('t')
geo_df = GeoDataFrame(df, crs={'init': '31256'})
traj = Trajectory(1, geo_df)
traj.apply_offset_seconds('value', -120)
self.assertEqual(traj.df.iloc[2].value, 5)
self.assertEqual(traj.df.iloc[2].geometry, Point(6, 6))
```
2 comments
1. In GeoDataFarm (http://geodatafarm.com/) I’ve made a similar implementation in order to “move” the gps point from the tractors gps point to the row location :)

• That looks like an awesome plugin. Thanks for sharing Axel!