TIL: Add instruction for reading the generated geoparquet file.

README.md

@@ -5,6 +5,7 @@
 My Today I Learned snippets. Inspired by [simonw/til](https://github.com/simonw/til).
 
 <!-- index starts -->
+
 ## Python
 
 - [Install and setup `miniforge`](https://cheginit.github.io/til/python/miniforge.html) - 2021-02-20
@@ -45,4 +46,5 @@ My Today I Learned snippets. Inspired by [simonw/til](https://github.com/simonw/
 ## Github Actions
 
 - [Speed up Github Actions with `mamba`](https://cheginit.github.io/til/github_actions/mamba.html) - 2021-02-26
+
 <!-- index ends -->

python/buildings.md

@@ -95,3 +95,19 @@ def overture_buildings(
 bbox_example = (-74.02169, 40.696423, -73.891338, 40.831263)
 overture_buildings(bbox_example, "building", "nyc_buildings_subset.parquet")
 ```
+
+You can read the GeoParquet file with GeoPandas using the following code snippet:
+
+```python
+import geopandas as gpd
+import pandas as pd
+import shapely.wkb
+
+
+manhatten = pd.read_parquet("nyc_buildings_subset.parquet")
+manhatten = gpd.GeoDataFrame(
+    manhatten.drop(columns="geometry"),
+    geometry=shapely.wkb.loads(manhatten["geometry"]),
+    crs=4326,
+)
+```

python/frechet.md

@@ -16,15 +16,17 @@ FloatArray = npt.NDArray[np.float64]
 
 
 @njit("f8(f8[:, ::1], f8[:, ::1])", fastmath=True, parallel=True)
-def frechet_distance(true_coords: FloatArray, pred_coords: FloatArray)-> float:
+def frechet_distance(true_coords: FloatArray, pred_coords: FloatArray) -> float:
     """Compute the discrete Fréchet distance between two lines"""
     n, m = len(true_coords), len(pred_coords)
     # Compute pairwise euclidean distance
     p = 2
     dist = np.zeros((n, m))
     for i in prange(n):
         for j in prange(m):
-            dist[i, j] = np.sum(np.abs(true_coords[i] - pred_coords[j]) ** p) ** (1.0 / p)
+            dist[i, j] = np.sum(np.abs(true_coords[i] - pred_coords[j]) ** p) ** (
+                1.0 / p
+            )
 
     cost = np.full((n, m), np.inf)
     cost[0, 0] = dist[0, 0]
@@ -34,6 +36,8 @@ def frechet_distance(true_coords: FloatArray, pred_coords: FloatArray)-> float:
         cost[0, j] = max(cost[0, j - 1], dist[0, j])
     for i in range(1, n):
         for j in range(1, m):
-            cost[i, j] = max(min(cost[i - 1, j], cost[i, j - 1], cost[i - 1, j - 1]), dist[i, j])
+            cost[i, j] = max(
+                min(cost[i - 1, j], cost[i, j - 1], cost[i - 1, j - 1]), dist[i, j]
+            )
     return cost[-1, -1]
 ```