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Merged
ianna merged 1 commit into from
Sep 16, 2026
Merged

docs: read the Chicago taxi dataset from an R2 mirror #4327

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6 changes: 3 additions & 3 deletions docs/getting-started/10-minutes-to-awkward-array.md
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Expand Up @@ -24,7 +24,7 @@ In this guide, we'll look at how to manipulate a jagged dataset to plot taxi rou

## Loading the dataset

Our dataset is formatted as a 611 MB [Apache Parquet](https://parquet.apache.org/) file, provided [here](https://zenodo.org/records/14537442/files/chicago-taxi.parquet). Alongside JSON, and raw buffers, Awkward can also read Parquet files and Arrow tables.
Our dataset is formatted as a 611 MB [Apache Parquet](https://parquet.apache.org/) file, provided [here](https://test-files.awkward-array.org/chicago-taxi.parquet) (a mirror of [this Zenodo record](https://zenodo.org/records/14537442)). Alongside JSON, and raw buffers, Awkward can also read Parquet files and Arrow tables.

Given that this file is so large, let's first look at the *metadata* with `ak.metadata_from_parquet` to see what we're working with:

Expand All @@ -43,7 +43,7 @@ import numpy as np
import awkward as ak

metadata = ak.metadata_from_parquet(
"https://zenodo.org/records/14537442/files/chicago-taxi.parquet"
"https://test-files.awkward-array.org/chicago-taxi.parquet"
)
```

Expand All @@ -59,7 +59,7 @@ There are a lot of different columns here (`trip.sec`, `trip.begin.lon`, `trip.p

```{code-cell} ipython3
taxi = ak.from_parquet(
"https://zenodo.org/records/14537442/files/chicago-taxi.parquet",
"https://test-files.awkward-array.org/chicago-taxi.parquet",
row_groups=[0],
columns=["trip.km", "trip.begin.l*", "trip.end.l*", "trip.path.*"],
)
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2 changes: 1 addition & 1 deletion docs/user-guide/how-to-examine-single-item.md
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Expand Up @@ -27,7 +27,7 @@ First, let's load the dataset using the {func}`ak.from_parquet` function. We wil
```{code-cell} ipython3
import awkward as ak

url = "https://zenodo.org/records/14537442/files/chicago-taxi.parquet"
url = "https://test-files.awkward-array.org/chicago-taxi.parquet"
taxi = ak.from_parquet(
url,
row_groups=[0],
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