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new 01736e97f3 [DOCS] Fix typos (#1936)
01736e97f3 is described below
commit 01736e97f3e9b1e02820b4ae9102f1026daca11b
Author: John Bampton <[email protected]>
AuthorDate: Sun May 4 05:28:24 2025 +1000
[DOCS] Fix typos (#1936)
* [DOCS] Fix typo
* More typos
---
docs/usecases/ApacheSedonaRaster.ipynb | 2 +-
docs/usecases/contrib/foot-traffic.ipynb | 12 ++++++------
2 files changed, 7 insertions(+), 7 deletions(-)
diff --git a/docs/usecases/ApacheSedonaRaster.ipynb
b/docs/usecases/ApacheSedonaRaster.ipynb
index f04105496d..007b3eb479 100644
--- a/docs/usecases/ApacheSedonaRaster.ipynb
+++ b/docs/usecases/ApacheSedonaRaster.ipynb
@@ -526,7 +526,7 @@
"### Perform Map Algebra operations\n",
"Sedona provides two ways to perform [Map
Algebra](https://sedona.apache.org/1.5.0/api/sql/Raster-map-algebra/) on
rasters:\n",
"1. Using RS_MapAlgebra (preferred for simpler algebraic functions)\n",
- "2. Using RS_BandAsArray and array based map algebra functions such as
RS_Add, RS_Multiply (Useful for complex algebriac functions involving mutating
each grid value differently.)\n",
+ "2. Using RS_BandAsArray and array based map algebra functions such as
RS_Add, RS_Multiply (Useful for complex algebraic functions involving mutating
each grid value differently.)\n",
"\n",
"The following example illustrates how RS_MapAlgebra can be used. \n",
"This example uses jiffle script to invert the colors of the above
illustrated rasterized geometry."
diff --git a/docs/usecases/contrib/foot-traffic.ipynb
b/docs/usecases/contrib/foot-traffic.ipynb
index 200da0dc72..154bd53942 100644
--- a/docs/usecases/contrib/foot-traffic.ipynb
+++ b/docs/usecases/contrib/foot-traffic.ipynb
@@ -223,7 +223,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Number of coffe shops patterns: 66607\n"
+ "Number of coffee shops patterns: 66607\n"
]
},
{
@@ -237,7 +237,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Number of coffe shops: 1679\n"
+ "Number of coffee shops: 1679\n"
]
},
{
@@ -504,8 +504,8 @@
}
],
"source": [
- "print(\"Number of coffe shops patterns: \", sample.count())\n",
- "print(\"Number of coffe shops: \",
sample.select(\"placekey\").distinct().count())\n",
+ "print(\"Number of coffee shops patterns: \", sample.count())\n",
+ "print(\"Number of coffee shops: \",
sample.select(\"placekey\").distinct().count())\n",
"sample.limit(10).toPandas().head()"
]
},
@@ -859,7 +859,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "1071 coffee shops have vistors' home <10 km away, out of 1688 coffee
shops.\n"
+ "1071 coffee shops have visitors' home <10 km away, out of 1688 coffee
shops.\n"
]
},
{
@@ -876,7 +876,7 @@
"display(furthest_traveled.filter(f.col(\"avg_median_dist_from_home\") <
10000))\n",
"print(\n",
" furthest_traveled.filter(f.col(\"avg_median_dist_from_home\") <
10000).count(),\n",
- " \" coffee shops have vistors' home <10 km away, out of \",\n",
+ " \" coffee shops have visitors' home <10 km away, out of \",\n",
" furthest_traveled.count(),\n",
" \"coffee shops.\",\n",
")"
