From 0638bd2f052b12c9312e1e323dba500ba8de0692 Mon Sep 17 00:00:00 2001 From: John Bampton Date: Thu, 26 Oct 2023 06:55:48 +1000 Subject: [PATCH] [DOCS] Standardize Markdown code blocks: word case and whitespace --- R/README.md | 8 ++++---- R/vignettes/articles/apache-sedona.Rmd | 2 +- README.md | 6 +++--- docs/api/flink/Function.md | 10 +++++----- docs/api/sql/Function.md | 10 +++++----- 5 files changed, 18 insertions(+), 18 deletions(-) diff --git a/R/README.md b/R/README.md index c37b33985b..b3202e6ae1 100644 --- a/R/README.md +++ b/R/README.md @@ -11,7 +11,7 @@ enabling higher-level access through a `{dplyr}` backend and familiar R function ## Installation To use Apache Sedona from R, you just need to install the apache.sedona package; Spark dependencies are managed directly by the package. -``` r +```r # Install released version from CRAN install.packages("apache.sedona") ``` @@ -21,7 +21,7 @@ To use the development version, you will need both the latest version of the pac To get the latest R package from GtiHub: -``` r +```r # Install development version from GitHub devtools::install_github("apache/sedona/R") ``` @@ -40,7 +40,7 @@ The path to the sedona-spark-shaded jars needs to be put in the `SEDONA_JAR_FILE The first time you load Sedona, Spark will download all the dependent jars, which can take a few minutes and cause the connection to timeout. You can either retry (some jars will already be downloaded and cached) or increase the `"sparklyr.connect.timeout"` parameter in the sparklyr config. -``` r +```r library(sparklyr) library(apache.sedona) @@ -51,7 +51,7 @@ sc <- spark_connect(master = "local") polygon_sdf <- spark_read_geojson(sc, location = "/tmp/polygon.json") ``` -``` r +```r mean_area_sdf <- polygon_sdf %>% dplyr::summarize(mean_area = mean(ST_Area(geometry))) print(mean_area_sdf) diff --git a/R/vignettes/articles/apache-sedona.Rmd b/R/vignettes/articles/apache-sedona.Rmd index 0d28210b55..b08e2dd306 100644 --- a/R/vignettes/articles/apache-sedona.Rmd +++ b/R/vignettes/articles/apache-sedona.Rmd @@ -362,7 +362,7 @@ to Sedona visualization routines. For example, the following is essentially the R equivalent of [this example in Scala](https://github.com/apache/sedona/blob/f6b1c5e24bdb67d2c8d701a9b2af1fb5658fdc4d/viz/src/main/scala/org/apache/sedona/viz/showcase/ScalaExample.scala#L142-L160). -``` {r} +```{r} resolution_x <- 1000 resolution_y <- 600 boundary <- c(-126.790180, -64.630926, 24.863836, 50.000) diff --git a/README.md b/README.md index a842b63ca6..1ecf592ed0 100644 --- a/README.md +++ b/README.md @@ -62,11 +62,11 @@ Apache Sedona is a widely used framework for working with spatial data, and it h This example loads NYC taxi trip records and taxi zone information stored as .CSV files on AWS S3 into Sedona spatial dataframes. It then performs spatial SQL query on the taxi trip datasets to filter out all records except those within the Manhattan area of New York. The example also shows a spatial join operation that matches taxi trip records to zones based on whether the taxi trip lies within the geographical extents of the zone. Finally, the last code snippet integrates the output of Sedona with GeoPandas and plots the spatial distribution of both datasets. #### Load NYC taxi trips and taxi zones data from CSV Files Stored on AWS S3 -``` python +```python taxidf = sedona.read.format('csv').option("header","true").option("delimiter", ",").load("s3a://your-directory/data/nyc-taxi-data.csv") taxidf = taxidf.selectExpr('ST_Point(CAST(Start_Lon AS Decimal(24,20)), CAST(Start_Lat AS Decimal(24,20))) AS pickup', 'Trip_Pickup_DateTime', 'Payment_Type', 'Fare_Amt') ``` -``` python +```python zoneDf = sedona.read.format('csv').option("delimiter", ",").load("s3a://your-directory/data/TIGER2018_ZCTA5.csv") zoneDf = zoneDf.selectExpr('ST_GeomFromWKT(_c0) as zone', '_c1 as zipcode') ``` @@ -105,7 +105,7 @@ We provide a Docker image for Apache Sedona with Python JupyterLab and a single- * To install the Python package: - ``` + ``` pip install apache-sedona ``` * To Compile the source code, please refer to [Sedona website](https://sedona.apache.org/latest-snapshot/setup/compile/) diff --git a/docs/api/flink/Function.md b/docs/api/flink/Function.md index e88e4da416..81d82542aa 100644 --- a/docs/api/flink/Function.md +++ b/docs/api/flink/Function.md @@ -1246,7 +1246,7 @@ Format: `ST_H3CellDistance(cell1: Long, cell2: Long)` Since: `v1.5.0` Example: -```SQL +```sql select ST_H3CellDistance(ST_H3CellIDs(ST_GeomFromWKT('POINT(1 2)'), 8, true)[1], ST_H3CellIDs(ST_GeomFromWKT('POINT(1.23 1.59)'), 8, true)[1]) ``` @@ -1291,7 +1291,7 @@ Format: `ST_H3CellIDs(geom: geometry, level: Int, fullCover: true)` Since: `v1.5.0` Example: -```SQL +```sql SELECT ST_H3CellIDs(ST_GeomFromText('LINESTRING(1 3 4, 5 6 7)'), 6, true) ``` @@ -1318,7 +1318,7 @@ Format: `ST_H3KRing(cell: Long, k: Int, exactRing: Boolean)` Since: `v1.5.0` Example: -```SQL +```sql select ST_H3KRing(ST_H3CellIDs(ST_GeomFromWKT('POINT(1 2)'), 8, true)[1], 1, false), ST_H3KRing(ST_H3CellIDs(ST_GeomFromWKT('POINT(1 2)'), 8, true)[1], 1, true) ``` @@ -1342,7 +1342,7 @@ Format: `ST_H3ToGeom(cells: Array[Long])` Since: `v1.5.0` Example: -```SQL +```sql SELECT ST_H3ToGeom(ST_H3CellIDs(ST_GeomFromWKT('POINT(1 2)'), 8, true)[0], 1, true)) ``` @@ -2189,7 +2189,7 @@ Since: `v1.4.0` Example: -```SQL +```sql SELECT ST_S2CellIDs(ST_GeomFromText('LINESTRING(1 3 4, 5 6 7)'), 6) ``` diff --git a/docs/api/sql/Function.md b/docs/api/sql/Function.md index 29147372bb..d41eeaf6a5 100644 --- a/docs/api/sql/Function.md +++ b/docs/api/sql/Function.md @@ -1257,7 +1257,7 @@ Format: `ST_H3CellDistance(cell1: Long, cell2: Long)` Since: `v1.5.0` Spark SQL example: -```SQL +```sql select ST_H3CellDistance(ST_H3CellIDs(ST_GeomFromWKT('POINT(1 2)'), 8, true)[0], ST_H3CellIDs(ST_GeomFromWKT('POINT(1.23 1.59)'), 8, true)[0]) ``` @@ -1302,7 +1302,7 @@ Format: `ST_H3CellIDs(geom: geometry, level: Int, fullCover: Boolean)` Since: `v1.5.0` Spark SQL example: -```SQL +```sql SELECT ST_H3CellIDs(ST_GeomFromText('LINESTRING(1 3 4, 5 6 7)'), 6, true) ``` @@ -1329,7 +1329,7 @@ Format: `ST_H3KRing(cell: Long, k: Int, exactRing: Boolean)` Since: `v1.5.0` Spark SQL example: -```SQL +```sql SELECT ST_H3KRing(ST_H3CellIDs(ST_GeomFromWKT('POINT(1 2)'), 8, true)[0], 1, true) cells union select ST_H3KRing(ST_H3CellIDs(ST_GeomFromWKT('POINT(1 2)'), 8, true)[0], 1, false) cells ``` @@ -1354,7 +1354,7 @@ Format: `ST_H3ToGeom(cells: Array[Long])` Since: `v1.5.0` Spark SQL example: -```SQL +```sql SELECT ST_H3ToGeom(ST_H3CellIDs(ST_GeomFromWKT('POINT(1 2)'), 8, true)[0], 1, true)) ``` @@ -2199,7 +2199,7 @@ Since: `v1.4.0` Spark SQL Example: -```SQL +```sql SELECT ST_S2CellIDs(ST_GeomFromText('LINESTRING(1 3 4, 5 6 7)'), 6) ```