From 01107f3222c2c39843b3b4f505219111929925d8 Mon Sep 17 00:00:00 2001 From: Alexis Cook Date: Wed, 22 Feb 2023 08:50:06 -0500 Subject: [PATCH 1/2] [Geospatial Analysis] kicking off a test checking if pinning shapely helps the staging image --- notebooks/geospatial/raw/tut1.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/notebooks/geospatial/raw/tut1.ipynb b/notebooks/geospatial/raw/tut1.ipynb index 6e2749939..e23b75ea6 100644 --- a/notebooks/geospatial/raw/tut1.ipynb +++ b/notebooks/geospatial/raw/tut1.ipynb @@ -6,7 +6,7 @@ "source": [ "# Introduction\n", "\n", - "In this micro-course, you'll learn about different methods to wrangle and visualize **geospatial data**, or data with a geographic location.\n", + "In this micro-course, you'll learn about different methods to wrangle and visualize **geospatial data**, or data with a geographic location. \n", "\n", "
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\n", From 9ba4fbe7afc812d62b2eccea6ddbbae4c1e645eb Mon Sep 17 00:00:00 2001 From: Alexis Cook Date: Wed, 22 Feb 2023 09:00:28 -0500 Subject: [PATCH 2/2] Update tut1.ipynb --- notebooks/geospatial/raw/tut1.ipynb | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/notebooks/geospatial/raw/tut1.ipynb b/notebooks/geospatial/raw/tut1.ipynb index e23b75ea6..3962652b9 100644 --- a/notebooks/geospatial/raw/tut1.ipynb +++ b/notebooks/geospatial/raw/tut1.ipynb @@ -6,7 +6,7 @@ "source": [ "# Introduction\n", "\n", - "In this micro-course, you'll learn about different methods to wrangle and visualize **geospatial data**, or data with a geographic location. \n", + "In this course, you'll learn about different methods to wrangle and visualize **geospatial data**, or data with a geographic location. \n", "\n", "
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\n", @@ -21,7 +21,7 @@ "\n", "You'll also visualize crime in the city of Boston, examine health facilities in Ghana, explore top universities in Europe, and track releases of toxic chemicals in the United States.\n", "\n", - "In this first tutorial, we'll quickly cover the pre-requisites that you'll need to complete this micro-course. And, if you'd like to review more deeply, we recommend the **[Pandas micro-course](https://www.kaggle.com/learn/pandas)**. \n", + "In this first tutorial, we'll quickly cover the pre-requisites that you'll need to complete this course. And, if you'd like to review more deeply, we recommend the **[Pandas course](https://www.kaggle.com/learn/pandas)**. \n", "\n", "We'll also get started with visualizing our first geospatial dataset!\n", "\n", @@ -43,7 +43,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "There are many, many different geospatial file formats, such as [shapefile](https://en.wikipedia.org/wiki/Shapefile), [GeoJSON](https://en.wikipedia.org/wiki/GeoJSON), [KML](https://en.wikipedia.org/wiki/Keyhole_Markup_Language), and [GPKG](https://en.wikipedia.org/wiki/GeoPackage). We won't discuss their differences in this micro-course, but it's important to mention that:\n", + "There are many, many different geospatial file formats, such as [shapefile](https://en.wikipedia.org/wiki/Shapefile), [GeoJSON](https://en.wikipedia.org/wiki/GeoJSON), [KML](https://en.wikipedia.org/wiki/Keyhole_Markup_Language), and [GPKG](https://en.wikipedia.org/wiki/GeoPackage). We won't discuss their differences in this course, but it's important to mention that:\n", "- shapefile is the most common file type that you'll encounter, and \n", "- all of these file types can be quickly loaded with the `gpd.read_file()` function.\n", "\n", @@ -91,7 +91,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "For instance, if we don't plan to use all of the columns, we can select a subset of them. (_To review other methods for selecting data, check out [this tutorial](https://www.kaggle.com/residentmario/indexing-selecting-assigning/) from the Pandas micro-course_.)" + "For instance, if we don't plan to use all of the columns, we can select a subset of them. (_To review other methods for selecting data, check out [this tutorial](https://www.kaggle.com/residentmario/indexing-selecting-assigning/) from the Pandas course_.)" ] }, { @@ -107,7 +107,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "We use the `value_counts()` method to see a list of different land types, along with how many times they appear in the dataset. (_To review this (and related methods), check out [this tutorial](https://www.kaggle.com/residentmario/summary-functions-and-maps) from the Pandas micro-course._)" + "We use the `value_counts()` method to see a list of different land types, along with how many times they appear in the dataset. (_To review this (and related methods), check out [this tutorial](https://www.kaggle.com/residentmario/summary-functions-and-maps) from the Pandas course._)" ] }, { @@ -124,7 +124,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "You can also use `loc` (and `iloc`) and `isin` to select subsets of the data. (_To review this, check out [this tutorial](https://www.kaggle.com/residentmario/indexing-selecting-assigning/) from the Pandas micro-course._)" + "You can also use `loc` (and `iloc`) and `isin` to select subsets of the data. (_To review this, check out [this tutorial](https://www.kaggle.com/residentmario/indexing-selecting-assigning/) from the Pandas course._)" ] }, { @@ -142,7 +142,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "If you're not familiar with the commands above, you are encouraged to bookmark this page for reference, so you can look up the commands as needed. (_Alternatively, you can take the [Pandas micro-course](https://www.kaggle.com/learn/pandas)._) We'll use these commands throughout this micro-course to understand and filter data before creating maps.\n", + "If you're not familiar with the commands above, you are encouraged to bookmark this page for reference, so you can look up the commands as needed. (_Alternatively, you can take the [Pandas course](https://www.kaggle.com/learn/pandas)._) We'll use these commands throughout this course to understand and filter data before creating maps.\n", "\n", "# Create your first map!\n", "\n",