From 9abe29e71038fa0ab328f2a801226de765023fe8 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Yvonne=20Fr=C3=B6hlich?=
 <94163266+yvonnefroehlich@users.noreply.github.com>
Date: Mon, 9 Dec 2024 07:54:17 -0500
Subject: [PATCH] Tutorial 02: Notes reading usage of own tabular data, dowload
 issue of river data (#35)

---
 book/tut02_spe_pd_gpd.ipynb | 18 ++++++++++++++----
 1 file changed, 14 insertions(+), 4 deletions(-)

diff --git a/book/tut02_spe_pd_gpd.ipynb b/book/tut02_spe_pd_gpd.ipynb
index 012b0a3..2bc7475 100755
--- a/book/tut02_spe_pd_gpd.ipynb
+++ b/book/tut02_spe_pd_gpd.ipynb
@@ -60,6 +60,7 @@
    "outputs": [],
    "source": [
     "import geopandas as gpd\n",
+    "import pandas as pd\n",
     "import pygmt\n",
     "\n",
     "# Use a resolution of only 150 dpi for the images within the Jupyter notebook, to keep the file small\n",
@@ -81,7 +82,8 @@
    "source": [
     "### 1.1 Tabular data - `pandas.DataFrame`\n",
     "\n",
-    "Use an example dataset with tabular data provided by `PyGMT` and load it into a `pandas.DataFrame`. This dataset contains earthquakes in the area of Japan."
+    "Use an example dataset with tabular data provided by `PyGMT` and load it into a `pandas.DataFrame`. This dataset contains earthquakes in the area of Japan.\n",
+    "You can read your own dataset into a `pandas.Dataframe` using [`pandas.read_csv`](https://pandas.pydata.org/docs/reference/api/pandas.read_csv.html) and use it in the same way to make the following plots; of course you have to adjust the column names accordantly."
    ]
   },
   {
@@ -92,7 +94,9 @@
    "outputs": [],
    "source": [
     "df_jp_eqs = pygmt.datasets.load_sample_data(name=\"japan_quakes\")\n",
-    "df_jp_eqs.head()"
+    "df_jp_eqs.head()\n",
+    "\n",
+    "# df_your_dataset = pd.read_csv(\"your_dataset.csv\")"
    ]
   },
   {
@@ -239,7 +243,12 @@
    "source": [
     "#### 2.1.1 Spatial Data - `geopandas.GeoDataFrame` with line geometry\n",
     "\n",
-    "First we download some data into in a [`geopandas.GeoDataFrame`](https://geopandas.org/en/stable/docs/reference/api/geopandas.GeoDataFrame.html). This dataset contains European rivers with their lengths and names."
+    "First we download some data into in a [`geopandas.GeoDataFrame`](https://geopandas.org/en/stable/docs/reference/api/geopandas.GeoDataFrame.html). This dataset contains European rivers with their lengths and names.\n",
+    "\n",
+    "In case you face issues with downloading these data:\n",
+    "1. Copy the URL \"https://www.eea.europa.eu/data-and-maps/data/wise-large-rivers-and-large-lakes/zipped-shapefile-with-wise-large-rivers-vector-line/zipped-shapefile-with-wise-large-rivers-vector-line/at_download/file/wise_large_rivers.zip\" into your browser.\n",
+    "2. Download the zip file and place it into `~/agu24workshop/book`. Do not unpack the ZIP file.\n",
+    "3. Replace the URL with the filename of the ZIP file \"wise_large_rivers.zip\" in [`geopandas.read_file`](https://geopandas.org/en/stable/docs/reference/api/geopandas.read_file.html)."
    ]
   },
   {
@@ -254,6 +263,7 @@
     "    + \"zipped-shapefile-with-wise-large-rivers-vector-line/zipped-shapefile-with-wise-large-rivers-vector-line/\"\n",
     "    + \"at_download/file/wise_large_rivers.zip\"\n",
     ")\n",
+    "# gpd_rivers_org = pd.read_file(\"wise_large_rivers.zip\")\n",
     "gpd_rivers_org.head()"
    ]
   },
@@ -542,7 +552,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.7"
+   "version": "3.12.6"
   }
  },
  "nbformat": 4,