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docs/python-dataviz-output/supplement_cartographic_elements.md

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+### Creating Maps with Cartographic Elements
+
+This notebook shows how to use the [EOMaps](https://eomaps.readthedocs.io/en/latest/index.html) to crate maps with cartographic elements such as north arrow, scalebar and gridlines.
+
+#### Setup and Data Download
+
+The following blocks of code will install the required packages and download the datasets to your Colab environment.
+
+
+```python
+%%capture
+if 'google.colab' in str(get_ipython()):
+  !pip install eomaps mapclassify
+```
+
+
+```python
+from eomaps import Maps
+import geopandas as gpd
+import matplotlib.pyplot as plt
+import os
+import pandas as pd
+import requests
+```
+
+
+```python
+data_folder = 'data'
+output_folder = 'output'
+
+if not os.path.exists(data_folder):
+    os.mkdir(data_folder)
+if not os.path.exists(output_folder):
+    os.mkdir(output_folder)
+```
+
+
+```python
+def download(url):
+    filename = os.path.join(data_folder, os.path.basename(url))
+    if not os.path.exists(filename):
+      with requests.get(url, stream=True, allow_redirects=True) as r:
+          with open(filename, 'wb') as f:
+              for chunk in r.iter_content(chunk_size=8192):
+                  f.write(chunk)
+      print('Downloaded', filename)
+```
+
+
+```python
+shapefile_name = 'tl_2019_06_tract'
+shapefile_exts = ['.shp', '.shx', '.dbf', '.prj']
+data_url = 'https://github.com/spatialthoughts/python-dataviz-web/releases/' \
+  'download/census/'
+
+for ext in shapefile_exts:
+  url = data_url + shapefile_name + ext
+  download(url)
+
+csv_name = 'ACSST5Y2019.S0101_data.csv'
+download(data_url + csv_name)
+
+```
+
+#### Data Pre-Processing
+
+Read the data and perform a table join.
+
+
+```python
+shapefile_path = os.path.join(data_folder, shapefile_name + '.shp')
+tracts = gpd.read_file(shapefile_path)
+csv_path = os.path.join(data_folder, csv_name)
+table = pd.read_csv(csv_path, skiprows=[1])
+filtered = table[['GEO_ID','NAME', 'S0101_C01_001E']]
+filtered = filtered.rename(columns = {'S0101_C01_001E': 'Population', 'GEO_ID': 'GEOID'})
+filtered['GEOID'] = filtered.GEOID.str[-11:]
+gdf = tracts.merge(filtered, on='GEOID')
+gdf['density'] = 1e6*gdf['Population']/gdf['ALAND']
+gdf
+```
+
+#### Create a Map using EOMaps
+
+Initialize a map with a CRS.
+
+Referemce: [`eomaps.Maps()`](https://eomaps.readthedocs.io/en/latest/generated/eomaps.eomaps.Maps.html#eomaps.eomaps.Maps)
+
+
+```python
+m = Maps(crs=Maps.CRS.Orthographic(-120, 35), figsize=(7, 8))
+```
+
+Set the map extent.
+
+
+```python
+xmin, ymin, xmax, ymax = gdf.total_bounds
+buffer = 0.1
+m.set_extent([xmin-buffer, xmax+buffer, ymin-buffer, ymax+buffer])
+```
+
+Add the gridlines.
+
+Reference: [`eomaps.Maps.add_gridlines()`](https://eomaps.readthedocs.io/en/latest/generated/eomaps.eomaps.Maps.add_gridlines.html)
+
+
+
+```python
+g = m.add_gridlines(1, lw=0.25, alpha=0.5, zorder=0)
+gl = g.add_labels(fontsize=8, every = 2)
+m.show()
+```
+
+Add North Arrow.
+
+Reference: [`eomaps.Maps.add_compass()`](https://eomaps.readthedocs.io/en/latest/generated/eomaps.eomaps.Maps.add_compass.html#eomaps.eomaps.Maps.add_compass)
+
+
+```python
+c = m.add_compass(style='compass', pos=(0.85, 0.9))
+m.show()
+```
+
+Add scalebar.
+
+Reference: [`eomaps.Maps.add_scalebar()`](https://eomaps.readthedocs.io/en/latest/generated/eomaps.eomaps.Maps.add_scalebar.html)
+
+
+```python
+s = m.add_scalebar(
+    n=4,
+    scale=50000,
+    auto_position=(0.05,0.08),
+    preset='bw',
+    rotation=90,
+    label_props={'rotation':90, 'offset':1.5, 'family':'Helvetica', 'weight':0.5},
+    scale_props={'colors': ('k','#bdbdbd','k','#bdbdbd','k')},
+    line_props={'lw':0, 'ls': 'solid'}
+)
+m.show()
+```
+
+Plot the GeoDataFrame.
+
+
+```python
+legend_kwds= {
+  'loc': 'upper right',
+  'bbox_to_anchor': (0.97, 0.80),
+  'fmt': '{:<5.0f}',
+  'frameon': True,
+  'fontsize': 8,
+  'title': 'persons/sq.km.'
+}
+classification_kwds={
+  'bins':[1,10,25,50,100, 250, 500, 1000, 5000]
+}
+
+m.add_gdf(gdf, column='density', cmap='RdYlGn_r', scheme='User_Defined',
+          classification_kwds=classification_kwds,
+          legend=True, legend_kwds=legend_kwds)
+m.show()
+```
+
+Save the map.
+
+
+```python
+output_folder = 'output'
+output_path = os.path.join(output_folder, 'map.png')
+m.savefig(output_path)
+```
+
+
+
+![](python-dataviz-output/supplement_cartographic_elements_files/supplement_cartographic_elements_24_0.png)
+
+