Estimate Localized Economic Impacts in Tourism (#18)

* Add visits notebook

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* Revert "[pre-commit.ci] auto fixes from pre-commit.com hooks"

This reverts commit aa824e3.

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docs/_toc.yml

@@ -23,6 +23,9 @@ parts:
       - file: notebooks/spill/spillover-README
         sections:
         - file: notebooks/spill/spill.ipynb
+      - file: notebooks/mobility/README.md
+        sections:
+        - file: notebooks/mobility/visits.ipynb
   - caption: Insights and Indicators
     chapters:
       - file: notebooks/indicators/conflict-and-trade.ipynb

notebooks/mobility/README.md

@@ -0,0 +1,21 @@
+# Economic Impacts in Tourism
+
+Understanding where and when population movement occurs can help inform disaster response and public policy, especially during crises.
+
+(mobility-data)=
+
+## Data
+
+The project team acquired longitudinal human mobility data. The mobility data was provided pro-bono by [Veraset](https://veraset.com) through the proposal [Measure Activity Levels on Tourism Sites Affected by the 2023 Red Sea Crisis](https://portal.datapartnership.org/readableproposal/565) via  the [Development Data Partnership](https://datapartnership.org). During the project’s execution, [Veraset Movement](https://www.veraset.com/products/movement/)’s global daily data feed was ingested and processed through the [Mobility](https://docs.datapartnership.org/collections/mobility/README.html) pipeline maintained by the [Development Data Partnership](https://datapartnership.org/). For additional information, please refer to the [Mobility Documentation](https://docs.datapartnership.org/collections/mobility/README.html) accessible to all World Bank staff.
+
+### Data Availability Statement
+
+Data are available upon request through the [Development Data Partnership](https://datapartnership.org). Licensing and access information for all other datasets are included in the documentation.
+
+## Methodology
+
+```{caution}
+The following working methodologies are a work in progress and awaiting review.
+```
+
+- [Estimating Activity Through Point of Interest Visits Using Mobility Data](./visits.ipynb)

pyproject.toml

@@ -4,6 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "red-sea-monitoring"
+dynamic = ["version"]
 description = ""
 readme = { file = "README.md", content-type = "text/markdown" }
 license = { file = "LICENSE" }
@@ -18,7 +19,10 @@ classifiers = [
 	"Topic :: Scientific/Engineering",
 ]
 requires-python = ">=3.10"
-dynamic = ["version"]
+dependencies = [
+	"bokeh>3,<4",
+    "geopandas>=0.12",
+]
 
 [project.optional-dependencies]
 docs = [
@@ -36,7 +40,7 @@ ignore-regex = '^\s*"image\/png":\s.*'
 ignore-words-list = "gost,"
 
 [tool.hatch.build.targets.wheel]
-packages = ["src/red-sea-monitoring"]
+packages = ["src/red_sea_monitoring"]
 
 [tool.hatch.version]
 source = "vcs"

src/red_sea_monitoring/mobility.py

@@ -0,0 +1,108 @@
+import datetime
+
+from bokeh.models import HoverTool, Legend, Span, Title
+from bokeh.plotting import figure
+
+COLORS = [
+    "#4E79A7",  # Blue
+    "#F28E2B",  # Orange
+    "#E15759",  # Red
+    "#76B7B2",  # Teal
+    "#59A14F",  # Green
+    "#EDC948",  # Yellow
+    "#B07AA1",  # Purple
+    "#FF9DA7",  # Pink
+    "#9C755F",  # Brown
+    "#BAB0AC",  # Gray
+    "#7C7C7C",  # Dark gray
+    "#6B4C9A",  # Violet
+    "#D55E00",  # Orange-red
+    "#CC61B0",  # Magenta
+    "#0072B2",  # Bright blue
+    "#329262",  # Peacock green
+    "#9E5B5A",  # Brick red
+    "#636363",  # Medium gray
+    "#CD9C00",  # Gold
+    "#5D69B1",  # Medium blue
+]
+
+
+def plot_visits(data, title="Points of Interest Visit Trends"):
+    """Plot number of visits to OSM points of interest"""
+
+    p = figure(
+        title=title,
+        width=750,
+        height=750,
+        x_axis_label="Date",
+        x_axis_type="datetime",
+        y_axis_label="Count of Devices",
+        y_axis_type="log",
+        y_range=(0.75, 5 * 10**3),
+        tools="pan,reset,save,box_select",
+    )
+    p.add_layout(Legend(), "right")
+    p.add_layout(
+        Title(
+            text="Count of Devices Identified with OpenStreetMap tag",
+            text_font_size="12pt",
+            text_font_style="italic",
+        ),
+        "above",
+    )
+    p.add_layout(
+        Title(
+            text=f"Source: Veraset Movement. Creation date: {datetime.datetime.today().strftime('%d %B %Y')}. Feedback: datalab@worldbank.org.",
+            text_font_size="10pt",
+            text_font_style="italic",
+        ),
+        "below",
+    )
+
+    # plot spans
+    p.renderers.extend(
+        [
+            Span(
+                location=datetime.datetime(2023, 10, 7),
+                dimension="height",
+                line_color="grey",
+                line_width=2,
+                line_dash=(4, 4),
+            ),
+            Span(
+                location=datetime.datetime(2023, 11, 17),
+                dimension="height",
+                line_color="grey",
+                line_width=2,
+                line_dash=(4, 4),
+            ),
+        ]
+    )
+
+    # plot lines
+    for column, color in zip(data.columns, COLORS):
+        try:
+            r = p.line(
+                data.index,
+                data[column],
+                legend_label=column,
+                line_color=color,
+                line_width=2,
+            )
+            if column != "hotel":
+                r.muted = True
+        except KeyError:
+            pass
+
+    p.add_tools(
+        HoverTool(
+            tooltips=[("Date", "@x{%F}"), ("Count", "@y")],
+            formatters={"@x": "datetime"},
+        )
+    )
+
+    p.legend.location = "bottom_left"
+    p.legend.click_policy = "mute"
+    p.title.text_font_size = "16pt"
+    # p.sizing_mode = "scale_both"
+    return p