updated charts for poverty

policyengine/charts/poverty/deep/by_age.py

@@ -0,0 +1,107 @@
+import plotly.graph_objects as go
+from policyengine_core.charts.formatting import *
+
+class DeepPovertyByAgeChart:
+    def __init__(self,country:str, data=None):
+        if data is None:
+            raise ValueError("Data must be provided")
+
+        self.data = data
+
+    def _get_color(self, value):
+        # All bars should be gray
+        return GRAY
+
+    def _get_change_direction(self, value):
+        if value > 0:
+            return "increase"
+        elif value < 0:
+            return "decrease"
+        else:
+            return "no change"
+
+    def ordinal_suffix(self, n):
+        """Return the ordinal suffix for an integer."""
+        if 10 <= n % 100 <= 20:
+            suffix = 'th'
+        else:
+            suffix = {1: 'st', 2: 'nd', 3: 'rd'}.get(n % 10, 'th')
+        return suffix
+
+    def generate_chart_data(self):
+        categories = list(self.data.keys())
+        values = [self.data[cat]['change'] for cat in categories]
+        baselines = [self.data[cat]['baseline'] * 100 for cat in categories]
+        reforms = [self.data[cat]['reform'] * 100 for cat in categories]
+
+        # Generate hover texts with baseline, reform, and percentage change
+        hover_texts = [
+            f"This reform would {self._get_change_direction(val)} the percentage of {category.lower()} in poverty by {abs(val):.1f}% from {baseline:.1f}% to {reform:.1f}%"
+            for category, val, baseline, reform in zip(categories, values, baselines, reforms)
+        ]
+
+        fig = go.Figure()
+
+        values_in_pct = values  # Use percentage values
+        colors = [self._get_color(value) for value in values]
+
+        # Add bar chart with percentage values
+        fig.add_trace(go.Bar(
+            x=categories,
+            y=values_in_pct,
+            marker=dict(color=colors, line=dict(width=1)),
+            width=0.6,
+            text=[f"{abs(value):.1f}%" for value in values],  # Display values as percentages
+            textposition='outside',
+            hovertemplate="<b>%{x}</b><br><br>%{customdata}<extra></extra>",  # Hover shows category
+            customdata=hover_texts
+        ))
+
+        # Update layout to reflect percentage values on y-axis
+        fig.update_layout(
+            yaxis=dict(
+                tickformat=",.1f%%",  # Format y-axis as percentages with one decimal place
+                title="Percentage Change in Poverty"
+            ),
+            xaxis=dict(
+                title="Category"
+            ),
+            hoverlabel=dict(
+                bgcolor="white",
+                font=dict(color="black", size=16)
+            ),
+            title="Change in Poverty Percentage by Category"
+        )
+
+        format_fig(fig)  # Keep the formatting logic from policyengine_core
+        return fig
+
+
+# # Example data
+# data = {
+#     'Child': {
+#         'Baseline': 0.32427219591395395,
+#         'Reform': 0.33392168532001054,
+#         'Change': 3.0
+#     },
+#     'Adult': {
+#         'Baseline': 0.17427822561729264,
+#         'Reform': 0.17757158627182623,
+#         'Change': 1.9
+#     },
+#     'Senior': {
+#         'Baseline': 0.12817646500651358,
+#         'Reform': 0.1370685860340031,
+#         'Change': 6.9
+#     },
+#     'All': {
+#         'Baseline': 0.19913534734369268,
+#         'Reform': 0.20487670454940832,
+#         'Change': 2.9
+#     }
+# }
+
+# # Generate chart for all categories
+# chart = OverallChart(data=data)
+# fig = chart.generate_chart_data()
+# fig.show()

policyengine/charts/poverty/deep/by_gender.py

@@ -0,0 +1,103 @@
+import plotly.graph_objects as go
+from policyengine_core.charts.formatting import *
+
+class DeepPovertyByGenderChart:
+    def __init__(self, country:str,data=None):
+        if data is None:
+            raise ValueError("Data must be provided")
+
+        self.data = data
+
+    def _get_color(self, value):
+        # All bars should be gray
+        return GRAY
+
+    def _get_change_direction(self, value):
+        if value > 0:
+            return "increase"
+        elif value < 0:
+            return "decrease"
+        else:
+            return "no change"
+
+    def ordinal_suffix(self, n):
+        """Return the ordinal suffix for an integer."""
+        if 10 <= n % 100 <= 20:
+            suffix = 'th'
+        else:
+            suffix = {1: 'st', 2: 'nd', 3: 'rd'}.get(n % 10, 'th')
+        return suffix
+
+    def generate_chart_data(self):
+        categories = list(self.data.keys())
+        values = [self.data[cat]['change'] for cat in categories]
+        baselines = [self.data[cat]['baseline'] * 100 for cat in categories]
+        reforms = [self.data[cat]['reform'] * 100 for cat in categories]
+
+        # Generate hover texts with baseline, reform, and percentage change
+        hover_texts = [
+            f"This reform would {self._get_change_direction(val)} the percentage of {category.lower()} in poverty by {abs(val):.1f}% from {baseline:.1f}% to {reform:.1f}%"
+            for category, val, baseline, reform in zip(categories, values, baselines, reforms)
+        ]
+
+        fig = go.Figure()
+
+        values_in_pct = values  # Use percentage values
+        colors = [self._get_color(value) for value in values]
+
+        # Add bar chart with percentage values
+        fig.add_trace(go.Bar(
+            x=categories,
+            y=values_in_pct,
+            marker=dict(color=colors, line=dict(width=1)),
+            width=0.6,
+            text=[f"{abs(value):.1f}%" for value in values],  # Display values as percentages
+            textposition='outside',
+            hovertemplate="<b>Category %{x}</b><br><br>%{customdata}<extra></extra>",  # Hover shows category
+            customdata=hover_texts
+        ))
+
+        # Update layout to reflect percentage values on y-axis
+        fig.update_layout(
+            yaxis=dict(
+                tickformat=",.1f%%",
+                ticksuffix = "%",  # Format y-axis as percentages with one decimal place
+                title="Percentage Change in Poverty"
+            ),
+            xaxis=dict(
+                title="Category"
+            ),
+            hoverlabel=dict(
+                bgcolor="white",
+                font=dict(color="black", size=16)
+            ),
+            title="Change in Poverty Percentage by Category"
+        )
+
+        format_fig(fig)  # Keep the formatting logic from policyengine_core
+        return fig
+
+
+# # Example data
+# data = {
+#     'Male': {
+#         'Baseline': 0.18412623468617267,
+#         'Reform': 0.18932591339284738,
+#         'Change': 2.8
+#     },
+#     'Female': {
+#         'Baseline': 0.21377616483057263,
+#         'Reform': 0.22004590877186603,
+#         'Change': 2.9
+#     },
+#     'All': {
+#         'Baseline': 0.19913534734369268,
+#         'Reform': 0.20487670454940832,
+#         'Change': 2.9
+#     }
+# }
+
+# # Generate chart for all categories
+# chart = OverallChart(data=data)
+# fig = chart.generate_chart_data()
+# fig.show()

policyengine/charts/poverty/regular/by_age.py

@@ -0,0 +1,107 @@
+import plotly.graph_objects as go
+from policyengine_core.charts.formatting import *
+
+class RegularPovertyByAgeChart:
+    def __init__(self,country:str, data=None):
+        if data is None:
+            raise ValueError("Data must be provided")
+
+        self.data = data
+
+    def _get_color(self, value):
+        # All bars should be gray
+        return GRAY
+
+    def _get_change_direction(self, value):
+        if value > 0:
+            return "increase"
+        elif value < 0:
+            return "decrease"
+        else:
+            return "no change"
+
+    def ordinal_suffix(self, n):
+        """Return the ordinal suffix for an integer."""
+        if 10 <= n % 100 <= 20:
+            suffix = 'th'
+        else:
+            suffix = {1: 'st', 2: 'nd', 3: 'rd'}.get(n % 10, 'th')
+        return suffix
+
+    def generate_chart_data(self):
+        categories = list(self.data.keys())
+        values = [self.data[cat]['change'] for cat in categories]
+        baselines = [self.data[cat]['baseline'] * 100 for cat in categories]
+        reforms = [self.data[cat]['reform'] * 100 for cat in categories]
+
+        # Generate hover texts with baseline, reform, and percentage change
+        hover_texts = [
+            f"This reform would {self._get_change_direction(val)} the percentage of {category.lower()} in poverty by {abs(val):.1f}% from {baseline:.1f}% to {reform:.1f}%"
+            for category, val, baseline, reform in zip(categories, values, baselines, reforms)
+        ]
+
+        fig = go.Figure()
+
+        values_in_pct = values  # Use percentage values
+        colors = [self._get_color(value) for value in values]
+
+        # Add bar chart with percentage values
+        fig.add_trace(go.Bar(
+            x=categories,
+            y=values_in_pct,
+            marker=dict(color=colors, line=dict(width=1)),
+            width=0.6,
+            text=[f"{abs(value):.1f}%" for value in values],  # Display values as percentages
+            textposition='outside',
+            hovertemplate="<b>%{x}</b><br><br>%{customdata}<extra></extra>",  # Hover shows category
+            customdata=hover_texts
+        ))
+
+        # Update layout to reflect percentage values on y-axis
+        fig.update_layout(
+            yaxis=dict(
+                tickformat=",.1f%%",  # Format y-axis as percentages with one decimal place
+                title="Percentage Change in Poverty"
+            ),
+            xaxis=dict(
+                title="Category"
+            ),
+            hoverlabel=dict(
+                bgcolor="white",
+                font=dict(color="black", size=16)
+            ),
+            title="Change in Poverty Percentage by Category"
+        )
+
+        format_fig(fig)  # Keep the formatting logic from policyengine_core
+        return fig
+
+
+# # Example data
+# data = {
+#     'Child': {
+#         'Baseline': 0.32427219591395395,
+#         'Reform': 0.33392168532001054,
+#         'Change': 3.0
+#     },
+#     'Adult': {
+#         'Baseline': 0.17427822561729264,
+#         'Reform': 0.17757158627182623,
+#         'Change': 1.9
+#     },
+#     'Senior': {
+#         'Baseline': 0.12817646500651358,
+#         'Reform': 0.1370685860340031,
+#         'Change': 6.9
+#     },
+#     'All': {
+#         'Baseline': 0.19913534734369268,
+#         'Reform': 0.20487670454940832,
+#         'Change': 2.9
+#     }
+# }
+
+# # Generate chart for all categories
+# chart = OverallChart(data=data)
+# fig = chart.generate_chart_data()
+# fig.show()