View difference between Paste ID: XkrBRDvh and xfjBCcm9

 # Data sources:
-# New study permits: 40k–60k
+# New study permits: 40k-60k
-# New work permits: 280k–360k
+# New work permits: 280k-360k
 # Study permits (new): capped at 437k for 2025. H1 likely 40k-60k new approvals (cap + seasonality).
 # Work permits (new): ~825k finalized Jan-Jul, but 40-50% are renewals. H1 ~280k-360k new approvals.
 # Combined H1 2025 “new” study+work ≈ 320k-420k.
 # StatsCan shows NPR stock fell in Q1 2025, meaning exits/extensions outweighed new arrivals.
 # https://www.canada.ca/en/immigration-refugees-citizenship/corporate/mandate/corporate-initiatives/levels/inventories-backlogs.html
 # https://www.canada.ca/en/immigration-refugees-citizenship/news/notices/2025-provincial-territorial-allocations-under-international-student-cap.html https://open.canada.ca/data/en/dataset/9b34e712-513f-44e9-babf-9df4f7256550
 # https://open.canada.ca/data/en/dataset/90115b00-f9b8-49e8-afa3-b4cff8facaee
 # https://open.canada.ca/data/en/dataset/360024f2-17e9-4558-bfc1-3616485d65b9
 # https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1710012101
 # https://www150.statcan.gc.ca/n1/daily-quotidien/250618/dq250618a-eng.htm
 # Births: https://www150.statcan.gc.ca/t1/tbl1/en/dtl!downloadDbLoadingData-nonTraduit.action?pid=1310041501&latestN=0&startDate=20000101&endDate=99990101&csvLocale=en&selectedMembers=%5B%5B1%5D%2C%5B%5D%2C%5B1%5D%5D&checkedLevels=1D1%2C1D2 (https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1310041501) - 351,878
 # Deaths: https://www150.statcan.gc.ca/t1/tbl1/en/dtl!downloadDbLoadingData-nonTraduit.action?pid=1310070801&latestN=0&startDate=20000101&endDate=99990101&csvLocale=en&selectedMembers=%5B%5B1%5D%2C%5B1%2C2%2C3%2C4%2C5%2C6%2C7%2C8%2C9%2C10%2C11%2C12%2C13%5D%2C%5B1%2C2%5D%5D&checkedLevels= (https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1310070801) - 326,215
 
 import matplotlib.pyplot as plt
 from matplotlib.lines import Line2D
-import numpy as np
+
 TOTAL_POP = 41_290_000
 BIRTHS = 351_878
-total_population = 41_290_000
+DEATHS = 326_215
-births = 351_878
+OBSERVED_POP_CHANGE = 20_107
-deaths = 326_215
+NATURAL_INCREASE = BIRTHS - DEATHS
-observed_pop_change = 20_107
+
-natural_increase = births - deaths
+NEW_STUDY_RANGE = (40_000, 60_000)
 NEW_WORK_RANGE  = (280_000, 360_000)
-new_study_range = (40_000, 60_000)
+RENEWED_WORK_RANGE = (330_000, 410_000)
-new_work_range  = (280_000, 360_000)
+
-renewed_work_range = (330_000, 410_000)
+STUDENT_EXPIRY_SHARE_RANGE = (0.30, 0.40)
-new_visas_range = (new_study_range[0] + new_work_range[0], new_study_range[1] + new_work_range[1])
+WORK_EXPIRY_SHARE_RANGE    = (0.60, 0.70)
 
-expiries_total_range = (
+def midpoint(lo: int, hi: int) -> float:
-    natural_increase + new_visas_range[0] + renewed_work_range[0] - observed_pop_change,
+    return (lo + hi) / 2.0
-    natural_increase + new_visas_range[1] + renewed_work_range[1] - observed_pop_change
+
 def halfspan(lo: int, hi: int) -> float:
     return (hi - lo) / 2.0
-student_share_range = (0.30, 0.40)
+
-work_share_range    = (0.60, 0.70)
+NEW_VISAS_RANGE = (NEW_STUDY_RANGE[0] + NEW_WORK_RANGE[0],
                    NEW_STUDY_RANGE[1] + NEW_WORK_RANGE[1])
-expiring_students_range = (int(expiries_total_range[0] * student_share_range[0]),
+
-                           int(expiries_total_range[1] * student_share_range[1]))
+EXPIRIES_TOTAL_RANGE = (
-expiring_work_range = (int(expiries_total_range[0] * work_share_range[0]),
+    NATURAL_INCREASE + NEW_VISAS_RANGE[0] + RENEWED_WORK_RANGE[0] - OBSERVED_POP_CHANGE,
-                       int(expiries_total_range[1] * work_share_range[1]))
+    NATURAL_INCREASE + NEW_VISAS_RANGE[1] + RENEWED_WORK_RANGE[1] - OBSERVED_POP_CHANGE
 )
-def midpoint(lo, hi): return (lo + hi) / 2.0
+
-def halfspan(lo, hi): return (hi - lo) / 2.0
+EXPIRING_STUDENTS_RANGE = (
     int(EXPIRIES_TOTAL_RANGE[0] * STUDENT_EXPIRY_SHARE_RANGE[0]),
     int(EXPIRIES_TOTAL_RANGE[1] * STUDENT_EXPIRY_SHARE_RANGE[1]),
 )
 EXPIRING_WORK_RANGE = (
     int(EXPIRIES_TOTAL_RANGE[0] * WORK_EXPIRY_SHARE_RANGE[0]),
     int(EXPIRIES_TOTAL_RANGE[1] * WORK_EXPIRY_SHARE_RANGE[1]),
 )
 
 categories = [
     "Births",
     "Deaths",
-values = np.array([
+
-    births,
+
-    -deaths,
+
-    midpoint(*new_visas_range),
+
-    midpoint(*renewed_work_range),
+
-    -midpoint(*expiring_students_range),
+
-    -midpoint(*expiring_work_range),
+
-    observed_pop_change
+values = [
-], dtype=float)
+    float(BIRTHS),
     -float(DEATHS),
-yerr = np.array([
+    midpoint(*NEW_VISAS_RANGE),
-    0,
+    midpoint(*RENEWED_WORK_RANGE),
-    0,
+    -midpoint(*EXPIRING_STUDENTS_RANGE),
-    halfspan(*new_visas_range),
+    -midpoint(*EXPIRING_WORK_RANGE),
-    halfspan(*renewed_work_range),
+    float(OBSERVED_POP_CHANGE),
-    halfspan(*expiring_students_range),
+
-    halfspan(*expiring_work_range),
+
-    0
+yerr = [
-], dtype=float)
+    0.0,
     0.0,
     halfspan(*NEW_VISAS_RANGE),
     halfspan(*RENEWED_WORK_RANGE),
     halfspan(*EXPIRING_STUDENTS_RANGE),
     halfspan(*EXPIRING_WORK_RANGE),
     0.0,
-plt.figure(figsize=(13,7))
+
 
 colors = [
     "#2ca02c", "#d62728", "#1f77b4",
     "#9467bd", "#ff7f0e", "#8c564b", "#7f7f7f"
 ]
 
 plt.figure(figsize=(13, 7))
 bars = plt.bar(categories, values, color=colors)
 
-    x = bar.get_x() + bar.get_width()/2
+
     if e > 0:
         plt.errorbar(i, v, yerr=e, fmt='none', capsize=6, elinewidth=1.5, ecolor='black')
         plt.scatter([i], [v], s=40, marker='D', edgecolor='black', zorder=3)
-        txt = f"central estimate*: {int(round(v)):,}\nrange: {int(round(lo)):,}–{int(round(hi)):,}"
+
 pad = 120_000
 for bar, v, e in zip(bars, values, yerr):
     x = bar.get_x() + bar.get_width() / 2
     va = 'bottom' if v >= 0 else 'top'
     if e > 0:
         lo, hi = v - e, v + e
         txt = f"central estimate*: {int(round(v)):,}\nrange: {int(round(lo)):,}-{int(round(hi)):,}"
     else:
         txt = f"{int(round(abs(v))):,}"
     y = v + (pad if v >= 0 else -pad)
     plt.text(x, y, txt, ha='center', va=va, fontsize=9)
 
 def add_group_bracket(ax, x0, x1, y, label, invert=False):
     if not invert:
         ax.plot([x0, x0, x1, x1], [y, y+40_000, y+40_000, y], lw=1.5, color='black')
         ax.text((x0+x1)/2, y+55_000, label, ha='center', va='bottom', fontsize=10)
     else:
         ax.plot([x0, x0, x1, x1], [y, y-40_000, y-40_000, y], lw=1.5, color='black')
         ax.text((x0+x1)/2, y-55_000, label, ha='center', va='top', fontsize=10)
 
 ax = plt.gca()
 
 nv_idx, rw_idx = 2, 3
 expS_idx, expW_idx = 4, 5
 
 y_nv = values[nv_idx] + yerr[nv_idx]
 y_rw = values[rw_idx] + yerr[rw_idx]
 y_expS = values[expS_idx] - yerr[expS_idx]
 y_expW = values[expW_idx] - yerr[expW_idx]
 
 y_group_top = max(y_nv, y_rw) + 200_000
 sum_new_renewed = int(round(values[nv_idx] + values[rw_idx]))
 add_group_bracket(ax, nv_idx, rw_idx, y_group_top, f"New+Renewed visas (sum): {sum_new_renewed:,}")
-    Line2D([0], [0], marker='D', color='w', markeredgecolor='black', label='Central estimate*', markersize=7)
+
 y_group_bottom = min(y_expS, y_expW) - 220_000
 sum_expiries = int(round(abs(values[expS_idx] + values[expW_idx])))
 add_group_bracket(ax, expS_idx, expW_idx, y_group_bottom, f"All expiries (sum): {sum_expiries:,}", invert=True)
 
 legend_elems = [
     Line2D([0], [0], color='black', lw=1.5, label='Range (vertical line)'),
     Line2D([0], [0], marker='D', color='w', markeredgecolor='black', label='Central estimate*', markersize=7),
-upper = max(values + yerr) * 1.7 + 200_000
+
-lower = min(values - yerr) * 1.7 - 200_000
+
 
 plt.axhline(0, linewidth=0.9, color='black')
 plt.title("Population Components: Canada (H1 2025)\nRanges shown with central estimate*", pad=16)
 plt.ylabel("Count (people)")
 
 upper = max((v + e) for v, e in zip(values, yerr)) * 1.7 + 200_000
 lower = min((v - e) for v, e in zip(values, yerr)) * 1.7 - 200_000
 plt.ylim(lower, upper)
 
 plt.xticks(rotation=10)
 plt.tight_layout()
 
 plt.figtext(
     0.5, 0.01,
     "*Estimate based on IRCC/StatCan data and a heuristic expiry split (30-40% students, 60-70% workers).",
     ha="center", fontsize=9, style="italic"
 )
 
 plt.show()