diff --git a/blocksnet/analysis/indicators/socio_economic/social_provision/core.py b/blocksnet/analysis/indicators/socio_economic/social_provision/core.py
index fd87ef8d..1e171d70 100644
--- a/blocksnet/analysis/indicators/socio_economic/social_provision/core.py
+++ b/blocksnet/analysis/indicators/socio_economic/social_provision/core.py
@@ -1,17 +1,24 @@
 import pandas as pd
+from tqdm import tqdm
 from loguru import logger
 from .indicator import SocialProvisionIndicator
-from .schemas import BlocksSchema
-from blocksnet.config import service_types_config
+from blocksnet.config import service_types_config, log_config
+from blocksnet.analysis.provision import competitive_provision, provision_strong_total
 
 
 def calculate_social_provision_indicators(
-    blocks_df: pd.DataFrame,
+    blocks_df: pd.DataFrame, acc_mx: pd.DataFrame
 ) -> tuple[dict[SocialProvisionIndicator, float], list[SocialProvisionIndicator]]:
 
     result = {}
     missing = []
-    for indicator in SocialProvisionIndicator:
+
+    disable_tqdm = log_config.disable_tqdm
+    logger_level = log_config.logger_level
+    log_config.set_disable_tqdm(True)
+    log_config.set_logger_level("ERROR")
+
+    for indicator in tqdm(list(SocialProvisionIndicator), disable=disable_tqdm):
 
         name = indicator.meta.name
         if not name in service_types_config:
@@ -19,20 +26,18 @@ def calculate_social_provision_indicators(
             missing.append(indicator)
             continue
 
-        _, demand, accessibility = service_types_config[name].values()
-
         column = f"capacity_{indicator.meta.name}"
         if not column in blocks_df.columns:
             logger.warning(f"{column} is missing. The indicator is skipped")
             missing.append(indicator)
             continue
 
-        df = BlocksSchema(blocks_df.rename(columns={column: "capacity"}))
-
-        population = df["population"].sum()
-        capacity = df["capacity"].sum()
-        provision = capacity / (population / 1000 * demand)
+        _, demand, accessibility = service_types_config[name].values()
+        df = blocks_df.rename(columns={column: "capacity"})
+        prov_df, _ = competitive_provision(df, acc_mx, accessibility, demand)
+        result[indicator] = provision_strong_total(prov_df)
 
-        result[indicator] = min(1.0, float(provision))
+    log_config.set_disable_tqdm(disable_tqdm)
+    log_config.set_logger_level(logger_level)
 
     return result, missing
diff --git a/blocksnet/analysis/indicators/socio_economic/social_provision/schemas.py b/blocksnet/analysis/indicators/socio_economic/social_provision/schemas.py
deleted file mode 100644
index 706edd2c..00000000
--- a/blocksnet/analysis/indicators/socio_economic/social_provision/schemas.py
+++ /dev/null
@@ -1,8 +0,0 @@
-from pandera import Field
-from pandera.typing import Series
-from blocksnet.utils.validation import DfSchema
-
-
-class BlocksSchema(DfSchema):
-    population: Series[int] = Field(ge=0)
-    capacity: Series[int] = Field(ge=0)
diff --git a/blocksnet/analysis/provision/competivive/core.py b/blocksnet/analysis/provision/competivive/core.py
index e4f46a3f..25bf529e 100644
--- a/blocksnet/analysis/provision/competivive/core.py
+++ b/blocksnet/analysis/provision/competivive/core.py
@@ -149,11 +149,16 @@ def _distribute_demand(
 
 
 def provision_strong_total(blocks_df: pd.DataFrame):
-    return blocks_df[DEMAND_WITHIN_COLUMN].sum() / blocks_df.demand.sum()
+    demand_within = blocks_df[DEMAND_WITHIN_COLUMN].sum()
+    demand = blocks_df.demand.sum()
+    return float(demand_within / demand)
 
 
 def provision_weak_total(blocks_df: pd.DataFrame):
-    return (blocks_df[DEMAND_WITHIN_COLUMN].sum() + blocks_df[DEMAND_WITHOUT_COLUMN].sum()) / blocks_df.demand.sum()
+    demand_within = blocks_df[DEMAND_WITHIN_COLUMN].sum()
+    demand_without = blocks_df[DEMAND_WITHOUT_COLUMN].sum()
+    demand = blocks_df.demand.sum()
+    return float((demand_within + demand_without) / demand)
 
 
 def competitive_provision(
@@ -173,7 +178,7 @@ def competitive_provision(
 
     links = []
     logger.info("Setting and solving LP problems until max depth or break condition reached")
-    for depth in tqdm(range(1, max_depth + 1), disable=log_config.disable_tqdm):
+    for depth in range(1, max_depth + 1):
         blocks_df, depth_links = _distribute_demand(blocks_df, accessibility_matrix, accessibility, depth)
         links.extend(depth_links)
         break_condition = blocks_df[DEMAND_LEFT_COLUMN].sum() == 0 or blocks_df[CAPACITY_LEFT_COLUMN].sum() == 0
diff --git a/blocksnet/preprocessing/imputing/__init__.py b/blocksnet/preprocessing/imputing/__init__.py
index 304a5905..bb10fcb4 100644
--- a/blocksnet/preprocessing/imputing/__init__.py
+++ b/blocksnet/preprocessing/imputing/__init__.py
@@ -1,3 +1,4 @@
 from .buildings import *
 from .services import *
 from .development import *
+from .population import *
diff --git a/blocksnet/preprocessing/imputing/population/__init__.py b/blocksnet/preprocessing/imputing/population/__init__.py
new file mode 100644
index 00000000..9ad2e07b
--- /dev/null
+++ b/blocksnet/preprocessing/imputing/population/__init__.py
@@ -0,0 +1 @@
+from .core import impute_population
diff --git a/blocksnet/preprocessing/imputing/population/core.py b/blocksnet/preprocessing/imputing/population/core.py
new file mode 100644
index 00000000..d4417651
--- /dev/null
+++ b/blocksnet/preprocessing/imputing/population/core.py
@@ -0,0 +1,51 @@
+import pandas as pd
+import numpy as np
+from loguru import logger
+from .schemas import Schema
+
+
+def _impute_population(df: pd.DataFrame, total_population: int) -> pd.DataFrame:
+    df = df.copy()
+    weights = df["living_area"] / df["living_area"].sum()
+    ideal = weights * total_population
+
+    alloc = np.floor(ideal).astype(int)
+    remainder = int(total_population - alloc.sum())
+    fractions = ideal - alloc
+
+    sorted_fractions = fractions.sort_values(ascending=False).head(remainder)
+    fractions_idx = sorted_fractions.index
+
+    alloc.loc[fractions_idx] += 1
+
+    df["population"] = alloc
+    return df
+
+
+def impute_population(df: pd.DataFrame, total_population: int) -> pd.DataFrame:
+    if not isinstance(total_population, int):
+        raise TypeError("Total population must be int")
+    if total_population <= 0:
+        raise ValueError("Total population must be greater than 0")
+    df = Schema(df)
+
+    sum_population = int(df["population"].sum())
+    delta_population = total_population - sum_population
+    if delta_population < 0:
+        raise ValueError(
+            f"Total population must be greater than population sum, got:\n{total_population} - {sum_population} = {delta_population}"
+        )
+    if delta_population == 0:
+        logger.warning("0 population to distribute")
+        return df.fillna(0)
+
+    idx = df[(df["population"].isna()) | ((df["population"] == 0) & (df["living_area"] > 0))].index
+    if len(idx) == 0:
+        logger.warning("No unknown population found")
+        return df
+
+    logger.info(f"Distributing {delta_population} population between {len(idx)} rows")
+
+    sub_df = _impute_population(df.loc[idx], delta_population)
+    df.loc[idx, df.columns] = sub_df
+    return df
diff --git a/blocksnet/preprocessing/imputing/population/schemas.py b/blocksnet/preprocessing/imputing/population/schemas.py
new file mode 100644
index 00000000..062f761a
--- /dev/null
+++ b/blocksnet/preprocessing/imputing/population/schemas.py
@@ -0,0 +1,8 @@
+from pandera import Field
+from pandera.typing import Series
+from blocksnet.utils.validation import DfSchema
+
+
+class Schema(DfSchema):
+    living_area: Series[float] = Field(ge=0)
+    population: Series[float] = Field(ge=0, nullable=True)
diff --git a/examples/analysis/indicators/socio_economic/evaluation.ipynb b/examples/analysis/indicators/socio_economic/evaluation.ipynb
index 453d7467..36f310c1 100644
--- a/examples/analysis/indicators/socio_economic/evaluation.ipynb
+++ b/examples/analysis/indicators/socio_economic/evaluation.ipynb
@@ -286,23 +286,23 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "\u001b[32m2025-10-06 05:59:28.678\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_college is missing. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:28.679\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_extracurricular is missing. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:28.679\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_ambulance is missing. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:28.680\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_special_medical is missing. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:28.681\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_preventive_medical is missing. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:28.682\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_gym is missing. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:28.683\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_stadium is missing. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:28.684\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_orphanage is missing. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:28.684\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_nursing_home is missing. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:28.685\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_social_service_center is missing. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:28.686\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_library is missing. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:28.687\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_cultural_center is missing. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:28.687\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_concert_hall is missing. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:28.688\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_ice_arena is missing. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:28.689\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_eco_trail is missing. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:28.689\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_fire_station is missing. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:28.690\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_tourist_base is missing. The indicator is skipped\u001b[0m\n"
+      "\u001b[32m2025-10-07 12:58:27.987\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_college is missing. The indicator is skipped\u001b[0m\n",
+      "\u001b[32m2025-10-07 12:58:27.988\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_extracurricular is missing. The indicator is skipped\u001b[0m\n",
+      "\u001b[32m2025-10-07 12:58:27.989\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_ambulance is missing. The indicator is skipped\u001b[0m\n",
+      "\u001b[32m2025-10-07 12:58:27.989\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_special_medical is missing. The indicator is skipped\u001b[0m\n",
+      "\u001b[32m2025-10-07 12:58:27.990\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_preventive_medical is missing. The indicator is skipped\u001b[0m\n",
+      "\u001b[32m2025-10-07 12:58:27.990\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_gym is missing. The indicator is skipped\u001b[0m\n",
+      "\u001b[32m2025-10-07 12:58:27.991\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_stadium is missing. The indicator is skipped\u001b[0m\n",
+      "\u001b[32m2025-10-07 12:58:27.991\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_orphanage is missing. The indicator is skipped\u001b[0m\n",
+      "\u001b[32m2025-10-07 12:58:27.992\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_nursing_home is missing. The indicator is skipped\u001b[0m\n",
+      "\u001b[32m2025-10-07 12:58:27.992\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_social_service_center is missing. The indicator is skipped\u001b[0m\n",
+      "\u001b[32m2025-10-07 12:58:27.993\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_library is missing. The indicator is skipped\u001b[0m\n",
+      "\u001b[32m2025-10-07 12:58:27.994\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_cultural_center is missing. The indicator is skipped\u001b[0m\n",
+      "\u001b[32m2025-10-07 12:58:27.994\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_concert_hall is missing. The indicator is skipped\u001b[0m\n",
+      "\u001b[32m2025-10-07 12:58:27.995\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_ice_arena is missing. The indicator is skipped\u001b[0m\n",
+      "\u001b[32m2025-10-07 12:58:27.996\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_eco_trail is missing. The indicator is skipped\u001b[0m\n",
+      "\u001b[32m2025-10-07 12:58:27.996\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_fire_station is missing. The indicator is skipped\u001b[0m\n",
+      "\u001b[32m2025-10-07 12:58:27.997\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_count.core\u001b[0m:\u001b[36mcalculate_social_count_indicators\u001b[0m:\u001b[36m20\u001b[0m - \u001b[33m\u001b[1mcount_tourist_base is missing. The indicator is skipped\u001b[0m\n"
      ]
     }
    ],
@@ -451,72 +451,50 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "\u001b[32m2025-10-06 05:59:28.788\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_provision.core\u001b[0m:\u001b[36mcalculate_social_provision_indicators\u001b[0m:\u001b[36m18\u001b[0m - \u001b[33m\u001b[1mcollege not found in config. The indicator is skipped\u001b[0m\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\u001b[32m2025-10-06 05:59:28.807\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_provision.core\u001b[0m:\u001b[36mcalculate_social_provision_indicators\u001b[0m:\u001b[36m18\u001b[0m - \u001b[33m\u001b[1mextracurricular not found in config. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:28.842\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_provision.core\u001b[0m:\u001b[36mcalculate_social_provision_indicators\u001b[0m:\u001b[36m18\u001b[0m - \u001b[33m\u001b[1mambulance not found in config. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:28.859\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_provision.core\u001b[0m:\u001b[36mcalculate_social_provision_indicators\u001b[0m:\u001b[36m18\u001b[0m - \u001b[33m\u001b[1mspecial_medical not found in config. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:28.860\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_provision.core\u001b[0m:\u001b[36mcalculate_social_provision_indicators\u001b[0m:\u001b[36m18\u001b[0m - \u001b[33m\u001b[1mpreventive_medical not found in config. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:28.877\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_provision.core\u001b[0m:\u001b[36mcalculate_social_provision_indicators\u001b[0m:\u001b[36m18\u001b[0m - \u001b[33m\u001b[1mgym not found in config. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:28.914\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_provision.core\u001b[0m:\u001b[36mcalculate_social_provision_indicators\u001b[0m:\u001b[36m26\u001b[0m - \u001b[33m\u001b[1mcapacity_stadium is missing. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:28.915\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_provision.core\u001b[0m:\u001b[36mcalculate_social_provision_indicators\u001b[0m:\u001b[36m18\u001b[0m - \u001b[33m\u001b[1morphanage not found in config. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:28.915\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_provision.core\u001b[0m:\u001b[36mcalculate_social_provision_indicators\u001b[0m:\u001b[36m26\u001b[0m - \u001b[33m\u001b[1mcapacity_nursing_home is missing. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:28.916\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_provision.core\u001b[0m:\u001b[36mcalculate_social_provision_indicators\u001b[0m:\u001b[36m18\u001b[0m - \u001b[33m\u001b[1msocial_service_center not found in config. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:28.966\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_provision.core\u001b[0m:\u001b[36mcalculate_social_provision_indicators\u001b[0m:\u001b[36m26\u001b[0m - \u001b[33m\u001b[1mcapacity_library is missing. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:28.999\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_provision.core\u001b[0m:\u001b[36mcalculate_social_provision_indicators\u001b[0m:\u001b[36m18\u001b[0m - \u001b[33m\u001b[1mcultural_center not found in config. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:29.255\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_provision.core\u001b[0m:\u001b[36mcalculate_social_provision_indicators\u001b[0m:\u001b[36m18\u001b[0m - \u001b[33m\u001b[1mconcert_hall not found in config. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:29.256\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_provision.core\u001b[0m:\u001b[36mcalculate_social_provision_indicators\u001b[0m:\u001b[36m18\u001b[0m - \u001b[33m\u001b[1mice_arena not found in config. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:29.302\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_provision.core\u001b[0m:\u001b[36mcalculate_social_provision_indicators\u001b[0m:\u001b[36m18\u001b[0m - \u001b[33m\u001b[1meco_trail not found in config. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:29.303\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_provision.core\u001b[0m:\u001b[36mcalculate_social_provision_indicators\u001b[0m:\u001b[36m18\u001b[0m - \u001b[33m\u001b[1mfire_station not found in config. The indicator is skipped\u001b[0m\n",
-      "\u001b[32m2025-10-06 05:59:29.349\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.analysis.indicators.socio_economic.social_provision.core\u001b[0m:\u001b[36mcalculate_social_provision_indicators\u001b[0m:\u001b[36m18\u001b[0m - \u001b[33m\u001b[1mtourist_base not found in config. The indicator is skipped\u001b[0m\n"
+      "100%|██████████| 39/39 [24:11<00:00, 37.22s/it]\n"
      ]
     }
    ],
    "source": [
     "from blocksnet.analysis.indicators.socio_economic import calculate_social_provision_indicators\n",
     "\n",
-    "sp_indicators, missing_sp_indicators = calculate_social_provision_indicators(blocks_gdf)"
+    "sp_indicators, missing_sp_indicators = calculate_social_provision_indicators(blocks_gdf, acc_mx)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 23,
    "id": "b63380e6",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "{Kindergarten: 1.0,\n",
-       " School: 0.7439112280591567,\n",
+       "{Kindergarten: 0.8603016459402336,\n",
+       " School: 0.7436043742686855,\n",
        " University: 1.0,\n",
        " Hospital: 1.0,\n",
-       " Polyclinic: 1.0,\n",
-       " Sanatorium: 0.6188338449201727,\n",
-       " Pharmacy: 0.5297230371339258,\n",
-       " Swimming pool: 0.4204798326698406,\n",
+       " Polyclinic: 0.9352319576749356,\n",
+       " Sanatorium: 0.5124186600678214,\n",
+       " Pharmacy: 0.5296512053038243,\n",
+       " Swimming pool: 0.4102340322914035,\n",
        " Pitch: 1.0,\n",
-       " Post: 0.13247488258333462,\n",
-       " Bank: 1.0,\n",
-       " Multifunctional center: 0.08335195640885756,\n",
+       " Post: 0.13060686015831136,\n",
+       " Bank: 0.9995247712961863,\n",
+       " Multifunctional center: 0.08335996201988478,\n",
        " Museum: 1.0,\n",
        " Theatre: 1.0,\n",
        " Cinema: 1.0,\n",
-       " Mall: 1.0,\n",
-       " Park: 1.0,\n",
-       " Beach: 0.4671288110663427,\n",
-       " Police: 1.0,\n",
+       " Mall: 0.9998162651294182,\n",
+       " Park: 0.9986561970132031,\n",
+       " Beach: 0.46726059685989374,\n",
+       " Police: 0.9901125759146793,\n",
        " Hotel: 1.0,\n",
-       " Hostel: 0.2422622744122756,\n",
-       " Cafe: 0.6083464972916206}"
+       " Hostel: 0.2435303954157065,\n",
+       " Cafe: 0.6058774519835122}"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 23,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -527,7 +505,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 24,
    "id": "3f07260e",
    "metadata": {},
    "outputs": [
@@ -553,7 +531,7 @@
        " Tourist base]"
       ]
      },
-     "execution_count": 18,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     }
diff --git a/examples/preprocessing/imputing/population.ipynb b/examples/preprocessing/imputing/population.ipynb
new file mode 100644
index 00000000..b9968d3d
--- /dev/null
+++ b/examples/preprocessing/imputing/population.ipynb
@@ -0,0 +1,488 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "2b501d14",
+   "metadata": {},
+   "source": [
+    "# Population imputing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 86,
+   "id": "3f00b280",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.microsoft.datawrangler.viewer.v0+json": {
+       "columns": [
+        {
+         "name": "index",
+         "rawType": "int64",
+         "type": "integer"
+        },
+        {
+         "name": "living_area",
+         "rawType": "float64",
+         "type": "float"
+        },
+        {
+         "name": "population",
+         "rawType": "float64",
+         "type": "float"
+        }
+       ],
+       "ref": "d0ae0fbf-714d-43cf-8079-1e501f7b6380",
+       "rows": [
+        [
+         "0",
+         "0.0",
+         "0.0"
+        ],
+        [
+         "1",
+         "0.0",
+         "0.0"
+        ],
+        [
+         "2",
+         "4197.188632965088",
+         "109.0"
+        ],
+        [
+         "3",
+         "3033.795606613159",
+         "77.0"
+        ],
+        [
+         "4",
+         "20860.965881347656",
+         "431.0"
+        ]
+       ],
+       "shape": {
+        "columns": 2,
+        "rows": 5
+       }
+      },
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>living_area</th>\n",
+       "      <th>population</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>4197.188633</td>\n",
+       "      <td>109.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3033.795607</td>\n",
+       "      <td>77.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>20860.965881</td>\n",
+       "      <td>431.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    living_area  population\n",
+       "0      0.000000         0.0\n",
+       "1      0.000000         0.0\n",
+       "2   4197.188633       109.0\n",
+       "3   3033.795607        77.0\n",
+       "4  20860.965881       431.0"
+      ]
+     },
+     "execution_count": 86,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "blocks_df = pd.read_pickle('./../../data/saint_petersburg/blocks.pickle')[['living_area', 'population']]\n",
+    "blocks_df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 87,
+   "id": "e75187b0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.microsoft.datawrangler.viewer.v0+json": {
+       "columns": [
+        {
+         "name": "index",
+         "rawType": "int64",
+         "type": "integer"
+        },
+        {
+         "name": "living_area",
+         "rawType": "float64",
+         "type": "float"
+        },
+        {
+         "name": "population",
+         "rawType": "float64",
+         "type": "float"
+        }
+       ],
+       "ref": "dd88a832-6ba9-4c5c-8256-787018924ebd",
+       "rows": [
+        [
+         "0",
+         "0.0",
+         null
+        ],
+        [
+         "1",
+         "0.0",
+         "0.0"
+        ],
+        [
+         "2",
+         "4197.188632965088",
+         "109.0"
+        ],
+        [
+         "3",
+         "3033.795606613159",
+         null
+        ],
+        [
+         "4",
+         "20860.965881347656",
+         "431.0"
+        ]
+       ],
+       "shape": {
+        "columns": 2,
+        "rows": 5
+       }
+      },
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>living_area</th>\n",
+       "      <th>population</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>4197.188633</td>\n",
+       "      <td>109.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3033.795607</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>20860.965881</td>\n",
+       "      <td>431.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    living_area  population\n",
+       "0      0.000000         NaN\n",
+       "1      0.000000         0.0\n",
+       "2   4197.188633       109.0\n",
+       "3   3033.795607         NaN\n",
+       "4  20860.965881       431.0"
+      ]
+     },
+     "execution_count": 87,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "frac = 0.2  \n",
+    "\n",
+    "np.random.seed(42)\n",
+    "\n",
+    "n = int(len(blocks_df) * frac)\n",
+    "idx = np.random.choice(blocks_df.index, size=n, replace=False)\n",
+    "\n",
+    "blocks_df.loc[idx, \"population\"] = None\n",
+    "blocks_df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "id": "96ac2a0b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "np.float64(4410417.0)"
+      ]
+     },
+     "execution_count": 88,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "blocks_df.population.sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 89,
+   "id": "f0a8bdb3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m2025-10-07 19:38:54.748\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mblocksnet.preprocessing.imputing.population.core\u001b[0m:\u001b[36mimpute_population\u001b[0m:\u001b[36m43\u001b[0m - \u001b[1mDistributing 1589583 population between 1906 rows\u001b[0m\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.microsoft.datawrangler.viewer.v0+json": {
+       "columns": [
+        {
+         "name": "index",
+         "rawType": "int64",
+         "type": "integer"
+        },
+        {
+         "name": "living_area",
+         "rawType": "float64",
+         "type": "float"
+        },
+        {
+         "name": "population",
+         "rawType": "float64",
+         "type": "float"
+        }
+       ],
+       "ref": "2b263ed2-e959-4658-b2e9-008f42541b38",
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+         "4197.188632965088",
+         "109.0"
+        ],
+        [
+         "3",
+         "3033.795606613159",
+         "139.0"
+        ],
+        [
+         "4",
+         "20860.965881347656",
+         "431.0"
+        ]
+       ],
+       "shape": {
+        "columns": 2,
+        "rows": 5
+       }
+      },
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>living_area</th>\n",
+       "      <th>population</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>4197.188633</td>\n",
+       "      <td>109.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3033.795607</td>\n",
+       "      <td>139.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>20860.965881</td>\n",
+       "      <td>431.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    living_area  population\n",
+       "0      0.000000         0.0\n",
+       "1      0.000000         0.0\n",
+       "2   4197.188633       109.0\n",
+       "3   3033.795607       139.0\n",
+       "4  20860.965881       431.0"
+      ]
+     },
+     "execution_count": 89,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from blocksnet.preprocessing.imputing import impute_population\n",
+    "\n",
+    "pop_df = impute_population(blocks_df, 6_000_000)\n",
+    "pop_df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "id": "46e6d8c2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "np.float64(6000000.0)"
+      ]
+     },
+     "execution_count": 91,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pop_df.population.sum()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}