diff --git a/blocksnet/analysis/network/origin_destination/core.py b/blocksnet/analysis/network/origin_destination/core.py
index b1c87706..2906ed79 100644
--- a/blocksnet/analysis/network/origin_destination/core.py
+++ b/blocksnet/analysis/network/origin_destination/core.py
@@ -25,6 +25,49 @@
 DEFAULT_ACCESSIBILITY = 10
 
 
+def _round_probabilistic_row_to_int(prob_row: pd.Series, trips: int) -> pd.Series:
+
+    # Convert one probability row into integer trips preserving row sum exactly.
+
+    raw = prob_row.to_numpy(dtype=float) * float(trips)
+    floored = np.floor(raw).astype("int64")
+    remainder = int(trips - floored.sum())
+
+    if remainder > 0:
+        fractional = raw - floored
+        order = np.argsort(-fractional, kind="mergesort")
+        floored[order[:remainder]] += 1
+
+    return pd.Series(floored, index=prob_row.index, dtype="int64")
+
+
+def _integerize_origin_constrained_od(od_prob_mx: pd.DataFrame, demand: pd.Series) -> pd.DataFrame:
+
+    # Integerize origin-constrained OD probabilities preserving integer row demand.
+
+    od_int = pd.DataFrame(0, index=od_prob_mx.index, columns=od_prob_mx.columns, dtype="int64")
+    demand_int = demand.round().clip(lower=0).astype("int64")
+
+    for origin, trips in demand_int.items():
+        trips = int(trips)
+        if trips <= 0:
+            continue
+
+        prob_row = od_prob_mx.loc[origin].astype(float)
+        row_sum = float(prob_row.sum())
+
+        if row_sum <= 0.0:
+            prob_row[:] = 0.0
+            if origin in prob_row.index:
+                prob_row.loc[origin] = 1.0
+        else:
+            prob_row = prob_row / row_sum
+
+        od_int.loc[origin] = _round_probabilistic_row_to_int(prob_row, trips)
+
+    return od_int
+
+
 def _calculate_nodes_weights(blocks_df: gpd.GeoDataFrame, acc_mx: pd.DataFrame, accessibility: float) -> pd.DataFrame:
 
     logger.info("Identifying nearest nodes to blocks")
@@ -45,9 +88,9 @@ def _calculate_nodes_weights(blocks_df: gpd.GeoDataFrame, acc_mx: pd.DataFrame,
     return nodes_df
 
 
-def _calculate_diversity(blocks_df: pd.DataFrame, services_dfs: list[pd.DataFrame]) -> pd.DataFrame:
+def _calculate_diversity(blocks_df: pd.DataFrame, services_count_dfs: list[pd.DataFrame]) -> pd.DataFrame:
     logger.info("Calculating diversity and density")
-    diversity_df = shannon_diversity(services_dfs)
+    diversity_df = shannon_diversity(services_count_dfs)
     blocks_df = blocks_df.join(diversity_df)
     blocks_df[DENSITY_COLUMN] = blocks_df[COUNT_COLUMN] / blocks_df.site_area
     return blocks_df
@@ -69,11 +112,20 @@ def _calculate_attractiveness(blocks_df: pd.DataFrame, lu_consts: dict[LandUse,
 def _calculate_od_mx(nodes_df: pd.DataFrame, acc_mx: pd.DataFrame) -> pd.DataFrame:
     logger.info("Calculating origin destination matrix")
     acc_mx = acc_mx.replace(0, np.nan)
-    return pd.DataFrame(
-        np.outer(nodes_df[POPULATION_COLUMN], nodes_df[ATTRACTIVENESS_COLUMN]) / acc_mx,
-        index=acc_mx.index,
-        columns=acc_mx.columns,
-    ).fillna(0.0)
+
+    # Origin-constrained gravity model:
+    # row sums match origin population and total OD matches total population.
+    gravity_weights = (1.0 / acc_mx).mul(nodes_df[ATTRACTIVENESS_COLUMN], axis=1).fillna(0.0)
+
+    # Preserve demand for isolated origins as intrazonal flow.
+    empty_rows = gravity_weights.sum(axis=1).eq(0.0)
+    for node_id in gravity_weights.index[empty_rows]:
+        gravity_weights.loc[node_id, node_id] = 1.0
+
+    row_sums = gravity_weights.sum(axis=1).replace(0.0, np.nan)
+    od_prob_mx = gravity_weights.div(row_sums, axis=0).fillna(0.0)
+
+    return _integerize_origin_constrained_od(od_prob_mx, nodes_df[POPULATION_COLUMN])
 
 
 def _validate_input(blocks_df: pd.DataFrame, blocks_to_nodes_mx: pd.DataFrame, nodes_to_nodes_mx: pd.DataFrame):
@@ -90,22 +142,93 @@ def origin_destination_matrix(
     blocks_df: pd.DataFrame,
     blocks_to_nodes_mx: pd.DataFrame,
     nodes_to_nodes_mx: pd.DataFrame,
-    services_dfs: list[pd.DataFrame],
+    services_count_dfs: list[pd.DataFrame],
     accessibility: float = DEFAULT_ACCESSIBILITY,
     lu_consts: dict[LandUse, float] = LU_CONSTS,
 ) -> pd.DataFrame:
+    
+    """
+    Build an origin-constrained OD matrix from block attributes and accessibility matrices.
+
+    The function estimates an integer-valued origin-destination (OD) matrix between network nodes
+    using an origin-constrained gravity model. Trip productions are derived from block population
+    (after distributing blocks to nearby nodes), while trip attractions are proportional to a
+    composite attractiveness score based on service density, service diversity (Shannon index),
+    and a land-use constant.
+
+    Parameters
+    ----------
+    blocks_df : pandas.DataFrame
+        Table of blocks (zones). Index must uniquely identify blocks and must match
+        ``blocks_to_nodes_mx.index``. Required columns are validated/coerced by ``BlocksSchema``.
+        Expected fields include at least:
+        - ``population`` (number of people living in block, a field mapped to :data:`POPULATION_COLUMN`)
+        - ``land_use`` (type of land use for urban block, values of :class:`blocksnet.enums.LandUse`)
+        - ``site_area`` (used for service density)
+    blocks_to_nodes_mx : pandas.DataFrame
+        Block-to-node generalized cost matrix (e.g., walk time), with blocks on rows and network
+        nodes on columns. Used to distribute each block's population/attractiveness across nearby
+        nodes. Its index must match ``blocks_df.index``.
+    nodes_to_nodes_mx : pandas.DataFrame
+        Node-to-node generalized cost matrix (e.g., travel time). Must be square with identical
+        index/columns, and its index must match ``blocks_to_nodes_mx.columns``.
+        Zeros are treated as missing costs for the gravity model.
+    services_count_dfs : list[pandas.DataFrame]
+        List of service-count tables (typically one per service category/type) used to compute
+        Shannon diversity and total service counts per block. Each table must be compatible with
+        :func:`blocksnet.analysis.diversity.shannon.core.shannon_diversity`.
+    accessibility : float, default=DEFAULT_ACCESSIBILITY
+        Threshold on ``blocks_to_nodes_mx`` costs defining which nodes are considered reachable
+        from a block for distribution. For each block, nodes with cost ``<= accessibility`` are
+        considered; additionally, the nearest node is always included to avoid empty supports.
+    lu_consts : dict[LandUse, float], default=LU_CONSTS
+        Mapping from land-use type to an additive attractiveness constant. If a block land-use is
+        missing in the mapping, :data:`DEFAULT_LU_CONST` is used.
+
+    Returns
+    -------
+    pandas.DataFrame
+        Integer OD matrix between network nodes. Index and columns correspond to
+        ``nodes_to_nodes_mx.index``. Row sums are equal to the corresponding origin node population
+        (rounded to integers and clipped at zero). Total trips equal the total distributed
+        population (after rounding).
+
+    Notes
+    -----
+    - This is an *origin-constrained* model: productions (row sums) are fixed by origin population,
+      while attractions (column sums) are not explicitly constrained.
+    - Blocks are not OD zones directly: block attributes are first distributed to network nodes
+      via inverse-cost weights derived from ``blocks_to_nodes_mx``. The OD matrix is then computed
+      between nodes.
+    - If an origin node has no valid outgoing gravity weights (e.g., all costs missing), its demand
+      is assigned as intrazonal flow (diagonal element).
+    - Integerization preserves each origin row sum exactly using largest-remainder rounding.
+
+    Raises
+    ------
+    ValueError
+        If indices/columns of the input matrices are inconsistent (do not align), or if the block
+        table does not satisfy the expected schema after validation.
+
+    Examples
+    --------
+    >>> od_nodes = origin_destination_matrix(
+    ...     blocks_df=blocks,
+    ...     blocks_to_nodes_mx=blocks_to_nodes,
+    ...     nodes_to_nodes_mx=nodes_to_nodes,
+    ...     services_count_dfs=[shops_counts, schools_counts],
+    ...     accessibility=10.0,
+    ... )
+    >>> od_nodes.shape
+    (len(nodes_to_nodes.index), len(nodes_to_nodes.index))
+    """
 
     blocks_df = BlocksSchema(blocks_df)
     _validate_input(blocks_df, blocks_to_nodes_mx, nodes_to_nodes_mx)
 
-    blocks_df = _calculate_diversity(blocks_df, services_dfs)
+    blocks_df = _calculate_diversity(blocks_df, services_count_dfs)
     blocks_df = _calculate_attractiveness(blocks_df, lu_consts)
 
-    scaler = MinMaxScaler()
-    blocks_df[[POPULATION_COLUMN, ATTRACTIVENESS_COLUMN]] = scaler.fit_transform(
-        blocks_df[[POPULATION_COLUMN, ATTRACTIVENESS_COLUMN]]
-    )
-
     nodes_gdf = _calculate_nodes_weights(blocks_df, blocks_to_nodes_mx, accessibility)
 
     return _calculate_od_mx(nodes_gdf, nodes_to_nodes_mx)
diff --git a/blocksnet/analysis/network/road_congestion/core.py b/blocksnet/analysis/network/road_congestion/core.py
index 542240ce..d3ce576d 100644
--- a/blocksnet/analysis/network/road_congestion/core.py
+++ b/blocksnet/analysis/network/road_congestion/core.py
@@ -1,5 +1,6 @@
 import pandas as pd
 import networkx as nx
+import numpy as np
 from blocksnet.relations.accessibility import validate_accessibility_graph
 from ..origin_destination import validate_od_matrix
 from tqdm import tqdm
@@ -8,28 +9,202 @@
 
 CONGESTION_KEY = "congestion"
 
+LANE_CAPACITY = 1000
 
-def road_congestion(od_mx: pd.DataFrame, graph: nx.Graph, weight_key: str = "time_min"):
+LANE_COEF = {
+    1: 1.0,
+    2: 0.95,
+    3: 0.90,
+    4: 0.86,
+    5: 0.84,
+    6: 0.82,
+}
 
-    validate_od_matrix(od_mx, graph)
-    validate_accessibility_graph(graph, weight_key)
-    graph = graph.copy()
 
-    logger.info("Calculating shortest path")
-    paths = dict(nx.all_pairs_dijkstra_path(graph, weight=weight_key))
+def _get_capacity_by_lanes(lanes):
+    capacity = LANE_CAPACITY * LANE_COEF[lanes] * lanes
 
-    logger.info("Evaluating congestion")
-    for edge in graph.edges(data=True):
-        data = edge[2]
-        data[CONGESTION_KEY] = 0.0
+    return capacity
 
+def _normalize_lanes(G: nx.Graph, default: int = 1) -> nx.Graph:
+    for _, _, data in G.edges(data=True):
+        raw = data.get("lanes", None)
+
+        # list -> возьмём минимальное 
+        if isinstance(raw, list):
+            raw = min(raw) if raw else None
+
+        # str -> попробуем вытащить число
+        if isinstance(raw, str):
+            s = raw.strip()
+            for sep in [";", "|", ","]:
+                if sep in s:
+                    s = s.split(sep)[0].strip()
+                    break
+            raw = s
+
+        try:
+            lanes = int(float(raw))  
+        except (TypeError, ValueError):
+            lanes = default
+
+        if lanes < 1:
+            lanes = default
+
+        data["lanes"] = lanes
+
+    return G
+
+
+def _add_intensity(G: nx.Graph, intensity_default: float = 0) -> nx.Graph:
+
+    for _, _, data in G.edges(data=True):
+        data["intensity"] = intensity_default
+
+    return G
+
+
+def _add_capacity(G: nx.Graph) -> nx.Graph:
+    for _, _, data in G.edges(data=True):
+        lanes = data.get("lanes", 1)
+        data["capacity"] = _get_capacity_by_lanes(lanes)
+    return G
+
+
+def _peprocess_graph(G: nx.Graph) -> nx.Graph:
+    H = G.copy()
+    _normalize_lanes(H)
+    _add_intensity(H)
+    _add_capacity(H)
+    return H
+
+
+def road_congestion(od_mx: pd.DataFrame, G: nx.MultiDiGraph, weight_key: str = "time_min") -> nx.MultiDiGraph:
+
+    """
+    Assign OD demand to a road network and compute per-edge congestion indicators.
+
+    This function performs a discrete, trip-by-trip shortest-path assignment on a directed
+    multigraph. For each OD pair `(i, j)` the demand value is rounded to an integer number of
+    trips. Each trip is routed along the current shortest path (Dijkstra) using `weight_key`
+    as edge cost. Traversed edges accumulate `intensity` (assigned trip count).
+
+    Edge capacities are derived from the `lanes` attribute and a simple lanes-based coefficient
+    model:
+
+    - If `lanes` is missing or invalid, it is treated as 1.
+    - Capacity is computed as::
+
+        capacity = LANE_CAPACITY * LANE_COEF[lanes] * lanes
+
+      where `LANE_CAPACITY = 1000` and `LANE_COEF` is defined for lanes 1..6.
+
+    During assignment, the routing graph is updated: if an edge becomes oversaturated
+    (`intensity / capacity > 1.0`) that specific multiedge (key) is removed from further routing.
+    The returned graph preserves the full original edge set (after preprocessing) and contains
+    the final `intensity` and `congestion_level` values.
+
+    Parameters
+    ----------
+    od_mx : pandas.DataFrame
+        Origin-destination matrix with node identifiers as index and columns. Values represent
+        demand between zones/nodes and are interpreted as trip counts after rounding to the
+        nearest integer. OD pairs with `i == j` or `demand <= 0` are skipped.
+    G : networkx.MultiDiGraph
+        Directed road network graph. Nodes must include all IDs present in `od_mx`.
+        Edges are expected to contain `weight_key` (e.g., travel time in minutes). The `lanes`
+        attribute is optional and may be `int`, `float`, `str` (e.g., "2", "2;1"), or `list`
+        (the minimal value is taken). Missing/invalid values are coerced to 1.
+    weight_key : str, default="time_min"
+        Edge attribute used as the weight for shortest-path routing.
+
+    Returns
+    -------
+    networkx.MultiDiGraph
+        A copy of the (preprocessed) input graph with added/updated edge attributes:
+
+        - `lanes` : int
+            Normalized number of lanes (at least 1).
+        - `capacity` : float
+            Per-edge capacity derived from `lanes`.
+        - `intensity` : float
+            Number of assigned trips traversing the edge.
+        - `congestion_level` : float
+            Congestion ratio computed as `intensity / capacity` (with `capacity` safeguarded by
+            `max(capacity, 1e-9)`).
+
+    Notes
+    -----
+    - Assignment is discrete (one unit of intensity per trip) and can be slow for large OD totals.
+      If you have fractional flows, they are rounded to integers before assignment.
+    - For parallel edges between the same `(u, v)`, the edge with the smallest `weight_key`
+      value is chosen for each step along the path.
+    - Oversaturated edges are removed only from the internal routing graph; the output graph
+      keeps all edges and reports their final loads.
+    - Lanes outside the supported range (1..6) will raise an error when capacity is computed
+      unless you extend `LANE_COEF` accordingly.
+
+    Raises
+    ------
+    ValueError
+        If the OD matrix and graph are incompatible (e.g., missing nodes) or if `weight_key`
+        cannot be used for routing due to invalid/missing edge weights.
+    networkx.NodeNotFound
+        If a source/target node from `od_mx` is not present in the routing graph.
+    networkx.NetworkXNoPath
+        If no path exists for an OD pair (routing for that pair stops).
+
+    Examples
+    --------
+    >>> import pandas as pd
+    >>> import networkx as nx
+    >>> od = pd.DataFrame([[0, 3], [1, 0]], index=[0, 1], columns=[0, 1])
+    >>> G = nx.MultiDiGraph()
+    >>> G.add_edge(0, 1, time_min=1.0, lanes=1)
+    >>> G.add_edge(1, 0, time_min=1.0, lanes=1)
+    >>> H = road_congestion(od, G, weight_key="time_min")
+    >>> H[0][1][0]["intensity"], round(H[0][1][0]["congestion_level"], 3)
+    (3.0, 0.003)
+    """
+
+    validate_od_matrix(od_mx, G)
+    validate_accessibility_graph(G, weight_key)
+
+    logger.info("Preprocessing graph")
+    H = _peprocess_graph(G)
+    graph_congestion = H.copy()
+    graph_routing = H.copy()
+
+    for _, _, k, data in graph_congestion.edges(keys=True, data=True):
+        data["intensity"] = 0.0
+
+    logger.info("Calculating shortest paths")
     for i in tqdm(od_mx.index, disable=log_config.disable_tqdm):
-        for j in od_mx.columns:
-            if i == j:
+        for j, demand in od_mx.loc[i].items():
+            if i == j or demand <= 0:
                 continue
-            if i in paths and j in paths[i]:
-                path = paths[i][j]
-                for k in range(len(path) - 1):
-                    # FIXME multidigraph edges split congestion
-                    graph[path[k]][path[k + 1]][0][CONGESTION_KEY] += od_mx[i][j]
-    return graph
+
+            trips = int(round(float(demand)))
+
+            for _ in range(trips):
+                try:
+                    route = nx.shortest_path(graph_routing, source=i, target=j, weight=weight_key, method="dijkstra")
+                except (nx.NetworkXNoPath, nx.NodeNotFound):
+                    break
+
+                for u, v in zip(route[:-1], route[1:]):
+                    k = min(graph_routing[u][v], key=lambda kk: graph_routing[u][v][kk].get(weight_key, np.inf))
+
+                    graph_routing[u][v][k]["intensity"] += 1.0
+                    graph_congestion[u][v][k]["intensity"] += 1.0
+
+                    capacity = float(graph_routing[u][v][k]["capacity"])
+                    congestion_level = graph_routing[u][v][k]["intensity"] / max(capacity, 1e-9)
+                    if congestion_level > 1.0:
+                        graph_routing.remove_edge(u, v, key=k)
+
+    logger.info("Computing congestion level")
+    for _, _, _, data in graph_congestion.edges(keys=True, data=True):
+        data["congestion_level"] = data["intensity"] / max(data["capacity"], 1e-9)
+
+    return graph_congestion
\ No newline at end of file
diff --git a/examples/analysis/network/od_and_rc.ipynb b/examples/analysis/network/od_and_rc.ipynb
index 27f09a53..f9a36bf2 100644
--- a/examples/analysis/network/od_and_rc.ipynb
+++ b/examples/analysis/network/od_and_rc.ipynb
@@ -9,7 +9,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {},
    "outputs": [
     {
@@ -34,138 +34,108 @@
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>geometry</th>\n",
-       "      <th>land_use</th>\n",
-       "      <th>is_living</th>\n",
-       "      <th>build_floor_area</th>\n",
-       "      <th>living_demand</th>\n",
-       "      <th>living_area</th>\n",
-       "      <th>share_living</th>\n",
-       "      <th>business_area</th>\n",
-       "      <th>share_business</th>\n",
        "      <th>site_area</th>\n",
+       "      <th>residential</th>\n",
+       "      <th>business</th>\n",
+       "      <th>recreation</th>\n",
+       "      <th>industrial</th>\n",
+       "      <th>transport</th>\n",
+       "      <th>special</th>\n",
+       "      <th>agriculture</th>\n",
+       "      <th>land_use</th>\n",
        "      <th>...</th>\n",
-       "      <th>capacity_bus_station</th>\n",
-       "      <th>capacity_bus_stop</th>\n",
-       "      <th>capacity_pier</th>\n",
-       "      <th>capacity_animal_shelter</th>\n",
-       "      <th>capacity_military_kom</th>\n",
        "      <th>capacity_prison</th>\n",
+       "      <th>count_prison</th>\n",
        "      <th>capacity_landfill</th>\n",
+       "      <th>count_landfill</th>\n",
        "      <th>capacity_plant_nursery</th>\n",
+       "      <th>count_plant_nursery</th>\n",
        "      <th>capacity_greenhouse_complex</th>\n",
+       "      <th>count_greenhouse_complex</th>\n",
        "      <th>capacity_warehouse</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>id</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
+       "      <th>count_warehouse</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
-       "      <td>POLYGON ((354918.622 6625258.829, 354901.464 6...</td>\n",
-       "      <td>None</td>\n",
-       "      <td>True</td>\n",
-       "      <td>43840.686518</td>\n",
-       "      <td>50.641057</td>\n",
-       "      <td>30688.480678</td>\n",
-       "      <td>2.199357</td>\n",
-       "      <td>13152.205840</td>\n",
-       "      <td>0.942581</td>\n",
-       "      <td>804466.712114</td>\n",
+       "      <td>POLYGON ((349424.859 6631180.891, 349424.751 6...</td>\n",
+       "      <td>0.032316</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>LandUse.TRANSPORT</td>\n",
        "      <td>...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td>POLYGON ((355412.142 6623378.149, 355411.7 662...</td>\n",
-       "      <td>transport</td>\n",
-       "      <td>True</td>\n",
-       "      <td>10294.395525</td>\n",
-       "      <td>53.114392</td>\n",
-       "      <td>2177.690063</td>\n",
-       "      <td>0.431105</td>\n",
-       "      <td>8116.705462</td>\n",
-       "      <td>1.606820</td>\n",
-       "      <td>23173.129862</td>\n",
+       "      <td>POLYGON ((352083.617 6633950.146, 352240.448 6...</td>\n",
+       "      <td>137101.088247</td>\n",
+       "      <td>0.099</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.079912</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.401072</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.417018</td>\n",
+       "      <td>LandUse.AGRICULTURE</td>\n",
        "      <td>...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>2 rows × 83 columns</p>\n",
+       "<p>2 rows × 137 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "                                             geometry   land_use  is_living  \\\n",
-       "id                                                                            \n",
-       "0   POLYGON ((354918.622 6625258.829, 354901.464 6...       None       True   \n",
-       "1   POLYGON ((355412.142 6623378.149, 355411.7 662...  transport       True   \n",
+       "                                            geometry      site_area  \\\n",
+       "0  POLYGON ((349424.859 6631180.891, 349424.751 6...       0.032316   \n",
+       "1  POLYGON ((352083.617 6633950.146, 352240.448 6...  137101.088247   \n",
        "\n",
-       "    build_floor_area  living_demand   living_area  share_living  \\\n",
-       "id                                                                \n",
-       "0       43840.686518      50.641057  30688.480678      2.199357   \n",
-       "1       10294.395525      53.114392   2177.690063      0.431105   \n",
+       "   residential  business  recreation  industrial  transport  special  \\\n",
+       "0        0.000       0.0    0.000000         0.0   1.000000      0.0   \n",
+       "1        0.099       0.0    0.079912         0.0   0.401072      0.0   \n",
        "\n",
-       "    business_area  share_business      site_area  ...  capacity_bus_station  \\\n",
-       "id                                                ...                         \n",
-       "0    13152.205840        0.942581  804466.712114  ...                     0   \n",
-       "1     8116.705462        1.606820   23173.129862  ...                     0   \n",
+       "   agriculture             land_use  ...  capacity_prison  count_prison  \\\n",
+       "0     0.000000    LandUse.TRANSPORT  ...              0.0           0.0   \n",
+       "1     0.417018  LandUse.AGRICULTURE  ...              0.0           0.0   \n",
        "\n",
-       "    capacity_bus_stop  capacity_pier  capacity_animal_shelter  \\\n",
-       "id                                                              \n",
-       "0                   0              0                        0   \n",
-       "1                   0              0                        0   \n",
+       "   capacity_landfill  count_landfill  capacity_plant_nursery  \\\n",
+       "0                0.0             0.0                     0.0   \n",
+       "1                0.0             0.0                     0.0   \n",
        "\n",
-       "    capacity_military_kom  capacity_prison  capacity_landfill  \\\n",
-       "id                                                              \n",
-       "0                       0                0                  0   \n",
-       "1                       0                0                  0   \n",
+       "   count_plant_nursery  capacity_greenhouse_complex  count_greenhouse_complex  \\\n",
+       "0                  0.0                          0.0                       0.0   \n",
+       "1                  0.0                          0.0                       0.0   \n",
        "\n",
-       "    capacity_plant_nursery  capacity_greenhouse_complex  capacity_warehouse  \n",
-       "id                                                                           \n",
-       "0                        0                            0                   0  \n",
-       "1                        0                            0                   0  \n",
+       "   capacity_warehouse  count_warehouse  \n",
+       "0                 0.0              0.0  \n",
+       "1                 0.0              0.0  \n",
        "\n",
-       "[2 rows x 83 columns]"
+       "[2 rows x 137 columns]"
       ]
      },
      "execution_count": 1,
@@ -174,9 +144,9 @@
     }
    ],
    "source": [
-    "import geopandas as gpd\n",
+    "import pandas as pd\n",
     "\n",
-    "blocks_gdf = gpd.read_parquet('./../data/blocks.parquet')\n",
+    "blocks_gdf = pd.read_pickle('./../data/blocks.pickle')\n",
     "blocks_gdf.head(2)"
    ]
   },
@@ -194,7 +164,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -212,6 +182,26 @@
     "blocks_gdf.plot().set_axis_off()"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "np.float64(208763.0)"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "blocks_gdf.population.sum()"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -221,7 +211,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -237,51 +227,43 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "\u001b[32m2025-06-08 15:38:00.477\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.relations.accessibility.graph.core\u001b[0m:\u001b[36mget_accessibility_graph\u001b[0m:\u001b[36m16\u001b[0m - \u001b[33m\u001b[1mCRS do not match IDUEDU required crs. Reprojecting\u001b[0m\n",
-      "\u001b[32m2025-06-08 15:38:00.551\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36miduedu.modules.drive_walk_builder\u001b[0m:\u001b[36mget_drive_graph_by_poly\u001b[0m:\u001b[36m91\u001b[0m - \u001b[1mDownloading drive graph from OSM, it may take a while for large territory ...\u001b[0m\n",
-      "\u001b[32m2025-06-08 15:38:01.897\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36miduedu.utils.utils\u001b[0m:\u001b[36mremove_weakly_connected_nodes\u001b[0m:\u001b[36m37\u001b[0m - \u001b[33m\u001b[1mRemoving 24 nodes that form 23 trap components. These are groups where you can enter but can't exit (or vice versa). Keeping the largest strongly connected component (663 nodes).\u001b[0m\n"
+      "\u001b[32m2026-02-25 13:54:55.793\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36miduedu.modules.drive_walk_builder\u001b[0m:\u001b[36mget_drive_graph_by_poly\u001b[0m:\u001b[36m91\u001b[0m - \u001b[1mDownloading drive graph from OSM, it may take a while for large territory ...\u001b[0m\n",
+      "\u001b[32m2026-02-25 13:54:56.789\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36miduedu.utils.utils\u001b[0m:\u001b[36mremove_weakly_connected_nodes\u001b[0m:\u001b[36m37\u001b[0m - \u001b[33m\u001b[1mRemoving 28 nodes that form 27 trap components. These are groups where you can enter but can't exit (or vice versa). Keeping the largest strongly connected component (712 nodes).\u001b[0m\n"
      ]
     }
    ],
    "source": [
-    "graph_drive = get_accessibility_graph(blocks_gdf, 'drive')"
+    "graph_drive = get_accessibility_graph(blocks_gdf, 'drive', additional_edgedata=[\"lanes\"])"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "\u001b[32m2025-06-08 15:38:01.927\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mblocksnet.relations.accessibility.graph.core\u001b[0m:\u001b[36mget_accessibility_graph\u001b[0m:\u001b[36m16\u001b[0m - \u001b[33m\u001b[1mCRS do not match IDUEDU required crs. Reprojecting\u001b[0m\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\u001b[32m2025-06-08 15:38:01.969\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36miduedu.modules.drive_walk_builder\u001b[0m:\u001b[36mget_walk_graph\u001b[0m:\u001b[36m217\u001b[0m - \u001b[1mDownloading walk graph from OSM, it may take a while for large territory ...\u001b[0m\n"
+      "\u001b[32m2026-02-25 13:54:56.835\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36miduedu.modules.drive_walk_builder\u001b[0m:\u001b[36mget_walk_graph\u001b[0m:\u001b[36m217\u001b[0m - \u001b[1mDownloading walk graph from OSM, it may take a while for large territory ...\u001b[0m\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "3cb46884cf6c4bf4b1573f29053cb56e",
+       "model_id": "8a23a85c6d9543afa922acdf62b6df2d",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "Calculating the weights of the walk graph:   0%|          | 0/48938 [00:00<?, ?it/s]"
+       "Calculating the weights of the walk graph:   0%|          | 0/50982 [00:00<?, ?it/s]"
       ]
      },
      "metadata": {},
@@ -301,12 +283,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -324,6691 +306,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
     "from iduedu import get_adj_matrix_gdf_to_gdf\n",
     "\n",
-    "blocks_to_nodes = get_adj_matrix_gdf_to_gdf(blocks_gdf, nodes_gdf, graph_walk)"
+    "blocks_to_nodes = get_adj_matrix_gdf_to_gdf(blocks_gdf, nodes_gdf, graph_walk, weight='time_min')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/vasilstar/masterplanning/.venv/lib/python3.10/site-packages/pandas/io/formats/format.py:1458: RuntimeWarning: overflow encountered in cast\n",
+      "/Users/sashamorozov/Documents/Code/blocksnet_road_traffic/blocksnet/.venv/lib/python3.10/site-packages/pandas/io/formats/format.py:1458: RuntimeWarning: overflow encountered in cast\n",
       "  has_large_values = (abs_vals > 1e6).any()\n"
      ]
     },
     {
      "data": {
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        "  </tbody>\n",
        "</table>\n",
-       "<p>5 rows × 663 columns</p>\n",
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        "</div>"
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       "text/plain": [
-       "        0       1       2       3       4       5       6       7       8    \\\n",
-       "id                                                                            \n",
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+       "          0          1          2          3          4          5    \\\n",
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        "\n",
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-       "id           ...                                                           \n",
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-       "113  1774.0  ...  3318.0  3806.0  4708.0  3880.0  5212.0  5340.0  5012.0   \n",
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-       "215  4352.0  ...  3124.0  3620.0  4452.0  3658.0  4372.0  4728.0  4148.0   \n",
+       "          6          7          8          9    ...       702       703  \\\n",
+       "5   49.750000  47.343750  35.531250  41.156250  ...  61.59375  63.25000   \n",
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+       "81   7.535156  10.179688  10.382812   4.500000  ...  82.43750  84.06250   \n",
+       "83  21.796875  18.546875   8.484375  14.109375  ...  72.75000  74.43750   \n",
        "\n",
-       "        660     661     662  \n",
-       "id                           \n",
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-       "113  5364.0  4676.0  5200.0  \n",
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-       "115  4944.0  5160.0  5284.0  \n",
-       "215  4752.0  5392.0  5380.0  \n",
+       "         704       705       706       707      708       709        710  \\\n",
+       "5   63.28125  63.71875  65.12500  60.93750  65.1250  65.25000  17.156250   \n",
+       "69  40.93750  41.37500  42.78125  39.31250  42.8125  42.90625   9.257812   \n",
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+       "81  84.12500  86.18750  88.37500  81.75000  88.3750  88.50000  44.843750   \n",
+       "83  74.43750  75.50000  76.93750  72.12500  76.9375  77.06250  28.937500   \n",
        "\n",
-       "[5 rows x 663 columns]"
+       "          711  \n",
+       "5   19.906250  \n",
+       "69   8.242188  \n",
+       "70   7.312500  \n",
+       "81  45.125000  \n",
+       "83  31.703125  \n",
+       "\n",
+       "[5 rows x 712 columns]"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -7247,6689 +548,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
-    "nodes_to_nodes = get_adj_matrix_gdf_to_gdf(nodes_gdf, nodes_gdf, graph_drive)"
+    "nodes_to_nodes = get_adj_matrix_gdf_to_gdf(nodes_gdf, nodes_gdf, graph_drive, weight='time_min')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/vasilstar/masterplanning/.venv/lib/python3.10/site-packages/pandas/io/formats/format.py:1458: RuntimeWarning: overflow encountered in cast\n",
+      "/Users/sashamorozov/Documents/Code/blocksnet_road_traffic/blocksnet/.venv/lib/python3.10/site-packages/pandas/io/formats/format.py:1458: RuntimeWarning: overflow encountered in cast\n",
       "  has_large_values = (abs_vals > 1e6).any()\n"
      ]
     },
     {
      "data": {
-      "application/vnd.microsoft.datawrangler.viewer.v0+json": {
-       "columns": [
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        "      <th>8</th>\n",
        "      <th>9</th>\n",
        "      <th>...</th>\n",
-       "      <th>653</th>\n",
-       "      <th>654</th>\n",
-       "      <th>655</th>\n",
-       "      <th>656</th>\n",
-       "      <th>657</th>\n",
-       "      <th>658</th>\n",
-       "      <th>659</th>\n",
-       "      <th>660</th>\n",
-       "      <th>661</th>\n",
-       "      <th>662</th>\n",
+       "      <th>702</th>\n",
+       "      <th>703</th>\n",
+       "      <th>704</th>\n",
+       "      <th>705</th>\n",
+       "      <th>706</th>\n",
+       "      <th>707</th>\n",
+       "      <th>708</th>\n",
+       "      <th>709</th>\n",
+       "      <th>710</th>\n",
+       "      <th>711</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
-       "      <td>0.000</td>\n",
-       "      <td>17.375</td>\n",
-       "      <td>371.50000</td>\n",
-       "      <td>315.250000</td>\n",
-       "      <td>215.0000</td>\n",
-       "      <td>664.0</td>\n",
-       "      <td>659.5</td>\n",
-       "      <td>349.000</td>\n",
-       "      <td>1181.0</td>\n",
-       "      <td>1254.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.020004</td>\n",
+       "      <td>0.379883</td>\n",
+       "      <td>0.320068</td>\n",
+       "      <td>0.229980</td>\n",
+       "      <td>0.680176</td>\n",
+       "      <td>0.669922</td>\n",
+       "      <td>0.360107</td>\n",
+       "      <td>1.200195</td>\n",
+       "      <td>1.530273</td>\n",
        "      <td>...</td>\n",
-       "      <td>3626.0</td>\n",
-       "      <td>3888.0</td>\n",
-       "      <td>4696.0</td>\n",
-       "      <td>3860.0</td>\n",
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-       "      <td>5592.0</td>\n",
-       "      <td>5080.0</td>\n",
-       "      <td>5576.0</td>\n",
-       "      <td>4276.0</td>\n",
-       "      <td>5016.0</td>\n",
+       "      <td>7.121094</td>\n",
+       "      <td>7.328125</td>\n",
+       "      <td>6.699219</td>\n",
+       "      <td>6.789062</td>\n",
+       "      <td>6.949219</td>\n",
+       "      <td>6.851562</td>\n",
+       "      <td>6.789062</td>\n",
+       "      <td>6.800781</td>\n",
+       "      <td>2.890625</td>\n",
+       "      <td>2.650391</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td>37.750</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>354.00000</td>\n",
-       "      <td>297.750000</td>\n",
-       "      <td>197.6250</td>\n",
-       "      <td>647.0</td>\n",
-       "      <td>642.0</td>\n",
-       "      <td>331.750</td>\n",
-       "      <td>1163.0</td>\n",
-       "      <td>1237.0</td>\n",
+       "      <td>0.040009</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.360107</td>\n",
+       "      <td>0.300049</td>\n",
+       "      <td>0.209961</td>\n",
+       "      <td>0.660156</td>\n",
+       "      <td>0.649902</td>\n",
+       "      <td>0.340088</td>\n",
+       "      <td>1.179688</td>\n",
+       "      <td>1.509766</td>\n",
        "      <td>...</td>\n",
-       "      <td>3610.0</td>\n",
-       "      <td>3870.0</td>\n",
-       "      <td>4680.0</td>\n",
-       "      <td>3842.0</td>\n",
-       "      <td>5376.0</td>\n",
-       "      <td>5576.0</td>\n",
-       "      <td>5060.0</td>\n",
-       "      <td>5556.0</td>\n",
-       "      <td>4256.0</td>\n",
-       "      <td>4996.0</td>\n",
+       "      <td>7.101562</td>\n",
+       "      <td>7.308594</td>\n",
+       "      <td>6.679688</td>\n",
+       "      <td>6.769531</td>\n",
+       "      <td>6.929688</td>\n",
+       "      <td>6.828125</td>\n",
+       "      <td>6.769531</td>\n",
+       "      <td>6.781250</td>\n",
+       "      <td>2.869141</td>\n",
+       "      <td>2.630859</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>267.500</td>\n",
-       "      <td>285.000</td>\n",
-       "      <td>0.00000</td>\n",
-       "      <td>5.519531</td>\n",
-       "      <td>107.1875</td>\n",
-       "      <td>354.5</td>\n",
-       "      <td>350.0</td>\n",
-       "      <td>39.375</td>\n",
-       "      <td>1281.0</td>\n",
-       "      <td>944.5</td>\n",
+       "      <td>0.270020</td>\n",
+       "      <td>0.290039</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.010002</td>\n",
+       "      <td>0.099976</td>\n",
+       "      <td>0.370117</td>\n",
+       "      <td>0.360107</td>\n",
+       "      <td>0.049988</td>\n",
+       "      <td>1.469727</td>\n",
+       "      <td>1.219727</td>\n",
        "      <td>...</td>\n",
-       "      <td>3894.0</td>\n",
-       "      <td>4156.0</td>\n",
-       "      <td>4964.0</td>\n",
-       "      <td>4128.0</td>\n",
-       "      <td>5660.0</td>\n",
-       "      <td>5860.0</td>\n",
-       "      <td>5344.0</td>\n",
-       "      <td>5844.0</td>\n",
-       "      <td>4544.0</td>\n",
-       "      <td>5284.0</td>\n",
+       "      <td>7.390625</td>\n",
+       "      <td>7.601562</td>\n",
+       "      <td>6.968750</td>\n",
+       "      <td>7.058594</td>\n",
+       "      <td>7.218750</td>\n",
+       "      <td>7.121094</td>\n",
+       "      <td>7.058594</td>\n",
+       "      <td>7.070312</td>\n",
+       "      <td>3.160156</td>\n",
+       "      <td>2.919922</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
-       "      <td>323.750</td>\n",
-       "      <td>341.000</td>\n",
-       "      <td>56.15625</td>\n",
+       "      <td>0.330078</td>\n",
+       "      <td>0.350098</td>\n",
+       "      <td>0.059998</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>163.3750</td>\n",
-       "      <td>349.0</td>\n",
-       "      <td>344.5</td>\n",
-       "      <td>33.875</td>\n",
-       "      <td>1275.0</td>\n",
-       "      <td>939.0</td>\n",
+       "      <td>0.160034</td>\n",
+       "      <td>0.360107</td>\n",
+       "      <td>0.350098</td>\n",
+       "      <td>0.040009</td>\n",
+       "      <td>1.530273</td>\n",
+       "      <td>1.209961</td>\n",
        "      <td>...</td>\n",
-       "      <td>3950.0</td>\n",
-       "      <td>4212.0</td>\n",
-       "      <td>5020.0</td>\n",
-       "      <td>4184.0</td>\n",
-       "      <td>5716.0</td>\n",
-       "      <td>5916.0</td>\n",
-       "      <td>5400.0</td>\n",
-       "      <td>5900.0</td>\n",
-       "      <td>4600.0</td>\n",
-       "      <td>5340.0</td>\n",
+       "      <td>7.449219</td>\n",
+       "      <td>7.660156</td>\n",
+       "      <td>7.031250</td>\n",
+       "      <td>7.121094</td>\n",
+       "      <td>7.281250</td>\n",
+       "      <td>7.179688</td>\n",
+       "      <td>7.121094</td>\n",
+       "      <td>7.128906</td>\n",
+       "      <td>3.220703</td>\n",
+       "      <td>2.980469</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
-       "      <td>160.375</td>\n",
-       "      <td>177.750</td>\n",
-       "      <td>532.00000</td>\n",
-       "      <td>475.500000</td>\n",
-       "      <td>0.0000</td>\n",
-       "      <td>824.5</td>\n",
-       "      <td>820.0</td>\n",
-       "      <td>509.500</td>\n",
-       "      <td>1341.0</td>\n",
-       "      <td>1415.0</td>\n",
+       "      <td>0.170044</td>\n",
+       "      <td>0.189941</td>\n",
+       "      <td>0.549805</td>\n",
+       "      <td>0.489990</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.850098</td>\n",
+       "      <td>0.839844</td>\n",
+       "      <td>0.529785</td>\n",
+       "      <td>1.370117</td>\n",
+       "      <td>1.700195</td>\n",
        "      <td>...</td>\n",
-       "      <td>3788.0</td>\n",
-       "      <td>4048.0</td>\n",
-       "      <td>4856.0</td>\n",
-       "      <td>4020.0</td>\n",
-       "      <td>5552.0</td>\n",
-       "      <td>5752.0</td>\n",
-       "      <td>5240.0</td>\n",
-       "      <td>5736.0</td>\n",
-       "      <td>4436.0</td>\n",
-       "      <td>5176.0</td>\n",
+       "      <td>7.289062</td>\n",
+       "      <td>7.500000</td>\n",
+       "      <td>6.871094</td>\n",
+       "      <td>6.960938</td>\n",
+       "      <td>7.121094</td>\n",
+       "      <td>7.019531</td>\n",
+       "      <td>6.960938</td>\n",
+       "      <td>6.968750</td>\n",
+       "      <td>3.060547</td>\n",
+       "      <td>2.820312</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>5 rows × 663 columns</p>\n",
+       "<p>5 rows × 712 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "       0        1          2           3         4      5      6        7    \\\n",
-       "0    0.000   17.375  371.50000  315.250000  215.0000  664.0  659.5  349.000   \n",
-       "1   37.750    0.000  354.00000  297.750000  197.6250  647.0  642.0  331.750   \n",
-       "2  267.500  285.000    0.00000    5.519531  107.1875  354.5  350.0   39.375   \n",
-       "3  323.750  341.000   56.15625    0.000000  163.3750  349.0  344.5   33.875   \n",
-       "4  160.375  177.750  532.00000  475.500000    0.0000  824.5  820.0  509.500   \n",
+       "        0         1         2         3         4         5         6    \\\n",
+       "0  0.000000  0.020004  0.379883  0.320068  0.229980  0.680176  0.669922   \n",
+       "1  0.040009  0.000000  0.360107  0.300049  0.209961  0.660156  0.649902   \n",
+       "2  0.270020  0.290039  0.000000  0.010002  0.099976  0.370117  0.360107   \n",
+       "3  0.330078  0.350098  0.059998  0.000000  0.160034  0.360107  0.350098   \n",
+       "4  0.170044  0.189941  0.549805  0.489990  0.000000  0.850098  0.839844   \n",
        "\n",
-       "      8       9    ...     653     654     655     656     657     658  \\\n",
-       "0  1181.0  1254.0  ...  3626.0  3888.0  4696.0  3860.0  5392.0  5592.0   \n",
-       "1  1163.0  1237.0  ...  3610.0  3870.0  4680.0  3842.0  5376.0  5576.0   \n",
-       "2  1281.0   944.5  ...  3894.0  4156.0  4964.0  4128.0  5660.0  5860.0   \n",
-       "3  1275.0   939.0  ...  3950.0  4212.0  5020.0  4184.0  5716.0  5916.0   \n",
-       "4  1341.0  1415.0  ...  3788.0  4048.0  4856.0  4020.0  5552.0  5752.0   \n",
+       "        7         8         9    ...       702       703       704       705  \\\n",
+       "0  0.360107  1.200195  1.530273  ...  7.121094  7.328125  6.699219  6.789062   \n",
+       "1  0.340088  1.179688  1.509766  ...  7.101562  7.308594  6.679688  6.769531   \n",
+       "2  0.049988  1.469727  1.219727  ...  7.390625  7.601562  6.968750  7.058594   \n",
+       "3  0.040009  1.530273  1.209961  ...  7.449219  7.660156  7.031250  7.121094   \n",
+       "4  0.529785  1.370117  1.700195  ...  7.289062  7.500000  6.871094  6.960938   \n",
        "\n",
-       "      659     660     661     662  \n",
-       "0  5080.0  5576.0  4276.0  5016.0  \n",
-       "1  5060.0  5556.0  4256.0  4996.0  \n",
-       "2  5344.0  5844.0  4544.0  5284.0  \n",
-       "3  5400.0  5900.0  4600.0  5340.0  \n",
-       "4  5240.0  5736.0  4436.0  5176.0  \n",
+       "        706       707       708       709       710       711  \n",
+       "0  6.949219  6.851562  6.789062  6.800781  2.890625  2.650391  \n",
+       "1  6.929688  6.828125  6.769531  6.781250  2.869141  2.630859  \n",
+       "2  7.218750  7.121094  7.058594  7.070312  3.160156  2.919922  \n",
+       "3  7.281250  7.179688  7.121094  7.128906  3.220703  2.980469  \n",
+       "4  7.121094  7.019531  6.960938  6.968750  3.060547  2.820312  \n",
        "\n",
-       "[5 rows x 663 columns]"
+       "[5 rows x 712 columns]"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -14139,75 +779,10 @@
     "## Calculating OD matrix"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "services_dfs = []\n",
-    "for column in [c for c in blocks_gdf.columns if 'capacity_' in c]:\n",
-    "    services_df = blocks_gdf[[column]].rename(columns={column:'capacity'})\n",
-    "    services_dfs.append(services_df)"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 12,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\u001b[32m2025-06-08 15:38:19.243\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mblocksnet.analysis.network.origin_destination.core\u001b[0m:\u001b[36m_validate_input\u001b[0m:\u001b[36m81\u001b[0m - \u001b[1mValidating input data\u001b[0m\n",
-      "\u001b[32m2025-06-08 15:38:19.244\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mblocksnet.analysis.network.origin_destination.core\u001b[0m:\u001b[36m_calculate_diversity\u001b[0m:\u001b[36m51\u001b[0m - \u001b[1mCalculating diversity and density\u001b[0m\n",
-      "\u001b[32m2025-06-08 15:38:19.633\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mblocksnet.analysis.network.origin_destination.core\u001b[0m:\u001b[36m_calculate_attractiveness\u001b[0m:\u001b[36m59\u001b[0m - \u001b[1mCalculating attractiveness\u001b[0m\n",
-      "\u001b[32m2025-06-08 15:38:19.640\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mblocksnet.analysis.network.origin_destination.core\u001b[0m:\u001b[36m_calculate_nodes_weights\u001b[0m:\u001b[36m32\u001b[0m - \u001b[1mIdentifying nearest nodes to blocks\u001b[0m\n",
-      "\u001b[32m2025-06-08 15:38:19.646\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mblocksnet.analysis.network.origin_destination.core\u001b[0m:\u001b[36m_calculate_nodes_weights\u001b[0m:\u001b[36m37\u001b[0m - \u001b[1mCalculating weights\u001b[0m\n",
-      "\u001b[32m2025-06-08 15:38:19.655\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mblocksnet.analysis.network.origin_destination.core\u001b[0m:\u001b[36m_calculate_nodes_weights\u001b[0m:\u001b[36m43\u001b[0m - \u001b[1mDistributing\u001b[0m\n",
-      "\u001b[32m2025-06-08 15:38:19.659\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mblocksnet.analysis.network.origin_destination.core\u001b[0m:\u001b[36m_calculate_od_mx\u001b[0m:\u001b[36m72\u001b[0m - \u001b[1mCalculating origin destination matrix\u001b[0m\n"
-     ]
-    }
-   ],
-   "source": [
-    "from blocksnet.analysis.network import origin_destination_matrix\n",
-    "\n",
-    "od_mx = origin_destination_matrix(blocks_gdf, blocks_to_nodes, nodes_to_nodes, services_dfs)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Calculating roads congestion"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\u001b[32m2025-06-08 15:41:45.987\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mblocksnet.analysis.network.road_congestion.core\u001b[0m:\u001b[36mroad_congestion\u001b[0m:\u001b[36m18\u001b[0m - \u001b[1mCalculating shortest path\u001b[0m\n",
-      "\u001b[32m2025-06-08 15:41:47.616\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mblocksnet.analysis.network.road_congestion.core\u001b[0m:\u001b[36mroad_congestion\u001b[0m:\u001b[36m21\u001b[0m - \u001b[1mEvaluating congestion\u001b[0m\n",
-      "100%|██████████| 663/663 [00:44<00:00, 15.04it/s]\n"
-     ]
-    }
-   ],
-   "source": [
-    "from blocksnet.analysis.network import road_congestion\n",
-    "\n",
-    "graph_congestion = road_congestion(od_mx, graph_drive)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -14230,70 +805,755 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th>length_meter</th>\n",
-       "      <th>time_min</th>\n",
-       "      <th>geometry</th>\n",
-       "      <th>congestion</th>\n",
+       "      <th>count_school</th>\n",
+       "      <th>count_kindergarten</th>\n",
+       "      <th>count_hospital</th>\n",
+       "      <th>count_polyclinic</th>\n",
+       "      <th>count_pitch</th>\n",
+       "      <th>count_swimming_pool</th>\n",
+       "      <th>count_theatre</th>\n",
+       "      <th>count_museum</th>\n",
+       "      <th>count_cinema</th>\n",
+       "      <th>count_mall</th>\n",
+       "      <th>...</th>\n",
+       "      <th>count_bus_station</th>\n",
+       "      <th>count_bus_stop</th>\n",
+       "      <th>count_pier</th>\n",
+       "      <th>count_animal_shelter</th>\n",
+       "      <th>count_prison</th>\n",
+       "      <th>count_landfill</th>\n",
+       "      <th>count_plant_nursery</th>\n",
+       "      <th>count_greenhouse_complex</th>\n",
+       "      <th>count_warehouse</th>\n",
+       "      <th>count</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <th>1</th>\n",
-       "      <td>17.379</td>\n",
-       "      <td>0.017</td>\n",
-       "      <td>LINESTRING (348610.46 6648540.586, 348595.032 ...</td>\n",
-       "      <td>0.058759</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
-       "      <th>339</th>\n",
-       "      <td>8.024</td>\n",
-       "      <td>0.008</td>\n",
-       "      <td>LINESTRING (348595.032 6648548.588, 348588.653...</td>\n",
-       "      <td>0.019130</td>\n",
+       "      <th>5</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>340</th>\n",
-       "      <td>245.966</td>\n",
-       "      <td>0.246</td>\n",
-       "      <td>LINESTRING (348595.032 6648548.588, 348581.331...</td>\n",
-       "      <td>0.040963</td>\n",
+       "      <th>69</th>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th rowspan=\"2\" valign=\"top\">2</th>\n",
-       "      <th>3</th>\n",
-       "      <td>5.515</td>\n",
-       "      <td>0.008</td>\n",
-       "      <td>LINESTRING (348859.015 6648442.978, 348857.583...</td>\n",
-       "      <td>0.000718</td>\n",
+       "      <th>70</th>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>8</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>107.189</td>\n",
-       "      <td>0.107</td>\n",
-       "      <td>LINESTRING (348859.015 6648442.978, 348847.224...</td>\n",
-       "      <td>0.048565</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
+       "      <th>81</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>83</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 61 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    count_school  count_kindergarten  count_hospital  count_polyclinic  \\\n",
+       "5              0                   0               0                 0   \n",
+       "69             0                   1               0                 0   \n",
+       "70             0                   1               0                 0   \n",
+       "81             0                   0               0                 0   \n",
+       "83             0                   0               0                 0   \n",
+       "\n",
+       "    count_pitch  count_swimming_pool  count_theatre  count_museum  \\\n",
+       "5             0                    0              0             0   \n",
+       "69            0                    0              0             0   \n",
+       "70            0                    0              0             0   \n",
+       "81            0                    0              0             0   \n",
+       "83            0                    0              0             0   \n",
+       "\n",
+       "    count_cinema  count_mall  ...  count_bus_station  count_bus_stop  \\\n",
+       "5              0           0  ...                  0               0   \n",
+       "69             0           0  ...                  0               0   \n",
+       "70             0           0  ...                  0               0   \n",
+       "81             0           0  ...                  0               0   \n",
+       "83             0           0  ...                  0               0   \n",
+       "\n",
+       "    count_pier  count_animal_shelter  count_prison  count_landfill  \\\n",
+       "5            0                     0             0               0   \n",
+       "69           0                     0             0               0   \n",
+       "70           0                     0             0               0   \n",
+       "81           0                     0             0               0   \n",
+       "83           0                     0             0               0   \n",
+       "\n",
+       "    count_plant_nursery  count_greenhouse_complex  count_warehouse  count  \n",
+       "5                     0                         0                0      0  \n",
+       "69                    0                         0                0      4  \n",
+       "70                    0                         0                0      8  \n",
+       "81                    0                         0                0      5  \n",
+       "83                    0                         0                0     13  \n",
+       "\n",
+       "[5 rows x 61 columns]"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from blocksnet.analysis.services import services_count\n",
+    "\n",
+    "count_df = services_count(blocks_gdf)\n",
+    "count_df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m2026-02-25 13:55:07.457\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mblocksnet.analysis.network.origin_destination.core\u001b[0m:\u001b[36m_validate_input\u001b[0m:\u001b[36m132\u001b[0m - \u001b[1mValidating input data\u001b[0m\n",
+      "\u001b[32m2026-02-25 13:55:07.457\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mblocksnet.analysis.network.origin_destination.core\u001b[0m:\u001b[36m_calculate_diversity\u001b[0m:\u001b[36m92\u001b[0m - \u001b[1mCalculating diversity and density\u001b[0m\n",
+      "\u001b[32m2026-02-25 13:55:07.702\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mblocksnet.analysis.diversity.shannon.core\u001b[0m:\u001b[36mshannon_diversity\u001b[0m:\u001b[36m23\u001b[0m - \u001b[1mCalculating Shannon diversity index\u001b[0m\n",
+      "100%|██████████| 254/254 [00:00<00:00, 3755.10it/s]\n",
+      "\u001b[32m2026-02-25 13:55:07.772\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mblocksnet.analysis.network.origin_destination.core\u001b[0m:\u001b[36m_calculate_attractiveness\u001b[0m:\u001b[36m100\u001b[0m - \u001b[1mCalculating attractiveness\u001b[0m\n",
+      "\u001b[32m2026-02-25 13:55:07.774\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mblocksnet.analysis.network.origin_destination.core\u001b[0m:\u001b[36m_calculate_nodes_weights\u001b[0m:\u001b[36m73\u001b[0m - \u001b[1mIdentifying nearest nodes to blocks\u001b[0m\n",
+      "\u001b[32m2026-02-25 13:55:07.778\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mblocksnet.analysis.network.origin_destination.core\u001b[0m:\u001b[36m_calculate_nodes_weights\u001b[0m:\u001b[36m78\u001b[0m - \u001b[1mCalculating weights\u001b[0m\n",
+      "\u001b[32m2026-02-25 13:55:07.783\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mblocksnet.analysis.network.origin_destination.core\u001b[0m:\u001b[36m_calculate_nodes_weights\u001b[0m:\u001b[36m84\u001b[0m - \u001b[1mDistributing\u001b[0m\n",
+      "\u001b[32m2026-02-25 13:55:07.785\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mblocksnet.analysis.network.origin_destination.core\u001b[0m:\u001b[36m_calculate_od_mx\u001b[0m:\u001b[36m113\u001b[0m - \u001b[1mCalculating origin destination matrix\u001b[0m\n"
+     ]
+    }
+   ],
+   "source": [
+    "from blocksnet.analysis.network import origin_destination_matrix\n",
+    "\n",
+    "od_mx = origin_destination_matrix(blocks_gdf, blocks_to_nodes, nodes_to_nodes, count_df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "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>0</th>\n",
+       "      <th>1</th>\n",
+       "      <th>2</th>\n",
+       "      <th>3</th>\n",
+       "      <th>4</th>\n",
+       "      <th>5</th>\n",
+       "      <th>6</th>\n",
+       "      <th>7</th>\n",
+       "      <th>8</th>\n",
+       "      <th>9</th>\n",
+       "      <th>...</th>\n",
+       "      <th>702</th>\n",
+       "      <th>703</th>\n",
+       "      <th>704</th>\n",
+       "      <th>705</th>\n",
+       "      <th>706</th>\n",
+       "      <th>707</th>\n",
+       "      <th>708</th>\n",
+       "      <th>709</th>\n",
+       "      <th>710</th>\n",
+       "      <th>711</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>14</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
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+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>4</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>18</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>707</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>708</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>27</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>709</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>710</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>711</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>712 rows × 712 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     0    1    2    3    4    5    6    7    8    9    ...  702  703  704  \\\n",
+       "0      0   14    1    1    2    1    1    1    0    0  ...    0    0    0   \n",
+       "1      4    0    1    1    1    0    0    1    0    0  ...    0    0    0   \n",
+       "2      1    1    0   18    2    1    1    4    0    0  ...    0    0    0   \n",
+       "3      1    1    4    0    2    1    1    5    0    0  ...    0    0    0   \n",
+       "4      2    2    1    1    0    1    1    1    0    0  ...    0    0    0   \n",
+       "..   ...  ...  ...  ...  ...  ...  ...  ...  ...  ...  ...  ...  ...  ...   \n",
+       "707    0    0    0    0    0    0    0    0    0    0  ...    1    1    1   \n",
+       "708    0    0    0    0    0    0    0    0    0    0  ...    0    0    1   \n",
+       "709    0    0    0    0    0    0    0    0    0    0  ...    0    0    1   \n",
+       "710    0    0    0    0    0    0    0    0    0    0  ...    0    0    0   \n",
+       "711    0    0    0    0    0    0    0    0    0    0  ...    0    0    0   \n",
+       "\n",
+       "     705  706  707  708  709  710  711  \n",
+       "0      0    0    0    0    0    0    0  \n",
+       "1      0    0    0    0    0    0    0  \n",
+       "2      0    0    0    0    0    0    0  \n",
+       "3      0    0    0    0    0    0    0  \n",
+       "4      0    0    0    0    0    0    0  \n",
+       "..   ...  ...  ...  ...  ...  ...  ...  \n",
+       "707    1    0    0    0    0    1    1  \n",
+       "708    1    0    1    0   27    1    1  \n",
+       "709    1    0    1    3    0    1    1  \n",
+       "710    0    0    0    0    0    0    3  \n",
+       "711    0    0    0    0    0    2    0  \n",
+       "\n",
+       "[712 rows x 712 columns]"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "od_mx"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "np.int64(208745)"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "od_mx.sum().sum()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Calculating roads congestion"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m2026-02-25 13:55:07.934\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mblocksnet.analysis.network.road_congestion.core\u001b[0m:\u001b[36mroad_congestion\u001b[0m:\u001b[36m173\u001b[0m - \u001b[1mPreprocessing graph\u001b[0m\n",
+      "\u001b[32m2026-02-25 13:55:07.946\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mblocksnet.analysis.network.road_congestion.core\u001b[0m:\u001b[36mroad_congestion\u001b[0m:\u001b[36m181\u001b[0m - \u001b[1mCalculating shortest paths\u001b[0m\n",
+      "100%|██████████| 712/712 [00:45<00:00, 15.70it/s]\n",
+      "\u001b[32m2026-02-25 13:55:53.292\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mblocksnet.analysis.network.road_congestion.core\u001b[0m:\u001b[36mroad_congestion\u001b[0m:\u001b[36m206\u001b[0m - \u001b[1mComputing congestion level\u001b[0m\n"
+     ]
+    }
+   ],
+   "source": [
+    "from blocksnet.analysis.network import road_congestion\n",
+    "\n",
+    "graph_congestion = road_congestion(od_mx, graph_drive)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "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></th>\n",
+       "      <th>length_meter</th>\n",
+       "      <th>time_min</th>\n",
+       "      <th>geometry</th>\n",
+       "      <th>lanes</th>\n",
+       "      <th>intensity</th>\n",
+       "      <th>capacity</th>\n",
+       "      <th>congestion_level</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <th>1</th>\n",
+       "      <td>17.379</td>\n",
+       "      <td>0.017</td>\n",
+       "      <td>LINESTRING (348610.46 6648540.586, 348595.032 ...</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1899.0</td>\n",
+       "      <td>1900.0</td>\n",
+       "      <td>0.999474</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
+       "      <th>343</th>\n",
+       "      <td>8.024</td>\n",
+       "      <td>0.008</td>\n",
+       "      <td>LINESTRING (348595.032 6648548.588, 348588.653...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1001.0</td>\n",
+       "      <td>1000.0</td>\n",
+       "      <td>1.001000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>344</th>\n",
+       "      <td>224.415</td>\n",
+       "      <td>0.224</td>\n",
+       "      <td>LINESTRING (348595.032 6648548.588, 348581.331...</td>\n",
+       "      <td>2</td>\n",
+       "      <td>796.0</td>\n",
+       "      <td>1900.0</td>\n",
+       "      <td>0.418947</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"2\" valign=\"top\">2</th>\n",
+       "      <th>3</th>\n",
+       "      <td>5.515</td>\n",
+       "      <td>0.008</td>\n",
+       "      <td>LINESTRING (348859.015 6648442.978, 348857.583...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>144.0</td>\n",
+       "      <td>1000.0</td>\n",
+       "      <td>0.144000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>99.884</td>\n",
+       "      <td>0.100</td>\n",
+       "      <td>LINESTRING (348859.015 6648442.978, 348847.224...</td>\n",
+       "      <td>2</td>\n",
+       "      <td>764.0</td>\n",
+       "      <td>1900.0</td>\n",
+       "      <td>0.402105</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
        "       length_meter  time_min  \\\n",
        "0 1          17.379     0.017   \n",
-       "1 339         8.024     0.008   \n",
-       "  340       245.966     0.246   \n",
+       "1 343         8.024     0.008   \n",
+       "  344       224.415     0.224   \n",
        "2 3           5.515     0.008   \n",
-       "  4         107.189     0.107   \n",
+       "  4          99.884     0.100   \n",
+       "\n",
+       "                                                geometry  lanes  intensity  \\\n",
+       "0 1    LINESTRING (348610.46 6648540.586, 348595.032 ...      2     1899.0   \n",
+       "1 343  LINESTRING (348595.032 6648548.588, 348588.653...      1     1001.0   \n",
+       "  344  LINESTRING (348595.032 6648548.588, 348581.331...      2      796.0   \n",
+       "2 3    LINESTRING (348859.015 6648442.978, 348857.583...      1      144.0   \n",
+       "  4    LINESTRING (348859.015 6648442.978, 348847.224...      2      764.0   \n",
        "\n",
-       "                                                geometry  congestion  \n",
-       "0 1    LINESTRING (348610.46 6648540.586, 348595.032 ...    0.058759  \n",
-       "1 339  LINESTRING (348595.032 6648548.588, 348588.653...    0.019130  \n",
-       "  340  LINESTRING (348595.032 6648548.588, 348581.331...    0.040963  \n",
-       "2 3    LINESTRING (348859.015 6648442.978, 348857.583...    0.000718  \n",
-       "  4    LINESTRING (348859.015 6648442.978, 348847.224...    0.048565  "
+       "       capacity  congestion_level  \n",
+       "0 1      1900.0          0.999474  \n",
+       "1 343    1000.0          1.001000  \n",
+       "  344    1900.0          0.418947  \n",
+       "2 3      1000.0          0.144000  \n",
+       "  4      1900.0          0.402105  "
       ]
      },
      "execution_count": 17,
@@ -14313,7 +1573,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 800x500 with 2 Axes>"
       ]
@@ -14323,7 +1583,7 @@
     }
    ],
    "source": [
-    "edges_gdf.plot('congestion', legend=True, figsize=(8,5)).set_axis_off()"
+    "edges_gdf.plot('congestion_level',cmap=\"RdYlGn_r\", legend=True, figsize=(8,5)).set_axis_off()"
    ]
   }
  ],
@@ -14343,7 +1603,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.10.18"
   }
  },
  "nbformat": 4,