diff --git a/solutions/sem01/lesson03/task1.py b/solutions/sem01/lesson03/task1.py
index f1d8fe26b..7b048e654 100644
--- a/solutions/sem01/lesson03/task1.py
+++ b/solutions/sem01/lesson03/task1.py
@@ -1,3 +1,3 @@
 def flip_bits_in_range(num: int, left_bit: int, right_bit: int) -> int:
     # ваш код
-    return num
\ No newline at end of file
+    return num
diff --git a/solutions/sem01/lesson03/task2.py b/solutions/sem01/lesson03/task2.py
index a3a738c2a..5cf2b6316 100644
--- a/solutions/sem01/lesson03/task2.py
+++ b/solutions/sem01/lesson03/task2.py
@@ -1,3 +1,3 @@
 def get_cube_root(n: float, eps: float) -> float:
     # ваш код
-    return n
\ No newline at end of file
+    return n
diff --git a/solutions/sem01/lesson04/task1.py b/solutions/sem01/lesson04/task1.py
index 47384423a..0135e399b 100644
--- a/solutions/sem01/lesson04/task1.py
+++ b/solutions/sem01/lesson04/task1.py
@@ -1,3 +1,3 @@
 def is_arithmetic_progression(lst: list[list[int]]) -> bool:
     # ваш код
-    return False
\ No newline at end of file
+    return False
diff --git a/solutions/sem01/lesson04/task2.py b/solutions/sem01/lesson04/task2.py
index 4591d0a3e..5d6f8ee8a 100644
--- a/solutions/sem01/lesson04/task2.py
+++ b/solutions/sem01/lesson04/task2.py
@@ -1,3 +1,3 @@
 def merge_intervals(intervals: list[list[int, int]]) -> list[list[int, int]]:
     # ваш код
-    return [[0,0]]
\ No newline at end of file
+    return [[0, 0]]
diff --git a/solutions/sem01/lesson04/task4.py b/solutions/sem01/lesson04/task4.py
index b21bc5a39..2664384d8 100644
--- a/solutions/sem01/lesson04/task4.py
+++ b/solutions/sem01/lesson04/task4.py
@@ -1,3 +1,3 @@
 def move_zeros_to_end(nums: list[int]) -> list[int]:
     # ваш код
-    return 0
\ No newline at end of file
+    return 0
diff --git a/solutions/sem01/lesson04/task5.py b/solutions/sem01/lesson04/task5.py
index 02d7742bb..ec6932ee4 100644
--- a/solutions/sem01/lesson04/task5.py
+++ b/solutions/sem01/lesson04/task5.py
@@ -1,3 +1,3 @@
 def find_row_with_most_ones(matrix: list[list[int]]) -> int:
     # ваш код
-    return 0
\ No newline at end of file
+    return 0
diff --git a/solutions/sem01/lesson04/task6.py b/solutions/sem01/lesson04/task6.py
index 16df27ca6..d16e77dda 100644
--- a/solutions/sem01/lesson04/task6.py
+++ b/solutions/sem01/lesson04/task6.py
@@ -1,3 +1,3 @@
-def count_cycles(arr: list[int]) -> int: 
+def count_cycles(arr: list[int]) -> int:
     # ваш код
-    return 0
\ No newline at end of file
+    return 0
diff --git a/solutions/sem01/lesson05/task1.py b/solutions/sem01/lesson05/task1.py
index 9a17211e5..fdf3b5488 100644
--- a/solutions/sem01/lesson05/task1.py
+++ b/solutions/sem01/lesson05/task1.py
@@ -1,3 +1,3 @@
 def is_palindrome(text: str) -> bool:
     # ваш код
-    return False
\ No newline at end of file
+    return False
diff --git a/solutions/sem01/lesson05/task2.py b/solutions/sem01/lesson05/task2.py
index 367503802..c70b40298 100644
--- a/solutions/sem01/lesson05/task2.py
+++ b/solutions/sem01/lesson05/task2.py
@@ -1,3 +1,3 @@
 def are_anagrams(word1: str, word2: str) -> bool:
     # ваш код
-    return False
\ No newline at end of file
+    return False
diff --git a/solutions/sem01/lesson05/task4.py b/solutions/sem01/lesson05/task4.py
index 4c4e9086e..7c2c26f17 100644
--- a/solutions/sem01/lesson05/task4.py
+++ b/solutions/sem01/lesson05/task4.py
@@ -1,3 +1,3 @@
 def unzip(compress_text: str) -> str:
     # ваш код
-    return compress_text
\ No newline at end of file
+    return compress_text
diff --git a/solutions/sem01/lesson05/task5.py b/solutions/sem01/lesson05/task5.py
index 076c5bb6c..da9e6d08c 100644
--- a/solutions/sem01/lesson05/task5.py
+++ b/solutions/sem01/lesson05/task5.py
@@ -1,3 +1,3 @@
-def reg_validator(reg_expr: str, text: str) -> bool:  
+def reg_validator(reg_expr: str, text: str) -> bool:
     # ваш код
-    return False
\ No newline at end of file
+    return False
diff --git a/solutions/sem01/lesson05/task6.py b/solutions/sem01/lesson05/task6.py
index 1b914ada7..63207797d 100644
--- a/solutions/sem01/lesson05/task6.py
+++ b/solutions/sem01/lesson05/task6.py
@@ -1,3 +1,3 @@
 def simplify_path(path: str) -> str:
     # ваш код
-    return path
\ No newline at end of file
+    return path
diff --git a/solutions/sem01/lesson06/task1.py b/solutions/sem01/lesson06/task1.py
index 2d1e30e96..353cb3616 100644
--- a/solutions/sem01/lesson06/task1.py
+++ b/solutions/sem01/lesson06/task1.py
@@ -1,3 +1,3 @@
 def int_to_roman(num: int) -> str:
     # ваш код
-    return ""
\ No newline at end of file
+    return ""
diff --git a/solutions/sem01/lesson06/task2.py b/solutions/sem01/lesson06/task2.py
index f535b5a0c..f1034e24e 100644
--- a/solutions/sem01/lesson06/task2.py
+++ b/solutions/sem01/lesson06/task2.py
@@ -1,3 +1,3 @@
 def get_len_of_longest_substring(text: str) -> int:
     # ваш код
-    return 0
\ No newline at end of file
+    return 0
diff --git a/solutions/sem01/lesson06/task3.py b/solutions/sem01/lesson06/task3.py
index 7449a1e72..b160d615a 100644
--- a/solutions/sem01/lesson06/task3.py
+++ b/solutions/sem01/lesson06/task3.py
@@ -2,6 +2,5 @@ def is_there_any_good_subarray(
     nums: list[int],
     k: int,
 ) -> bool:
-    
     # ваш код
     return False
diff --git a/solutions/sem01/lesson06/task4.py b/solutions/sem01/lesson06/task4.py
index 5b75a110c..95a7098e4 100644
--- a/solutions/sem01/lesson06/task4.py
+++ b/solutions/sem01/lesson06/task4.py
@@ -1,3 +1,3 @@
 def count_unique_words(text: str) -> int:
     # ваш код
-    return 0
\ No newline at end of file
+    return 0
diff --git a/solutions/sem01/lesson08/task1.py b/solutions/sem01/lesson08/task1.py
index 4390f6c84..7fa724ef8 100644
--- a/solutions/sem01/lesson08/task1.py
+++ b/solutions/sem01/lesson08/task1.py
@@ -1,5 +1,6 @@
 from typing import Callable
 
+
 def make_averager(accumulation_period: int) -> Callable[[float], float]:
     # ваш код
-    pass
\ No newline at end of file
+    pass
diff --git a/solutions/sem01/lesson08/task2.py b/solutions/sem01/lesson08/task2.py
index 6e4af8707..cc2ae4303 100644
--- a/solutions/sem01/lesson08/task2.py
+++ b/solutions/sem01/lesson08/task2.py
@@ -2,9 +2,7 @@
 
 T = TypeVar("T")
 
-def collect_statistic(
-    statistics: dict[str, list[float, int]]
-) -> Callable[[T], T]:
-    
+
+def collect_statistic(statistics: dict[str, list[float, int]]) -> Callable[[T], T]:
     # ваш код
-    pass
\ No newline at end of file
+    pass
diff --git a/solutions/sem02/lesson03/task1.py b/solutions/sem02/lesson03/task1.py
index 2c3fc0b58..9fe8943a8 100644
--- a/solutions/sem02/lesson03/task1.py
+++ b/solutions/sem02/lesson03/task1.py
@@ -8,13 +8,24 @@ class ShapeMismatchError(Exception):
 def sum_arrays_vectorized(
     lhs: np.ndarray,
     rhs: np.ndarray,
-) -> np.ndarray: ...
+) -> np.ndarray:
+    if lhs.shape != rhs.shape:
+        raise ShapeMismatchError
 
+    return lhs + rhs
 
-def compute_poly_vectorized(abscissa: np.ndarray) -> np.ndarray: ...
+
+def compute_poly_vectorized(abscissa: np.ndarray) -> np.ndarray:
+    return 3 * abscissa**2 + 2 * abscissa + 1
 
 
 def get_mutual_l2_distances_vectorized(
     lhs: np.ndarray,
     rhs: np.ndarray,
-) -> np.ndarray: ...
+) -> np.ndarray:
+    if lhs.shape[1] != rhs.shape[1]:
+        raise ShapeMismatchError
+
+    diff = lhs[:, np.newaxis, :] - rhs[np.newaxis, :, :]
+
+    return np.sqrt(np.sum(diff**2, axis=-1))
diff --git a/solutions/sem02/lesson03/task2.py b/solutions/sem02/lesson03/task2.py
index fc823c1d6..30da3f28c 100644
--- a/solutions/sem02/lesson03/task2.py
+++ b/solutions/sem02/lesson03/task2.py
@@ -9,11 +9,27 @@ def convert_from_sphere(
     distances: np.ndarray,
     azimuth: np.ndarray,
     inclination: np.ndarray,
-) -> tuple[np.ndarray, np.ndarray, np.ndarray]: ...
+) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
+    if distances.shape != azimuth.shape or distances.shape != inclination.shape:
+        raise ShapeMismatchError
+
+    x = distances * np.sin(inclination) * np.cos(azimuth)
+    y = distances * np.sin(inclination) * np.sin(azimuth)
+    z = distances * np.cos(inclination)
+
+    return x, y, z
 
 
 def convert_to_sphere(
     abscissa: np.ndarray,
     ordinates: np.ndarray,
     applicates: np.ndarray,
-) -> tuple[np.ndarray, np.ndarray, np.ndarray]: ...
+) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
+    if abscissa.shape != ordinates.shape or abscissa.shape != applicates.shape:
+        raise ShapeMismatchError
+
+    distances = np.sqrt(abscissa**2 + ordinates**2 + applicates**2)
+    azimuth = np.arctan2(ordinates, abscissa)
+    inclination = np.arctan2(np.sqrt(abscissa**2 + ordinates**2), applicates)
+
+    return distances, azimuth, inclination
diff --git a/solutions/sem02/lesson03/task3.py b/solutions/sem02/lesson03/task3.py
index 477acd0ce..2bc50c3c9 100644
--- a/solutions/sem02/lesson03/task3.py
+++ b/solutions/sem02/lesson03/task3.py
@@ -3,4 +3,18 @@
 
 def get_extremum_indices(
     ordinates: np.ndarray,
-) -> tuple[np.ndarray, np.ndarray]: ...
+) -> tuple[np.ndarray, np.ndarray]:
+    if ordinates.size < 3:
+        raise ValueError
+
+    middle = ordinates[1:-1]
+    left = ordinates[:-2]
+    right = ordinates[2:]
+
+    minima_mask = (middle < left) & (middle < right)
+    maxima_mask = (middle > left) & (middle > right)
+
+    minima_indices = np.where(minima_mask)[0] + 1
+    maxima_indices = np.where(maxima_mask)[0] + 1
+
+    return minima_indices, maxima_indices
diff --git a/solutions/sem02/lesson04/task1.py b/solutions/sem02/lesson04/task1.py
index 1b5526c1f..bffd75dbd 100644
--- a/solutions/sem02/lesson04/task1.py
+++ b/solutions/sem02/lesson04/task1.py
@@ -2,16 +2,41 @@
 
 
 def pad_image(image: np.ndarray, pad_size: int) -> np.ndarray:
-    # ваш код
-    return image
+    if pad_size < 1:
+        raise ValueError
+
+    height, width = image.shape[:2]
+    new_shape = (height + 2 * pad_size, width + 2 * pad_size) + image.shape[2:]
+
+    padded = np.zeros(new_shape, dtype=image.dtype)
+    padded[pad_size : pad_size + height, pad_size : pad_size + width] = image
+
+    return padded
 
 
 def blur_image(
     image: np.ndarray,
     kernel_size: int,
 ) -> np.ndarray:
-    # ваш код
-    return image
+    if kernel_size < 1 or kernel_size % 2 == 0:
+        raise ValueError
+
+    if kernel_size == 1:
+        return image.copy()
+
+    pad_size = kernel_size // 2
+    padded = pad_image(image, pad_size)
+
+    height, width = image.shape[:2]
+    accumulator = np.zeros(image.shape, dtype=np.float64)
+
+    for di in range(kernel_size):
+        for dj in range(kernel_size):
+            accumulator += padded[di : di + height, dj : dj + width]
+
+    result = accumulator / (kernel_size**2)
+
+    return result.astype(image.dtype)
 
 
 if __name__ == "__main__":
diff --git a/solutions/sem02/lesson04/task2.py b/solutions/sem02/lesson04/task2.py
index be9a2288f..a73a9b307 100644
--- a/solutions/sem02/lesson04/task2.py
+++ b/solutions/sem02/lesson04/task2.py
@@ -5,6 +5,22 @@ def get_dominant_color_info(
     image: np.ndarray[np.uint8],
     threshold: int = 5,
 ) -> tuple[np.uint8, float]:
-    # ваш код
+    if threshold < 1:
+        raise ValueError("threshold must be positive")
 
-    return 0, 0
+    total = image.size
+    histogram = np.bincount(image.flatten(), minlength=256)
+
+    cumulative = np.concatenate(([0], np.cumsum(histogram)))
+
+    colors = np.arange(256)
+    left = np.maximum(0, colors - threshold + 1)
+    right = np.minimum(256, colors + threshold)
+
+    counts = cumulative[right] - cumulative[left]
+    counts[histogram == 0] = -1
+
+    dominant_color = np.argmax(counts)
+    percent = counts[dominant_color] / total * 100
+
+    return np.uint8(dominant_color), percent
diff --git a/solutions/sem02/lesson05/task1.py b/solutions/sem02/lesson05/task1.py
index e9c7c3c56..5431d6301 100644
--- a/solutions/sem02/lesson05/task1.py
+++ b/solutions/sem02/lesson05/task1.py
@@ -9,4 +9,18 @@ def can_satisfy_demand(
     costs: np.ndarray,
     resource_amounts: np.ndarray,
     demand_expected: np.ndarray,
-) -> bool: ...
+) -> bool:
+    if costs.ndim != 2:
+        raise ShapeMismatchError
+
+    m, n = costs.shape
+
+    if resource_amounts.shape != (m,):
+        raise ShapeMismatchError
+
+    if demand_expected.shape != (n,):
+        raise ShapeMismatchError
+
+    resources_required = costs @ demand_expected
+
+    return bool(np.all(resources_required <= resource_amounts))
diff --git a/solutions/sem02/lesson05/task2.py b/solutions/sem02/lesson05/task2.py
index be1fb9d2b..fc7e71a98 100644
--- a/solutions/sem02/lesson05/task2.py
+++ b/solutions/sem02/lesson05/task2.py
@@ -8,4 +8,23 @@ class ShapeMismatchError(Exception):
 def get_projections_components(
     matrix: np.ndarray,
     vector: np.ndarray,
-) -> tuple[np.ndarray | None, np.ndarray | None]: ...
+) -> tuple[np.ndarray | None, np.ndarray | None]:
+    if matrix.ndim != 2 or matrix.shape[0] != matrix.shape[1]:
+        raise ShapeMismatchError
+
+    if matrix.shape[1] != vector.shape[0]:
+        raise ShapeMismatchError
+
+    n = matrix.shape[0]
+
+    if np.linalg.matrix_rank(matrix) != n:
+        return None, None
+
+    scalar_products = matrix @ vector
+    squared_norms = np.sum(matrix**2, axis=1)
+    coefficients = scalar_products / squared_norms
+
+    projections = coefficients[:, np.newaxis] * matrix
+    components = vector - projections
+
+    return projections, components
diff --git a/solutions/sem02/lesson05/task3.py b/solutions/sem02/lesson05/task3.py
index 0c66906cb..9cf085890 100644
--- a/solutions/sem02/lesson05/task3.py
+++ b/solutions/sem02/lesson05/task3.py
@@ -9,4 +9,25 @@ def adaptive_filter(
     Vs: np.ndarray,
     Vj: np.ndarray,
     diag_A: np.ndarray,
-) -> np.ndarray: ...
+) -> np.ndarray:
+    if Vs.ndim != 2 or Vj.ndim != 2 or diag_A.ndim != 1:
+        raise ShapeMismatchError
+
+    if Vs.shape[0] != Vj.shape[0]:
+        raise ShapeMismatchError
+
+    if Vj.shape[1] != diag_A.shape[0]:
+        raise ShapeMismatchError
+
+    m = Vs.shape[0]
+    k = Vj.shape[1]
+
+    Vj_H = Vj.conj().T
+    A = np.diag(diag_A)
+
+    inner = np.eye(k) + Vj_H @ Vj @ A
+    inner_inv = np.linalg.inv(inner)
+
+    R_inv = np.eye(m) - Vj @ inner_inv @ Vj_H
+
+    return R_inv @ Vs
diff --git a/solutions/sem02/lesson07/task1.py b/solutions/sem02/lesson07/task1.py
index 3a505d89b..8e452a90b 100644
--- a/solutions/sem02/lesson07/task1.py
+++ b/solutions/sem02/lesson07/task1.py
@@ -1,5 +1,4 @@
 from typing import Any
-
 import matplotlib.pyplot as plt
 import numpy as np
 
@@ -13,16 +12,57 @@ def visualize_diagrams(
     ordinates: np.ndarray,
     diagram_type: Any,
 ) -> None:
-    # ваш код
-    pass
+    if abscissa.shape != ordinates.shape:
+        raise ShapeMismatchError("Razmery massivov ne sovpadayut")
 
+    dopustimye_tipy = ("hist", "box", "violin")
+    if diagram_type not in dopustimye_tipy:
+        raise ValueError("Nedopustimyi tip diagrammy")
 
-if __name__ == "__main__":
-    mean = [2, 3]
-    cov = [[1, 1], [1, 2]]
-    space = 0.2
+    figura = plt.figure(figsize=(8, 8))
+    prosvet = 0.3
+    setka = plt.GridSpec(4, 4, wspace=prosvet, hspace=prosvet)
+
+    os_glavnaya = figura.add_subplot(setka[:-1, 1:])
+    os_glavnaya.scatter(abscissa, ordinates, color="seagreen", alpha=0.5, s=15)
+
+    if diagram_type == "hist":
+        os_v = figura.add_subplot(setka[:-1, 0], sharey=os_glavnaya)
+        os_g = figura.add_subplot(setka[-1, 1:], sharex=os_glavnaya)
+
+        os_g.hist(abscissa, bins=50, color="indianred", alpha=0.6, density=True)
+        os_v.hist(
+            ordinates, bins=50, color="indianred", alpha=0.6, density=True, orientation="horizontal"
+        )
+
+        os_g.invert_yaxis()
+        os_v.invert_xaxis()
+
+    elif diagram_type == "violin":
+        os_v = figura.add_subplot(setka[:-1, 0], sharey=os_glavnaya)
+        os_g = figura.add_subplot(setka[-1, 1:], sharex=os_glavnaya)
 
-    abscissa, ordinates = np.random.multivariate_normal(mean, cov, size=1000).T
+        os_v.violinplot(ordinates, vert=True, showmedians=True)
+        os_g.violinplot(abscissa, vert=False, showmedians=True)
+
+        os_g.invert_yaxis()
+        os_v.invert_xaxis()
+
+    elif diagram_type == "box":
+        os_v = figura.add_subplot(setka[:-1, 0], sharey=os_glavnaya)
+        os_g = figura.add_subplot(setka[-1, 1:], sharex=os_glavnaya)
+
+        os_v.boxplot(ordinates, vert=True, patch_artist=True)
+        os_g.boxplot(abscissa, vert=False, patch_artist=True)
+
+        os_g.invert_yaxis()
+        os_v.invert_xaxis()
 
-    visualize_diagrams(abscissa, ordinates, "hist")
     plt.show()
+
+
+if __name__ == "__main__":
+    x = np.random.normal(2, 1, 1000)
+    y = x + np.random.normal(1, 1, 1000)
+
+    visualize_diagrams(x, y, "hist")
diff --git a/solutions/sem02/lesson08/task1.py b/solutions/sem02/lesson08/task1.py
index 89f88572f..217f8a7d7 100644
--- a/solutions/sem02/lesson08/task1.py
+++ b/solutions/sem02/lesson08/task1.py
@@ -1,35 +1,89 @@
 from functools import partial
-
 import matplotlib.pyplot as plt
 import numpy as np
-
 from IPython.display import HTML
 from matplotlib.animation import FuncAnimation
 
 
+def _calculate_signal(time_array, modulation, fc):
+    carrier = np.sin(2 * np.pi * fc * time_array)
+
+    if modulation is not None:
+        return modulation(time_array) * carrier
+    else:
+        return carrier
+
+
+def _update_frame(frame_id, line, axis, modulation, fc, plot_duration, time_step, animation_step):
+    start_time = frame_id * animation_step
+    end_time = start_time + plot_duration
+
+    t = np.arange(start_time, end_time, time_step)
+    y = _calculate_signal(t, modulation, fc)
+
+    line.set_data(t, y)
+    axis.set_xlim(start_time, end_time)
+    axis.set_ylim(-2.5, 2.5)
+
+    return (line,)
+
+
 def create_modulation_animation(
-    modulation, 
-    fc, 
-    num_frames, 
-    plot_duration, 
-    time_step=0.001, 
-    animation_step=0.01,
-    save_path=""
+    modulation, fc, num_frames, plot_duration, time_step=0.001, animation_step=0.01, save_path=""
 ) -> FuncAnimation:
-    # ваш код
-    return FuncAnimation()
+    fig, ax = plt.subplots(figsize=(10, 5))
+
+    fig.patch.set_facecolor(
+        "#004488"
+    )  # рассцветку фона и линий нагло украл из инженерных чертежей из мультов, она очень стильная
+    ax.set_facecolor("#004488")
+
+    ax.set_title("Amplitude Modulation Signal", fontsize=14, fontweight="bold", color="white")
+    ax.set_xlabel("Time, [s]", color="white")
+    ax.set_ylabel("Amplitude", color="white")
+
+    ax.grid(True, color="gray", linestyle="--", alpha=0.5)
+
+    ax.tick_params(colors="white")
+    for spine in ax.spines.values():
+        spine.set_edgecolor("white")
+
+    (line,) = ax.plot([], [], lw=2, color="white")
+
+    update_with_args = partial(
+        _update_frame,
+        line=line,
+        axis=ax,
+        modulation=modulation,
+        fc=fc,
+        plot_duration=plot_duration,
+        time_step=time_step,
+        animation_step=animation_step,
+    )
+
+    anim = FuncAnimation(
+        fig, update_with_args, frames=num_frames, interval=animation_step * 1000, blit=False
+    )
+
+    if save_path != "":
+        anim.save(save_path, writer="pillow")
+    else:
+        pass
+
+    return anim
 
 
 if __name__ == "__main__":
+
     def modulation_function(t):
-        return np.cos(t * 6) 
+        return np.cos(t * 6)
 
-    num_frames = 100  
-    plot_duration = np.pi / 2 
-    time_step = 0.001  
-    animation_step = np.pi / 200 
-    fc = 50  
-    save_path_with_modulation = "modulated_signal.gif"
+    num_frames = 100
+    plot_duration = np.pi / 2
+    time_step = 0.001
+    animation_step = np.pi / 200
+    fc = 50
+    save_path_with_modulation = "blueprint_signal.gif"
 
     animation = create_modulation_animation(
         modulation=modulation_function,
@@ -38,6 +92,7 @@ def modulation_function(t):
         plot_duration=plot_duration,
         time_step=time_step,
         animation_step=animation_step,
-        save_path=save_path_with_modulation
+        save_path=save_path_with_modulation,
     )
-    HTML(animation.to_jshtml())
\ No newline at end of file
+
+    HTML(animation.to_jshtml())
diff --git a/solutions/sem02/lesson08/task2.py b/solutions/sem02/lesson08/task2.py
index b677c0702..43d11ac93 100644
--- a/solutions/sem02/lesson08/task2.py
+++ b/solutions/sem02/lesson08/task2.py
@@ -7,28 +7,26 @@
 from matplotlib.animation import FuncAnimation
 
 
-
-
 def animate_wave_algorithm(
-    maze: np.ndarray, 
-    start: tuple[int, int], 
-    end: tuple[int, int], 
-    save_path: str = ""
-)  -> FuncAnimation:
+    maze: np.ndarray, start: tuple[int, int], end: tuple[int, int], save_path: str = ""
+) -> FuncAnimation:
     # ваш код
     return FuncAnimation()
 
+
 if __name__ == "__main__":
     # Пример 1
-    maze = np.array([
-        [0, 0, 0, 0, 0, 0, 0],
-        [0, 1, 1, 1, 1, 1, 0],
-        [1, 1, 0, 1, 0, 1, 0],
-        [0, 0, 1, 1, 0, 1, 0],
-        [0, 0, 0, 0, 0, 1, 0],
-        [1, 1, 1, 1, 1, 1, 0],
-        [0, 0, 0, 0, 0, 0, 0],
-    ])
+    maze = np.array(
+        [
+            [0, 0, 0, 0, 0, 0, 0],
+            [0, 1, 1, 1, 1, 1, 0],
+            [1, 1, 0, 1, 0, 1, 0],
+            [0, 0, 1, 1, 0, 1, 0],
+            [0, 0, 0, 0, 0, 1, 0],
+            [1, 1, 1, 1, 1, 1, 0],
+            [0, 0, 0, 0, 0, 0, 0],
+        ]
+    )
 
     start = (2, 0)
     end = (5, 0)
@@ -36,9 +34,9 @@ def animate_wave_algorithm(
 
     animation = animate_wave_algorithm(maze, start, end, save_path)
     HTML(animation.to_jshtml())
-    
+
     # Пример 2
-    
+
     maze_path = "./data/maze.npy"
     loaded_maze = np.load(maze_path)
 
@@ -49,5 +47,3 @@ def animate_wave_algorithm(
 
     loaded_animation = animate_wave_algorithm(loaded_maze, start, end, loaded_save_path)
     HTML(loaded_animation.to_jshtml())
-    
-    
\ No newline at end of file
diff --git a/solutions/sem02/lesson10/task1.ipynb b/solutions/sem02/lesson10/task1.ipynb
index 4b4e9e335..a3c1a7217 100644
--- a/solutions/sem02/lesson10/task1.ipynb
+++ b/solutions/sem02/lesson10/task1.ipynb
@@ -39,9 +39,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
     "import seaborn as sns\n",
     "\n",
-    "\n",
     "titanic_data = sns.load_dataset(\"titanic\")\n",
     "titanic_data.sample(5)"
    ]
@@ -70,9 +71,7 @@
    "id": "cd2f1773",
    "metadata": {},
    "outputs": [],
-   "source": [
-    "# ваш код"
-   ]
+   "source": "propuski = titanic_data.isnull().sum()\npropuski"
   },
   {
    "cell_type": "markdown",
@@ -92,9 +91,7 @@
    "id": "7e458447",
    "metadata": {},
    "outputs": [],
-   "source": [
-    "# ваш код"
-   ]
+   "source": "n_strok = titanic_data.shape[0]\nn_stolbtsov = titanic_data.shape[1]\n\nporog_stolbtsov = n_strok / 2\ntitanic_chistiy = titanic_data.dropna(axis=\"columns\", thresh=porog_stolbtsov)\n\nporog_strok = titanic_chistiy.shape[1] / 2\ntitanic_chistiy = titanic_chistiy.dropna(thresh=porog_strok).copy()\n\nprint(f\"размер таблицы(я кстати даже тут зафейлил): {titanic_chistiy.shape}\")\ntitanic_chistiy.isnull().sum()"
   },
   {
    "cell_type": "markdown",
@@ -115,9 +112,7 @@
    "id": "f7db5e99",
    "metadata": {},
    "outputs": [],
-   "source": [
-    "# ваш код"
-   ]
+   "source": "vozrast_est = titanic_chistiy[\"age\"].notnull()\n\nmuzhchiny = titanic_chistiy[\"who\"] == \"man\"\nzhenschiny = titanic_chistiy[\"who\"] == \"woman\"\ndeti = titanic_chistiy[\"who\"] == \"child\"\n\nvozrast_muzhchin = titanic_chistiy.loc[vozrast_est & muzhchiny, \"age\"]\nvozrast_zhenschin = titanic_chistiy.loc[vozrast_est & zhenschiny, \"age\"]\nvozrast_detey = titanic_chistiy.loc[vozrast_est & deti, \"age\"]\n\nmediana_muzhchin = round(vozrast_muzhchin.median())\nmediana_zhenschin = round(vozrast_zhenschin.median())\nmediana_detey = round(vozrast_detey.median())\n\nprint(f\"срзнач мужчин: {mediana_muzhchin}\")\nprint(f\"женщин: {mediana_zhenschin}\")\nprint(f\"детей: {mediana_detey}\")\n\nvozrast_pusto = titanic_chistiy[\"age\"].isnull()\n\ntitanic_chistiy.loc[vozrast_pusto & muzhchiny, \"age\"] = mediana_muzhchin\ntitanic_chistiy.loc[vozrast_pusto & zhenschiny, \"age\"] = mediana_zhenschin\ntitanic_chistiy.loc[vozrast_pusto & deti, \"age\"] = mediana_detey\n\nprint(f\"пропуски в столбце age: {titanic_chistiy['age'].isnull().sum()}\")\ntitanic_chistiy.isnull().sum()"
   },
   {
    "cell_type": "markdown",
@@ -135,9 +130,7 @@
    "id": "67a0c6bc",
    "metadata": {},
    "outputs": [],
-   "source": [
-    "# ваш код"
-   ]
+   "source": "n_stolbtsov_teper = titanic_chistiy.shape[1]\nmin_znacheniy = n_stolbtsov_teper - 1\ntitanic_chistiy = titanic_chistiy.dropna(thresh=min_znacheniy)\n\nvse_propuski = titanic_chistiy.isnull().sum().sum()\nprint(f\"размер: {titanic_chistiy.shape}\")\nprint(f\"пропуски: {vse_propuski}\")"
   },
   {
    "cell_type": "markdown",
@@ -155,9 +148,7 @@
    "id": "6a2d0ae9",
    "metadata": {},
    "outputs": [],
-   "source": [
-    "# ваш код"
-   ]
+   "source": "goroda = titanic_chistiy[\"embark_town\"].value_counts()\n\nglavniy_gorod = goroda.index[0]\n\nprint(f\"самый популярный город: {glavniy_gorod}\")\ngoroda"
   },
   {
    "cell_type": "markdown",
@@ -175,9 +166,7 @@
    "id": "11acb4b4",
    "metadata": {},
    "outputs": [],
-   "source": [
-    "# ваш код"
-   ]
+   "source": "vyzhilo = titanic_chistiy[\"survived\"].sum()\nvsego = titanic_chistiy.shape[0]\n\ndolya = vyzhilo / vsego\nprotcent = round(dolya * 100, 2)\n\nprint(f\"сыжившие: {vyzhilo} из {vsego}\")\nprint(f\"процент: {protcent}%\")"
   },
   {
    "cell_type": "markdown",
@@ -195,9 +184,7 @@
    "id": "59ec7295",
    "metadata": {},
    "outputs": [],
-   "source": [
-    "# ваш код"
-   ]
+   "source": "vyzhivshiye = titanic_chistiy[titanic_chistiy[\"survived\"] == 1]\n\nvyzhivshiye_po_gorodam = vyzhivshiye[\"embark_town\"].value_counts()\nvyzhivshiye_po_gorodam"
   },
   {
    "cell_type": "markdown",
@@ -215,9 +202,7 @@
    "id": "34daca28",
    "metadata": {},
    "outputs": [],
-   "source": [
-    "# ваш код"
-   ]
+   "source": "klassy = titanic_chistiy[\"class\"].unique()\nslovar_protsentov = {}\n\nfor klass in klassy:\n    gruppa = titanic_chistiy[titanic_chistiy[\"class\"] == klass]\n\n    vsego_v_klasse = gruppa.shape[0]\n    vyzhilo_v_klasse = gruppa[\"survived\"].sum()\n\n    protcent = round(vyzhilo_v_klasse / vsego_v_klasse * 100, 2)\n    slovar_protsentov[klass] = protcent\n\nprotcenty_po_klassam = pd.Series(slovar_protsentov)\nprotcenty_po_klassam"
   },
   {
    "cell_type": "markdown",
@@ -235,9 +220,7 @@
    "id": "1fc0d667",
    "metadata": {},
    "outputs": [],
-   "source": [
-    "# ваш код"
-   ]
+   "source": "bogatiye = titanic_chistiy[titanic_chistiy[\"fare\"] >= 100]\n\nvsego_bogatikh = bogatiye.shape[0]\nvyzhilo_bogatikh = bogatiye[\"survived\"].sum()\n\nprotcent_bogatikh = round(vyzhilo_bogatikh / vsego_bogatikh * 100, 2)\nprint(f\"Богатые: {vsego_bogatikh}\")\nprint(f\"выжило: {vyzhilo_bogatikh}\")\nprint(f\"Процент: {protcent_bogatikh}%\")"
   },
   {
    "cell_type": "markdown",
@@ -255,16 +238,14 @@
    "id": "480352b6",
    "metadata": {},
    "outputs": [],
-   "source": [
-    "# ваш код"
-   ]
+   "source": "rebyata = titanic_chistiy[\"who\"] == \"child\"\nodni = titanic_chistiy[\"alone\"]\n\ndeti_odni = titanic_chistiy[rebyata & odni]\n\nprint(f\"дети в одиночку: {deti_odni.shape[0]}\")"
   },
   {
    "cell_type": "markdown",
    "id": "aac62cfd",
    "metadata": {},
    "source": [
-    "Какие выводы вы можете сделать о выживших пассажирах Титаника? "
+    "почему я не был на титанике :(("
    ]
   }
  ],
@@ -289,4 +270,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
+}
\ No newline at end of file