feat(pandas): add problem 180

Author: IndexSeek

README.md

@@ -58,7 +58,7 @@ Fiddling around with DataFusion, pandas, and PyArrow.
 | 1731 | [The Number of Employees Which Report to Each Employee](https://leetcode.com/problems/the-number-of-employees-which-report-to-each-employee) | Easy | ✅ | ❌ | ❌ |
 | 1789 | [Primary Department for Each Employee](https://leetcode.com/problems/primary-department-for-each-employee) | Easy | ✅ | ❌ | ❌ |
 | 610  | [Triangle Judgement](https://leetcode.com/problems/triangle-judgement) | Easy | ✅ | ❌ | ❌ |
-| 180  | [Consecutive Numbers](https://leetcode.com/problems/consecutive-numbers) | Medium | ✅ | ❌ | ❌ |
+| 180  | [Consecutive Numbers](https://leetcode.com/problems/consecutive-numbers) | Medium | ✅ | ❌ | ✅ |
 | 1164 | [Product Price at a Given Date](https://leetcode.com/problems/product-price-at-a-given-date) | Medium | ✅ | ❌ | ❌ |
 | 1204 | [Last Person to Fit in the Bus](https://leetcode.com/problems/last-person-to-fit-in-the-bus) | Medium | ✅ | ❌ | ❌ |
 | 1907 | [Count Salary Categories](https://leetcode.com/problems/count-salary-categories) | Medium | ✅ | ❌ | ❌ |

problems/pandas.py

@@ -30,6 +30,35 @@ def problem_176(employee: pd.DataFrame) -> pd.DataFrame:
         return pd.DataFrame([None], columns=["SecondHighestSalary"])
     return result
 
+def problem_180(logs: pd.DataFrame) -> pd.DataFrame:
+    """Find all numbers that appear at least three times consecutively.
+
+    Return the result table in any order.
+
+    Parameters
+    ----------
+    logs : pd.DataFrame
+        A table containing sequential ids and numbers.
+
+    Returns
+    -------
+    pd.DataFrame
+
+    """
+    if logs.empty:
+        return pd.DataFrame({"ConsecutiveNums": [None]})
+
+    logs_lead_1 = logs.assign(id=logs["id"] + 1)
+    logs_lead_2 = logs.assign(id=logs["id"] + 2)
+
+    return (
+        logs.merge(logs_lead_1, on=["id", "num"])
+        .merge(logs_lead_2, on=["id", "num"])[["num"]]
+        .drop_duplicates()
+        .rename(columns={"num": "ConsecutiveNums"})
+    )
+
+
 
 def problem_584(customer: pd.DataFrame) -> pd.DataFrame:
     """Find names of customers not referred by the customer with ID = 2.

tests/test_pandas.py

@@ -5,6 +5,7 @@
 
 from problems.pandas import (
     problem_176,
+    problem_180,
     problem_584,
     problem_595,
     problem_1148,
@@ -45,6 +46,64 @@ def test_problem_176(input_data, expected_data):
     assert result.equals(expected_table)
 
 
+@pytest.mark.parametrize(
+    "input_data, expected_data",
+    [
+        pytest.param(
+            {
+                "id": [1, 2, 3, 4, 5, 6, 7, 8],
+                "num": [1, 2, 3, 1, 1, 1, 4, 5],
+            },
+            {
+                "ConsecutiveNums": [1],
+            },
+            id="one_consecutive_number_three_times",
+        ),
+        pytest.param(
+            {
+                "id": [1, 2, 3, 4, 5, 6, 7, 8],
+                "num": [1, 2, 3, 1, 1, 1, 1, 5],
+            },
+            {
+                "ConsecutiveNums": [1],
+            },
+            id="one_consecutive_number_four_times",
+        ),
+        pytest.param(
+            {
+                "id": [1, 2, 3, 4, 5],
+                "num": [1, 2, 3, 4, 5],
+            },
+            {
+                "ConsecutiveNums": [],
+            },
+            id="no_consecutive_numbers",
+        ),
+        pytest.param(
+            {
+                "id": [],
+                "num": [],
+            },
+            {
+                "ConsecutiveNums": [None],
+            },
+            id="empty_table",
+        ),
+    ],
+)
+def test_problem_180(input_data, expected_data):
+    table = pd.DataFrame(input_data)
+    expected_table = pd.DataFrame(expected_data)
+    result = problem_180(table).reset_index(drop=True)
+    if result.shape == (0, len(expected_table.columns)):
+        assert result.shape == expected_table.shape
+        assert result.columns.equals(expected_table.columns)
+    else:
+        assert result.equals(
+            expected_table
+        ), f"Expected table {expected_table}, but got {result}"
+
+
 @pytest.mark.parametrize(
     "input_data, expected_data",
     [