Day 2

day2/part-1.py

@@ -0,0 +1,37 @@
+import pandas as pd
+import os
+
+data_path = os.path.join(os.getcwd(), "data.txt")
+reports_df = pd.read_csv(data_path, header=None, sep=" ", names=range(0, 8))
+
+
+def verify_levels_safety(levels):
+    safe = True
+
+    for index in range(levels.shape[0]):
+        if index == 0:
+            continue
+
+        diff = abs(levels.iloc[index - 1] - levels.iloc[index])
+
+        if diff == 0 or diff > 3:
+            safe = False
+            break
+
+    return safe
+
+
+def verify_report_safety(row):
+    row_no_nan = row.dropna()
+    row_asc = row_no_nan.sort_values(ascending=True)
+    row_desc = row_no_nan.sort_values(ascending=False)
+
+    if row_no_nan.equals(row_asc) or row_no_nan.equals(row_desc):
+        return verify_levels_safety(row_no_nan)
+
+    return False
+
+
+is_safe_df = reports_df.apply(verify_report_safety, axis=1)
+safe_reports_num = is_safe_df.sum()
+print(safe_reports_num)

day2/part-2.py

@@ -0,0 +1,52 @@
+import pandas as pd
+import os
+
+data_path = os.path.join(os.getcwd(), "data.txt")
+reports_df = pd.read_csv(data_path, header=None, sep=" ", names=range(0, 8))
+
+
+def verify_levels_safety(levels):
+    levels_asc = levels.sort_values(ascending=True)
+    levels_desc = levels.sort_values(ascending=False)
+
+    if not levels.equals(levels_asc) and not levels.equals(levels_desc):
+        return False
+
+    safe = True
+
+    for index in range(levels.shape[0]):
+        if index == 0:
+            continue
+
+        diff = abs(levels.iloc[index - 1] - levels.iloc[index])
+
+        if diff == 0 or diff > 3:
+            safe = False
+            break
+
+    return safe
+
+
+def verify_report_safety(levels):
+    row_no_nan = levels.dropna()
+    safe = verify_levels_safety(row_no_nan)
+
+    if safe:
+        return True
+
+    safe_single_bad = False
+
+    for index_to_delete in range(row_no_nan.shape[0]):
+        levels_copy = row_no_nan.copy()
+        levels_single_bad = levels_copy.drop(levels_copy.iloc[[index_to_delete]].index)
+        safe_single_bad = verify_levels_safety(levels_single_bad)
+
+        if safe_single_bad:
+            break
+
+    return safe_single_bad
+
+
+is_safe_df = reports_df.apply(verify_report_safety, axis=1)
+safe_reports_num = is_safe_df.sum()
+print(safe_reports_num)