feat: implementar estatísticas

utils/stats.py

@@ -0,0 +1,96 @@
+# pyright: basic
+
+import os
+
+import pandas as pd
+import numpy as np
+
+STAT_MENU = """=== Earthquakes ===
+ == Estatísticas == 
+[1] Média
+[2] Variância
+[3] Desvio padrão
+[4] Máximo
+[5] Mínimo
+
+[Q] Voltar ao menu principal
+"""
+
+
+def stat_menu(df: pd.DataFrame):
+    inStats = True
+    while inStats:
+        os.system("cls")
+        print(STAT_MENU)
+        usrIn = input("Opção: ").lower()
+
+        match usrIn:
+            case "1":
+                pass
+            case "2":
+                pass
+            case "3":
+                pass
+            case "4":
+                pass
+            case "5":
+                pass
+            case "q":
+                inStats = False
+                pass
+            case _:
+                pass
+
+
+def average(df: pd.DataFrame, filter_by):
+    values = df[filter_by].to_numpy()
+
+    if filter_by == "Magnitudes":
+        values = _unpack_mags(values)
+
+    return np.average(values)
+
+
+def variance(df, filter_by):
+    values = df[filter_by].to_numpy()
+
+    if filter_by == "Magnitudes":
+        values = _unpack_mags(values)
+
+    return np.var(values)
+
+
+def std_dev(df, filter_by):
+    values = df[filter_by].to_numpy()
+
+    if filter_by == "Magnitudes":
+        values = _unpack_mags(values)
+    
+    return np.std(values)
+
+
+def max(df, filter_by):
+    values = df[filter_by].to_numpy()
+
+    if filter_by == "Magnitudes":
+        values = _unpack_mags(values)
+    
+    return np.max(values)
+
+
+def min(df, filter_by):
+    values = df[filter_by].to_numpy()
+
+    if filter_by == "Magnitudes":
+        values = _unpack_mags(values)
+    
+    return np.min(values)
+
+
+def _unpack_mags(arr: np.ndarray):
+    newVals = np.empty(0)
+    for v in arr:
+        for m in v:
+            newVals = np.append(newVals, np.float32(m["Magnitude"]))
+    return newVals
+