falta extra

TPC1/tpc1.py

@@ -1,14 +1,15 @@
+import matplotlib.pyplot as plt
+
 # idade -> i, sexo -> s, tensao -> t, colesterol -> c, batimento -> b, doenca -> d
 # estrutura de dados: [{"i": 1 , "s" : F | M}]
 data = []
 
-
 def readFile(filename):
-    f = open(filename, "r")
+    f = open(filename, 'r')
     lines = f.readlines()
     lines.pop(0)
     for line in lines:
-        values = line.split(",")
+        values = line.split(',')
         idade = int(values[0])
         sexo = values[1]
         tensao = int(values[2])
@@ -16,28 +17,96 @@ def readFile(filename):
         batimento = int(values[4])
         temDoenca = bool(values[5])
         data_entry = {
-                      "i": idade,
-                      "s": sexo,
-                      "t": tensao,
-                      "c": colesterol,
-                      "b": batimento,
-                      "d": temDoenca
+                      'i': idade,
+                      's': sexo,
+                      't': tensao,
+                      'c': colesterol,
+                      'b': batimento,
+                      'd': temDoenca
                 }
         data.append(data_entry)
 
-# distrib colesterol: fazer uma lista em que o index dos elementos e a divisao inteira dos valores
-# distribuicoes vao ser dicionarios   
+def distrib_sexo():
+    dist = {}
+    size_of_data = len(data)
+    for entry in data:
+        if entry['d']:
+            if dist.keys().__contains__(entry['s']):
+                dist[entry['s']] += 1
+            else:
+                dist[entry['s']] = 1
+    for (k,v) in dist.items():
+        percentage = v/size_of_data 
+        dist[k] = percentage 
+    return dist
 
 
+def distrib_etaria():
+    dist = {}
+    size_of_data = len(data)
+
+    for entry in data:
+        if entry['i'] >= 30 and entry['d']:
+            lim_inf = (entry['i'] // 5) * 5
+            lim_sup = lim_inf + 4
+            position = str(lim_inf) + '-' + str(lim_sup)
+            if dist.keys().__contains__(position):
+                dist[position] += 1
+            else:
+                dist[position] = 1
+
+    for (k,v) in dist.items():
+        percentage = v/size_of_data 
+        dist[k] = percentage 
+    return dist
+
+
+def distrib_colesterol():
+    dist = {}
+    size_of_data = len(data)
+    
+    for entry in data:
+        lim_inf = (entry['c'] // 10) * 10
+        lim_sup = lim_inf + 9
+        position = str(lim_inf) + '-' + str(lim_sup)
+        if dist.keys().__contains__(position):
+            dist[position] += 1
+        else:
+            dist[position] = 1
+
+    for (k,v) in dist.items():
+        percentage = v/size_of_data 
+        dist[k] = percentage 
+    return dist
+
+
+def show_distrib(type,dist):
+    title_key = "Key"
+    title_val = "Valor"
+    match type:
+        case 0:
+            title_key = "Sexo"
+        case 1:
+            title_key = "Faixa Etaria"
+        case 2:
+            title_key = "Colesterol"
+    max_key_len = max(max(len(str(k)) for k in dist.keys()),len(title_key))
+    max_val_len = max(max(len(str(v)) for v in dist.values()),len(title_val))
+
+    print('+' + '-'*(max_key_len+2) + '+' + '-'*(max_val_len+2) + '+')
+    print('| {:{}} | {:{}} |'.format(title_key, max_key_len, title_val, max_val_len))
+    print('+' + '-'*(max_key_len+2) + '+' + '-'*(max_val_len+2) + '+')
+    for title_key, title_val in sorted(dist.items()):
+        print('| {:{}} | {:{}} |'.format(title_key, max_key_len, title_val, max_val_len))
+    print('+' + '-'*(max_key_len+2) + '+' + '-'*(max_val_len+2) + '+')
      
 
 def main():
     readFile("myheart.csv")
-    min = 200
-    for entry in data:
-        if entry['i'] < min:
-            min = entry["i"]
-    print(f"idade min -> {min}")
+    dist_sexo = distrib_sexo()
+    dist_etaria = distrib_etaria()
+    dist_colesterol = distrib_colesterol()
+    show_distrib(1,dist_etaria)
      
 
 if __name__ == "__main__":