fix: Grouped Frequency Last Row Keep Append Even Though 0 Frequency

brotherzhafif · Oct 13, 2024 · e012ff0 · e012ff0
1 parent cb20062
commit e012ff0
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Showing 2 changed files with 47 additions and 49 deletions.
diff --git a/FrequencyTable.py b/FrequencyTable.py
@@ -93,12 +93,13 @@ def PopulateGrouped(self):
         mode = []
 
         # Initiating Used Parameter for Frequency Table
+        old_number = 0
         interval = self.interval
         current_number = self.base - 1
-        old_number = 0
+        current_top_cumulative_frequency = 1
 
         # Processing the Frequency Table Data
-        while current_number <= self.top - 3:
+        while current_top_cumulative_frequency != 0:
             # Finding Class Lowest Value
             old_number = current_number + 1
             bottom.append(old_number)

diff --git a/Main.py b/Main.py
@@ -5,70 +5,67 @@
 
 # Raw Data
 dataset = [
-    'Mango', 'Pineapple', 'Banana', 'Banana', 'Pineapple', 'Banana', 
-    'Banana', 'Grapes', 'Pear', 'Pineapple', 'Orange', 'Strawberry', 
-    'Orange', 'Mango', 'Banana', 'Pineapple', 'Orange', 'Banana', 
-    'Strawberry', 'Pear', 'Apple', 'Banana', 'Pineapple', 'Orange', 
-    'Mango', 'Apple', 'Pear', 'Pear', 'Pear', 'Grapes', 'Pear', 
-    'Orange', 'Grapes', 'Strawberry', 'Mango', 'Orange', 'Orange', 
-    'Mango', 'Pear', 'Strawberry', 'Pear', 'Orange', 'Mango', 
-    'Mango', 'Pear', 'Grapes', 'Apple', 'Mango', 'Pineapple', 
-    'Strawberry', 'Strawberry', 'Grapes', 'Apple', 'Banana', 
-    'Grapes', 'Banana', 'Strawberry', 'Mango', 'Strawberry', 
-    'Orange', 'Pear', 'Grapes', 'Orange', 'Apple'
+    12.5, 12.5, 12.1, 12.6, 12.7, 12.5, 43.2, 43.2, 43.2, 43.5,
+    34.2, 34.1, 34.3, 34.2, 34.0, 34.5, 56.7, 56.8, 56.5, 56.6,
+    56.9, 57.0, 67.9, 67.8, 67.5, 67.6, 67.7, 78.4, 78.1, 78.3,
+    78.2, 78.9, 78.8, 89.0, 89.1, 89.2, 90.5, 91.2, 90.3, 90.0,
+    98.3, 98.1, 98.0, 99.5, 99.4, 99.6, 99.1, 99.2, 99.3, 99.0,
+    22.4, 22.3, 22.5, 22.2, 22.1, 22.0, 25.4, 25.5, 25.6, 25.0,
+    32.4, 32.5, 32.3, 32.2, 32.1, 32.0, 45.6, 45.5, 45.4, 45.0,
+    56.3, 56.4, 56.2, 56.1, 56.0, 60.5, 64.0, 64.1, 64.2, 64.3,
+    71.3, 71.4, 71.5, 71.6, 71.7, 71.8, 84.2, 84.3, 84.1, 84.0,
+    12.9, 12.8, 12.7, 12.6, 12.5, 12.4
 ]
 
 
 # Initiate Object From The Raw Data
 data = ft.FrequencyTable(dataset)
 
 # Processing Raw Data to Frequency Grouped Frequency Table
-# data.PopulateGrouped() # Grouped Data
-data.PopulateSimple() # Simple Data
+data.PopulateGrouped() # Grouped Data
+# data.PopulateSimple() # Simple Data
 
 # Transform The Data To A Frequency Table
 # Initiating The Data Using Pandas
 # Grouped Populated Data
-# dfg = pd.DataFrame(
-#     {
-#         "Class Interval" : data.grouped.ranges,
-#         "Class Limit" : data.grouped.limit,
-#         "Frequency" : data.grouped.frequency,
-#         "Midpoint" : data.grouped.midpoint,
-
-#         "C <" : data.grouped.bottom_limit,
-#         "CF <" : data.grouped.bottom_cumulative_frequency,
-#         "C >" : data.grouped.top_limit,
-#         "CF >" : data.grouped.top_cumulative_frequency,
-#         "Relative Frequency" : data.grouped.percentage_relative_frequency
-#     }
-# )
-
-# Simple Populated Data
-dfs = pd.DataFrame(
+dfg = pd.DataFrame(
     {
-        "Class" : data.simple.classval,
-        "Frequency" : data.simple.frequency,
-        "Relative Frequency" : data.simple.percentage_relative_frequency
+        "Class Interval" : data.grouped.ranges,
+        "Class Limit" : data.grouped.limit,
+        "Frequency" : data.grouped.frequency,
+        "Midpoint" : data.grouped.midpoint,
+
+        "C <" : data.grouped.bottom_limit,
+        "CF <" : data.grouped.bottom_cumulative_frequency,
+        "C >" : data.grouped.top_limit,
+        "CF >" : data.grouped.top_cumulative_frequency,
+        "Relative Frequency" : data.grouped.percentage_relative_frequency
     }
 )
 
-# Converting Pandas Data Into Tabulate
-tablesimple = tabulate.tabulate(
-    dfs,
-    headers='keys',
-    tablefmt='pipe'
-) 
-
-# tablegrouped = tabulate.tabulate(
-#     dfg,
-#     headers='keys',
-#     tablefmt='pipe',
+# Simple Populated Data
+# dfs = pd.DataFrame(
+#     {
+#         "Class" : data.simple.classval,
+#         "Frequency" : data.simple.frequency,
+#         "Relative Frequency" : data.simple.percentage_relative_frequency
+#     }
 # )
 
-# Print The Processed Data
-print(tablesimple)
-# print(tablegrouped)
+# Converting Pandas Data Into Tabulate
+# tablesimple = tabulate.tabulate(
+#     dfs,
+#     headers='keys',
+#     tablefmt='pipe'
+# ) 
 
+tablegrouped = tabulate.tabulate(
+    dfg,
+    headers='keys',
+    tablefmt='pipe',
+)
 
+# Print The Processed Data
+# print(tablesimple)
+print(tablegrouped)