Adding Example Code Tranforming Processed Data into Frequency Table w…

…ith Pandas and Tabulate

FrequencyTable.py

@@ -94,7 +94,7 @@ def Populate(self):
 
 
         # Append Processed Data into Data Attributes
-        self.data = ProcessedData(bottom, top, bottom_limit, top_limit, frequency, data_range, data_limit, data_midpoint, bot_cumulative_frequency, top_cumulative_frequency, relative_frequency)
+        self.final = ProcessedData(bottom, top, bottom_limit, top_limit, frequency, data_range, data_limit, data_midpoint, bot_cumulative_frequency, top_cumulative_frequency, relative_frequency)
 
     # Base 5 Rounding
     def roundy(self, x, base = 5):
@@ -124,4 +124,4 @@ def __init__(self, bot, top, bot_L, top_L, F, R, L, M, bot_CF, top_CF, RF):
         self.bottom_cumulative_frequency = bot_CF
         self.top_cumulative_frequency = top_CF
         self.relative_frequency = RF
-
+

Main.py

@@ -1,8 +1,10 @@
 # EXAMPLE PROGRAM
 import FrequencyTable as ft
+import pandas as pd
+import tabulate as tabulate
 
 # Raw Data
-data = (
+dataset = (
   58, 67, 45, 89, 72, 60, 76, 93, 
   55, 48, 62, 85, 79, 56, 41, 90, 
   77, 54, 68, 82, 46, 73, 57, 92, 
@@ -11,12 +13,39 @@
   83, 70, 44, 61, 75, 80, 71, 63, 47,51)
 
 # Initiate Object From The Raw Data
-table = ft.FrequencyTable(data)
+data = ft.FrequencyTable(dataset)
 
 # Processing Raw Data to Frequency Table
-table.Populate()
+data.Populate()
+
+# Adding Percent Symbol into The Relative Frequency Coloumn
+relative_frequency_with_percentage = [
+    f"{rf * 1:.2f}%" for rf in data.final.relative_frequency
+]
+
+# Transform The Data To A Frequency Table
+# Initiating The Data Using Pandas
+df = pd.DataFrame(
+    {
+        "Class Interval" : data.final.ranges,
+        "Class Limit" : data.final.limit,
+        "Frequency" : data.final.frequency,
+        "Midpoint" : data.final.midpoint,
+
+        "C <" : data.final.bottom_limit,
+        "CF <" : data.final.bottom_cumulative_frequency,
+        "C >" : data.final.top_cumulative_frequency,
+        "CF >" : data.final.top_cumulative_frequency,
+        "Relative Frequency" : relative_frequency_with_percentage
+    }
+)
+
+# Converting Pandas Data Into Tabulate
+table = tabulate.tabulate(
+    df,
+    headers='keys',
+    tablefmt='pipe'
+) 
+
+print(table)
 
-# Print The Data
-print(table.data.ranges) 
-print(table.data.frequency)
-print(table.data.relative_frequency)

README.md

@@ -15,6 +15,14 @@
 
       pip install numpy
 
+- Tabulate
+
+      pip install tabulate
+
+- Pandas
+
+      pip install pandas
+
 ### Structure
 - Program Structure