Skip to content

Commit

Permalink
feat: Adding Simple Frequency Table
Browse files Browse the repository at this point in the history
  • Loading branch information
@brotherzhafif
brotherzhafif committed Oct 12, 2024
1 parent a3f7bca commit b929b19
Show file tree
Hide file tree
Showing 2 changed files with 95 additions and 35 deletions.
87 changes: 69 additions & 18 deletions FrequencyTable.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -36,8 +36,13 @@ def __init__(self, dataset):
# Formula for Standard Deviation
self.deviation = (self.variance ** 0.5)



# Formula to find Dataset Skewness
self.skewness = (self.length / ((self.length - 1) * (self.length - 2))) * sum(((x - self.mean) / self.deviation) ** 3 for x in self.dataset)

# Formula to find Dataset
self.kurtosis = (self.length * (self.length + 1) * sum(((x - self.mean) / self.deviation) ** 4 for x in self.dataset) / ((self.length - 1) * (self.length - 2) * (self.length - 3))) - \
(3 * (self.length - 1) ** 2) / ((self.length - 2) * (self.length - 3))

# Populate Grouped Table Frequency Data Method
def PopulateGrouped(self):
# Initiating Used List
Expand Down Expand Up @@ -72,8 +77,8 @@ def PopulateGrouped(self):
top.append(current_number)

# Append Class Bottom Limit
current_bot_limit = old_number - 0.5
bottom_limit.append(current_bot_limit)
current_bottom_limit = old_number - 0.5
bottom_limit.append(current_bottom_limit)

# Append Class Top Limit
current_top_limit = current_number + 0.5
Expand All @@ -88,7 +93,7 @@ def PopulateGrouped(self):
data_range.append(current_data_range)

# Adding Data Range Limit Of The Class Frequency
current_data_limit = f"{current_bot_limit} ~ {current_top_limit}"
current_data_limit = f"{current_bottom_limit} ~ {current_top_limit}"
data_limit.append(current_data_limit)

# Adding Data Midpoint of The Class Frequency
Expand All @@ -99,7 +104,7 @@ def PopulateGrouped(self):
current_bot_cumulative_frequency = self.find_frequency(self.lowest, old_number)
bot_cumulative_frequency.append(current_bot_cumulative_frequency)

# Adding Bottom Cumulative Frequency of The Class
# Adding Top Cumulative Frequency of The Class
current_top_cumulative_frequency = self.find_frequency(old_number, self.highest)
top_cumulative_frequency.append(current_top_cumulative_frequency)

Expand All @@ -112,25 +117,72 @@ def PopulateGrouped(self):
mode_index = [i for i, val in enumerate(frequency) if val == max(frequency)]
mode = [data_range[i] for i in mode_index]

# Formula to find Dataset Skewness
skewness = (self.length / ((self.length - 1) * (self.length - 2))) * sum(((x - self.mean) / self.deviation) ** 3 for x in self.dataset)

# Formula to find Dataset
kurtosis = (self.length * (self.length + 1) * sum(((x - self.mean) / self.deviation) ** 4 for x in self.dataset) / ((self.length - 1) * (self.length - 2) * (self.length - 3))) - \
(3 * (self.length - 1) ** 2) / ((self.length - 2) * (self.length - 3))

# Append Processed Data into Data Attributes
self.grouped = ProcessedData(bottom, top, bottom_limit, top_limit,
self.grouped = ProcessedData(None, bottom, top, bottom_limit, top_limit,
frequency, data_range, data_limit, data_midpoint,
bot_cumulative_frequency, top_cumulative_frequency,
relative_frequency, skewness, kurtosis, mode)
relative_frequency, mode)

def PopulateSimple(self):
# Deleting Duplicate and Sort the Data
data = sorted(set(self.dataset))

# Initiating Used Variable
top_limit = []
bottom_limit = []
frequency = []
top_cumulative_frequency = []
bot_cumulative_frequency = []
relative_frequency = []
mode = []

for current_class in data:
# Bottom Limit of the Class
current_top_limit = current_class + 0.5
current_bottom_limit = current_class - 0.5

# Top Limit of the Class
top_limit.append(current_top_limit)
bottom_limit.append(current_bottom_limit)

# Calculate Current Class Frequency
current_frequency = self.dataset.count(current_class)
frequency.append(current_frequency)

# Calculate Current Class Bottom Cumulative Frequency
current_bot_cumulative_frequency = self.find_frequency(self.lowest, current_class)
bot_cumulative_frequency.append(current_bot_cumulative_frequency)

# Calculate Current Class Top Cumulative Frequency
current_top_cumulative_frequency = self.find_frequency(current_class, self.highest)
top_cumulative_frequency.append(current_top_cumulative_frequency)

# Calculate Current Class Relative Frequency
current_relative_frequency = np.round((current_frequency / self.length) * 100)
relative_frequency.append(current_relative_frequency)

# Temukan modus
mode_index = [i for i, val in enumerate(frequency) if val == max(frequency)]
mode = [data[i] for i in mode_index]

# Buat objek ProcessedData
self.simple = ProcessedData(data, None, None, bottom_limit, top_limit,
frequency, None, None, None,
bot_cumulative_frequency, top_cumulative_frequency,
relative_frequency, mode)

# Base 5 Rounding
def roundy(self, x, base = 5):
return base * round(x/base)

# Function To Find Frequency in Dataset with Desired Range (Top and Down Limit)
def find_frequency(self, bot, top):
try:
bot = int(bot)
top = int(top)
except (ValueError, TypeError) as e:
print(f"Error converting to int: {e}")

total_frequency = 0
for i in range(bot, top + 1):
frequency = self.dataset.count(i)
Expand All @@ -140,7 +192,8 @@ def find_frequency(self, bot, top):
# Processed Data Assignment
class ProcessedData:
# Limit (L), Frequency (F), Ranges (R), Midpoint (M), Cumulative (C), Relative (R)
def __init__(self, bot, top, bot_L, top_L, F, R, L, M, bot_CF, top_CF, RF, skew, kurt, mode):
def __init__(self, data, bot, top, bot_L, top_L, F, R, L, M, bot_CF, top_CF, RF, mode):
self.classval = data
self.bottom = bot
self.top = top
self.bottom_limit = bot_L
Expand All @@ -155,8 +208,6 @@ def __init__(self, bot, top, bot_L, top_L, F, R, L, M, bot_CF, top_CF, RF, skew,
self.relative_frequency = RF

self.percentage_relative_frequency = [ f"{rf * 1:.2f}%" for rf in self.relative_frequency ]
self.skewness = skew
self.kurtosis = kurt
self.mode = mode


43 changes: 26 additions & 17 deletions Main.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -4,37 +4,45 @@
import tabulate as tabulate

# Raw 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,
81, 53, 66, 74, 64, 52, 91, 78,
49, 87, 88, 50, 69, 84, 43, 65,
83, 70, 44, 61, 75, 80, 71, 63, 47,51)
dataset = (1,1,1,4,6,7,3,6,7,1,2,2,5,3,1,8,3,2)

# Initiate Object From The Raw Data
data = ft.FrequencyTable(dataset)

# Processing Raw Data to Frequency Grouped Frequency Table
data.PopulateGrouped()
data.PopulateSimple()

# Transform The Data To A Frequency Table
# Initiating The Data Using Pandas
# df = 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
# }
# )

df = pd.DataFrame(
{
"Class Interval" : data.grouped.ranges,
"Class Limit" : data.grouped.limit,
"Frequency" : data.grouped.frequency,
"Midpoint" : data.grouped.midpoint,
"Class" : data.simple.classval,
"Frequency" : data.simple.frequency,

"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
"C <" : data.simple.bottom_limit,
"CF <" : data.simple.bottom_cumulative_frequency,
"C >" : data.simple.top_limit,
"CF >" : data.simple.top_cumulative_frequency,
"Relative Frequency" : data.simple.percentage_relative_frequency
}
)


# Converting Pandas Data Into Tabulate
table = tabulate.tabulate(
df,
Expand All @@ -45,3 +53,4 @@
# Print Output Data
print(table)


0 comments on commit b929b19

Please sign in to comment.