diff --git a/FrequencyTable.py b/FrequencyTable.py index 4910f37..781bb8d 100644 --- a/FrequencyTable.py +++ b/FrequencyTable.py @@ -108,69 +108,77 @@ def find_frequency(self, bot, top): # Populate Grouped Table Frequency Data Method def PopulateGrouped(self): - self.reset() # Reset the frequency table data before processing - - # Initiating Used Parameter for Frequency Table - old_number = 0 - interval = self.interval - current_number = self.base - 1 - current_top_cumulative_frequency = 1 - - # Processing the Frequency Table Data - while current_top_cumulative_frequency != 0: - # Finding Class Lowest Value - old_number = current_number + 1 - bottom.append(old_number) - - # Finding Class Highest Value - current_number = current_number + interval - top.append(current_number) - - # Append Class Bottom Limit - current_bottom_limit = old_number - 0.5 - bottom_limit.append(current_bottom_limit) + try: + # Check if the dataset contains text + if any(isinstance(item, str) for item in self.dataset): + raise ValueError("Text data is not allowed for grouped frequency tables. Please provide numeric data only.") + + self.reset() # Reset the frequency table data before processing + + # Initiating Used Parameter for Frequency Table + old_number = 0 + interval = self.interval + current_number = self.base - 1 + current_top_cumulative_frequency = 1 + + # Processing the Frequency Table Data + while current_top_cumulative_frequency != 0: + # Finding Class Lowest Value + old_number = current_number + 1 + bottom.append(old_number) + + # Finding Class Highest Value + current_number = current_number + interval + top.append(current_number) + + # Append Class Bottom 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 - top_limit.append(current_top_limit) + # Append Class Top Limit + current_top_limit = current_number + 0.5 + top_limit.append(current_top_limit) - # Finding The Frequency That Range - current_frequency = self.find_frequency(old_number, current_number + 1) - frequency.append(current_frequency) + # Finding The Frequency That Range + current_frequency = self.find_frequency(old_number, current_number + 1) + frequency.append(current_frequency) - # Adding The Number Range From Both Frequency - current_data_range = f"{old_number:.2f} ~ {current_number:.2f}" if not all(isinstance(x, int) for x in self.dataset) else f"{old_number} ~ {current_number}" - data_range.append(current_data_range) + # Adding The Number Range From Both Frequency + current_data_range = f"{old_number:.2f} ~ {current_number:.2f}" if not all(isinstance(x, int) for x in self.dataset) else f"{old_number} ~ {current_number}" + data_range.append(current_data_range) - # Adding Data Range Limit Of The Class Frequency - current_data_limit = f"{current_bottom_limit:.2f} ~ {current_top_limit:.2f}" if not all(isinstance(x, int) for x in self.dataset) else f"{current_bottom_limit} ~ {current_top_limit}" - data_limit.append(current_data_limit) + # Adding Data Range Limit Of The Class Frequency + current_data_limit = f"{current_bottom_limit:.2f} ~ {current_top_limit:.2f}" if not all(isinstance(x, int) for x in self.dataset) else f"{current_bottom_limit} ~ {current_top_limit}" + data_limit.append(current_data_limit) - # Adding Data Midpoint of The Class Frequency - current_data_midpoint = (old_number + current_number) / 2 - data_midpoint.append(current_data_midpoint) + # Adding Data Midpoint of The Class Frequency + current_data_midpoint = (old_number + current_number) / 2 + data_midpoint.append(current_data_midpoint) - # Adding Bottom Cumulative Frequency of The Class - current_bot_cumulative_frequency = self.find_frequency(self.lowest - 1, old_number) - bot_cumulative_frequency.append(current_bot_cumulative_frequency) + # Adding Bottom Cumulative Frequency of The Class + current_bot_cumulative_frequency = self.find_frequency(self.lowest - 1, old_number) + bot_cumulative_frequency.append(current_bot_cumulative_frequency) - # Adding Top Cumulative Frequency of The Class - current_top_cumulative_frequency = self.find_frequency(current_number + 1, self.highest + 1) - top_cumulative_frequency.append(current_top_cumulative_frequency) - - # Counting the Relative Frequency in Percentage - current_relative_frequency = np.round((current_frequency / self.length) * 100) - relative_frequency.append(current_relative_frequency) + # Adding Top Cumulative Frequency of The Class + current_top_cumulative_frequency = self.find_frequency(current_number + 1, self.highest + 1) + top_cumulative_frequency.append(current_top_cumulative_frequency) + + # Counting the Relative Frequency in Percentage + current_relative_frequency = np.round((current_frequency / self.length) * 100) + relative_frequency.append(current_relative_frequency) - # Find Mode or Data that appears most frequently - mode_index = [i for i, val in enumerate(frequency) if val == max(frequency)] - mode = [data_range[i] for i in mode_index] - - # Append Processed Data into Data Attributes - 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, mode) + # Find Mode or Data that appears most frequently + mode_index = [i for i, val in enumerate(frequency) if val == max(frequency)] + mode = [data_range[i] for i in mode_index] + + # Append Processed Data into Data Attributes + 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, mode) + + except ValueError as e: + print(f"Error: {e}") # Populate Simple Table Frequency Data Method def PopulateSimple(self):