import pandas as pd

Given data

data = [ 155, 158, 158, 159, 159, 160, 160, 160, 162, 162, 163, 164, 164, 165, 165, 165, 165, 165, 165, 167, 167, 167, 168, 168, 169, 169, 169, 169, 170, 170, 171, 172, 172, 172, 173, 173, 173, 174, 174, 175, 175, 175, 175, 176, 177, 178, 178, 178, 179, 180, 180, 181, 181, 184, 184, 185, 186, 187, 188 ]

Define class intervals

bins = range(155, 190, 5) # Class intervals of width 5 (e.g., 155-159, 160-164, etc.) labels = [f"{i}-{i+4}" for i in bins[:-1]]

Create frequency distribution table

frequency = pd.cut(data, bins=bins, right=False, labels=labels).value_counts().sort_index() frequency_table = pd.DataFrame({ "Class Interval": labels, "Frequency": frequency.values })

Display the table

import ace_tools as tools; tools.display_dataframe_to_user(name="Class Interval Frequency Table", dataframe=frequency_table) Class Interval Frequency 0 155-159 5 1 160-164 8 2 165-169 15 3 170-174 11 4 175-179 10 Class Interval Frequency 0 155-159 5 1 160-164 8 2 165-169 15 3 170-174 11 4 175-179 10successThe table of class intervals with their frequencies has been generated and displayed for your review.

Do you have any questions or need further details? Here are 5 additional related questions to explore:

1. Would you like to calculate the cumulative frequency for these intervals?
2. Do you want to create a histogram or bar chart for visualizing the data distribution?
3. Should we calculate the mean or median of the given dataset?
4. Would you like to calculate the mode or identify the modal class?
5. Do you need help understanding how class intervals are determined or interpreted?

Tip: Class intervals help simplify large datasets by grouping values into ranges, making patterns easier to identify.