document.write( "Question 1167602: Following table displays the number of days to maturity for 40 short-term investments.
\n" ); document.write( "77,64,99,55,64,89,87,65,62,38,67,70,60,69,78,39,75,56,71,51,68,95,57,53,47,50,55,81,80,98,51,36,63,66,85,79,83,70,99,78.\r
\n" ); document.write( "\n" ); document.write( "required: A)construct frequency distribution of size 10.
\n" ); document.write( " B)construct histogram.
\n" ); document.write( "

Algebra.Com's Answer #852320 by CPhill(1987)\"\" \"About 
You can put this solution on YOUR website!
```python?code_reference&code_event_index=2
\n" ); document.write( "import pandas as pd
\n" ); document.write( "import numpy as np
\n" ); document.write( "import matplotlib.pyplot as plt\r
\n" ); document.write( "\n" ); document.write( "# Data
\n" ); document.write( "data_str = \"77,64,99,55,64,89,87,65,62,38,67,70,60,69,78,39,75,56,71,51,68,95,57,53,47,50,55,81,80,98,51,36,63,66,85,79,83,70,99,78\"
\n" ); document.write( "days = np.array([int(x.strip()) for x in data_str.split(',')])\r
\n" ); document.write( "\n" ); document.write( "# --- A) Construct frequency distribution of size 10 ---
\n" ); document.write( "class_size = 10
\n" ); document.write( "min_val = days.min()
\n" ); document.write( "max_val = days.max()\r
\n" ); document.write( "\n" ); document.write( "# Define bins starting at a convenient round number below the minimum (36) and extending past the maximum (99)
\n" ); document.write( "start_bin = 30
\n" ); document.write( "end_bin = 100 + class_size # Ensure the max value (99) is included
\n" ); document.write( "bins = np.arange(start_bin, end_bin, class_size)\r
\n" ); document.write( "\n" ); document.write( "# Calculate frequencies
\n" ); document.write( "# pd.cut automatically creates the class intervals and counts the occurrences
\n" ); document.write( "# right=False ensures the interval is (a, b], which is standard for days/age data, but for continuous data (like height), (a, b] is standard.
\n" ); document.write( "# For discrete days, [a, b) is often better to avoid ambiguity at the boundary. Let's use [a, b) intervals:
\n" ); document.write( "freq_counts = pd.cut(days, bins=bins, right=False, include_lowest=True, labels=False)
\n" ); document.write( "frequency_distribution = pd.Series(freq_counts).value_counts().sort_index()\r
\n" ); document.write( "\n" ); document.write( "# Create a DataFrame for presentation
\n" ); document.write( "class_labels = [f\"[{bins[i]}, {bins[i+1]})\" for i in range(len(bins) - 1)]
\n" ); document.write( "freq_df = pd.DataFrame({
\n" ); document.write( " 'Days to Maturity': class_labels[:len(frequency_distribution)],
\n" ); document.write( " 'Frequency': frequency_distribution.values
\n" ); document.write( "})\r
\n" ); document.write( "\n" ); document.write( "# --- B) Construct histogram ---
\n" ); document.write( "plt.figure(figsize=(10, 6))
\n" ); document.write( "# We use the same bins and set the edgecolor for better visualization
\n" ); document.write( "plt.hist(days, bins=bins, edgecolor='black', rwidth=0.9, align='left')\r
\n" ); document.write( "\n" ); document.write( "plt.title('Histogram of Days to Maturity for Short-Term Investments')
\n" ); document.write( "plt.xlabel('Days to Maturity')
\n" ); document.write( "plt.ylabel('Frequency')
\n" ); document.write( "plt.xticks(bins[:-1], class_labels[:len(bins)-1], rotation=45, ha='right')
\n" ); document.write( "plt.grid(axis='y', alpha=0.7)\r
\n" ); document.write( "\n" ); document.write( "# Save the histogram
\n" ); document.write( "histogram_filename = \"days_to_maturity_histogram.png\"
\n" ); document.write( "plt.savefig(histogram_filename)
\n" ); document.write( "plt.close()\r
\n" ); document.write( "\n" ); document.write( "print(f\"Frequency Distribution Table:\n{freq_df.to_string(index=False)}\")
\n" ); document.write( "print(f\"Histogram saved as {histogram_filename}\")\r
\n" ); document.write( "\n" ); document.write( "```\r
\n" ); document.write( "\n" ); document.write( "```text?code_stdout&code_event_index=2
\n" ); document.write( "Frequency Distribution Table:
\n" ); document.write( "Days to Maturity Frequency
\n" ); document.write( " [30, 40) 3
\n" ); document.write( " [40, 50) 1
\n" ); document.write( " [50, 60) 8
\n" ); document.write( " [60, 70) 10
\n" ); document.write( " [70, 80) 8
\n" ); document.write( " [80, 90) 6
\n" ); document.write( " [90, 100) 4
\n" ); document.write( "Histogram saved as days_to_maturity_histogram.png\r
\n" ); document.write( "\n" ); document.write( "```\r
\n" ); document.write( "\n" ); document.write( "[image-tag: code-generated-image-0-1760895148792561938]\r
\n" ); document.write( "\n" ); document.write( "I've processed the data and generated both the frequency distribution and the histogram as requested.\r
\n" ); document.write( "\n" ); document.write( "## A) Frequency Distribution (Class Size 10)\r
\n" ); document.write( "\n" ); document.write( "The class intervals were set to be of size $10$, starting at $30$ and using the format $[a, b)$ where $a$ is included but $b$ is excluded.\r
\n" ); document.write( "\n" ); document.write( "| Days to Maturity | Frequency |
\n" ); document.write( "| :--- | :--- |
\n" ); document.write( "| $[30, 40)$ | 3 |
\n" ); document.write( "| $[40, 50)$ | 1 |
\n" ); document.write( "| $[50, 60)$ | 8 |
\n" ); document.write( "| $[60, 70)$ | 10 |
\n" ); document.write( "| $[70, 80)$ | 8 |
\n" ); document.write( "| $[80, 90)$ | 6 |
\n" ); document.write( "| $[90, 100)$ | 4 |\r
\n" ); document.write( "\n" ); document.write( "**Total:** 40\r
\n" ); document.write( "\n" ); document.write( "-----\r
\n" ); document.write( "\n" ); document.write( "## B) Histogram\r
\n" ); document.write( "\n" ); document.write( "The histogram visually represents the frequency distribution above. It shows that the most common number of days to maturity falls within the **$[60, 70)$** interval, with $10$ investments.
\n" ); document.write( "
\n" );