Command Line Interface Reference

Real Simple Stats includes a command-line tool for quick calculations without writing Python code.

Installation and Setup

The CLI is automatically installed with the package:

pip install real-simple-stats

Verify installation:

rss-calc --help

Basic Usage

The CLI uses subcommands for different types of operations:

rss-calc <subcommand> [options]

Available subcommands:

  • stats - Descriptive statistics calculations

  • probability - Probability calculations

  • hypothesis - Hypothesis testing

  • glossary - Statistical term lookup

Global Options

--help, -h

Show help message and exit

--version

Show version information

Statistics Commands

Calculate descriptive statistics for datasets.

Basic Usage

rss-calc stats --data "1,2,3,4,5" --stat mean

Options

--data DATA

Comma-separated list of numeric values (required)

--stat STATISTIC

Statistic to calculate. Options:

  • mean - Arithmetic mean

  • median - Middle value

  • mode - Most frequent value

  • variance - Population variance

  • std - Standard deviation

  • cv - Coefficient of variation

  • all - All available statistics

Examples

Calculate mean:

rss-calc stats --data "10,20,30,40,50" --stat mean
# Output: Mean: 30.0

Calculate all statistics:

rss-calc stats --data "1,2,2,3,4,5" --stat all
# Output:
# Mean: 2.83
# Median: 2.5
# Mode: 2
# Variance: 2.47
# Standard Deviation: 1.57
# Coefficient of Variation: 55.56%

Probability Commands

Perform probability calculations and work with distributions.

Basic Usage

rss-calc probability --type binomial --n 10 --k 3 --p 0.5

Options

--type TYPE

Type of probability calculation:

  • binomial - Binomial probability

  • normal - Normal distribution (PDF or CDF)

  • bayes - Bayes’ theorem

Normal Distribution Options

--x X

Value at which to evaluate the PDF or CDF (required for normal)

--mean MEAN

Mean of the normal distribution (default: 0.0)

--std STD

Standard deviation of the normal distribution (default: 1.0, must be positive)

--cdf

Calculate cumulative distribution function (CDF) instead of PDF

Binomial Distribution Options

--n N

Number of trials (required for binomial, must be non-negative)

--k K

Number of successes (required for binomial, must be between 0 and n)

--p P

Probability of success (required for binomial, must be between 0 and 1)

Bayes’ Theorem Options

--p_b_given_a P_B_GIVEN_A

Conditional probability P(B|A) (required, must be between 0 and 1)

--p_a P_A

Prior probability P(A) (required, must be between 0 and 1)

--p_b P_B

Prior probability P(B) (required, must be between 0 and 1, cannot be zero)

Combination/Permutation Options

--n N

Total number of items

--k K

Number of items to choose/arrange

Simple Probability Options

--favorable F

Number of favorable outcomes

--total T

Total number of possible outcomes

Examples

Normal distribution PDF:

rss-calc prob --type normal --x 0 --mean 0 --std 1
# Output: PDF(X = 0.0) = 0.398942

Normal distribution CDF:

rss-calc prob --type normal --x 1.96 --mean 0 --std 1 --cdf
# Output: P(X ≤ 1.96) = 0.975002

Binomial probability:

rss-calc prob --type binomial --n 10 --k 3 --p 0.5
# Output: P(X = 3) = 0.117188

Bayes’ theorem:

rss-calc prob --type bayes --p_b_given_a 0.9 --p_a 0.01 --p_b 0.05
# Output: P(A|B) = 0.180000

Hypothesis Testing Commands

Perform statistical hypothesis tests.

Basic Usage

rss-calc hypothesis --test t-test --data "1,2,3,4,5" --mu 3.0

Options

--test TEST

Type of hypothesis test:

  • t-test - One-sample t-test

--data DATA

Comma-separated sample data (required)

--mu MU

Null hypothesis mean (required for t-test)

--alpha ALPHA

Significance level (default: 0.05)

Examples

One-sample t-test:

rss-calc hypothesis --test t-test --data "23,25,27,24,26" --mu 24.0 --alpha 0.05
# Output:
# One-sample t-test:
# Sample data: [23.0, 25.0, 27.0, 24.0, 26.0]
# Null hypothesis mean: 24.0
# Significance level: α = 0.05

Glossary Commands

Look up definitions of statistical terms.

Basic Usage

rss-calc glossary --term "standard deviation"

Options

--term TERM

Statistical term to look up (required)

--list

List all available terms

Examples

Look up a term:

rss-calc glossary --term "p-value"
# Output: [Definition of p-value]

List all terms:

rss-calc glossary --list
# Output: [List of all available terms]

Advanced Usage

Piping and Redirection

Save results to file:

rss-calc stats --data "1,2,3,4,5" --stat all > results.txt

Use with other commands:

echo "10,20,30,40,50" | rss-calc stats --stat mean

Batch Processing

Process multiple datasets:

#!/bin/bash
datasets=("1,2,3,4,5" "10,20,30" "100,200,300,400")

for data in "${datasets[@]}"; do
    echo "Dataset: $data"
    rss-calc stats --data "$data" --stat mean
    echo "---"
done

Integration with Scripts

Use in Python scripts:

import subprocess

result = subprocess.run([
    'rss-calc', 'stats',
    '--data', '1,2,3,4,5',
    '--stat', 'mean'
], capture_output=True, text=True)

print(result.stdout)

Error Handling

Common Errors and Solutions

Command not found: rss-calc

  • Ensure the package is installed: pip install real-simple-stats

  • Check if it’s in your PATH

  • Try: python -m real_simple_stats.cli --help

Invalid data format

  • Use comma-separated values without spaces: "1,2,3,4,5"

  • Ensure all values are numeric

  • Quote the data string to prevent shell interpretation

Missing required arguments

  • Check the help for required options: rss-calc <subcommand> --help

  • The CLI will tell you exactly which arguments are missing

Invalid argument values

  • Binomial: --n must be non-negative, --k must be between 0 and n, --p must be between 0 and 1

  • Normal: --std must be positive

  • Bayes: All probabilities must be between 0 and 1, and --p_b cannot be zero

  • You’ll get a specific error message explaining what’s wrong

Invalid statistic type

  • Use --stat all to see available options

  • Check spelling of statistic names

Tips and Best Practices

  1. Quote your data: Always quote comma-separated data to prevent shell issues

  2. Use meaningful filenames: When redirecting output, use descriptive names

  3. Check help first: Use --help with any command to see available options

  4. Validate your data: Ensure your input data makes sense for the calculation

  5. Use appropriate precision: Consider rounding results for readability

Output Formats

The CLI provides human-readable output by default.

Getting More Help

  • Use --help with any command for detailed usage

  • Check the main documentation for Python API details

  • Report CLI bugs on GitHub Issues

  • Request new CLI features through GitHub

The CLI is straightforward to use. Start with simple commands and explore more features as you need them.