C2Percentiles 0.1.0

All nine Hyndman-Fan sample-quantile estimators plus pandas helpers & plots.

C2Percentiles

A lightweight, zero-dependency (core) Python package that delivers all nine Hyndman-Fan sample-quantile estimators—plus ready-made helpers for multi-column, group-wise, and visual work-flows.

PyPI pip install C2Percentiles

License MIT

Python ≥ 3.8

---

Why this package?

Standard libraries (NumPy, pandas) give you only one estimator—Type 7.
Research or regulatory work often needs Type 8 (median-unbiased) or Type 9 (normal QQ-plots).
C2Percentiles gives you all nine in a single line, plus batteries-included helpers for:

• single vectors
• many columns at once
• stratification by groups
• quick Seaborn/ Matplotlib visuals

---

Installation

# core only – no plotting
pip install C2Percentiles

# with plotting extras
pip install "C2Percentiles[plots]"

---

60-second tutorial

import numpy as np, pandas as pd, quantile_kit as qk

# any 1-D data
x = np.random.randn(100)

# all nine 0.25, 0.50, 0.75 quantiles
qk.quantile_custom(x, [0.25, 0.5, 0.75], qtype="all")
# → DataFrame indexed by probability

# only Types 7 & 8, 4 sig-digits, pretty strings
qk.quantile_custom(x, [0.1, 0.9], qtype=[7, 8], sig_digits=4)

# many columns at once
df = pd.DataFrame({"A": np.random.randn(80),
                   "B": np.random.randn(80)*50 + 100,
                   "Group": np.random.choice(["G1", "G2"], 80)})

qk.quantiles_for_vars(df, ["A", "B"], probs=[0.05, 0.5, 0.95])
# → long table: Variable | Probability | Type1 … Type9

# group-wise
qk.quantiles_by_group(df, "Group", ["A", "B"], probs=[0.25, 0.75])

# quick plot – estimator spread
qk.plot_quantile_line(df["B"], probs=[0.05, 0.5, 0.95])

---

API reference

Signature	Description
quantile_custom(x, probs, qtype=7, sig_digits=None)	core engine
quantiles_for_vars(df, vars, probs, qtype, sig_digits)	multi-column
quantiles_by_group(df, group_var, num_vars, probs, qtype, sig_digits)	grouped
plot_quantile_line(x, probs, …)	single-variable plot
plot_qfv(df, vars, probs, …)	faceted by variable
plot_qbg(df, group_var, vars, probs, …)	faceted by group & variable

Full doc-strings are available via help(...) or your IDE.

---

Citation

If you use this package in research, please cite:

Hyndman, R. J. and Fan, Y. (1996) “Sample Quantiles in Statistical Packages”, American Statistician 50(4): 361–365.

---

License

MIT – see LICENSE file.