Coming from dplR

dplPy is a Python companion to the R library dplR, and most workflows translate almost one-to-one. The biggest differences are ergonomic rather than conceptual:

• Data structure. dplR uses a data.frame of class "rwl" (years as row names); dplPy uses a pandas DataFrame indexed by year. Same idea, same orientation (years down, series across).
• Naming. R's dotted names become Python underscores (read.crn → read_crn, chron.ars → chron_ars).
• Calling style. library(dplR); chron(rwi) becomes import dplpy as dpl; dpl.chron(rwi).
• Return values. Some functions that print in R return a dict or DataFrame in dplPy (for example xdate returns a dict of segment correlations and flags).

Function map

Reading & writing

dplR	dplPy	Notes
read.rwl, read.tucson, read.compact	readers	Auto-detects format; readers_url for URLs
read.crn	read_crn	Single, stacked, and combined multi-site files
read.ids	read_ids	Site–tree–core parsing
write.rwl / write.tucson	writers(..., format="rwl")
write.crn	writers(..., format="crn")
combine.rwl	combine_rwl

Descriptive statistics

dplR	dplPy	Notes
rwl.stats	stats	Per-series mean, stdev, skew, kurtosis, gini, AR1, …
rwl.report	report
rwl.check	check	Findings-as-data QC checker (dplR 1.8.0 rwl.check)
summary	summary
sens1, sens2	sens1, sens2	Mean sensitivity (kept out of stats, as in dplR)
gini.coef	(column in stats)	Reported in the stats table

Detrending & standardization

dplR	dplPy	Notes
detrend, detrend.series	detrend	fit= selects Spline / ModNegExp / ModHugershoff / Mean / AgeDepSpline
rcs	rcs	Curve via fit=, arithmetic via method=, stiffness via period=; preset="crust" for the CRUST curve. Pith offset differs — see below.
ssf	ssf	Signal-free; preset="crust" variant
ads (age-dependent spline)	ads	Also detrend(fit="AgeDepSpline")
powt	powt	Power transformation

Chronology

dplR	dplPy	Notes
chron	chron	prewhiten=True adds the residual chronology
chron.ars	chron_ars	ARSTAN-style
chron.stabilized	chron_stabilized	Variance stabilization
ar / AR modelling	autoreg, ar_func	Yule-Walker by default, matching R's ar()

Crossdating

dplR	dplPy	Notes
corr.rwl.seg	xdate	dplR-faithful default; returns a dict
corr.series.seg	series_corr	Single-series diagnostics
ccf.series.rwl	series_corr	Cross-correlation view of one series
interseries.cor	interseries_corr	Overall interseries correlation
xdate.floater	xdate_floater	Extended with Wilson (2026) t-statistics
xdate.report	xdate_report	COFECHA-style batch report (xdate.report arrived in dplR 1.8.0)
(COFECHA itself has no dplR equivalent)	xdate(preset="COFECHA")	Full COFECHA emulation mode

Signal strength, agreement & indices

dplR	dplPy	Notes
rwi.stats, rwi.stats.running	rwi_stats, rwi_stats_running
sss	sss	Subsample signal strength
glk, sgc	glk, sgc	Gleichläufigkeit / synchronous growth changes
treeMean	tree_mean	Average cores to tree level
common.interval	common_interval
bai.out, bai.in	bai_out, bai_in	Basal area increment
po.to.wc, wc.to.po	po_to_wc, wc_to_po	Pith-offset conversion. dplPy's pith_offset is a true offset (0 = pith present); dplR's is the cambial age of the first ring (1 = pith present), so subtract 1 from a dplR po table.
fill.internal.NA	fill_internal	Interior-gap infilling

Plotting

dplR	dplPy	Notes
plot.rwl, plot.crn, spag.plot, seg.plot	plot	type= selects the plot style
crossdating plots	xdate(plot=True), xdate_plot, series_corr(plot=True)

Beyond dplR

dplPy adds LiPD interchange, which dplR does not provide:

dplPy	Notes
to_lipd, from_lipd, lipd_metadata	Requires the [lipd] extra

Not yet ported

dplPy targets the core standardization, chronology, and crossdating workflow. Some specialized dplR tools — for example superposed epoch analysis, spectral and wavelet methods, skeleton-plot crossdating, and interactive detrending — are not yet available. dplR 1.8.0 also added insert.ring (insert a missing or false ring and refit the series length), chron.ci (bootstrap chronology confidence intervals), and read.sheet / write.sheet (tidy/long and delimited spreadsheet I/O); these are not yet in dplPy. Check the API Reference for the current surface, and the project repository to request or contribute a port.

A note on fidelity

Where dplPy claims to reproduce a dplR (or COFECHA, or ARSTAN) method, the behavior is checked against those reference implementations, and deliberate departures are documented in the relevant function's docstring. The clearest example is crossdating: xdate's A flag reproduces dplR's corr.rwl.seg exactly. dplR 1.8.0 added a lag search of its own (corr.rwl.seg(lag.max=)) but reports it separately and still flags on significance alone; dplPy's B (lag-shift) flag folds that lag result into an explicit COFECHA-style flag.