Function reference • brolgar

Data

Datasets that come with brolgar

wages: Wages data from National Longitudinal Survey of Youth (NLSY)

heights: World Height Data

pisa: Student data from 2000-2018 PISA OECD data

ggplot helpers

ggplot2 functions to help explore your data

facet_sample(): Facet data into groups to facilitate exploration

facet_strata(): Facet data into groups to facilitate exploration

Sampling helpers

Functions to help sampling series from the data

sample_n_keys() sample_frac_keys(): Sample a number or fraction of keys to explore

stratify_keys(): Stratify the keys into groups to facilitate exploration

Features

Identify features in your data:

feat_three_num() feat_five_num() feat_ranges() feat_spread() feat_monotonic() feat_brolgar() feat_diff_summary(): Calculate features of a tsibble object in conjunction with features()

Exploratory tools (Experimental)

Tools to help with exploratory modelling of your data

key_slope() add_key_slope() add_key_slope.default(): Fit linear model for each key

keys_near(): Return keys nearest to a given statistics or summary.

keys_near(<data.frame>): Return keys nearest to a given statistics or summary.

keys_near(<tbl_ts>): Return keys nearest to a given statistics or summary.

Find observations near a value

Identify observations near some summary value

near_between(): Return x percent to y percent of values

near_middle(): Return the middle x percent of values

near_quantile(): Which values are nearest to any given quantiles

nearest_lgl() nearest_qt_lgl(): Is x nearest to y?

Summaries

Functions that are used to power the summary functions in brolgar

b_min() b_max() b_median() b_mean() b_q25() b_q75() b_range() b_range_diff() b_sd() b_var() b_mad() b_iqr() b_diff_var() b_diff_sd() b_diff_mean() b_diff_median() b_diff_q25() b_diff_q75() b_diff_max() b_diff_min() b_diff_iqr(): Brolgar summaries (b_summaries)

l_five_num l_three_num: A named list of the five number summary

Helpers

Helper functions to assist summarising data

n_obs(): Return the number of observations

add_n_obs(): Add the number of observations for each key in a tsibble

reexports features features_at features_if features_all as_tsibble n_keys: Objects exported from other packages

increasing() decreasing() unvarying() monotonic(): Are values monotonic? Always increasing, decreasing, or unvarying?

index_regular() index_summary(): Index summaries