Package index • lares

All functions

ROC(): AUC and ROC Curves Data

autoline(): New Line Feed for Long Strings (Wrapper)

balance_data(): Balance Binary Data by Resampling: Under-Over Sampling

bind_files(): Bind Files into Dataframe

bring_api(): Get API (JSON) and Transform into data.frame

cache_write() cache_read() cache_exists() cache_clear() cache_pipe(): Cache Save and Load (Write and Read)

categ_reducer(): Reduce categorical values

check_opts() check_attr(): Validate inputs (attributions, options, ...)

chr2num() chr2logical() chr2date(): Check character values for date/numeric/logical and change datatype

ci_lower() ci_upper(): Lower/Upper Confidence Intervals

ci_var(): Confidence Intervals on Dataframe

cleanText() cleanNames(): Clean text strings automatically

clusterKmeans(): Automated K-Means Clustering + PCA/t-SNE

clusterOptimalK(): Visualize K-Means Clusters for Several K Methods

clusterVisualK(): Visualize K-Means Clusters for Several K

conf_mat(): Confussion Matrix

corr(): Correlation table

corr_cross(): Ranked cross-correlation across all variables

corr_var() plot(<corr_var>): Correlation between variable and dataframe

cran_logs(): Download and plot daily downloads of CRAN packages

crosstab(): Weighted Cross Tabulation

dalex_local(): DALEX Local

dalex_residuals(): DALEX Residuals

dalex_variable(): DALEX Partial Dependency Plots (PDP)

date_cuts(): Convert Date into Year + Cut

date_feats(): One Hot Encoding for Date/Time Variables (Dummy Variables)

db_download(): Download/Import Dropbox File by File's Name

db_upload(): Upload Local Files to Dropbox

df_str(): Dataset columns and rows structure

dfr: Results for AutoML Predictions

dft: Titanic Dataset

dist2d(): Distance from specific point to line

distr(): Compare Variables with their Distributions

errors() rmse() mae() mse() mape() rsq() rsqa(): Calculate Continuous Values Errors

etf_sector(): ETF's Sectors Breakdown

export_plot(): Export ggplot2, gridExtra, or any plot object into rendered file

export_results(): Export h2o_automl's Results

fb_accounts(): Facebook Ad Accounts

fb_ads(): Facebook Ads API

fb_creatives(): Facebook Creatives API

fb_insights(): Facebook Insights API

fb_process(): Paginate and Process Facebook's API Results

fb_report_check(): Facebook API Report Status Check

fb_rf(): Facebook Reach and Frequency API

fb_token(): Facebook's Long-Life User API Token

file_name() file_type(): Extract file raw name and type from file names

filesGD(): Google Drive Files (API v4)

files_functions(): List all functions used in R script files by package

removenacols() removenarows() numericalonly(): Remove/Drop Columns in which ALL or SOME values are NAs

font_exists(): Check if Font is Installed

forecast_arima(): ARIMA Forecast

formatColoured(): Print Coloured Messages

formatHTML() formatNum(): Format a string text as markdown/HTML

freqs(): Frequencies Calculations and Plot

freqs_df(): Plot for All Frequencies on Dataframe

freqs_list(): Frequencies on Lists and UpSet Plot

freqs_plot(): Combined Frequencies Plot for Categorical Features

gain_lift(): Cumulative Gain, Lift and Response

gemini_ask() gemini_image(): Gemini API Interaction with R

get_credentials() get_creds(): Load Credentials from a YML File

get_currency(): Download Historical Currency Exchange Rate

get_mp3(): Download MP3 from URL

get_tweets(): Get Tweets

gg_fill_customs() gg_colour_customs() gg_text_customs() gg_vals(): Custom fill, colour and text colours for ggplot2

glued(): Interpolate a string [glue wrapper]

readGS() writeGS(): Google Sheets Reading and Writing (API v4)

gtrends_related() gtrends_time(): Google Trends: Related and Time Plots

gpt_ask() gpt_history() gpt_table() gpt_classify() gpt_tag() gpt_extract() gpt_format() gpt_convert() gpt_translate(): ChatGPT API Interaction with R

gpt_prompter(): Structured Prompt Builder for LLM (ChatGPT)

grepl_letters(): Pattern Matching for Letters considering Blanks

grepm(): Pattern Matching for Any or All Multiple Matches

h2o_automl() plot(<h2o_automl>) print(<h2o_automl>): Automated H2O's AutoML

h2o_explainer(): DALEX Explainer for H2O

h2o_predict_MOJO() h2o_predict_binary() h2o_predict_model() h2o_predict_API(): Calculate predictions of h2o Models

h2o_results(): Automated H2O's AutoML Results

h2o_selectmodel(): Select Model from h2o_automl's Leaderboard

h2o_shap() plot(<h2o_shap>): SHAP values for H2O Models

haveInternet(): Internet Connection Check

holidays(): Holidays in your Country

image_metadata(): Get Meta Data from Image Files

importxlsx(): Import Excel File with All Its Tabs

impute(): Impute Missing Values (using MICE)

install_recommended(): Install/Update Additional Recommended Libraries

ip_data(): Scrap data based on IP address

is_url() is_ip() are_id() are_constant() are_binary(): Check if input is_* or are_*

iter_seeds(): Iterate Seeds on AutoML

json2vector(): Convert Python JSON string to R vector (data.frame with 1 row)

lares-exports %>%: Pipe operator

lares-package lares: Analytics, Data Mining & Machine Learning Sidekick

lares_logo(): Print lares R library Logo

lares_pal(): Personal Colours Palette

lasso_vars(): Most Relevant Features Using Lasso Regression

left() right(): Left or Right N characters of a string

li_auth(): OAuth Linkedin

li_profile(): Get My Personal LinkedIn Data

list_cats(): List categorical values for data.frame

listfiles(): List files in a directory

loglossBinary(): Logarithmic Loss Function for Binary Models

mail_send(): Send Emails with Attachments (POST)

markdown2df(): Convert markdown string tables to data.frame

maze_solve() print(<maze_solve>) maze_gridsearch(): Maze Solver, inspired by Micromouse competitions

missingness(): Calculate and Visualize Missingness

model_metrics(): Model Metrics and Performance

model_preprocess(): Automate Data Preprocess for Modeling

move_files(): Move files from A to B

mplot_conf(): Confussion Matrix Plot

mplot_cuts(): Cuts by quantiles for score plot

mplot_cuts_error(): Cuts by quantiles on absolute and percentual errors plot

mplot_density(): Density plot for discrete and continuous values

mplot_full(): MPLOTS Score Full Report Plots

mplot_gain(): Cumulative Gain Plot

mplot_importance(): Variables Importances Plot

mplot_lineal(): Linear Regression Results Plot

mplot_metrics(): Model Metrics and Performance Plots

mplot_response(): Cumulative Response Plot

mplot_roc(): ROC Curve Plot

mplot_splits(): Split and compare quantiles plot

mplot_topcats(): Top Hit Ratios for Multi-Classification Models

msplit(): Split a dataframe for training and testing sets

myip(): What's my IP?

ngrams(): Build N-grams and keep most frequent

noPlot(): Plot Result with Nothing to Plot

normalize(): Normalize Vector

num_abbr(): Abbreviate or dis-abbreviate numerical values

ohe_commas(): One Hot Encoding for a Vector with Comma Separated Values

ohse(): One Hot Smart Encoding (Dummy Variables)

outlier_turkey(): Outliers: Tukey’s fences

outlier_zscore(): Outliers: Z-score method

outlier_zscore_plot(): Outliers: Z-score method plot

plot_cats(): Plot All Categorical Features (Frequencies)

plot_chord(): Chords Plot

plot_df(): Plot Summary of Numerical and Categorical Features

plot_nums(): Plot All Numerical Features (Boxplots)

plot_palette(): Plot Palette Colours

plot_survey(): Visualize Survey Results

plot_timeline(): Plot timeline as Gantt Plot

prophesize(): Facebook's Prophet Forecast

quants(): Calculate cuts by quantiles

queryDB(): PostgreSQL Queries on Database (Read)

queryGA(): Queries on Google Analytics

quiet(): Quiet prints and verbose noise

read.file(): Read Files Quickly (Auto-detected)

reduce_pca(): Reduce Dimensionality with PCA

reduce_tsne(): Reduce Dimensionality with t-SNE

remove_stopwords(): Remove stop-words and patterns from character vector

replaceall(): Replace Values With

replacefactor(): Replace Factor Values

robyn_crossmmm() print(<robyn_crossmmm>): Cross-MMM Budget Optimization

robyn_hypsbuilder(): Robyn: Generate default hyperparameters

robyn_modelselector() plot(<robyn_modelselector>): Robyn: Model Selection by Weighted Criteria Scores

robyn_performance(): Robyn: Dynamic Performance and Contribution Report

rtistry_sphere(): Generative Art: Sphere XmodY

scale_x_comma() scale_y_comma() scale_x_percent() scale_y_percent() scale_x_dollar() scale_y_dollar() scale_x_abbr() scale_y_abbr() scale_x_formatNum() scale_y_formatNum(): Axis scales format

scrabble_dictionary() scrabble_score() scrabble_points() scrabble_words(): Scrabble: Dictionaries

sentimentBreakdown(): Sentiment Breakdown on Text

shap_var(): SHAP-based dependence plots for categorical/numerical features (PDP)

slackSend(): Send Slack Message (Webhook)

spread_list(): Spread list column into new columns

statusbar(): Progressive Status Bar (Loading)

stocks_quote() stocks_hist() plot(<stocks_hist>): Download Stocks Historical and Current Values

splot_summary() splot_change() splot_growth() splot_divs() splot_roi() splot_types() splot_etf(): Investing Portfolio Reporting Plots

stocks_file() daily_stocks() daily_portfolio() stocks_obj() stocks_report(): Build a Personal Investing Portfolio Report

sudoku_solver(): Solve Sudoku Puzzles

target_set(): Set Target Value in Target Variable

textCloud(): Wordcloud Plot

textFeats(): Create features out of text

textTokenizer(): Tokenize Vectors into Words

theme_lares(): Theme for ggplot2 (lares)

tic() toc(): Stopwatch to measure timings in R

topics_rake(): Keyword/Topic identification using RAKE

tree_var(): Recursive Partitioning and Regression Trees

trim_mp3(): Trim MP3 Audio File

try_require(): Check if Specific Package is Installed

updateLares(): Update the library (dev or CRAN version)

vector2text() v2t(): Convert a vector into a comma separated text

warnifnot(): Test the Truth of R Expressions and Warn

weighted_value(): Calculate weighted stock values using FIFO/LIFO

what_size(): Calculate the size of any R object or directory

winsorize(): Outliers: Winsorize

wordle_check() print(<wordle_check>) wordle_dictionary() wordle_simulation() print(<wordle_simulation>): Wordle Game Validation

x2y() x2y_metric() plot(<x2y_preds>) plot(<x2y>) x2y_preds(): Ranked Predictive Power of Cross-Features (x2y)

year_month() year_quarter() year_week(): Convert Date into Year-Month, Year-Quarter or Year-Week Format

zerovar(): Zero Variance Columns