Package index
-
explore() - Explore a dataset or variable
-
explore_all() - Explore all variables
-
explore_bar() - Explore categorical variable using bar charts
-
explore_col() - Explore data without aggregation (label + value)
-
explore_cor() - Explore the correlation between two variables
-
explore_count() - Explore count data (categories + frequency)
-
explore_density() - Explore density of variable
-
explore_shiny() - Explore dataset interactive
-
explore_targetpct() - Explore variable + binary target (values 0/1)
-
explore_tbl() - Explore table
-
interact() - Make a explore-plot interactive
-
describe() - Describe a dataset or variable
-
describe_all() - Describe all variables of a dataset
-
describe_cat() - Describe categorical variable
-
describe_num() - Describe numerical variable
-
describe_tbl() - Describe table
-
explain_forest() - Explain a target using Random Forest.
-
explain_logreg() - Explain a binary target using a logistic regression (glm). Model chosen by AIC in a Stepwise Algorithm (
MASS::stepAIC()).
-
explain_tree() - Explain a target using a simple decision tree (classification or regression)
-
explain_xgboost() - Explain a binary target using xgboost
-
balance_target() - Balance target variable
-
weight_target() - Weight target variable
-
predict_target() - Predict target using a trained model.
-
report() - Generate a report of all variables
-
get_var_buckets() - Put variables into "buckets" to create a set of plots instead one large plot
-
total_fig_height() - Get fig.height for RMarkdown-junk using explore_all()
-
plot_legend_targetpct() - Plots a legend that can be used for explore_all with a binary target
-
create_notebook_explore() - Generate a notebook
-
abtest() - A/B testing
-
abtest_shiny() - A/B testing interactive
-
abtest_targetnum() - A/B testing comparing two mean
-
abtest_targetpct() - A/B testing comparing percent per group
-
add_var_id() - Add a variable id at first column in dataset
-
add_var_random_01() - Add a random 0/1 variable to dataset
-
add_var_random_cat() - Add a random categorical variable to dataset
-
add_var_random_dbl() - Add a random double variable to dataset
-
add_var_random_int() - Add a random integer variable to dataset
-
add_var_random_moon() - Add a random moon variable to dataset
-
add_var_random_starsign() - Add a random starsign variable to dataset
-
create_data_abtest() - Create data of A/B testing
-
create_data_app() - Create data app
-
create_data_buy() - Create data buy
-
create_data_churn() - Create data churn
-
create_data_empty() - Create an empty dataset
-
create_data_esoteric() - Create data esoteric
-
create_data_newsletter() - Create data newsletter
-
create_data_person() - Create data person
-
create_data_random() - Create data random
-
create_data_unfair() - Create data unfair
-
use_data_beer() - Use the beer data set
-
use_data_diamonds() - Use the diamonds data set
-
use_data_iris() - Use the iris flower data set
-
use_data_mpg() - Use the mpg data set
-
use_data_mtcars() - Use the mtcars data set
-
use_data_penguins() - Use the penguins data set
-
use_data_starwars() - Use the starwars data set
-
use_data_titanic() - Use the titanic data set
-
use_data_wordle() - Use the wordle data set
-
clean_var() - Clean variable
-
drop_obs_if() - Drop all observations where expression is true
-
drop_obs_with_na() - Drop all observations with NA-values
-
drop_var_by_names() - Drop variables by name
-
drop_var_low_variance() - Drop all variables with low variance
-
drop_var_no_variance() - Drop all variables with no variance
-
drop_var_not_numeric() - Drop all not numeric variables
-
drop_var_with_na() - Drop all variables with NA-values
-
count_pct() - Adds percentage to dplyr::count()
-
data_dict_md() - Create a data dictionary Markdown file
-
decrypt() - decrypt text
-
encrypt() - encrypt text
-
get_type() - Return type of variable
-
guess_cat_num() - Return if variable is categorical or numerical
-
plot_text() - Plot a text
-
replace_na_with() - Replace NA
-
rescale01() - Rescales a numeric variable into values between 0 and 1
-
simplify_text() - Simplifies a text string
-
get_color() - Get predefined colors
-
mix_color() - Mix colors
-
show_color() - Show color vector as ggplot
-
yyyymm_calc() - Calculate with periods (format yyyymm)
-
format_num_auto() - Format number as character string (auto)
-
format_num_kMB() - Format number as character string (kMB)
-
format_num_space() - Format number as character string (space as big.mark)
-
format_target() - Format target
-
format_type() - Format type description
-
target_explore_cat() - Explore categorical variable + target
-
target_explore_num() - Explore Nuberical variable + target
-
log_info_if() - Log conditional
-
plot_var_info() - Plot a variable info
-
check_vec_low_variance() - Check vector for low variance
-
cut_vec_num_avg() - Cut a variable