Package index • relper

All functions

as_num(): Coerce character to numeric

calc_acf(): Auto-correlation computation

calc_association(): Compute association coefficents

calc_auc(): Area under the curve computation

calc_combination(): Combination/Permutation computation

calc_correlation(): Correlation coefficents computation

calc_cv(): Coefficient of variation computation

calc_error(): Error metrics computation

calc_kurtosis(): Kurtosis computation

calc_mean(): Mean computation

calc_modality(): Modality computation

calc_mode(): Mode computation

calc_peak_density(): Peak density value computation

calc_perc(): Compute a percentage

calc_skewness(): Skewness computation

count2(): Compute the frequency of counts, giving a group variable

count_na(): Count the number of NA observations

cut_by_quantile(): Convert numeric vector to factor, using quantiles intervals

dttm_diff(): Difference between two dates

dttm_vars(): Create auxiliar variables for a date variable

expand_grid_unique(): All combinations of inputs without repetitions

format_digit(): Format value to complete with zeroes to the left

format_num(): Format numeric value to add marks

format_p_value(): Format p value

format_scale(): Rescale data

is_blank(): Conditional check for a blank value

is_date(): Conditional check for a date variable

is_datetime(): Conditional check for a datetime variable

is_even(): Conditional check for an even value

is_integer(): Conditional check for an integer value

is_negative(): Conditional check for a negative value

is_odd(): Conditional check for an odd value

is_outlier(): Conditional check for an outlier value

is_positive(): Conditional check for a positive value

is_string(): Conditional check for an string value

is_weekend(): Conditional check if a date is a weekend

is_zero(): Conditional check for a value equal to zero

isnot_in(): Conditional check if a value is not contained in a vector

isnot_na(): Conditional check if a value is not a NA

obj_to_string(): Return an object name as a string

pal_div(): Palettes for divergent scale

pal_qua(): Palettes for qualitative scale

pal_seq(): Palettes for sequential scale

pal_two(): Palettes with two constrast colors

pals_div: List of palettes

pals_qua: List of palettes

pals_seq: List of palettes

pals_two: List of palettes

plt_flip_y_title: ggplot2: Flip y axis title

plt_identity_line(): ggplot2: Add a identity line to a scatter plot

plt_no_background: ggplot2: Apply a transparent background.

plt_no_grid: ggplot2: Removal of grid

plt_no_labels: ggplot2: Removal of all labels

plt_no_text: ggplot2: Removal of all text and ticks from both axis

plt_pinpoint(): ggplot2: Add a single point with two lines in a ggplot2

plt_regression_line(): ggplot2: Add a regression line to a scatter plot

plt_scale_auto(): ggplot2: Add an automatic scale to a plot

plt_scale_y_mirror(): ggplot2: Mirror the y axis on the right side

plt_theme_map(): ggplot2: A clean black and white theme for maps

plt_theme_x(): ggplot2: A black and white theme without major grid lines in the y axis

plt_theme_xy(): ggplot2: A black and white theme without minor grid lines

plt_theme_y(): ggplot2: A black and white theme without major grid lines in the x axis

plt_water_mark(): ggplot2: Application of a watermark

replace_boolean(): Replace a boolean variable

replace_na(): Replace a NA value

row_number_unique(): Create a rank given unique values from a variable

rpearson(): Generate two variables linear correlated

stat_missing_values(): Calculate the percentage of missing values

stat_normality(): Test the normality of a numeric variable

stat_two_cat(): Summary table for comparative analysis between two categorical variables

stat_two_num(): Summary table for comparative analysis between two numeric variables

str_clean(): Remove punctuation and/or accent from a string

str_extract_char(): Extract a specific character from a string

str_keep(): Keep only a type of characters in a string

str_select(): Select parts of a string, given patterns

str_to_abb(): Convert case of a string, without impacting abbreviations

summary_cat(): Summary of categorical variables

summary_num(): Summary of a numeric variable

summary_seq(): Summary of sequence of values

summary_xy(): Summary of two numeric variables

vfx_watermark: Watermark example

vfx_watermark_white: Watermark example