Function reference
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as_num()
- Coerce character to numeric
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calc_acf()
- Auto-correlation computation
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calc_association()
- Compute association coefficents
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calc_auc()
- Area under the curve computation
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calc_combination()
- Combination/Permutation computation
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calc_correlation()
- Correlation coefficents computation
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calc_cv()
- Coefficient of variation computation
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calc_error()
- Error metrics computation
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calc_kurtosis()
- Kurtosis computation
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calc_mean()
- Mean computation
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calc_modality()
- Modality computation
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calc_mode()
- Mode computation
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calc_peak_density()
- Peak density value computation
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calc_perc()
- Compute a percentage
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calc_skewness()
- Skewness computation
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count2()
- Compute the frequency of counts, giving a group variable
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count_na()
- Count the number of NA observations
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cut_by_quantile()
- Convert numeric vector to factor, using quantiles intervals
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dttm_diff()
- Difference between two dates
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dttm_vars()
- Create auxiliar variables for a date variable
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expand_grid_unique()
- All combinations of inputs without repetitions
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format_digit()
- Format value to complete with zeroes to the left
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format_num()
- Format numeric value to add marks
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format_p_value()
- Format p value
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format_scale()
- Rescale data
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is_blank()
- Conditional check for a blank value
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is_date()
- Conditional check for a date variable
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is_datetime()
- Conditional check for a datetime variable
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is_even()
- Conditional check for an even value
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is_integer()
- Conditional check for an integer value
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is_negative()
- Conditional check for a negative value
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is_odd()
- Conditional check for an odd value
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is_outlier()
- Conditional check for an outlier value
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is_positive()
- Conditional check for a positive value
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is_string()
- Conditional check for an string value
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is_weekend()
- Conditional check if a date is a weekend
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is_zero()
- Conditional check for a value equal to zero
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isnot_in()
- Conditional check if a value is not contained in a vector
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isnot_na()
- Conditional check if a value is not a NA
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obj_to_string()
- Return an object name as a string
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pal_div()
- Palettes for divergent scale
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pal_qua()
- Palettes for qualitative scale
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pal_seq()
- Palettes for sequential scale
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pal_two()
- Palettes with two constrast colors
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pals_div
- List of palettes
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pals_qua
- List of palettes
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pals_seq
- List of palettes
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pals_two
- List of palettes
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plt_flip_y_title
- ggplot2: Flip y axis title
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plt_identity_line()
- ggplot2: Add a identity line to a scatter plot
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plt_no_background
- ggplot2: Apply a transparent background.
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plt_no_grid
- ggplot2: Removal of grid
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plt_no_labels
- ggplot2: Removal of all labels
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plt_no_text
- ggplot2: Removal of all text and ticks from both axis
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plt_pinpoint()
- ggplot2: Add a single point with two lines in a ggplot2
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plt_regression_line()
- ggplot2: Add a regression line to a scatter plot
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plt_scale_auto()
- ggplot2: Add an automatic scale to a plot
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plt_scale_y_mirror()
- ggplot2: Mirror the y axis on the right side
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plt_theme_map()
- ggplot2: A clean black and white theme for maps
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plt_theme_x()
- ggplot2: A black and white theme without major grid lines in the y axis
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plt_theme_xy()
- ggplot2: A black and white theme without minor grid lines
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plt_theme_y()
- ggplot2: A black and white theme without major grid lines in the x axis
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plt_water_mark()
- ggplot2: Application of a watermark
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replace_boolean()
- Replace a boolean variable
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replace_na()
- Replace a NA value
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row_number_unique()
- Create a rank given unique values from a variable
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rpearson()
- Generate two variables linear correlated
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stat_missing_values()
- Calculate the percentage of missing values
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stat_normality()
- Test the normality of a numeric variable
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stat_two_cat()
- Summary table for comparative analysis between two categorical variables
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stat_two_num()
- Summary table for comparative analysis between two numeric variables
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str_clean()
- Remove punctuation and/or accent from a string
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str_extract_char()
- Extract a specific character from a string
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str_keep()
- Keep only a type of characters in a string
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str_select()
- Select parts of a string, given patterns
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str_to_abb()
- Convert case of a string, without impacting abbreviations
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summary_cat()
- Summary of categorical variables
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summary_num()
- Summary of a numeric variable
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summary_seq()
- Summary of sequence of values
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summary_xy()
- Summary of two numeric variables
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vfx_watermark
- Watermark example
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vfx_watermark_white
- Watermark example