Remove the funModeling package dependency of the binning_rgr() function. (thanks to Pablo Casas, #96)
Error occurred in binning() during CRAN test. (#104)
Moved partykit package from Imports to Suggests (#105)
Tasks for submitting to CRAN. (#117)
Fixed misstyop in html_missing(), html_paged_missing(), html_missing(), and some functions. (thanks to @jcochanc, #103)
Fixed a wrong of degree of freedom in eda_web_report(), eda_paged_report(). (thanks to Jessica N Busler, #98)
Fixed an error that occurred when there was a non-character data type (such as a date) among categorical variables in diagnose_category(). (thanks to @hope-data-science, #100, @marcozanotti, #102)
Reduce example execution time (#112)
Fixed an error that occurred when CRAN was submitted. (#109)
Fixed an error that is “Errors with eda_paged_report”. (#86)
Fixed blank pages in EDA paged reports. (#114)
Fixed CRAN submit for suggests packages. (#118)
Fixed EDA report failing when target variable is number or integer in eda_web_report() and eda_paged_report(). (thanks to neural-oracle, #75)
Added exception handling logic for errors that occur when the bandwidth estimate of a numeric variable is 0 in plot.relate(). (#76)
Fixed error while performing eda_web_report() without target variable. (thanks to Ashirwad Barnwal, #81, #83)
Fixed an error in eda_web_report() when variable is
included in the name of a variable applied to select(). (thanks to
Ashirwad Barnwal, #65)
Fixed a wrong summary in univar_category() when x is
included in the name of a variable applied to select(). (#69)
Fixed some wrong case in plot.correlate. (#66)
Cases that may cause errors in the binning process are not output in the report. For example, if you want to bin constant value. (thanks to Iqbal Jamal, #68)
Fixed an error in eda_web_report() when there are missing values in categorical data. (#72)
dlookr supports ‘tbl_dbi’ that can be analyzed in conjunction with DBMS. This is done using the dbplyr package. The related code has been modified to be compatible with the new version 2.2.0 of the dbplyr package. This work was done by Maximilian Girlich. (thanks to @mgirlich, #70)
Now, possible to implement imputation capping in imputate_outlier() function with user specified values of caps. (thanks to @Tomas Janik, #71)
Fixed an error in describe() when variable is
included in the name of a variable applied to group_by(). (thanks to
@SchmidtPaul,
#59)
Fixed an error that occurred when the value of the ‘marginal’ argument of summary.compare_category() was TRUE and a variable with only one level was included among the variables. (#61)
Fix an error in ‘normality-list’ section of eda_web_report(). (#62)
Fix an issue where table and table detail do not match in html_compare_category() under certain conditions . (#63)
Fixed an error in html_compare_category() when the number of levels of one of the two categorical variables is 1. (#63)
Added a new binning function called binning_rgr(), plot.infogain_bins(). This function bins using recursive information gain ratio maximization. (thanks to Luca Zavarella, #15)
Implemented the PPS(Predictive Power Score) with pps.data.frame(), pps.target_df(), summary.pps(), plot.pps(). (thanks to Luca Zavarella, #20)
By fixing bug #59, the variable ‘variable’ in the describe() result was changed to ‘described_variables’.
Added a new method that is summary.correlate() for summarizing correlation coefficient and plot.correlate() for visualize correlation coefficient. The new method is Cramer’s V and Theil’s U. (#64)
Added ‘all.combinations’ argument to describe() and describe.tbl_dbi(). When used with group_by(), this argument expresses all combinations of group combinations. If the argument value is TRUE, cases that do not exist as actual data are also included in the output. (thanks to @SchmidtPaul, #59)
For a function that visualizes correlation coefficients, change the direction of the diagonal(top-left to bottom-right) and invert the color of the cells(-1: red, 1: blue) in plot.
Fixed an error that occurred when attaching a package in an offline environment.
Fixed an error that occurred when the number of breaks and the number of labels in plot.compare_category() are different.
Fixed an error that occurred when check in the CRAN in r-devel-windows-x86_64-old
Fixed an error in plot_hist_numeric() when variable names contain spaces.
Fixed an error that occurred in compare_numeric() when using a tibble object as an argument.
Fixed an error that occurred in eda_paged_report() and eda_web_report() when using a tibble object as an argument.
Fixed an error that occurred when generating outliers information in diagnose_paged_report() in case of a tibble object.
Fixed an error where the base_family argument was not applied to the plot in the Outlier section in diagnose_web_report().
Remove unnecessary formula output when executing binning_by().
Fixed an issue that the correlation visualization was not plot in the EDA report in “Grouped Correlation” sction in eda_web_report(). (#55)
Fixed the logic has been modified so that an error does not occur even when the independent variable x has only one unique value in compare_numeric().
Fixed an error in the visualization where the number of levels of a categorical variable was 1 combined with this variable in the “Compare Categorical Variables” section of the report in eda_web_report(), eda_paged_report().
Changed the way fonts are imported into the R environment to insert fonts into the plot. For this method, the extrafont package was changed to the showtext package. (#48, #53)
The reason is that the extrafont package uses the Rttf2pt1 package, because Winston Chang, the author of the Rttf2pt1 package, says:
“ttf2pt1 has not been maintained since 2003, and it is getting increasingly difficult to make it compile without significant warnings on modern compilers, which in turn is making it difficult to maintain this package on CRAN. It is possible that in the future, I will not have time to keep this package on CRAN.”
Added the ability to specify the font family in the report function. This feature is useful for visualization by users using non-ASCII characters.
Added the ability to specify the font family in the visualization function. This feature is useful for visualization by users using non-ASCII characters.
Added the ability to specify the font family in the reporting function. This feature is useful for visualization by users using non-ASCII characters.
Fixed an error that is in diagnose_paged_report(), diagnose_web_report(), when there are no numerical variables in the dataset. (#49)
Fixed an error that is in diagnose_paged_report(), when there are no categorical variables in the dataset.
Fixed an error that is in eda_paged_report(), eda_web_report(), when there are no numerical variables in the dataset.
Fixed an error that is in eda_paged_report(), when there are no categorical variables in the dataset.
Fixed an error that is in diagnose_paged_report(), diagnose_web_report(), when there are only one variable that include missing values. (#50)
Add a new function plot_hist_numeric() to report histogram of numerical variables.
Add a new function diagnose_web_report() to report the information of data diagnosis with wep page that support dynamic analytics.
Add a new function eda_web_report() to report the information of exploratory data analysis with wep page that support dynamic analytics.
Add a new function transformation_web_report() to report the information of transform numerical variables with wep page that support dynamic analytics.
Add a new function diagnose_paged_report() to report the information of data diagnosis with static pages.
Add a new function eda_paged_report() to report the information of exploratory data analysis with static pages.
Add a new function transformation_paged_report() to report the information of transform numerical variables with static pages.
Fixed an error that is in diagnose_category.tbl_dbi(), when in_database argument is FALSE. (thanks @verajosemanuel, #43)
Fixed an issue that is x axis overlaps labels in plot.optimal_bins() (thanks @verajosemanuel, #45)
Added the duplicated information in overview() and summary.overview().
In the result of overview(), included ordered in factor in data type.
Change grade of missing value in plot_na_pareto().
Added the “date_categorical”, “date_categorical2” for type argument that find Date and POSIXct classes in find_class().
Added the ‘add_date’ argument for Date, POSIXct class in diagnose_category().
In describe(), the user can select the type of statistic.
Added the ability to set x-axis labels in plot.optimal_bins(). This is a useful function when labels overlap because they are long.
plot_correlate() changed the look & feel that draw the viz from high-level graphic function to ggplot2.
Fixed an error that is in plot.univar_category(), if the number of categories is more than 10, no output after 10.
Fixed a bug where the bar color of NA was not displayed in plot.optimal_bins(). (#39)
Fixed an error occurs when there are no observations corresponding to levels (may occur depending on data characteristics when the binning type is “equal”) in plot.bins().
Fixed a miss typo in plot_outlier(). (thanks @jmanacup, #41)
Fixed an error in the describe() for data containing variables with 3 or fewer complete cases. (thanks @davidfgeorge, #42)
Added datasets that are ‘heartfailure’ and ‘jobchange’.
Changed the manpages are diagnose(), diagnose_category(), diagnose_numeric(), diagnose_outlier(), plot_outlier(), plot_outlier.target_df(), diagnose_report(), univar_category.data.frame(), summary.univar_category(), plot.univar_category(), univar_numeric.data.frame(), summary.univar_numeric(), plot.univar_numeric(), plot_bar_category(), plot_qq_numeric(), plot_box_numeric(), plot_na_hclust(), plot_na_pareto(), plot_na_intersect(), imputate_na(), summary.imputation(), plot.imputation(), normality(), plot_normality(), transform(), summary.transform(), plot.transform(), transformation_report(), compare_category(), compare_numeric(), summary.compare_category(), summary.compare_numeric(), plot.compare_category(), plot.compare_numeric(), get_column_info(), diagnose.tbl_dbi(), diagnose_category.tbl_dbi(), diagnose_numeric.tbl_dbi(), diagnose_outlier.tbl_dbi(), plot_outlier.tbl_dbi(), normality.tbl_dbi(), plot_normality.tbl_dbi(), correlate.tbl_dbi(), plot_correlate.tbl_dbi(), describe.tbl_dbi(), target_by.tbl_dbi(), diagnose_report.tbl_dbi(), eda_report.tbl_dbi(), target_by.data.frame(), relate(), print.relate(), plot.relate(), binning(), summary.bins(), plot.bins(), binning_by(), summary.optimal_bins(), plot.optimal_bins(), plot.optimal_bins(), extract.bins(), performance_bin(), summary.performance_bin(), plot.performance_bin(), get_class(), find_na(), find_outliers(), find_skewness(), correlate.data.frame(), plot_correlate.data.frame(), overview(), summary.overview(), plot.overview(), eda_report.data.frame(), describe.data.frame().
Changed default type of diagnose_category() from “rank” to “n”.
Fixed an error that occurred when “section 1.2.1 Diagnosis of categorical variables” of diagnose_report() shows unnecessary records in cases with a lot of ties in the frequency rank. (thanks @sedechio, #34)
Fixed a bug in which when an object created with diagnose_category(), the rank variable is just row numbers.
The type argument was added to diagnose_category(). “rank” returns the rows corresponding to the top n rank, and “n” returns the top n rows.
Remove the suggested package that are stringr and DMwR.
Added exception handling logic in examples and vignettes using suggested package(classInt, rpart, forecast).
Fixed an error that occurred when calling get_transform() with the Box-Cox method when the forecast package version is less than 8.3. Changed forecast package dependency to 8.3 or higher.
Fixed an error that occurred when calling eda_report() with the shapiro.test() function when the data included many missing values.
Fixed .onAttach() error when loading package in MS-Windows OS. (thanks @Roberto Passera)
Fixed a bug in which when an object created with binning() and binning_by() is extracted with the extract() function, the ordered factor is also extracted as a factor.
Fixed .onAttach() error when installing package in solaris OS.
Fixed extract() not extracting factor from “bins” object.
Import dependency was modified to limit the version of the knitr package for report generation to 1.22 or higher.
In the visualization result of plot.bins(), the x-axis text of the lower plot was rotated 45 degrees and expressed without overlapping.
changed the dependency of hrbrthemes from hrbrthemes to hrbrthemes(>= 0.8.0) because error that occurs in an environment where the hrbrthemes package is installed before version 0.6.0. So, modified the dependency of hrbrthemes(thanks @coissac, #33).
Fixed .onAttach() failed which occurred when installing in Solaris environment.
Fixed an issue where unnecessary blank plots were displayed in plot_box_numeric(), plot_qq_numeric(), plot_bar_category().
Fixed an Resolves an issue where an installation error occurs in an environment using the old tidyselect package without all_of().
Fixed an error in plot_box_numeric(), plot_bar_category(), plot_outlier(), compare_numeric(), plot.univar_numeric() when the ggplot2 package version is out of date.
Fixed an error that occurred in plot_box_numeric.grouped_df(), plot_bar_category.grouped_df(), plot_qq_numeric.grouped_df() when the dplyr package version is less than 0.8.0
Fixed an error that occurred in binning_by(), target_by() when the dplyr package version is less than 0.8.0
Fixed an bug that occurred in binning(), when the approxy.lab argument is TRUE, the maximum value is sometimes omitted from binning and mapped to NA.
Add a new function entropy() to compute Shannon’s entropy.
Add a new function get_percentile() to compute percentile position.
Add a new function get_transform() to transform numeric variable.
Add a new function kld() to computes the Kullback-Leibler divergence between two probability distributions.
Add a new function jsd() to computes the Jensen-Shannon divergence between two probability distributions.
Add a new function overview() to describe overview of data.
Add a new function summary.overview() to summarizes the data information from the overview class object created with overview().
Add a new function plot.overview() to visualizes the data information from the overview class object created with overview().
Add a new function plot_bar_category() to visualizes the distribution of categorical data by level or relationship to specific numerical data by level.
Add a new function plot_qq_numeric() to visualizes the Q-Q plot of numeric data or relationship to specific categorical data.
Add a new function plot_box_numeric() to visualizes the box plot of numeric data or relationship to specific categorical data.
Add a new function plot_outlier.target_df() to visualizes the information of outliers by target variable.
Add a new function performance_bin(), summary.performance_bin(), plot.performance_bin() to diagnose the binned variable for binomial classification model.
Add a new function summary.optimal_bins() to summaries the binned variable for optimal binning.
eda_report() change the correlation plot and normality test (log+1: include 0, log+a/Box-Cox: include minus).
plot_correlate() change the correlation plot that support 2 case plots(number of variable >=20, <20).
plot_na_pareto() changed the legend that show the all levels and display the more information.
transform(), summary.transform(), plot.transform() supports Box-Cox transform and Yeo-Johnson transform. (thanks @lucazav, #21).
plot_normality() supports log+1, log+a, 1/x, x^2, x^3, Box-Cox, Yeo-Johnson transform. (thanks @lucazav, #21).
transform(), summary.transform(), plot.transform() supports Box-Cox transform. (thanks @lucazav, #21).
transform(), summary.transform(), plot.transform() supports Box-Cox transform. (thanks @lucazav, #21).
transform(), summary.transform(), plot.transform() supports Box-Cox transform. (thanks @lucazav, #21).
plot.optimal_bins() changed the plot from smbinning package to own code using ggplot2.
plot.bins(), plot.compare_category(), plot.compare_numeric(), plot_outlier(), plot_normality() changed the look & feel that draw the viz from high-level graphic function to ggplot2.
plot.optimal_bins(), plot_na_hclust(), plot_na_pareto(), plot_na_intersect(), plot.relate(), plot_bar_category(), plot_qq_numeric(), plot_box_numeric() append argemt typographic thst is whether to apply focuses on typographic elements.
modified visualization of report by diagnose_report(), eda_report(), transformation_report().
eda_report() fixed error when data have a only 1 complated numeric variable (thanks @EvanLuff, #27).
eda_report() fixed error when transform numeric variables that include minus values (thanks @Roberto Passera).
Add a new function univar_category() to compute information to examine the individual categorical variables. and print.univar_category(), summary.univar_category() is print and summary for “univar_category” class. (thanks @Roberto Passera)
Add a new function plot.univar_category() to visualize bar plot by attribute of “univar_category” class. (thanks @Roberto Passera)
Add a new function univar_numeric() to compute information to examine the indivisual numerical variables. and print.univar_numeric(), summary.univar_numeric() is print and summary for “univar_numeric” class. (thanks @Roberto Passera)
Add a new function plot.univar_numeric() to visualize box plot and histogram by attribute of “univar_numeric” class. (thanks @Roberto Passera)
Add a new function compare_category() to compute information to examine the relationship between numerical variables. and print.compare_category(), summary.compare_category() is print and summary for “compare_category” class. (thanks @Roberto Passera)
Add a new function plot.compare_category() to visualize mosaics plot by attribute of “compare_category” class. (thanks @Roberto Passera)
Add a new function compare_numeric() to compute information to examine the relationship between numerical variables. and print.compare_numeric(), summary.compare_numeric() is print and summary for “compare_numeric” class. (thanks @Roberto Passera)
Add a new function plot.compare_numeric() to visualize scatter plot included boxplots by attribute of “compare_numeric” class. (thanks @Roberto Passera)
Add a new function plot_na_pareto() to visualize pareto chart for variables with missing value.
Add a new function plot_na_hclust() to visualize distribution of missing value by combination of variables. (thanks @Luca Zavarella)
Add a new function plot_na_intersect() to visualize the patterns of missing value, or rather the combinations of missing value across cases. (thanks @Luca Zavarella)
Add a new vignette Introduce dlookr.
correlate() add the non-parametric correlation coefficient, like “spearman” and “kendall” (thanks @Roberto Passera)
plot_correlate() add the non-parametric correlation coefficient, like “spearman”” and “kendall” (thanks @Roberto Passera)
relate() fixed error when using character type as a categorical variable (thanks @jgduenasl, #14).
plot.transform() fixed miss typo in title of plot (thanks @MarioPrado1148, #26).
Corrected sentence and typo in manuals and vignettes.
plot_normality() fixed an issue where plots are not drawn correctly if data contains Inf.
normality() fixed an issue where NaN is returned in the result if
the data contains Inf. And fixed warning message that is
“cols is now required.”
binning() fixed error an issue where some bining errors could occur at values close to breaks for large numbers. And appended approxy.lab argument that choice large number breaks are approximated to pretty numbers.
describe() fixed warning message that is “cols is
now required.”
imputate_na() appended no_attrs argument that choice the return value. return object of imputation class or numerical/categorical variable.
imputate_outlier() appended no_attrs argument that choice the return value. return object of imputation class or numerical vector.
diagnose_report() Adjusted the pdf margins to increase the number of columns represented in the table. In the latex, duplicate table labels were removed.
eda_report() Adjusted the pdf margins to increase the number of columns represented in the table. In the latex, duplicate table labels were removed.
transformation_report() Adjusted the pdf margins to increase the number of columns represented in the table. In the latex, duplicate table labels were removed.
plot_outlier() fixed error run against a dataset with a numeric column where all values are NA(thanks @rhinomlbox, #8).
describe(), describe.grouped_df() fixed error run against a dataset with a numeric column where number of complate values are 0 to 3.
binning() fixed error like “‘breaks’ are not unique”. and fixed error of binning with a column where all values are NA.
imputate_na() fixed the problem of imputation using (‘rpart’, ‘mode’, ‘mice’) method with a column where all values are NA.
imputate_na() fixed the problem of imputation using ‘knn’ method when the complete case is small.
summary.imputation() fixed the problem of imputation object isn’t compleate.
transformation_report() fixed the problem of trying to output Korean language report in English operating system environment.
transformation_report() fixed the LaTeX error like “Illegal unit of measure (pt inserted)” in Binning section.
transformation_report() fixed the error imputate_na() function call.
find_class() handled ‘labelled’ vectors as categorical variables.
imputate_na() modified to set the random number generation version to 3.5.0 in the ‘mice’ method.
Set the random number generation version to 3.5.0 before calling set.seed() in the code of vignette of “EDA”.
Set the random number generation version to 3.5.0 before calling set.seed() in the code of vignette of “Data Transformation”.
diagnose_report() fixed errors when number of numeric variables is zero.
eda_report() fixed errors that are outputting abnormalities in pdf documents when the target variable name contains “_“.
diagnose_report(), eda_report(), transformation_report() was converted to Korean version of Hangul Report in Korean O/S.
diagnose_report() was added an argument to choose whether to present the report results to the browser.
diagnose_report() limited the maximum number of cases per “Categorical variable level top 10” to 50 cases.
eda_report() was added an argument to choose whether to present the report results to the browser.
transformation_report() was added an argument to choose whether to present the report results to the browser.
plot_outlier() change message in data where all variables are categorical variables.
diagnose_report() modify the table column name in pdf report and lower the number of decimal places.
diagnose_category() fixed subscript error in data where all variables are numeric variables.
diagnose_numeric(), diagnose_outlier() fixed subscript error in data where all variables are categorical variables.
eda_report() fixed errors in pdf report when variable name contains “_“.
find_outliers() fixed errors in index or name extraction of variables containing outliers.
find_skewness() fixed errors in index or name extraction of variables with skewness exceeds the threshold.
eda_report() fixed in table caption of EDA report. and added ability to set font family of pdf report figure.
fixed in table caption of Transformation report. and added ability to set font family of pdf report figure.
plot.relate() supports hexabin plotting when this target variable is numeric and the predictor is also a numeric type.
Add a new function get_column_info() to show the table information of the DBMS.
diagnose() supports diagnosing columns of table in the DBMS.
diagnose_category() supports diagnosing character columns of table in the DBMS.
diagnose_numeric() supports diagnosing numeric columns of table in the DBMS.
diagnose_outlier() supports diagnosing outlier of numeric columns of table in the DBMS.
plot_outlier() supports diagnosing outlier of numeric columns of table in the DBMS.
normality() supports test of normality for numeric columns of table in the DBMS.
plot_normality() supports test of normality for numeric columns of table in the DBMS.
correlate(), plot_correlate() supports computing the correlation coefficient of numeric columns of table in the DBMS.
describe() supports computing descriptive statistic of numeric columns of table in the DBMS.
target_by() supports columns of table in the DBMS.
The plot_outlier() supports a col argument that a
color to be used to fill the bars. (thanks @hangtime79, #3).
Remove the name of the numeric vector to return when index = TRUE
in find_na (), find_outliers(),
find_skewness().
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