Preface | Supported data structures | Data: nycflights13 | Data diagnosis | General diagnosis of all variables with diagnose() | Diagnosis of numeric variables with diagnose_numeric() | Diagnosis of categorical variables with diagnose_category() | Diagnosing outliers with diagnose_outlier() | Visualization of outliers using plot_outlier() | Visualization for missing values | visualize pareto chart using plot_na_pareto() | visualize combination chart using plot_na_hclust() | visualize combination chart using plot_na_intersect() | Automated report | Create a diagnostic report using diagnose_web_report() | Contents of dynamic web report | Some arguments for dynamic web report | Screenshot of dynamic report | Create a diagnostic report using diagnose_paged_report() | Contents of static paged report | Some arguments for static paged report | Screenshot of static report | Diagnosing tables in DBMS | Preparing table data | Diagnose data quality of variables in the DBMS | Diagnose data quality of categorical variables in the DBMS | Diagnose data quality of numerical variables in the DBMS | Diagnose outlier of numerical variables in the DBMS | Plot outlier information of numerical data diagnosis in the DBMS | Reporting the information of data diagnosis for table of thr DBMS

Preface | datasets | Imputation of missing values | imputes the missing value with imputate_na() | Collaboration with dplyr | Impute outliers | imputes the outliers with imputate_outlier() | Standardization and Resolving Skewness | Introduction to the use of transform() | Standardization with transform() | Resolving Skewness data with transform() | Binning | Binning of individual variables using binning() | Optimal Binning with binning_by() | Automated report | Create a dynamic report using transformation_web_report() | Contents of dynamic web report | Some arguments for dynamic web report | Screenshot of dynamic report | Create a static report using transformation_paged_report() | Contents of static paged report | Some arguments for static paged report | Screenshot of static report

Preface | Supported data structures | datasets | Univariate data EDA | Calculating descriptive statistics using describe() | Test of normality on numeric variables using normality() | Visualization of normality of numerical variables using plot_normality() | EDA of bivariate data | Calculation of correlation coefficient using correlate() | Visualization of the correlation matrix using plot.correlate() | EDA based on target variable | Definition of target variable | EDA when target variable is categorical variable | Cases where predictors are numeric variable | Cases where predictors are categorical variable | EDA when target variable is numerical variable | Automated report | Create a dynamic report using eda_web_report() | Contents of dynamic web report | Some arguments for dynamic web report | Screenshot of dynamic report | Create a EDA report using eda_paged_report() | Contents of static paged report | Some arguments for static paged report | Screenshot of static report | Exploratory data analysis for tables in DBMS | Preparing table data | Calculating descriptive statistics of numerical column of table in the DBMS | Test of normality on numeric columns using in the DBMS | Normalization visualization of numerical column in the DBMS | Compute the correlation coefficient between two columns of the table in DBMS | Visualize correlation plot of numerical columns in the DBMS | Reporting the information of EDA for table of the DBMS

Preface | How to perform modeling

Preface | How to perform cleansing the data set

Overview | Install alookr | Usage | How to use alookr package

Preface | How to perform split the data

Preface | Supported data structures | List of supported tasks of data analytics | Diagnose Data | Overall Diagnose Data | Visualize Missing Values | Reporting | EDA | Univariate EDA | Bivariate EDA | Normality Test | Relationship between target variable and predictors | Transform Data | Find Variables | Imputation | Binning | Diagnose Binned Variable | Transformation | Miscellaneous | Statistics | Programming