status

For each variable it returns: Quantity and percentage of zeros (q_zeros and p_zeros respectevly). Same metrics for NA values (q_NA/p_na), and infinite values (q_inf/p_inf). Last two columns indicates data type and quantity of unique values.
'status' function is the evolution of 'df_status'. Main change is to have the decimal points as it is, except in percentage. For example now p_na=0.04 means 4
This time it's easier to embbed in a data process flow and to take actions based on this number.

Around 10% of almost any predictive modeling project is spent in predictive modeling, 'funModeling' and the book Data Science Live Book (<https://livebook.datascienceheroes.com/>) are intended to cover remaining 90%: data preparation, profiling, selecting best variables 'dataViz', assessing model performance and other functions.

Pablo Casas

funModeling

Exploratory Data Analysis and Data Preparation Tool-Box

status function

<dl><dt>data</dt>
<dd>data frame, tibble or a single vector</dd></dl>

Arguments

Get a summary for the given data frame (o vector). — status

<dl>

<dt>data</dt>
<dd>data frame, tibble or a single vector</dd>

</dl>

status: Get a summary for the given data frame (o vector).

Description

Usage

Value

Arguments

Examples