The available options are

• Run till node
• Run from node
• Publish as a model
• Publish code

Task Name

It displays the name of the selected task.

You can click the text field to edit or modify the name of the task as required.

Features

It allows you to select the features for which you want to get statistical information.

• Multiple features can be selected.
• Statistical information is provided only for numerical datatype.
• Frequency and Frequency Percentage is provided only for categorical datatype.

Total No. of Observations

It provides the total number of observations present in the dataset

It is the total count of the number of rows.

Missing

It shows the number of missing values present in the selected features.

You cannot build some models if data contains missing values.
Perform Missing Value Imputation to treat (remove or replace) missing values. Refer to Missing Value Imputation.

Frequency

It provides the frequency of the number of times the data has occurred.

It is calculated only for categorical datatype.

Frequency Percentage

It provides the frequency percentage of the number of times the data has occurred.

It is calculated only for categorical datatype.

Mean

It provides average of the selected features.

It is calculated only for numerical datatype.

Standard Deviation

It measures the dispersion of a dataset relative to its mean.

• It is calculated only for numerical datatype.
• If standard deviation is high, the data is more spread out, and data points are more spread out in the distribution.
• It is measured as the square root of variance.

Variance

It measures how far a set of numbers are spread out from their average value.

• It is calculated only for numerical datatype.
• It is measured as the average square deviation of each number in the data set from its mean.

Min

It provides the minimum value for the selected features.

It is calculated only for numerical datatype.

Q1

It provides the 25th percentile of the data.

• It is calculated only for numerical datatype.
• It is the value below which 25% of the observations in the data are found.

Median (Q2)

It provides the middle value for the selected features.

• It is calculated only for numerical datatype.
• It is the value below which 50% of the observations in the data are found.

Q3

It provides the 75th percentile of the data.

• It is calculated only for numerical datatype.
• It is the value below which 75% of the observations in the data are found.

Max

It provides the maximum value for the selected features.

It is calculated only for numerical datatype.

Range

It is the difference between maximum and minimum value.

It is calculated only for numerical datatype.

Mode

It provides the value that has occurred maximum times.

• It is calculated only for numerical datatype.
• There can be one mode, two modes, or multiple modes present.

Skewness

It provides the distribution of data points.
If the value of skewness is

• less than −1 or greater than +1, the distribution is highly skewed
• between -1 and 0.5, the distribution is negatively skewed
• between 0.5 and 1, the distribution is positively skewed
• between −1 and −0.5 or between +0.5 and +1, the distribution is moderately skewed
• between −0.5 and +0.5, the distribution is approximately symmetric

• It is calculated only for numerical datatype.
• The skewness value can be positive, zero, negative, or undefined.
• Right skewed data (positive): right tail is longer, and data is concentrated more towards left.
• Left skewed data (negative): left tail is longer, and data is concentrated more towards right.
• Normal distribution (zero): data is symmetrically distributed on both sides of the mean.

In other words,

• If Mean > Median > Mode distribution is positively skewed
• If Mean < Median < Mode distribution is negatively skewed
• If Mean = Median = Mode distribution is symmetric

Kurtosis

It identifies whether the tails of a given distributed data contain extreme values.

• It is calculated only for numerical datatype.
• It measures the outliers present in the distribution.

Standard error

It represents the standard deviation of the mean within a dataset. It provides a measurement for the spread of data.

• It is calculated only for numerical datatype.
• The smaller the spread, the more accurate the dataset.