## General information

Brick provide wide possibility of data visualization with different dashboards, they are:

**bar plot**for tracking changes over time or comparing different groups

**box plot**for showing distributions, identifying outliers or finding differences between categories

**scatter plot**for showing relationship between two variables and exploring patterns of this relationship

**heatmap plot**for visualizing concentration of values in two dimensions

**histogram plot**for showing distributions

**line plot**to visualize changes over time or to display data over numerical axis

**pie chart**to show parts of the whole

**treemap**for organizing hierarchical data

**Gantt chart**for planning and scheduling processes, based on time and resources needed

**radar chart**(the same as spider chart) to visualize multidimensional data

## Description

### Brick Locations

**Bricks → Views → Charts**

### Brick Parameters

**Plotting speed optimization**

Choose this option if you want to build your plots more fast but will lose a bit in resolution.

**Add a chart****Diagram Type****Chart Name****X column****Y column****Group by****Aggregation****Сolumns****Group column****Show outliers****Display as a violin****X column****Y column****Size****Color****Opacity****Linear approximation****X column****Y column****Aggregation****Columns****Show Distribution****Show rug****X column****Y column****Group by****Show data points****Columns Hierarchy****Data Column****Labels Column****Aggregation****Parent Column****Date Column****Event Column****Color Column****Categories Column****Names Column**

To add a new

Specify type of dashboard to plot on. There are:

*bar, box, scatter, heatmap, histogram, line, pie, treemap, gantt, radar.*A name for the chart

Then, for different type of charts there are different parameters that are needed to be filled.

## bar

The column that would be on the x (horizontal) axis

The column that would be on the y (vertical) axis

The column by which divide the bars

Different type of aggregation: count, mean, max, min, sum, median, mode.

## box

The column which would be represented on the plot

The column by which the values would be grouped

Turn parameter on to show dots which are out of IQR

Turn parameter on to show it in the violin form

## scatter

The column that would be on the x (horizontal) axis

The column that would be on the y (vertical) axis

Can be chosen for either value or column

Can be chosen for either value or column

The level of opacity varies from 0.1 to 1

Turn parameter on to show the line trend

## heatmap

The column that would be on the x (horizontal) axis

The column that would be on the y (vertical) axis

Different type of aggregation: count, mean, max, min, sum, median, mode.

## histogram

Columns for plotting dashboards

Turn parameter on to show distribution of selected data

Turn parameter on to show rug

## line

The column that would be on the x (horizontal) axis

The column that would be on the y (vertical) axis

The column by which divide the bars

Turn on to show points as well as line

## pie

You can insert pie chart inside of another chart and you can order them in any way

## treemap

Column which contains values

Column which maps label to a data

Different type of aggregation: count, mean, max, min, sum, median, mode.

Column which maps the parent to a label

## Gantt

Column with a date values in it

Column which contains names of events

Column with colours for each event

## radar

Column that consists ranking in different categories

Column that consists names of the items

**Open dashboard view**

Shows all the plots that have been built. In this view it is possible to download a png file, zoom a plot, autoscale or reset axes.

### Brick Inputs/Outputs

**Inputs**

Brick takes the data to plot

## Example of usage

Let's consider the binary classification problem. The inverse target variable takes two values - survived (0) - good or non-event case / not-survived (1) - bad or event case. The general information about predictors is represented below:

- passengerid (category) - ID of passenger

- name (category) - Passenger's name

- pclass (category) - Ticket class

- sex (category) - Gender

- age (numeric) - Age in years

- sibsp (numeric) - Number of siblings / spouses aboard the Titanic

- parch (category) - Number of parents / children aboard the Titanic

- ticket (category) - Ticket number

- fare (numeric) - Passenger fare

- cabin (category) - Cabin number

- embarked (category) - Port of Embarkation

Let’s move to some visualizations.

- First one will be
**scatter plot**with settings listed below with result:

- We will show
**a bar chart**where on x axis we put sex column and for y axis survived column.

- We build a
**pie chart**for pclass:

- We will build a
**box plot**for fare column

- We will show how to build a
**heatmap plot**:

- To plot a
**Treemap chart**we need to create some synthetic data, the data and chart build will be presented below:

- Next example will be associated with a
**radar****chart**, for this example we also need to create some synthetic data. Let’s visualize results we have: