Data Wrangling

Data wrangling, which involves restructuring, enriching, and transforming data into a more valuable format, is important for various purposes, including analytics. CanvasXpress applies a data wrangling process across data sets, integrates information from various data sources to solve problems, and achieve analytical goals.

The CanvasXpress library has a unique set of functionalities that support data-wrangling without the need to contact a server. This result-oriented function empowers our end users to effectively access their data without any hassle. These functions can be called programmatically or used directly through one of the UIs.

Consider the following dataset to showcase some of these methods.

Name	Weight	Height	Waist	Hip	Age	Gender	Excercise
Keith	65.6	174	71.5	93.5	21	Male	Low
Nina	51.6	161	66.5	92.0	22	Female	Moderate
Freddy	80.7	194	83.2	95.0	28	Male	Moderate
Tracey	49.2	160	61.2	91.0	19	Female	Moderate
Isabelle	55.2	173	66.5	90.3	32	Female	Low
Penny	48.7	151	61.6	90.0	35	Female	Intense

# Grouping Data

Grouping can be done through the CanvasXpress configuration

Configuration

new CanvasXpress(
  targetId,
  data, {
    graphType: "Boxplot",
    ...
    groupingFactors: ["Gender"],
});

or a function call after the visualization has been rendered

var cX = new CanvasXpress(targetId, data, config);
cX.groupSamples(["Gender"]);

# Facets

Facets can be done through the CanvasXpress configuration

Configuration

new CanvasXpress(
  targetId,
  data, {
    graphType: "Bar",
    ...
    segregateSamplesBy: ["Excercise"],
});

or a function call after the visualization has been rendered

var cX = new CanvasXpress(targetId, data, config);
cX.segregateSamples(["Excercise"]);

# Sort Data

Sorting can be done through the CanvasXpress configuration

Configuration

// Sort data by Age
new CanvasXpress(
  targetId,
  data, {
    graphType: "Bar",
    sortData: [['var', 'smp', 'Age']]
});

//Sort data by Height
new CanvasXpress(
  targetId,
  data, {
    graphType: "Bar",
    sortData: [['cat', 'smp', 'Height']]
});

or a function call after the visualization has been rendered

var cX = new CanvasXpress(targetId, data, config);

// Sort by Age
cX.modifySort(['var', 'smp', 'Age']);

// Sort by Height
cX.modifySort(['cat', 'smp', 'Height']);

# Corelating Data

Data can be correlated to its meta-data

Correlation can be done through a function call

Configuration

var cX = new CanvasXpress(targetId, data, config);
cX.correlateData(true, "Hip");

# Histogram Data

Histograms can be created through the CanvasXpress configuration

Configuration

new CanvasXpress(
  targetId,
  data, {
    graphType: "Bar",
    showHistogram: true
});

or a function call after the visualization has been rendered

var cX = new CanvasXpress(targetId, data, config);
cX.createHistogram();

# Clustering Data

Cluster data can be done through the CanvasXpress configuration

Configuration

new CanvasXpress(
  targetId,
  data, {
    graphType: "Bar",
    samplesClustered: true
});

or a function call after the visualization has been rendered

var cX = new CanvasXpress(targetId, data, config);
cX.clusterSamples();

# Transform Data

Data transformation can be done through a funciton call

Configuration

var cX = new CanvasXpress(targetId, data, config);
cX.transform("log2");

# Transpose Data

Transposing data can be done through the CanvasXpress configuration

Configuration

new CanvasXpress(
  targetId,
  data, {
    graphType: "Bar",
    transposeData: true
});

or a function call after the visualization has been rendered

var cX = new CanvasXpress(targetId, data, config);
cX.transpose();

# Pivot Data

Pivot data can be done through a funciton call

Configuration

var cX = new CanvasXpress(targetId, data, config);
cX.pivotX("Gender");