Libraries.Compute.Statistics.DataFrame Documentation
The DataFrame class is a collection of columns and rows, like a spreadsheet, that can be used for statistics and other calculations. By default, it can load comma separated files. Other file types can be supported using the Load action with a file loader for the custom type. DataFrame objects can also be transformed using the Transform action, which is useful for sorting, filtering, or other operations. Transforms generally make a copy of the data frame and act on that copy, not the original.
Example Code
use Libraries.Compute.Statistics.DataFrame
//Load a comma separated file
DataFrame frame
frame:Load("Data.csv")
Inherits from: Libraries.Language.Object
Summary
Actions Summary Table
Actions | Description |
---|---|
Add(Libraries.Compute.Statistics.DataFrameSelectionListener listener) | Classes can register as listeners of the selection in the DataFrame. |
AddColumn(integer index, Libraries.Compute.Statistics.DataFrameColumn column) | This action adds a column to the data frame. |
AddColumn(Libraries.Compute.Statistics.DataFrameColumn column) | This action adds a column to the data frame. |
AddColumnOnLoad(integer index, Libraries.Compute.Statistics.DataFrameColumn column) | This action adds a column that, when the DataFrame is loaded will be used for processing a particular column. |
AddSelectedColumn(integer index) | This adds a column to the selected range. |
AddSelectedColumnRange(integer start, integer finish) | This adds adds columns to the selected range, starting from start and ending at finish, inclusive. |
AddSelectedColumns(text headers) | This action reads a comma separated list of header names and determines the indices from this list. |
AddSelectedFactor(integer index) | This adds a factor of a particular index anywhere from the selection. |
AddSelectedFactorRange(integer start, integer finish) | This adds adds factors to the selected range, starting from start and ending at finish, inclusive. |
AddSelectedFactors(text headers) | This action reads a comma separated list of header names and determines the indices from this list. |
BarChart() | This action creates a BarChart from the current column selection in the DataFrame. |
BoxPlot() | This action creates a BoxPlot from the current column selection in the DataFrame. |
Calculate(Libraries.Compute.Statistics.DataFrameCalculation calculation) | This action runs a calculation on the data frame. |
Compare(Libraries.Language.Object object) | This action compares two object hash codes and returns an integer. |
CompareSelectedColumnToMean(number mean) | This action uses the selection to conduct a comparison between a column and a mean. |
CompareSelectedColumns() | This action uses the selection to conduct a comparison between two or more columns. |
CompareSelectedVariances() | This action uses the selection to conduct a comparison variances in columns. |
ConvertToMatrix() | This action takes a DataFrame and converts it into a matrix with number values. |
Copy(text source) | This action takes a Quorum expression text value and then filters the DataFrame on a copy. |
Copy() | This action returns a copy of the data frame, which deep copies every column. |
Copy(integer columnStart, integer columnEnd, integer rowStart, integer rowEnd) | Returns a copy of the data frame, except that it only copies certain columns and rows |
CorrelateSelectedColumns() | This action uses the selection to conduct a correlation between two or more columns. |
CorrelateSelectedRanks() | This action uses the selection to conduct a correlation between the ranks of values between two or more columns. |
CreateChart(Libraries.Compute.Statistics.DataFrameChartCreator creator) | This action creates a chart, given a particular DataFrameChartCreator instance and returns a chart from it for this particular data. |
CrossTab() | The CrossTab class takes a DataFrame and its selection to decide how to transform it. |
DonutChart() | This action creates a PieChart with a donut hole of 0. |
DonutChart(number donutHolePercent) | This action creates a PieChart with a donut hole of variable size from the current selection in the DataFrame. |
EmptyColumnsOnLoad() | This action empties the columns loaded and frees up memory from the initialization. |
EmptySelectedColumns() | This action empties the selection, so that no columns are selected. |
EmptySelectedFactors() | This action empties the selection, so that no factors are selected. |
Equals(Libraries.Language.Object object) | This action determines if two objects are equal based on their hash code values. |
Filter(text source) | This action takes a Quorum expression text value and then filters the DataFrame. |
GetColumn(text header) | This action returns the first column with the name "header" in its header row. |
GetColumn(integer index) | This action obtains a column from the DataFrame. |
GetColumnOnLoad(integer index) | This action returns a column to load with at a particular index, if one exists. |
GetColumns() | This action gets the columns in the DataFrame. |
GetHashCode() | This action gets the hash code for an object. |
GetListeners() | This action returns an iterator of the listeners on the DataFrame's selection. |
GetSelectedColumnSize() | This action obtains how many columns are selected in the selection. |
GetSelectedFactorSize() | This action obtains how many factors are selected in the selection. |
GetSelection() | This action gets the selection in the DataFrame. |
GetSize() | This action returns the number of columns in the data frame. |
Histogram(integer binWidth) | This action creates a Histogram from the current column selection in the DataFrame. |
Histogram(number binWidth) | This action creates a Histogram from the current column selection in the DataFrame. |
Histogram() | This action creates a Histogram from the current column selection in the DataFrame. |
InterQuartileRange() | This action calculates the InterQuartileRange of the selected column. |
InterQuartileRangeSelectedColumns() | This action calculates the interquartile range of the selected columns. |
IsEmpty() | This action returns true if the number of columns is zero |
Kurtosis() | This action calculates the kurtosis of the selected column. |
KurtosisSelectedColumns() | This action calculates the kurtosis of the selected columns. |
LineChart() | This action creates a LineChart from the current column selection in the DataFrame. |
Load(Libraries.System.File file, Libraries.Compute.Statistics.DataFrameLoader loader) | This action loads data from a file and then places it into the existing data frame. |
Load(text location) | This action loads a data frame from a file relative to the working directory, which is typically where the executable lives. |
Load(Libraries.System.File file) | This action loads a data frame from a file. |
Mean() | This action calculates the mean of the selected column. |
MeanSelectedColumns() | This action calculates the mean of the selected columns. |
Median() | This action calculates the median of the selected column. |
MedianSelectedColumns() | This action calculates the median of the selected columns. |
PieChart() | This action creates a PieChart from the current selection in the DataFrame. |
RegressionOnSelected() | This action uses the selection to conduct a regression. |
Remove(Libraries.Compute.Statistics.DataFrameSelectionListener listener) | Classes can also de-register as listeners of the selection in the DataFrame. |
RemoveColumnAt(integer index) | This action removes a column from the data frame. |
RemoveColumnOnLoad(integer index) | This action removes a column from the on load procedure. |
RemoveSelectedColumn(integer index) | This removes a column of a particular index anywhere from the selection. |
RemoveSelectedColumnAt(integer index) | This removes a column at the index of the selection. |
RemoveSelectedColumnRange(integer start, integer finish) | This adds removes columns from the selected range, starting from start and ending at finish, inclusive. |
RemoveSelectedColumns(text headers) | This action reads a comma separated list of header names and determines the indices from this list. |
RemoveSelectedFactor(integer index) | This removes a factor of a particular index anywhere from the selection. |
RemoveSelectedFactorAt(integer index) | This removes a factor at a particular index from the selection. |
RemoveSelectedFactorRange(integer start, integer finish) | This adds removes factors from the selected range, starting from start and ending at finish, inclusive. |
RemoveSelectedFactors(text headers) | This action reads a comma separated list of header names and determines the indices from this list. |
Save(text location) | This action saves a data frame from a file relative to the working directory, which is typically where the executable lives. |
Save(Libraries.System.File file, Libraries.Compute.Statistics.DataFrameSaver saver) | This action data to a file from a data frame. |
ScatterPlot() | This action creates a ScatterPlot from the current two column selection in the DataFrame. |
SetColumns(Libraries.Containers.Array<Libraries.Compute.Statistics.DataFrameColumn> columns) | This action replaces the columns in the DataFrame. |
SetSelectedColumnRange(integer start, integer finish) | This adds sets columns to the selected range, starting from start and ending at finish, inclusive. |
SetSelectedColumns(text headers) | This action reads a comma separated list of header names and determines the indices from this list. |
SetSelectedFactorRange(integer start, integer finish) | This adds sets factors to the selected range, starting from start and ending at finish, inclusive. |
SetSelectedFactors(text headers) | This action reads a comma separated list of header names and determines the indices from this list. |
Skew() | This action calculates the skew of the selected column. |
SkewSelectedColumns() | This action calculates the skew of the selected columns. |
Sort(text headers) | This action reads a comma separated list of header names and determines the indices from this list. |
StandardDeviation() | This action calculates the standard deviation of the selected column. |
StandardDeviationSelectedColumns() | This action calculates the standard deviation of the selected columns. |
Summarize() | This action calculates summary information for the column. |
SummarizeSelectedColumns() | This action calculates summaries of the selected columns. |
ToText() | This action returns a text based representation of the data frame. |
ToText(integer row) | This action returns a text based representation of the data frame at a particular row. |
Transform(Libraries.Compute.Statistics.DataFrameTransform transform) | This action takes the data from the current DataFrame then transforms into a copy of this data frame. |
Variance() | This action calculates the variance of the selected column. |
VarianceSelectedColumns() | This action calculates the variance of the selected columns. |
ViolinPlot() | This action creates a ViolinPlot from the current column selection in the DataFrame. |
Actions Documentation
Add(Libraries.Compute.Statistics.DataFrameSelectionListener listener)
Classes can register as listeners of the selection in the DataFrame.
Parameters
AddColumn(integer index, Libraries.Compute.Statistics.DataFrameColumn column)
This action adds a column to the data frame. It is destructive in that it changes the existing DataFrame without making a copy.
Example Code
//We need the DataFrame class to load in files for Data Science operations.
use Libraries.Compute.Statistics.DataFrame
use Libraries.Compute.Statistics.Columns.NumberColumn
use Libraries.Containers.Array
use Libraries.Compute.Statistics.DataFrameColumn
//Create a DataFrame, which is essentially a table that understands
//more information about the data that is being loaded.
DataFrame frame
//This creates a NumberColumn, which contains numbers
NumberColumn column
column:SetHeader("My Column")
column:Add(1)
column:Add(2)
column:Add(3)
column:Add(4)
column:Add(5)
column:Add(6)
frame:AddColumn(0, column)
//The system loaded the file, but can also output it a text value, or the console, if we want that.
output frame:ToText()
Parameters
- integer index: the position of the column
- Libraries.Compute.Statistics.DataFrameColumn: The column to add.
AddColumn(Libraries.Compute.Statistics.DataFrameColumn column)
This action adds a column to the data frame. It is destructive in that it changes the existing DataFrame without making a copy.
Example Code
//We need the DataFrame class to load in files for Data Science operations.
use Libraries.Compute.Statistics.DataFrame
use Libraries.Compute.Statistics.Columns.NumberColumn
use Libraries.Containers.Array
use Libraries.Compute.Statistics.DataFrameColumn
//Create a DataFrame, which is essentially a table that understands
//more information about the data that is being loaded.
DataFrame frame
//This creates a NumberColumn, which contains numbers
NumberColumn column
column:SetHeader("My Column")
column:Add(1)
column:Add(2)
column:Add(3)
column:Add(4)
column:Add(5)
column:Add(6)
frame:AddColumn(column)
//The system loaded the file, but can also output it a text value, or the console, if we want that.
output frame:ToText()
Parameters
- Libraries.Compute.Statistics.DataFrameColumn: The column to add.
AddColumnOnLoad(integer index, Libraries.Compute.Statistics.DataFrameColumn column)
This action adds a column that, when the DataFrame is loaded will be used for processing a particular column. This will allow the loader to use customized type information specific to a particular file or situation.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
NumberColumn column
frame:AddColumnOnLoad(0, column)
frame:Load("Data/Sheet.csv")
output frame:ToText()
Parameters
- integer index: the position of the index on loading. For example, an index of means the column at index 0, if one is loaded.
- Libraries.Compute.Statistics.DataFrameColumn: the DataFrameColumn to use and enter into the DataFrame.
AddSelectedColumn(integer index)
This adds a column to the selected range.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumn(0)
output frame:ToText()
Parameters
- integer index: the column index of the column to add
AddSelectedColumnRange(integer start, integer finish)
This adds adds columns to the selected range, starting from start and ending at finish, inclusive. In this case, this means that calculations will be conducted across this entire range.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumnRange(0, 2)
output frame:ToText()
Parameters
- integer start: the start of the range
- integer finish: the end of the range
AddSelectedColumns(text headers)
This action reads a comma separated list of header names and determines the indices from this list. This action is inherently strict, where if the parsing fails, the headers are not unique, or there are other issues in the list, this action throws an error.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumns("name1,name2")
output frame:GetSelectedColumnSize()
Parameters
- text headers: the columns to select
AddSelectedFactor(integer index)
This adds a factor of a particular index anywhere from the selection.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedFactor(0)
output frame:ToText()
Parameters
- integer index: the index of the factor to add
AddSelectedFactorRange(integer start, integer finish)
This adds adds factors to the selected range, starting from start and ending at finish, inclusive. In this case, this means that calculations will be conducted across this entire range.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedFactorRange(0, 2)
output frame:ToText()
Parameters
- integer start: the start of the range
- integer finish: the end of the range
AddSelectedFactors(text headers)
This action reads a comma separated list of header names and determines the indices from this list. This action is inherently strict, where if the parsing fails, the headers are not unique, or there are other issues in the list, this action throws an error.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedFactors("name1,name2")
output frame:GetSelectedColumnSize()
Parameters
- text headers: the columns to select
BarChart()
This action creates a BarChart from the current column selection in the DataFrame. By default, it uses the first column in the selection as the x-axis and the second column as the y-axis. This can be reversed by changing the selection order.
Example Code
use Libraries.Compute.Statistics.DataFrame
use Libraries.Interface.Controls.Charts.BarChart
DataFrame frame
frame:Load("Data.csv")
frame:SetSelectedColumnRange(0,1)
BarChart chart = frame:BarChart()
chart:SetTitle("My Awesome Title")
chart:SetXAxisTitle("Time")
chart:Display()
Return
Libraries.Interface.Controls.Charts.BarChart: a BarChart chart that can be displayed or placed into a user interface or game.
BoxPlot()
This action creates a BoxPlot from the current column selection in the DataFrame. By default, it uses all columns as separate values in the selection as the chart area. Multiple columns will result in multiple plots of different colors labeled along the the x-axis. If a factor is given, the plots will be grouped based by that factor.
Example Code
use Libraries.Compute.Statistics.DataFrame
use Libraries.Interface.Controls.Charts.BoxPlot
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumn(1)
BoxPlot chart = frame:BoxPlot()
chart:SetTitle("My Awesome Title")
chart:SetXAxisTitle("Time")
chart:Display()
Return
Libraries.Interface.Controls.Charts.BoxPlot: a chart that can be displayed or placed into a user interface or game.
Calculate(Libraries.Compute.Statistics.DataFrameCalculation calculation)
This action runs a calculation on the data frame. Calculations are not intended to be destructive to the original data.
Example Code
use Libraries.Compute.Statistics.DataFrame
use Libraries.System.File
//Load a comma separated file
DataFrame frame
File file
file:SetPath("Data.csv")
frame:Load(file)
Parameters
- Libraries.Compute.Statistics.DataFrameCalculation: The calculation we want conducted on this frame.
Compare(Libraries.Language.Object object)
This action compares two object hash codes and returns an integer. The result is larger if this hash code is larger than the object passed as a parameter, smaller, or equal. In this case, -1 means smaller, 0 means equal, and 1 means larger. This action was changed in Quorum 7 to return an integer, instead of a CompareResult object, because the previous implementation was causing efficiency issues.
Example Code
Object o
Object t
integer result = o:Compare(t) //1 (larger), 0 (equal), or -1 (smaller)
Parameters
- Libraries.Language.Object: The object to compare to.
Return
integer: The Compare result, Smaller, Equal, or Larger.
CompareSelectedColumnToMean(number mean)
This action uses the selection to conduct a comparison between a column and a mean. The comparison is traditionally called a one sample t-test. The CompareGroupToMean object returned gives information back in several formats, including text formatted in the American Psychological Association (APA) style.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumn(0)
CompareGroupToMean result = CompareSelectedColumnToMean(0)
output result:GetFormalSummary()
Parameters
Return
Libraries.Compute.Statistics.Tests.CompareGroupToMean: an object representing the comparison
CompareSelectedColumns()
This action uses the selection to conduct a comparison between two or more columns. The comparison is traditionally called a 1-way ANOVA. The CompareGroups object returned gives information back in several formats, including text formatted in the American Psychological Association (APA) style.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumnRange(0,2)
CompareGroups groups = CompareSelectedColumns()
output groups:GetFormalSummary()
Return
Libraries.Compute.Statistics.Tests.CompareGroups: an object representing the comparison
CompareSelectedVariances()
This action uses the selection to conduct a comparison variances in columns. The comparison is traditionally called a Levene's Test. The CompareGroups object returned gives information back in several formats, including text formatted in the American Psychological Association (APA) style.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumnRange(0,2)
CompareVariances groups = frame:CompareSelectedVariances()
output groups:GetFormalSummary()
Return
Libraries.Compute.Statistics.Tests.CompareVariances: an object representing the comparison
ConvertToMatrix()
This action takes a DataFrame and converts it into a matrix with number values. If the data frame contains columns that cannot be converted to numbers, this action throws an exception. Finally, all columns must have the same size for this conversion to work.
Example Code
use Libraries.Compute.Statistics.DataFrame
use Libraries.Compute.Matrix
//Load a comma separated file
DataFrame frame
frame:Load("Data.csv")
//reverse the data frame
Matrix matrix = frame:ConvertToMatrix()
output matrix:ToText()
Return
Libraries.Compute.Matrix: A matrix of real number values
Copy(text source)
This action takes a Quorum expression text value and then filters the DataFrame on a copy. The expression follows the normal rules for Quorum, using the DataFrame's columns as the allowable variables. For example, if a DataFrame has a column, Group, and is an integer, then a value like Group = 2 would look for any value in the column that has the integer 2 and retain only those rows. The filter call is on a copy, meaning it does not change the original DataFrame. If we instead want to filter destructively, we should call Filter instead.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("file.csv")
DataFrame newFrame = frame:Copy("Group > 3")
output newFrame:ToText()
Parameters
Return
Libraries.Compute.Statistics.DataFrame:
Copy()
This action returns a copy of the data frame, which deep copies every column.
Example Code
use Libraries.Compute.Statistics.DataFrame
//Load a comma separated file
DataFrame frame
frame:Load("Data.csv")
//return a copy of the entire DataFrame
DataFrame copy = frame:Copy()
Return
Libraries.Compute.Statistics.DataFrame: A copy of the data frame with constrained columns and rows
Copy(integer columnStart, integer columnEnd, integer rowStart, integer rowEnd)
Returns a copy of the data frame, except that it only copies certain columns and rows
Example Code
use Libraries.Compute.Statistics.DataFrame
//Load a comma separated file
DataFrame frame
frame:Load("Data.csv")
//return a copy with a max of the first five rows
DataFrame copy = frame:Copy(0, frame:GetSize(), 0, 5)
Parameters
- integer columnStart: The 0-indexed first column
- integer columnEnd: The 0-indexed last column
- integer rowStart: The 0-indexed first row
- integer rowEnd: The 0-indexed last row
Return
Libraries.Compute.Statistics.DataFrame: A copy of the data frame with constrained columns and rows
CorrelateSelectedColumns()
This action uses the selection to conduct a correlation between two or more columns. The comparison is traditionally called a Pearson Correlation. The CompareGroups object returned gives information back in several formats, including text formatted in the American Psychological Association (APA) style.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumnRange(0,2)
CorrelateGroups groups = CorrelateSelectedColumns()
output groups:GetFormalSummary()
Return
Libraries.Compute.Statistics.Tests.CorrelateGroups: an object representing the comparison
CorrelateSelectedRanks()
This action uses the selection to conduct a correlation between the ranks of values between two or more columns. The comparison is traditionally called a Spearman Correlation. The CompareGroups object returned gives information back in several formats, including text formatted in the American Psychological Association (APA) style.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumnRange(0,2)
CorrelateRanks groups = CorrelateSelectedRanks()
output groups:GetFormalSummary()
Return
Libraries.Compute.Statistics.Tests.CorrelateRanks: an object representing the comparison
CreateChart(Libraries.Compute.Statistics.DataFrameChartCreator creator)
This action creates a chart, given a particular DataFrameChartCreator instance and returns a chart from it for this particular data.
Example Code
use Libraries.Compute.Statistics.DataFrame
use Libraries.Compute.Statistics.Charts.BarChartCreator
use Libraries.System.File
//Load a comma separated file
DataFrame frame
frame:Load("Data.csv")
//We might instantiate an object to create a bar chart, setting some properties if we want to
BarChartCreator create
frame:CreateChart(create)
Parameters
- Libraries.Compute.Statistics.DataFrameChartCreator: The object that converts the DataFrame into a chart
Return
Libraries.Interface.Controls.Charts.Chart: A chart object, which can be embedded into a user interface
CrossTab()
The CrossTab class takes a DataFrame and its selection to decide how to transform it. Specifically, CrossTab takes the first column in the selection and places it on the left-most column of the new frame, then the second column and places it on top. In both cases, the columns are filtered for unique items and sorted. Once these columns are placed, the CrossTab calculates how many of each unique item pair exist in the original DataFrame. For example, if the first row of the original DataFrame has the value 'test' and the right-most value has '11.2,' then the position in the transformed CrossTab DataFrame will increment this value in the table. Thus, if there were no other test, 11.2 pairs, this value in the new DataFrame would be 1.
Example Code
use Libraries.Compute.Statistics.DataFrame
//Create a DataFrame, load it, and set which column to focus on
DataFrame frame
frame:Load("Words.csv")
frame:AddSelectedColumn(2)
frame:AddSelectedColumn(3)
DataFrame crossTab = frame:CrossTab()
crossTab:Save("Cross.csv")
output "File Saved."
Return
Libraries.Compute.Statistics.DataFrame:
DonutChart()
This action creates a PieChart with a donut hole of 0.5 (50%) from the current selection in the DataFrame. By default, it uses all columns as separate values in the selection as the chart area.
Example Code
use Libraries.Compute.Statistics.DataFrame
use Libraries.Interface.Controls.Charts.Piechart
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumn(1)
frame:AddSelectedColumn(2)
PieChart chart = frame:DonutChart()
chart:SetTitle("My Awesome Title")
chart:Display()
Return
Libraries.Interface.Controls.Charts.PieChart: a chart that can be displayed or placed into a user interface or game.
DonutChart(number donutHolePercent)
This action creates a PieChart with a donut hole of variable size from the current selection in the DataFrame. By default, it uses all columns as separate values in the selection as the chart area.
Example Code
use Libraries.Compute.Statistics.DataFrame
use Libraries.Interface.Controls.Charts.Piechart
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumn(1)
frame:AddSelectedColumn(2)
PieChart chart = frame:DonutChart(0.25)
chart:SetTitle("My Awesome Title")
chart:Display()
Parameters
Return
Libraries.Interface.Controls.Charts.PieChart: a chart that can be displayed or placed into a user interface or game.
EmptyColumnsOnLoad()
This action empties the columns loaded and frees up memory from the initialization. After any load operation, this action is automatically called.
EmptySelectedColumns()
This action empties the selection, so that no columns are selected.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedFactor(0)
frame:EmptySelectedColumns()
output frame:ToText()
EmptySelectedFactors()
This action empties the selection, so that no factors are selected.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedFactor(0)
frame:EmptySelectedFactors()
output frame:ToText()
Equals(Libraries.Language.Object object)
This action determines if two objects are equal based on their hash code values.
Example Code
use Libraries.Language.Object
use Libraries.Language.Types.Text
Object o
Text t
boolean result = o:Equals(t)
Parameters
- Libraries.Language.Object: The to be compared.
Return
boolean: True if the hash codes are equal and false if they are not equal.
Filter(text source)
This action takes a Quorum expression text value and then filters the DataFrame. The expression follows the normal rules for Quorum, using the DataFrame's columns as the allowable variables. For example, if a DataFrame has a column, Group, and is an integer, then a value like Group = 2 would look for any value in the column that has the integer 2 and retain only those rows. The filter call is destructive, meaning it changes the DataFrame itself. If we instead want to obtain a new DataFrame with only the non-filtered data, but to retain this one, the same expression can be used in the Copy action.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("file.csv")
frame:Filter("Group > 3")
output frame:ToText()
Parameters
GetColumn(text header)
This action returns the first column with the name "header" in its header row. If multiple columns have the same name, then to get them all, you will need to iterate and find each one using GetColumn(integer) instead.
Example Code
use Libraries.Compute.Statistics.DataFrame
//Load a comma separated file
DataFrame frame
frame:Load("Data.csv")
DataFrameColumn column = frame:GetColumn("Gender")
Parameters
- text header: The column we want back.
Return
Libraries.Compute.Statistics.DataFrameColumn: the column, possibly undefined if no column of that name exists
GetColumn(integer index)
This action obtains a column from the DataFrame. This column is the original, not a copy, so modifications made to the column will be permanent. If the goal is to obtain a copy, then either the Copy actions or the Transform classes should be used.
Example Code
use Libraries.Compute.Statistics.DataFrame
//Load a comma separated file
DataFrame frame
frame:Load("Data.csv")
DataFrameColumn column = frame:GetColumn(0)
Parameters
- integer index: The column we want back.
Return
Libraries.Compute.Statistics.DataFrameColumn:
GetColumnOnLoad(integer index)
This action returns a column to load with at a particular index, if one exists.
Parameters
Return
Libraries.Compute.Statistics.DataFrameColumn:
GetColumns()
This action gets the columns in the DataFrame. This allows direct control of the columns for this particular data frame. We suggest not using these values directly unless required by an application.
Example Code
use Libraries.Compute.Statistics.DataFrame
//Load a comma separated file
DataFrame frame
frame:Load("Data.csv")
Array<DataFrameColumn> col = frame:GetColumns()
Return
GetHashCode()
This action gets the hash code for an object.
Example Code
Object o
integer hash = o:GetHashCode()
Return
integer: The integer hash code of the object.
GetListeners()
This action returns an iterator of the listeners on the DataFrame's selection.
Return
Libraries.Containers.Iterator:
GetSelectedColumnSize()
This action obtains how many columns are selected in the selection.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumn(0)
output frame:GetSelectedColumnSize()
Return
integer:
GetSelectedFactorSize()
This action obtains how many factors are selected in the selection.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedFactor(0)
output frame:GetSelectedFactorSize()
Return
integer:
GetSelection()
This action gets the selection in the DataFrame.
Return
Libraries.Compute.Statistics.DataFrameSelection: the selection of the frame
GetSize()
This action returns the number of columns in the data frame. This value is not related to the number of rows in any particular column.
Example Code
use Libraries.Compute.Statistics.DataFrame
//Load a comma separated file
DataFrame frame
frame:Load("Data.csv")
output frame:GetSize()
Return
integer: the number of columns in the DataFrame.
Histogram(integer binWidth)
This action creates a Histogram from the current column selection in the DataFrame. By default, Histogram() uses the interquartile range to calculate its bin width, whereas in this version, this is overriden and this bin width is used instead.
Example Code
use Libraries.Compute.Statistics.DataFrame
use Libraries.Interface.Controls.Charts.Histogram
DataFrame frame
frame:Load("Dogs.csv")
frame:AddSelectedColumns("Maximum Life Span")
Histogram chart = frame:Histogram(5)
chart:SetTitle("Maximum Life Span of Dog Breeds")
chart:SetXAxisTitle("Max Life Span")
chart:Display()
Parameters
Return
Libraries.Interface.Controls.Charts.Histogram: a Histogram chart that can be displayed or placed into a user interface or game.
Histogram(number binWidth)
This action creates a Histogram from the current column selection in the DataFrame. By default, Histogram() uses the interquartile range to calculate its bin width, whereas in this version, this is overriden and this bin width is used instead.
Example Code
use Libraries.Compute.Statistics.DataFrame
use Libraries.Interface.Controls.Charts.Histogram
DataFrame frame
frame:Load("Dogs.csv")
frame:AddSelectedColumns("Maximum Life Span")
Histogram chart = frame:Histogram(5)
chart:SetTitle("Maximum Life Span of Dog Breeds")
chart:SetXAxisTitle("Max Life Span")
chart:Display()
Parameters
Return
Libraries.Interface.Controls.Charts.Histogram: a Histogram chart that can be displayed or placed into a user interface or game.
Histogram()
This action creates a Histogram from the current column selection in the DataFrame. By default, it uses the interquartile range to calculate its bin width. This can be overriden by calling Histogram(integer) and passing the bin width directly.
Example Code
use Libraries.Compute.Statistics.DataFrame
use Libraries.Interface.Controls.Charts.Histogram
DataFrame frame
frame:Load("Dogs.csv")
frame:AddSelectedColumns("Maximum Life Span")
Histogram chart = frame:Histogram()
chart:SetTitle("Maximum Life Span of Dog Breeds")
chart:SetXAxisTitle("Max Life Span")
chart:Display()
Return
Libraries.Interface.Controls.Charts.Histogram: a Histogram chart that can be displayed or placed into a user interface or game.
InterQuartileRange()
This action calculates the InterQuartileRange of the selected column.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumn(0)
InterQuartileRange range = frame:InterQuartileRange()
Return
Libraries.Compute.Statistics.Calculations.InterQuartileRange: the interquartile range
InterQuartileRangeSelectedColumns()
This action calculates the interquartile range of the selected columns. In this case, the full calculation objects are returned.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumnRange(0,2)
Array<InterQuartileRange> values = frame:InterQuartileRangeSelectedColumns()
Return
Libraries.Containers.Array: an array of the calculations
IsEmpty()
This action returns true if the number of columns is zero
Example Code
use Libraries.Compute.Statistics.DataFrame
//Load a comma separated file
DataFrame frame
frame:Load("Data.csv")
output frame:IsEmpty()
Return
boolean: true if the number of columns is zero.
Kurtosis()
This action calculates the kurtosis of the selected column.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumn(0)
output frame:Kurtosis()
Return
number: the kurtosis
KurtosisSelectedColumns()
This action calculates the kurtosis of the selected columns. In this case, the full calculation objects are returned.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumnRange(0,2)
Array<Kurtosis> values = frame:KurtosisSelectedColumns()
Return
Libraries.Containers.Array: an array of the calculations
LineChart()
This action creates a LineChart from the current column selection in the DataFrame. By default, it uses all columns as separate lines in the selection as the chart area. Only one factor is allowed and this factor controls the y-axis for all of the lines. The scale can be set manually by using the LineChart
Example Code
use Libraries.Compute.Statistics.DataFrame
use Libraries.Interface.Controls.Charts.LineChart
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumn(1)
frame:AddSelectedFactor(0)
LineChart chart = frame:BarChart()
chart:SetTitle("My Awesome Title")
chart:SetXAxisTitle("Time")
chart:Display()
Return
Libraries.Interface.Controls.Charts.LineChart: a BarChart chart that can be displayed or placed into a user interface or game.
Load(Libraries.System.File file, Libraries.Compute.Statistics.DataFrameLoader loader)
This action loads data from a file and then places it into the existing data frame. If data already exists in this data frame, it is discarded and replaced.
Example Code
use Libraries.Compute.Statistics.DataFrame
use Libraries.Compute.Statistics.Loaders.CommaSeparatedLoader
use Libraries.System.File
//Load a comma separated file
DataFrame frame
File file
file:SetPath("Data.csv")
CommaSeparatedLoader loader
frame:Load(file, loader)
Parameters
- Libraries.System.File: The file we want processed
- Libraries.Compute.Statistics.DataFrameLoader: The object we want to manage loading the file type
Load(text location)
This action loads a data frame from a file relative to the working directory, which is typically where the executable lives.
Example Code
use Libraries.Compute.Statistics.DataFrame
//Load a comma separated file
DataFrame frame
frame:Load("Data.csv")
Parameters
- text location: The file to load, parsed as text relative to the working directly. This is usually the directory of the executable.
Load(Libraries.System.File file)
This action loads a data frame from a file.
Example Code
use Libraries.Compute.Statistics.DataFrame
use Libraries.System.File
//Load a comma separated file
DataFrame frame
File file
file:SetPath("Data.csv")
frame:Load(file)
Parameters
- Libraries.System.File: The file to load.
Mean()
This action calculates the mean of the selected column.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumn(0)
output frame:Mean()
Return
number: the mean
MeanSelectedColumns()
This action calculates the mean of the selected columns. In this case, the full calculation objects are returned.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumnRange(0,2)
Array<Mean> values = frame:MeanSelectedColumns()
Return
Libraries.Containers.Array: an array of the calculations
Median()
This action calculates the median of the selected column.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumn(0)
output frame:Median()
Return
number: the median
MedianSelectedColumns()
This action calculates the median of the selected columns. In this case, the full calculation objects are returned.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumnRange(0,2)
Array<Median> values = frame:MedianSelectedColumns()
Return
Libraries.Containers.Array: an array of the calculations
PieChart()
This action creates a PieChart from the current selection in the DataFrame. By default, it uses all columns as separate values in the selection as the chart area.
Example Code
use Libraries.Compute.Statistics.DataFrame
use Libraries.Interface.Controls.Charts.Piechart
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumn(1)
frame:AddSelectedColumn(2)
PieChart chart = frame:PieChart()
chart:SetTitle("My Awesome Title")
chart:Display()
Return
Libraries.Interface.Controls.Charts.PieChart: a chart that can be displayed or placed into a user interface or game.
RegressionOnSelected()
This action uses the selection to conduct a regression. The comparison is traditionally called a Regression. The CompareGroups object returned gives information back in several formats, including text formatted in the American Psychological Association (APA) style.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumn(0)
frame:AddSelectedFactor(1)
frame:AddSelectedFactor(2)
frame:AddSelectedFactor(3)
Regression result = frame:RegressionOnSelected()
output result:GetFormalSummary()
Return
Libraries.Compute.Statistics.Tests.Regression: an object representing the comparison
Remove(Libraries.Compute.Statistics.DataFrameSelectionListener listener)
Classes can also de-register as listeners of the selection in the DataFrame.
Parameters
RemoveColumnAt(integer index)
This action removes a column from the data frame. It is destructive in that it changes the existing DataFrame without making a copy.
Example Code
//We need the DataFrame class to load in files for Data Science operations.
use Libraries.Compute.Statistics.DataFrame
use Libraries.Compute.Statistics.Columns.NumberColumn
use Libraries.Containers.Array
use Libraries.Compute.Statistics.DataFrameColumn
//Create a DataFrame, which is essentially a table that understands
//more information about the data that is being loaded.
DataFrame frame
//This creates a NumberColumn, which contains numbers
NumberColumn column
column:SetHeader("My Column")
column:Add(1)
column:Add(2)
column:Add(3)
column:Add(4)
column:Add(5)
column:Add(6)
frame:AddColumn(column)
//The system loaded the file, but can also output it a text value, or the console, if we want that.
output frame:ToText()
Parameters
RemoveColumnOnLoad(integer index)
This action removes a column from the on load procedure.
Parameters
RemoveSelectedColumn(integer index)
This removes a column of a particular index anywhere from the selection.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumn(0)
frame:RemoveSelectedColumn(0)
output frame:ToText()
Parameters
- integer index: the column index of the column to remove
RemoveSelectedColumnAt(integer index)
This removes a column at the index of the selection.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumn(0)
frame:RemoveSelectedColumnAt(0)
output frame:ToText()
Parameters
- integer index: the selection index of the column to remove
RemoveSelectedColumnRange(integer start, integer finish)
This adds removes columns from the selected range, starting from start and ending at finish, inclusive. In this case, this means that calculations will be conducted across this entire range.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumnRange(0, 2)
frame:RemoveSelectedColumnRange(1, 2)
output frame:ToText()
Parameters
- integer start: the start of the range
- integer finish: the end of the range
RemoveSelectedColumns(text headers)
This action reads a comma separated list of header names and determines the indices from this list. This action is inherently strict, where if the parsing fails, the headers are not unique, or there are other issues in the list, this action throws an error. This action removes the selection from the list of headers.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:SetSelectedColumns("name1,name2")
frame:RemoveSelectedColumns("name2")
output frame:GetSelectedColumnSize()
Parameters
- text headers: the columns to select
RemoveSelectedFactor(integer index)
This removes a factor of a particular index anywhere from the selection.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedFactor(0)
frame:RemoveSelectedFactor(0)
output frame:ToText()
Parameters
- integer index: the factor index of the factor to remove
RemoveSelectedFactorAt(integer index)
This removes a factor at a particular index from the selection.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedFactor(0)
frame:RemoveSelectedFactorAt(0)
output frame:ToText()
Parameters
- integer index: the selection index of the factor to remove
RemoveSelectedFactorRange(integer start, integer finish)
This adds removes factors from the selected range, starting from start and ending at finish, inclusive. In this case, this means that calculations will be conducted across this entire range.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedFactorRange(0, 2)
frame:RemoveSelectedFactorRange(1, 2)
output frame:ToText()
Parameters
- integer start: the start of the range
- integer finish: the end of the range
RemoveSelectedFactors(text headers)
This action reads a comma separated list of header names and determines the indices from this list. This action is inherently strict, where if the parsing fails, the headers are not unique, or there are other issues in the list, this action throws an error. This action removes the selection from the list of headers.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:SetSelectedFactors("name1,name2")
frame:RemoveSelectedFactors("name2")
output frame:GetSelectedColumnSize()
Parameters
- text headers: the columns to select
Save(text location)
This action saves a data frame from a file relative to the working directory, which is typically where the executable lives. The file must have a csv file extension for this to save. Otherwise, it fails silently.
Example Code
use Libraries.Compute.Statistics.DataFrame
//Load a comma separated file
DataFrame frame
frame:Save("Data.csv")
Parameters
- text location: The file to save. This action uses the default format of comma separate values (CSV).
Save(Libraries.System.File file, Libraries.Compute.Statistics.DataFrameSaver saver)
This action data to a file from a data frame.
Example Code
use Libraries.Compute.Statistics.DataFrame
use Libraries.Compute.Statistics.Loaders.CommaSeparatedSaver
use Libraries.System.File
//Load a comma separated file
DataFrame frame
File file
file:SetPath("Data.csv")
CommaSeparatedLoader loader
frame:Load(file, loader)
CommaSeparatedSaver saver
frame:Save(file, saver)
Parameters
- Libraries.System.File: The file we want processed
- Libraries.Compute.Statistics.DataFrameSaver: The object we want to manage saving the file type
ScatterPlot()
This action creates a ScatterPlot from the current two column selection in the DataFrame. By default, it uses all columns as separate values in the selection as the chart area. Factors have no impact on this action.
Example Code
use Libraries.Compute.Statistics.DataFrame
use Libraries.Interface.Controls.Charts.ScatterPlot
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumn(1)
frame:AddSelectedColumn(2)
ScatterPlot chart = frame:ScatterPlot()
chart:SetTitle("My Awesome Title")
chart:SetXAxisTitle("Time")
chart:Display()
Return
Libraries.Interface.Controls.Charts.ScatterPlot: a chart that can be displayed or placed into a user interface or game.
SetColumns(Libraries.Containers.Array<Libraries.Compute.Statistics.DataFrameColumn> columns)
This action replaces the columns in the DataFrame. It is needed by the Loader infrastructure in order to change the columns. However, for most users, the Transform infrastructure should be used instead of adjusting these manually. In other words, do not use this action unless you know what you are doing.
Example Code
use Libraries.Compute.Statistics.DataFrame
//Load a comma separated file
DataFrame frame
frame:Load("Data.csv")
Array<DataFrameColumn> col
frame:SetColumns(col)
Parameters
- Libraries.Containers.Array: The new columns.
SetSelectedColumnRange(integer start, integer finish)
This adds sets columns to the selected range, starting from start and ending at finish, inclusive. In this case, this means that calculations will be conducted across this entire range. If any previous range was indicated, it is removed.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:SetSelectedColumnRange(0, 2)
output frame:ToText()
Parameters
- integer start: the start of the range
- integer finish: the end of the range
SetSelectedColumns(text headers)
This action reads a comma separated list of header names and determines the indices from this list. This action is inherently strict, where if the parsing fails, the headers are not unique, or there are other issues in the list, this action throws an error. This action removes any previous selection.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:SetSelectedColumns("name1,name2")
output frame:GetSelectedColumnSize()
Parameters
- text headers: the columns to select
SetSelectedFactorRange(integer start, integer finish)
This adds sets factors to the selected range, starting from start and ending at finish, inclusive. In this case, this means that calculations will be conducted across this entire range. If any previous range was indicated, it is removed.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:SetSelectedFactorRange(0, 2)
output frame:ToText()
Parameters
- integer start: the start of the range
- integer finish: the end of the range
SetSelectedFactors(text headers)
This action reads a comma separated list of header names and determines the indices from this list. This action is inherently strict, where if the parsing fails, the headers are not unique, or there are other issues in the list, this action throws an error. This action removes any previous selection.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:SetSelectedFactors("name1,name2")
output frame:GetSelectedColumnSize()
Parameters
- text headers: the columns to select
Skew()
This action calculates the skew of the selected column.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumn(0)
output frame:Skew()
Return
number: the skew
SkewSelectedColumns()
This action calculates the skew of the selected columns. In this case, the full calculation objects are returned.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumnRange(0,2)
Array<Skew> values = frame:SkewSelectedColumns()
Return
Libraries.Containers.Array: an array of the calculations
Sort(text headers)
This action reads a comma separated list of header names and determines the indices from this list. This action is inherently strict, where if the parsing fails, the headers are not unique, or there are other issues in the list, this action throws an error.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:Sort("name1,name2")
output frame:ToText()
Parameters
- text headers: the columns to sort
StandardDeviation()
This action calculates the standard deviation of the selected column.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumn(0)
output frame:StandardDeviation()
Return
number: the standard deviation
StandardDeviationSelectedColumns()
This action calculates the standard deviation of the selected columns. In this case, the full calculation objects are returned.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumnRange(0,2)
Array<StandardDeviation> values = frame:StandardDeviationSelectedColumns()
Return
Libraries.Containers.Array: an array of the calculations
Summarize()
This action calculates summary information for the column.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumn(0)
Summarize summary = frame:Summarize()
Return
Libraries.Compute.Statistics.Calculations.Summarize: the summary
SummarizeSelectedColumns()
This action calculates summaries of the selected columns. In this case, the full calculation objects are returned.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumnRange(0,2)
Array<Summarize> values = frame:SummarizeSelectedColumns()
Return
Libraries.Containers.Array: an array of the calculations
ToText()
This action returns a text based representation of the data frame.
Example Code
use Libraries.Compute.Statistics.DataFrame
//Load a comma separated file
DataFrame frame
frame:Load("Data.csv")
//output the frame to the console
output frame:ToText()
Return
text: a text based representation, in comma separated format
ToText(integer row)
This action returns a text based representation of the data frame at a particular row.
Example Code
use Libraries.Compute.Statistics.DataFrame
//Load a comma separated file
DataFrame frame
frame:Load("Data.csv")
//output the frame to the console
output frame:ToText(0)
Parameters
Return
text: a text based representation, in comma separated format
Transform(Libraries.Compute.Statistics.DataFrameTransform transform)
This action takes the data from the current DataFrame then transforms into a copy of this data frame. While custom Transforms can choose to adjust the original, by default they do not.
Example Code
use Libraries.Compute.Statistics.DataFrame
use Libraries.Compute.Statistics.Transforms.ReverseTransform
use Libraries.System.File
//Load a comma separated file
DataFrame frame
frame:Load("Data.csv")
//reverse the data frame
ReverseTransform reverse
frame:Transform(reverse)
Parameters
- Libraries.Compute.Statistics.DataFrameTransform: The object we want to copy and transform the frame
Return
Libraries.Compute.Statistics.DataFrame: Typically a copy of the DataFrame, transformed by the transformer.
Variance()
This action calculates the variance of the selected column.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumn(0)
output frame:Variance()
Return
number: the variance
VarianceSelectedColumns()
This action calculates the variance of the selected columns. In this case, the full calculation objects are returned.
Example Code
use Libraries.Compute.Statistics.DataFrame
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumnRange(0,2)
Array<Variance> values = frame:VarianceSelectedColumns()
Return
Libraries.Containers.Array: an array of the calculations
ViolinPlot()
This action creates a ViolinPlot from the current column selection in the DataFrame. By default, it uses all columns as separate values in the selection as the chart area. Factors have no impact on this action.
Example Code
use Libraries.Compute.Statistics.DataFrame
use Libraries.Interface.Controls.Charts.ViolinPlot
DataFrame frame
frame:Load("Data.csv")
frame:AddSelectedColumn(1)
ViolinPlot chart = frame:ViolinPlot()
chart:SetTitle("My Awesome Title")
chart:SetXAxisTitle("Time")
chart:Display()
Return
Libraries.Interface.Controls.Charts.ViolinPlot: a chart that can be displayed or placed into a user interface or game.