Points¶
- class nimble.core.data.Points¶
Methods that apply to the points axis of a Base object.
This object can be used to iterate over the points and contains methods that operate over the data in the associated Base object point-by-point.
A point is an abstract slice containing data elements within some shared context. In a concrete sense, points can be thought of as the data rows but a row can be organized in many ways. To optimize for machine learning, each row should be modified to meet the definition of a point.
Methods
append(toAppend, *[, useLog])Append points to this object.
calculate(function[, points, useLog])Apply a calculation to each point.
combineByExpandingFeatures(...[, ...])Combine similar points based on a differentiating feature.
copy([toCopy, start, end, number, ...])Copy certain points of this object.
count(condition[, features])The number of points which satisfy the condition.
delete([toDelete, start, end, number, ...])Remove certain points from this object.
extract([toExtract, start, end, number, ...])Move certain points of this object into their own object.
fillMatching(fillWith, matchingElements[, ...])Replace given values in each point with other values.
getIndex(identifier)The index of a point name.
getIndices(names)The indices of a list of point names.
getName(index)The name of the point at the provided index.
getNames()The point names ordered by index.
hasName(name)Determine if point name exists.
insert(insertBefore, toInsert, *[, useLog])Insert more points into this object.
mapReduce(mapper, reducer, *[, useLog])Transforms each point in this object using a specified mapper function and then aggregates the data using the specified reducer function.
matching(function, *[, useLog])Identifying points matching the given criteria.
max()Returns a nimble object representing the maximum value along the points axis.
mean()Returns a nimble object representing the mean value along the points axis.
median()Returns a nimble object representing the median value along the points axis.
Returns a nimble object representing the median absolute deviation along the points axis.
min()Returns a nimble object representing the minimum value along the points axis.
mode()Retirms a nimble object representing the mode along the points axis.
permute([order, useLog])Permute the indexing of the points.
plot([points, horizontal, outPath, show, ...])Bar chart comparing points.
plotMeans([points, horizontal, outPath, ...])Plot point means with 95% confidence interval bars.
plotStatistics(statistic[, points, ...])Bar chart comparing an aggregate statistic between points.
Returns a nimble object representing the population standard deviation along the points axis.
Returns a nimble object representing the proportion of values that are None or NaN along the points axis.
Returns a nimble object representing the proportion of values that are equal to zero along the points axis.
Returns a nimble object representing the quartiles along the points axis.
repeat(totalCopies, copyPointByPoint, *[, ...])Create an object using copies of this object's points.
replace(data[, points, useLog])Replace the data in one or more of the points in this object.
retain([toRetain, start, end, number, ...])Keep only certain points of this object.
setNames(assignments[, oldIdentifiers, useLog])Set or rename all of the point names of this object.
similarities(similarityFunction)Calculate similarities between points.
sort([by, reverse, useLog])Arrange the points in this object.
splitByCollapsingFeatures(...[, useLog])Separate feature/value pairs into unique points.
Returns a nimble object representing the standard deviation along the points axis.
statistics(statisticsFunction)Calculate point statistics.
sum()Returns a nimble object representing the sum along the points axis.
transform(function[, points, useLog])Modify this object by applying a function to each point.
unique()Only the unique points from this object.
Returns a nimble object representing the number of unique values along the points axis.
variance()Returns a nimble object representing the variance along the points axis.