Data Manipulation
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Data Manipulation

Origin provides multiple powerful data manipulation tools which can be used for pre-analysis data processing. The pre-analysis data processing can be carried out right after importing data into Origin, and help to get the data into a desired form for analysis in a quick and intuitive way.

You can reorganize worksheet data by sorting, stacking and unstacking, or aggregating data by creating a pivot table. It is also easy to change the values, order or volume of your data with multiple data transformation tools. In case you have a lot of raw data, you could use the data reduction and extraction features to obtain desired data. In addition, interpolation allows you to produce new values of a dependent variable for desired values of an independent variable.

The Data Filter tool is used to conditionally select rows and leave out undesired rows from graphing and analysis.
The Worksheet Query tool is capable of locating and extracting subsets of your data in Origin’s worksheets.
Average data points to reduce data size and create evenly spaced X, so that the data size is largely reduced but the plot shape remains
Use Origin's Stack Columns tool to combine several data columns into a single column.
Use Origin's Unstack Columns tool to split grouped data into multiple new columns.
The Pivot Table in Origin provides a quick way to summarize your data and also to analyze, compare, and detect relationships within it.
The Set Column Values dialog provides a flexible, powerful interface for performing column-based calculations on your data.
A Gridding dialog is provided in Origin, so that you can easily transform XYZ worksheet data into a matrix or vice versa.
Matrix data can be expanded by bilinear interpolation, or reduced by simple averaging of the grid points.
These 3D scatter plots show that after shrink/expand, the matrix data will be reduced/increased.
Origin provides a tool with multiple normalization methods for performing normalization of data either from a worksheet or a graph.
An example of data interpolation, in which new data points were added between pairs of existing data points to form a smooth connection line.

Data Reduction

Data Reorganization

Data Transformation

Data Interpolation

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