Tabular Processing Overview
Topic Overview Tabular data is data structured like a two-dimensional table, with each column of data representing a variable and being of the same type, such as numbers or dates, and each row representing a measurement of all the column variables. Tabular data is ubiquitous, such as in relational and multidimensional databases, spreadsheets and tabular data formats. Tabular data is easy to transform, visualize and model for insights. The Wolfram Language provides state-of-art functionality for tabular processing, from access to data sources, data cleaning to transforming, visualizing and modeling to gain insights to communicating the results for actions.
Tabular Objects »
Tabular — representing tabular data with column-oriented types
ToTabular ▪ FromTabular ▪ ColumnKeys ▪ ColumnTypes ▪ ...
Tabular Data Sources »
DataConnectionObject — connection to data stores handling authentication, queries, etc.
Import — importing of tabular file formats
"CSV" ▪ "XLSX" ▪ "Parquet" ▪ "ArrowIPC" ▪ "SAS7BDAT" ▪ ...
Tabular Data Cleaning »
TransformMissing — handling missing data values
TransformAnomalies ▪ RenameColumns ▪ CastColumns ▪ PivotToColumns ▪ ...
Tabular Transformation »
TransformColumns — compute new columns from existing ones
AggregateRows ▪ PivotTable ▪ ConstructColumns ▪ ColumnwiseThread ▪ ...
Tabular Visualization »
ListPlot — scatter plots of data
Histogram ▪ BarChart ▪ SmoothHistogram ▪ ...
Tabular Modeling »
Mean — find the mean of numbers, dates, etc.
LinearModelFit — linear regression–based predictions
Predict — machine learning–based prediction function
Classify ▪ FindClusters ▪ FindDistribution ▪ ...
Tabular Communication »
CloudPublish — share notebooks and data on the Wolfram Cloud
NotebookTemplate — template notebook for automatic report generation
Export ▪ GenerateDocument ▪ Manipulate ▪ ...