Quantipy
0.1.3
  • Release notes
    • Latest (09/04/2019)
    • Archived release notes
      • sd (14/01/2019)
      • sd (26/10/2018)
      • sd (01/10/2018)
      • sd (04/06/2018)
      • sd (04/04/2018)
      • sd (27/02/2018)
      • sd (12/01/2018)
      • sd (18/12/2017)
      • sd (28/11/2017)
      • sd (13/11/2017)
      • sd (17/10/2017)
      • sd (15/09/2017)
      • sd (31/08/2017)
      • sd (24/07/2017)
      • sd (08/06/2017)
      • sd (17/05/2017)
      • sd (04/05/2017)
      • sd (24/04/2017)
      • sd (06/04/2017)
      • sd (29/03/2017)
      • sd (20/03/2017)
      • sd (07/03/2017)
      • sd (24/02/2017)
      • sd (16/02/2017)
      • sd (04/01/2017)
      • sd (8/12/2016)
      • sd (23/11/2016)
      • sd (16/11/2016)
      • sd (11/11/2016)
      • sd (09/11/2016)
    • How-to-snippets
      • DataSet Dimensions compatibility
        • The compatibility mode
        • Accessing and creating array data
      • Different ways of creating categorical values
      • Derotation
        • What is derotation
        • How to use DataSet.derotate()
        • What about arrays?
  • Data processing
    • DataSet components
      • Case and meta data
      • columns and masks objects
      • Languages: text and text_key mappings
      • Categorical values object
      • The array type
    • I/O
      • Starting from native components
        • Using a standalone pd.DataFrame
        • .csv / .json pairs
      • Third party conversions
        • Supported conversions
        • SPSS Statistics
        • Dimensions
        • Decipher
        • Ascribe
        • Confirmit
    • DataSet management
      • Setting the variable order
      • Cloning, filtering and subsetting
      • Merging
        • Vertical (cases/rows) merging
        • Horizontal (variables/columns) merging
      • Savepoints and state rollback
    • Inspecting variables
      • Querying and slicing case data
      • Variable and value existence
      • Variable types
      • Slicing & dicing metadata objects
    • Editing metadata
      • Creating meta from scratch
      • Renaming
      • Changing & adding text info
      • Extending the values object
      • Reordering the values object
      • Removing DataSet objects
    • Transforming variables
      • Copying
      • Inplace type conversion
      • Banding and categorization
      • Array transformations
    • Logic and set operaters
      • Ranges
      • Complex logic
        • union
        • intersection
        • “List” logic
        • has_any
        • not_any
        • has_all
        • not_all
        • has_count
        • not_count
      • Boolean slicers and code existence
    • Custom data recoding
      • The recode() method in detail
        • target
        • mapper
        • default
        • append
        • intersect
        • initialize
        • fillna
      • Custom recode examples
        • Building a net code
        • Create-and-fill
        • Numerical banding
        • Complicated segmentation
        • Variable creation
        • Adding derived variables
        • Interlocking variables
        • Condition-based code removal
  • Weights
    • Background and methodology
      • The statistical problem
      • Rim weighting concept
    • Weight scheme setup
      • Using the Rim class
      • Target distributions
      • Weight groups and filters
      • Setting group targets
    • Integration within DataSet
      • Weighting and weighted aggregations
      • The isolated weight dataframe
    • Diagnostics
      • The weighting efficiency
      • Gotchas
  • Batch
    • Creating/ Loading a qp.Batch instance
    • Adding variables to a qp.Batch instance
      • x-keys and y-keys
      • Arrays
      • Verbatims/ open ends
      • Special aggregations
    • Set properties of a qp.Batch
      • Filter, weights and significance testing
      • Cell items and language
    • Inherited qp.DataSet methods
  • Analysis & aggregation
    • Collecting aggregations
      • What is a qp.Link?
      • Populating a qp.Stack
    • The computational engine
    • Significance testing
    • View aggregation
      • Basic views
      • Non-categorical variables
      • Descriptive statistics
      • Nets
        • Net definitions
        • Calculations
      • Cumulative sums
      • Significance tests
  • Builds
    • Combining results
      • Organizing View aggregations
      • Creating Chain aggregations
    • Deriving post aggregation results
      • Summarizing and reducing results
      • Custom calculations
  • API references
    • Chain
    • Cluster
    • DataSet
    • quantify.engine
    • QuantipyViews
    • Rim
    • Stack
    • View
    • ViewMapper
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