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Getting started

  • Getting Started
    • crandas and pandas
    • Installation (local python)
    • First steps
    • Combining data
    • Approvals
    • Deployments

User Guide

  • User Guide
    • Importing/exporting data
    • Data structures in crandas
    • Basic table operations
    • Selecting data
    • Data types
    • Working with numeric data
    • Working with text data
    • Working with dates
    • Working with missing data
    • Categorical data
    • Merge, join, and concatenate
    • Group by: split-apply-combine
    • Binomial logistic regression
    • Linear regression
    • Authorization
    • Tips and tricks

Reference

  • API documentation
    • crandas.base
    • crandas.crandas
    • crandas.crlearn
    • crandas.ctypes
    • crandas.errors
    • crandas.groupby
    • crandas.placeholders
    • crandas.re
    • crandas.stateobject
    • crandas.transactions
    • crandas.script

Tutorials

  • Tutorials
    • Joining data
      • Joining data - [Party 2]
      • Joining data - [Party 1]
    • Regression
      • Linear regression
      • Logistic regression
    • Authorization
      • Authorization: Design
      • Authorization: Production
    • Fuzzy matching
    • Data exploration
Versions
    1.15.x
    1.14.x
    1.13.x
    1.12.x
    1.11.x
    1.10.x
    1.9.x
    1.8.x
    1.7.x
    1.6.x
    1.5.x
Current Version:
1.8.x
Changelog
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Getting StartedΒΆ

Welcome to the Getting Started guide for crandas!

In this document, you will learn how to install crandas, connect it to the Virtual Data Lake and use it. Follow along to learn how to use the basic functionalities of crandas. crandas is based on the ubiquitous data science library pandas and people familiar with it might be interested in how they compare.

  • crandas and pandas
  • Installation (local python)
  • First steps
  • Combining data
  • Approvals
  • Deployments
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crandas and pandas
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