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daru-io is a plugin gem to the existing daru gem, which aims to add support to Importing DataFrames from / Exporting DataFrames to multiple formats.

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Daru-IO

Gem Version Build Status Yard Docs Inline docs Code Climate Stories in Ready License: MIT

A Ruby plugin-gem to daru gem, that extends support for many Import and Export methods of Daru::DataFrame. This gem is intended to help Rubyists who are into Data Analysis or Web Development, by serving as a general purpose conversion library that takes input in one format (say, JSON) and converts it another format (say, Avro) while also making it incredibly easy to getting started on analyzing data with daru.

While supporting various IO modules, daru-io also provides an easier way of adding more Importers / Exporters. It's strongly recommended to have a look at 'Creating your own IO modules' section, if you're interested in creating new Importers / Exporters.

Table of contents

Installation

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  • If you're working with a Gemfile,

    • Add this line to your application's Gemfile:

      gem 'daru-io'
    • And then execute on your terminal:

      $ bundle
  • If you're NOT working with a Gemfile, simply install it yourself by executing on your terminal:

    $ gem install daru-io
  • Require daru-io gem in your application:

    require 'daru/io' #! Requires all Importers & Exporters
    require 'daru/io/importers' #! Requires all Importers and no Exporters
    require 'daru/io/importers/json' #! Requires only JSON Importer

Note: Each IO module has it's own set of dependencies. Have a look at the Importers and Exporters section for dependency-specific information.

Importers

The Daru::IO Importers are intended to return a Daru::DataFrame from the given arguments. Generally, all Importers can be called in two ways - from Daru::IO or Daru::DataFrame.

#! Partially requires Format Importer
require 'daru/io/importers/format'

#! Usage from Daru::IO
instance = Daru::IO::Importers::Format.from(connection)
# or,
instance = Daru::IO::Importers::Format.read(path)
df = instance.call(opts)

#! Usage from Daru::DataFrame
df1 = Daru::DataFrame.from_format(connection, opts)
df2 = Daru::DataFrame.read_format(path, opts)

Note: Please have a look at the respective Importer Doc links below, for having a look at arguments and examples.

ActiveRecord Importer

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Imports a Daru::DataFrame from an ActiveRecord connection.

  • Docs: rubydoc.info
  • Gem Dependencies: activerecord gem
  • Other Dependencies: Install database server(s) such as SQL / Postgresql / etc.
  • Usage:
    #! Partially require just ActiveRecord Importer
    require 'daru/io/importers/active_record'
    
    #! Usage from Daru::IO
    df = Daru::IO::Importers::ActiveRecord.from(activerecord_relation).call(:field_1, :field_2)
    
    #! Usage from Daru::DataFrame
    df = Daru::DataFrame.from_activerecord(activerecord_relation, :field_1, :field_2)

Avro Importer

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Imports a Daru::DataFrame from an .avro file.

  • Docs: rubydoc.info
  • Gem Dependencies: avro and snappy gems
  • Usage:
    #! Partially require just Avro Importer
    require 'daru/io/importers/avro'
    
    #! Usage from Daru::IO
    df = Daru::IO::Importers::Avro.read('path/to/file.avro').call
    
    #! Usage from Daru::DataFrame
    df = Daru::DataFrame.read_avro('path/to/file.avro')

CSV Importer

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Imports a Daru::DataFrame from a .csv or .csv.gz file.

  • Docs: rubydoc.info
  • Usage:
    #! Partially require just CSV Importer
    require 'daru/io/importers/csv'
    
    #! Usage from Daru::IO
    df1 = Daru::IO::Importers::CSV.read('path/to/file.csv').call(skiprows: 10, col_sep: ' ')
    df2 = Daru::IO::Importers::CSV.read('path/to/file.csv.gz').call(skiprows: 10, compression: :gzip)
    
    #! Usage from Daru::DataFrame
    df1 = Daru::DataFrame.read_csv('path/to/file.csv', skiprows: 10, col_sep: ' ')
    df2 = Daru::DataFrame.read_csv('path/to/file.csv.gz', skiprows: 10, compression: :gzip)

Excel Importer

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Imports a Daru::DataFrame from a .xls file.

  • Docs: rubydoc.info
  • Gem Dependencies: spreadsheet gem
  • Usage:
    #! Partially require just Excel Importer
    require 'daru/io/importers/excel'
    
    #! Usage from Daru::IO
    df = Daru::IO::Importers::Excel.read('path/to/file.xls').call(worksheet_id: 1)
    
    #! Usage from Daru::DataFrame
    df = Daru::DataFrame.read_excel('path/to/file.xls', worksheet_id: 1)

Excelx Importer

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Imports a Daru::DataFrame from a .xlsx file.

  • Docs: rubydoc.info
  • Gem Dependencies: roo gem
  • Usage:
    #! Partially require just Excel Importer
    require 'daru/io/importers/excelx'
    
    #! Usage from Daru::IO
    df = Daru::IO::Importers::Excelx.read('path/to/file.xlsx').call(sheet: 2, skiprows: 10, skipcols: 2)
    
    #! Usage from Daru::DataFrame
    require 'daru/io/importers/excel'
    df = Daru::DataFrame.read_excel('path/to/file.xlsx', sheet: 2, skiprows: 10, skipcols: 2)

HTML Importer

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Note: This module works only for static tables on a HTML page, and won't work in cases where the table is being loaded into the HTML table by inline Javascript. This is how the Nokogiri gem works, and the HTML Importer also follows suit.

Imports an Array of Daru::DataFrames from a .html file or website.

  • Docs: rubydoc.info
  • Gem Dependencies: nokogiri gem
  • Usage:
    #! Partially require just HTML Importer
    require 'daru/io/importers/html'
    
    #! Usage from Daru::IO
    df1 = Daru::IO::Importers::HTML.read('https://some/url/with/tables').call(match: 'market', name: 'Shares analysis')
    df2 = Daru::IO::Importers::HTML.read('path/to/file.html').call(match: 'market', name: 'Shares analysis')
    
    #! Usage from Daru::DataFrame
    df1 = Daru::DataFrame.read_html('https://some/url/with/tables', match: 'market', name: 'Shares analysis')
    df2 = Daru::DataFrame.read_html('path/to/file.html', match: 'market', name: 'Shares analysis')

JSON Importer

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Imports a Daru::DataFrame from a .json file / response.

  • Docs: rubydoc.info
  • Gem Dependencies: jsonpath gem
  • Usage:
    #! Partially require just JSON Importer
    require 'daru/io/importers/json'
    
    #! Usage from Daru::IO
    df1 = Daru::IO::Importers::JSON.read('https://path/to/json/response').call(index: '$..time', col1: '$..name', col2: '$..age')
    df2 = Daru::IO::Importers::JSON.read('path/to/file.json').call(index: '$..time', col1: '$..name', col2: '$..age')
    
    #! Usage from Daru::DataFrame
    df1 = Daru::DataFrame.read_json('https://path/to/json/response', index: '$..time', col1: '$..name', col2: '$..age')
    df2 = Daru::DataFrame.read_json('path/to/file.json', index: '$..time', col1: '$..name', col2: '$..age')

Mongo Importer

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Note: The Mongo gem faces Argument Error : expected Proc Argument issue due to the bug in MRI Ruby 2.4.0 mentioned here. This seems to have been fixed in Ruby 2.4.1 onwards. Hence, please avoid using this Mongo Importer in Ruby version 2.4.0.

Imports a Daru::DataFrame from a Mongo collection.

  • Docs: rubydoc.info
  • Gem Dependencies: jsonpath and mongo gems
  • Other Dependencies: Install MongoDB
  • Usage:
    #! Partially require just Mongo Importer
    require 'daru/io/importers/mongo'
    
    #! Usage from Daru::IO
    df = Daru::IO::Importers::Mongo.from('mongodb://127.0.0.1:27017/test').call('cars')
    
    #! Usage from Daru::DataFrame
    df = Daru::DataFrame.from_mongo('mongodb://127.0.0.1:27017/test', 'cars')

Plaintext Importer

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Imports a Daru::DataFrame from a .dat plaintext file (space separated table of simple strings and numbers). For a sample format of the plaintext file, have a look at the example bank2.dat file.

  • Docs: rubydoc.info
  • Usage:
    #! Partially require just Plaintext Importer
    require 'daru/io/importers/plaintext'
    
    #! Usage from Daru::IO
    df = Daru::IO::Importers::Plaintext.read('path/to/file.dat').call([:col1, :col2, :col3])
    
    #! Usage from Daru::DataFrame
    df = Daru::DataFrame.read_plaintext('path/to/file.dat', [:col1, :col2, :col3])

RData Importer

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Imports a Daru::DataFrame from a variable in .rdata file.

  • Docs: rubydoc.info
  • Gem Dependencies: rsruby gem
  • Other Dependencies: Install R and set R_HOME variable as given in the Contribution Guidelines
  • Usage:
    #! Partially require just RData Importer
    require 'daru/io/importers/r_data'
    
    #! Usage from Daru::IO
    df = Daru::IO::Importers::RData.read('path/to/file.RData').call('ACS3')
    
    #! Usage from Daru::DataFrame
    df = Daru::DataFrame.read_rdata('path/to/file.RData', 'ACS3')

RDS Importer

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Imports a Daru::DataFrame from a .rds file.

  • Docs: rubydoc.info
  • Gem Dependencies: rsruby gem
  • Other Dependencies: Install R and set R_HOME variable as given in the Contribution Guidelines
  • Usage:
    #! Partially require just RDS Importer
    require 'daru/io/importers/rds'
    
    #! Usage from Daru::IO
    df = Daru::IO::Importers::RDS.read('path/to/file.rds').call
    
    #! Usage from Daru::DataFrame
    df = Daru::DataFrame.read_rds('path/to/file.rds')

Redis Importer

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Imports a Daru::DataFrame from Redis key(s).

  • Docs: rubydoc.info
  • Gem Dependencies: redis gem
  • Other Dependencies: Install Redis, and run an instance of redis-server
  • Usage:
    #! Partially require just Redis Importer
    require 'daru/io/importers/redis'
    
    #! Usage from Daru::IO
    df = Daru::IO::Importers::Redis.from({url: 'redis://:password@host:port/db'}).call(match: 'time:1*', count: 1000)
    
    #! Usage from Daru::DataFrame
    df = Daru::DataFrame.from_redis({url: 'redis://:password@host:port/db'}, match: 'time:1*', count: 1000)

SQL Importer

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Imports a Daru::DataFrame from a sqlite.db file / DBI connection.

  • Docs: rubydoc.info
  • Gem Dependencies: dbd-sqlite3, activerecord, dbi and sqlite3 gems
  • Usage:
    #! Partially require just SQL Importer
    require 'daru/io/importers/sql'
    
    #! Usage from Daru::IO
    df1 = Daru::IO::Importers::SQL.read('path/to/file.sqlite').call('SELECT * FROM test')
    df2 = Daru::IO::Importers::SQL.from(dbi_connection).call('SELECT * FROM test')
    
    #! Usage from Daru::DataFrame
    df1 = Daru::DataFrame.read_sql('path/to/file.sqlite', 'SELECT * FROM test')
    df2 = Daru::DataFrame.from_sql(dbi_connection, 'SELECT * FROM test')

Exporters

The Daru::IO Exporters are intended to 'migrate' a Daru::DataFrame into a file, or database. All Exporters can be called in two ways - from Daru::IO or Daru::DataFrame.

#! Partially requires Format Exporter
require 'daru/io/exporters/format'

#! Usage from Daru::IO
instance = Daru::IO::Exporters::Format.new(df, opts)
instance.to_s #=> Provides a file-writable string, which can be used in web applications for file download purposes
instance.to #=> Provides a Format instance
instance.write(path) #=> Writes to the given path

#! Usage from Daru::DataFrame
string = df.to_format_string(opts) #=> Provides a file-writable string, which can be to write into a file later
instance = df.to_format(opts) #=> Provides a Format instance
df.write_format(path, opts) #=> Writes to the given path

Note: Please have a look at the respective Exporter Doc links below, for having a look at arguments and examples.

Avro Exporter

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Exports a Daru::DataFrame into a .avro file.

  • Docs: rubydoc.info
  • Gem Dependencies: avro gem
  • Usage:
    #! Partially require just Avro Exporter
    require 'daru/io/exporters/avro'
    
    avro_schema = {
      'type' => 'record',
      'name' => 'Example',
      'fields' => [
        {'name' => 'col_1', 'type' => 'string'},
        {'name' => 'col_2', 'type' => 'int'},
        {'name' => 'col_3', 'type'=> 'boolean'}
      ]
    }
    
    #! Usage from Daru::IO
    string = Daru::IO::Exporters::Avro.new(df, avro_schema).to_s
    Daru::IO::Exporters::Avro.new(df, avro_schema).write('path/to/file.avro')
    
    #! Usage from Daru::DataFrame
    string = df.to_avro_string(avro_schema)
    df.write_avro('path/to/file.avro', avro_schema)

CSV Exporter

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Exports a Daru::DataFrame into a .csv or .csv.gz file.

  • Docs: rubydoc.info
  • Usage:
    #! Partially require just CSV Exporter
    require 'daru/io/exporters/csv'
    
    #! Usage from Daru::IO
    csv_string = Daru::IO::Exporters::CSV.new(df, converters: :numeric, convert_comma: true).to_s
    Daru::IO::Exporters::CSV.new(df, converters: :numeric, convert_comma: true).write('path/to/file.csv')
    csv_gz_string = Daru::IO::Exporters::CSV.new(df, converters: :numeric, compression: :gzip, convert_comma: true).to_s
    Daru::IO::Exporters::CSV.new(df, converters: :numeric, compression: :gzip, convert_comma: true).write('path/to/file.csv.gz')
    
    #! Usage from Daru::DataFrame
    csv_string = df.to_csv_string(converters: :numeric, convert_comma: true)
    df.write_csv('path/to/file.csv', converters: :numeric, convert_comma: true)
    csv_gz_string = df.to_csv_string(converters: :numeric, compression: :gzip, convert_comma: true)
    df.write_csv('path/to/file.csv.gz', converters: :numeric, compression: :gzip, convert_comma: true)

Excel Exporter

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Exports a Daru::DataFrame into a .xls file.

  • Docs: rubydoc.info
  • Gem Dependencies: spreadsheet gem
  • Usage:
    #! Partially require just Excel Exporter
    require 'daru/io/exporters/excel'
    
    #! Usage from Daru::IO
    string = Daru::IO::Exporters::Excel.new(df, header: {color: :red, weight: :bold}, data: {color: :blue }, index: false).to_s
    Daru::IO::Exporters::Excel.new(df, header: {color: :red, weight: :bold}, data: {color: :blue }, index: false).write('path/to/file.xls')
    
    #! Usage from Daru::DataFrame
    string = df.to_excel_string(header: {color: :red, weight: :bold}, data: {color: :blue }, index: false)
    df.write_excel('path/to/file.xls', header: {color: :red, weight: :bold}, data: {color: :blue }, index: false)

JSON Exporter

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Exports a Daru::DataFrame into a .json file.

  • Docs: rubydoc.info
  • Gem Dependencies: jsonpath gem
  • Usage:
    #! Partially require just JSON Exporter
    require 'daru/io/exporters/json'
    
    #! Usage from Daru::IO
    hashes = Daru::IO::Exporters::JSON.new(df, orient: :records, pretty: true, name: '$.person.name', age: '$.person.age').to
    string = Daru::IO::Exporters::JSON.new(df, 'path/to/file.json', orient: :records, pretty: true, name: '$.person.name', age: '$.person.age').to_s
    Daru::IO::Exporters::JSON.new(df, orient: :records, pretty: true, name: '$.person.name', age: '$.person.age').write('path/to/file.json')
    
    #! Usage from Daru::DataFrame
    hashes = df.to_json('orient: :records, pretty: true, name: '$.person.name', age: '$.person.age')
    string = df.to_json_string(orient: :records, pretty: true, name: '$.person.name', age: '$.person.age')
    df.write_json('path/to/file.json', orient: :records, pretty: true, name: '$.person.name', age: '$.person.age')

RData Exporter

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Exports multiple Daru::DataFrames into a .rdata file.

  • Docs: rubydoc.info
  • Gem Dependencies: rsruby gem
  • Other Dependencies: Install R and set R_HOME variable as given in the Contribution Guidelines
  • Usage:
    #! Partially require just RData Exporter
    require 'daru/io/exporters/r_data'
    
    #! Usage from Daru::IO
    string = Daru::IO::Exporters::RData.new('first.df': df1, 'second.df': df2).to_s
    Daru::IO::Exporters::RData.new('first.df': df1, 'second.df': df2).write('path/to/file.RData')

RDS Exporter

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Exports a Daru::DataFrame into a .rds file.

  • Docs: rubydoc.info
  • Gem Dependencies: rsruby gem
  • Other Dependencies: Install R and set R_HOME variable as given in the Contribution Guidelines
  • Usage:
    #! Partially require just RDS Exporter
    require 'daru/io/exporters/rds'
    
    #! Usage from Daru::IO
    string = Daru::IO::Exporters::RDS.new(df, 'sample.dataframe').to_s
    Daru::IO::Exporters::RDS.new(df, 'sample.dataframe').write('path/to/file.rds')
    
    #! Usage from Daru::DataFrame
    string = df.to_rds_string('sample.dataframe')
    df.write_rds('path/to/file.rds', 'sample.dataframe')

SQL Exporter

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Exports a Daru::DataFrame into a database (SQL) table through DBI connection.

  • Docs: rubydoc.info
  • Gem Dependencies: dbd-sqlite3, dbi and sqlite3 gems
  • Other Dependencies: Install SQL database server
  • Usage:
    #! Partially require just SQL Exporter
    require 'daru/io/exporters/sql'
    
    #! Usage from Daru::IO
    Daru::IO::Exporters::SQL.new(df, DBI.connect('DBI:Mysql:database:localhost', 'user', 'password'), 'cars_table').to
    
    #! Usage from Daru::DataFrame
    df.to_sql(DBI.connect('DBI:Mysql:database:localhost', 'user', 'password'), 'cars_table')

Creating your own IO modules

Daru-IO currently supports various Import / Export methods, as it can be seen from the above list. But the list is NEVER complete - there may always be specific use-case format(s) that you need very badly, but might not fit the needs of majority of the community. In such a case, don't worry - you can always tweak (aka monkey-patch) daru-io in your application. The architecture of daru-io provides a neater way of monkey-patching into Daru::DataFrame to support your unique use-case.

  • Adding new IO modules to Daru-IO

    Say, your unique use-case is of YAML IO Modules. Here's how you can proceed with tweaking -

    #! YAML Importer
    
    require 'daru/io'
    
    class Daru::IO::Importers::YAML < Daru::IO::Importers::Base
      Daru::DataFrame.register_io_module :from_yaml, self
      Daru::DataFrame.register_io_module :read_yaml, self
    
      def initialize
        optional_gem 'yaml'
        #! Add all required gem(s) here.
      end
    
      def from(instance)
        #! Your code to create initialize instance
        self
      end
    
      def read(path)
        #! Your code to read the YAML file
        #! and create Daru::DataFrame
        self
      end
    
      def call(opts)
        #! Unified code to create Daru::DataFrame
        #! irrespective of which method
        #! (from / read) is used by user
      end
    end
    
    df = Daru::DataFrame.read_yaml('path/to/file.yaml', skip: 10)
    # or,
    df = Daru::IO::Importers::YAML.read('path/to/file.yaml').call(skip: 10)
    #! YAML Exporter
    
    require 'daru/io'
    
    class Daru::IO::Exporters::YAML < Daru::IO::Exporters::Base
      Daru::DataFrame.register_io_module :to_yaml, self
      Daru::DataFrame.register_io_module :to_yaml_string, self
      Daru::DataFrame.register_io_module :write_yaml, self
    
      def initialize(dataframe, opts)
        super(dataframe) #! Have a look at documentation of Daru::IO::Exporters::Base#initialize
        @opts = opts
      end
    
      def to
        #! Your code to return a YAML instance
      end
    
      def to_s
        super
        #! By default, Exporters::Base adds this to_s method to all Exporters,
        #! by making the write mthod to write to a tempfile, and then reading it.
      end
    
      def write(path)
        #! Your code to write the YAML file
        #! with the data in the @dataframe
      end
    end
    
    df = Daru::DataFrame.new(x: [1,2], y: [3,4])
    
    df.to_yaml(rows: 10..19) #! or, Daru::IO::Exporters::YAML.new(df, rows: 10..19).to
    df.to_yaml_string(rows: 10..19) #! or, Daru::IO::Exporters::YAML.new(df, rows: 10..19).to_s
    df.write_yaml('dataframe.yml', rows: 10..19) #! or, Daru::IO::Exporters::YAML.new(df, rows: 10..19).write('dataframe.yml')
  • Adding new IO modules to custom modules

    Behaviour of existing IO modules can also be reused according to your needs, similar to the above example. For example, if the CSV Importer has to be tweaked with a faster processing gem, simply follow an approach similar to this -

    class CustomNamespace::Importers::CSV < Daru::IO::Importers::CSV
      Daru::DataFrame.register_io_module :custom_csv, self
    
      #! Your CSV Importer code here
    end

Note: The new module can be made to inherit from another module (like Importers::JSON) rather than Importers::Base, depending on use-case (say, parse a complexly nested API response with JsonPaths).

Contributing

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Contributions are always welcome. But, please have a look at the contribution guidelines first before contributing. 🎉

License

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The MIT License (MIT) 2017 - Athitya Kumar and Ruby Science Foundation. Please have a look at the LICENSE.md for more details.

About

daru-io is a plugin gem to the existing daru gem, which aims to add support to Importing DataFrames from / Exporting DataFrames to multiple formats.

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