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R to python data wrangling snippets

The dplyr package in R makes data wrangling significantly easier. The beauty of dplyr is that, by design, the options available are limited. Specifically, a set of key verbs form the core of the package. Using these verbs you can solve a wide range of data problems effectively in a shorter timeframe. Whilse transitioning to Python I have greatly missed the ease with which I can think through and solve problems using dplyr in R. The purpose of this document is to demonstrate how to execute the key dplyr verbs when manipulating data using Python (with the pandas package).

dplyr is organised around six key verbs:

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package whoop.whoop

import java.util.concurrent.TimeUnit

import org.openjdk.jmh.annotations._

import scala.util.control.NoStackTrace

@State(Scope.Benchmark)
@BenchmarkMode(Array(Mode.AverageTime))

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package com.tumblr.fibr.service.filter

import com.tumblr.fibr.config.FilterConfig
import com.tumblr.fibr.tsdb.{TsdbRequest, TsdbResponse}
import com.google.common.cache.{Cache, CacheBuilder}
import com.twitter.finagle.Service
import com.twitter.util.Future
import java.util.concurrent.{Callable, TimeUnit}

/**

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Latency numbers every programmer should know

L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns
L2 cache reference ........................... 7 ns
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns             
Compress 1K bytes with Zippy ............. 3,000 ns  =   3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns  =  20 µs
SSD random read ........................ 150,000 ns  = 150 µs

Read 1 MB sequentially from memory ..... 250,000 ns = 250 µs

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Twitter公式クライアントのコンシューマキー

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import scala.math.{BigInt, BigDecimal}

object RecursiveStreams
{
  // natural numbers
  lazy val N: Stream[BigInt] = Stream.cons(BigInt(1), N.map(_ + 1))

  // fibonacci series
  lazy val fib: Stream[BigInt] = Stream.cons(BigInt(0), Stream.cons(BigInt(1), fib.zip(fib.tail).map(a => a._1 + a._2)))

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/*
 * Copyright © 2009, Componentix.  All rights reserved.
 */
package com.componentix.hibernate.dialect;

import java.sql.Types;


/**
 * A proper dialect for Microsoft SQL Server 2000 and 2005.