880 search results for "sql"

Data corruption in R 3.0.2 when using read.csv

January 29, 2014
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Introduction It may be old news to some, but I just recently discovered that the automatic type inference system that R uses when parsing CSV files assumes that data sets will never contain 64-bit integer values. Specially, if an integer value read from a CSV file is too large to fit in a 32-bit integer

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BLATting the internet: the most frequent gene?

January 23, 2014
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BLATting the internet: the most frequent gene?

I enjoyed this story from the OpenHelix blog today, describing a Microsoft Research project to mine DNA sequences from web pages and map them to UCSC genome builds. Laura DeMare asks: what was the most-hit gene? Most hit gene? APOE? MT @GenomeBrowser We BLATed the Internet! DNA sequences from 40 billion webpages mapped to hg19

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Database Reflection using dplyr

January 22, 2014
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Database Reflection using dplyr

At work I write a ton of SQL, and I do most of my querying using R.  The workflow goes: Create a string with the SQL in R Plug the string into fetchQuery (see my previous post) This solution works relatively well, but i’m a bit unhappy writing strings rather than using function calls. I

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Introducing dplyr

January 20, 2014
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Introducing dplyr

dplyr is a new package which provides a set of tools for efficiently manipulating datasets in R. dplyr is the next iteration of plyr, focussing on only data frames. dplyr is faster, has a more consistent API and should be easier to use. There are three key ideas that underlie dplyr: Your time is important,

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In data scientist survey, R is the most-used tool (other than databases)

January 15, 2014
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In data scientist survey, R is the most-used tool (other than databases)

O'Reilly has just published the results of the Data Scientist Salary Survey, based on data collected from attendees of the O'Reilly Strata conferences in 2012 and 2013. There were some interesting results from the salary portion of the survey: data scientists at early-stage startups earned a median salary of US$130,000 data scientists at public companies earned a higher median...

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Load PostGIS geometries in R without rgdal

January 14, 2014
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As I said in my last post, rgdal lacks some of the features of GDAL, including the ability to subset columns and rows the source layer, and I demonstrated a workaround. The workaround relied upon the RPostgreSQL package, and this raises a question: Is it possible to transfer geographic data from PostGIS to R just

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Why R is Better Than Excel for Fantasy Football (and most other) Data Analysis

January 13, 2014
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Many articles have been written on why R is better than Excel for data analysis.  In this post, I will summarize the reasons why R is advantageous in most data The post Why R is Better Than Excel for Fantasy Football (and most other) Data Analysis appeared first on Fantasy Football Analytics.

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Data Analysis Tools

January 7, 2014
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As mentioned in my previous post , in this post I will be listing out the tools, blogs and forums, online courses that I have gathered over the past one year, which I felt necessary in my journey, which will be helpful to my fellow data science aspirants. Skillset Required: Knowledge in Statistics – Exploratory analysis, doing initial...

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Pivoting Data in R Excel-style

January 2, 2014
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Pivoting Data in R Excel-style

(This article is referring to an initial proof-of-concept version of r-big-pivot) I have to admit that I very much enjoy pivoting through data using Excel. Its pivoting tool is great for getting a quick insight into a data set’s structure … Continue reading → The post Pivoting Data in R Excel-style appeared first on joy...

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Subsetting in readOGR

December 31, 2013
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The function readOGR in the rgdal package is used to bring vector spatial data sources into R. readOGR() relies upon OGR (part of the GDAL/OGR library) for format conversion. Unfortunately, while OGR supports the ability to subset columns (with the -select switch) or rows (with the -where switch), or even to request a layer using

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