579 search results for "sql"

10 R packages every data scientist should know about

February 18, 2013
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The yhat blog lists 10 R packages they wish they'd known about earlier. Drew Conway calls them "10 reasons to always start your analysis in R". They're all very useful R packages that every data scientist should be aware of. They are: sqldf (for selecting from data frames using SQL) forecast (for easy forecasting of time series) plyr (data...

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Saving R Objects in Oracle Database using Oracle R Enterprise 1.3 Datastore

February 18, 2013
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Saving R Objects in Oracle Database using Oracle R Enterprise 1.3 Datastore

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Google Statistician uses R and other programming tools

February 16, 2013
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A great interview on the Simply Statistics blog with Google's Nick Chamandy, Phd in Statistics.  Explains that he mainly uses R among other tools to perform his work at Google.  Also of note is the active data science community within Google ...

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R database interfaces

February 14, 2013
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Several packages on CRAN provide (or relate to) interfaces between databases and R.  Here is a summary, mostly in the words of the package descriptions.  Remember that package names are case-sensitive. The packages that talk about being DBI-compliant are referring to the DBI package (see below in “Other SQL”). MySQL dbConnect: Provides a graphical user The post R...

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A Shiny example – SAP HANA, R and Shiny

February 13, 2013
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A Shiny example – SAP HANA, R and Shiny

As you may already know...I love R...a fancy, open source statistics programming language. So today, I decided to learn something new using R.There aren't much Web Servers for R, but there's one that I really like called Rook, that I covered on my blog...

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F1Stats – Correlations Between Qualifying, Grid and Race Classification

February 9, 2013
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F1Stats – Correlations Between Qualifying, Grid and Race Classification

Following directly on from F1Stats – Visually Comparing Qualifying and Grid Positions with Race Classification, and continuing in my attempt to replicate some of the methodology and results used in A Tale of Two Motorsports: A Graphical-Statistical Analysis of How Practice, Qualifying, and Past SuccessRelate to Finish Position in NASCAR and Formula One Racing, here’s

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Generating Labels for Supervised Text Classification using CAT and R

February 4, 2013
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Generating Labels for Supervised Text Classification using CAT and R

The explosion in the availability of text has opened new opportunities to exploit text as data for research. As Justin Grimmer and Brandon Stewart discuss in the above paper, there are a number of approaches to reducing human text to … Continue reading →

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analyze the survey of income and program participation (sipp) with r

February 4, 2013
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if the census bureau's budget was gutted and only one complex sample survey survived, pray it's the survey of income and program participation (sipp).  it's giant.  it's rich with variables.  it's monthly.  it follows households over three, four, now five year panels.  the congressional budget office uses it for their health insurance simulation.  analysts read that sipp has...

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F1Stats – Visually Comparing Qualifying and Grid Positions with Race Classification

January 30, 2013
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F1Stats – Visually Comparing Qualifying and Grid Positions with Race Classification

Following the roundabout tour of F1Stats – A Prequel to Getting Started With Rank Correlations, here’s a walk through of my attempt to replicate the first part of A Tale of Two

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Another Benchmark for Joining Two Data Frames

January 29, 2013
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Another Benchmark for Joining Two Data Frames

In my post yesterday comparing efficiency in joining two data frames, I overlooked the computing cost used to convert data.frames to data.tables / ff data objects. Today, I did the test again with the consideration of library loading and data conversion. After the replication of 10 times in rbenchmark package, the joining method with data.table

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