{ "cells": [ { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "[![AnalyticsDojo](https://github.com/rpi-techfundamentals/spring2019-materials/blob/master/fig/final-logo.png?raw=1)](http://rpi.analyticsdojo.com)\n", "

Introduction to R - DataFrames

\n", "

rpi.analyticsdojo.com

\n", "\n" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "## Introduction to R DataFrames\n", "- Data frames are combinations of vectors of the same length, but can be of different types.\n", "- It is a special type of list. \n", "- Data frames are what is used for standard rectangular (record by field) datasets, similar to a spreadsheet\n", "- Data frames are a functionality that both sets R aside from some languages (e.g., Matlab) and provides functionality similar to some statistical packages (e.g., Stata, SAS) and Python's Pandas Packages.\n" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "text/html": [ "'data.frame'" ], "text/latex": [ "'data.frame'" ], "text/markdown": [ "'data.frame'" ], "text/plain": [ "[1] \"data.frame\"" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
sepal_lengthsepal_widthpetal_lengthpetal_widthspecies
5.1 3.5 1.4 0.2 setosa
4.9 3.0 1.4 0.2 setosa
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sepal_lengthsepal_widthpetal_lengthpetal_widthspecies
1456.7 3.3 5.7 2.5 virginica
1466.7 3.0 5.2 2.3 virginica
1476.3 2.5 5.0 1.9 virginica
1486.5 3.0 5.2 2.0 virginica
1496.2 3.4 5.4 2.3 virginica
1505.9 3.0 5.1 1.8 virginica
\n" ], "text/latex": [ "\\begin{tabular}{r|lllll}\n", " & sepal\\_length & sepal\\_width & petal\\_length & petal\\_width & species\\\\\n", "\\hline\n", "\t145 & 6.7 & 3.3 & 5.7 & 2.5 & virginica\\\\\n", "\t146 & 6.7 & 3.0 & 5.2 & 2.3 & virginica\\\\\n", "\t147 & 6.3 & 2.5 & 5.0 & 1.9 & virginica\\\\\n", "\t148 & 6.5 & 3.0 & 5.2 & 2.0 & virginica\\\\\n", "\t149 & 6.2 & 3.4 & 5.4 & 2.3 & virginica\\\\\n", "\t150 & 5.9 & 3.0 & 5.1 & 1.8 & virginica\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "| | sepal_length | sepal_width | petal_length | petal_width | species | \n", "|---|---|---|---|---|---|\n", "| 145 | 6.7 | 3.3 | 5.7 | 2.5 | virginica | \n", "| 146 | 6.7 | 3.0 | 5.2 | 2.3 | virginica | \n", "| 147 | 6.3 | 2.5 | 5.0 | 1.9 | virginica | \n", "| 148 | 6.5 | 3.0 | 5.2 | 2.0 | virginica | \n", "| 149 | 6.2 | 3.4 | 5.4 | 2.3 | virginica | \n", "| 150 | 5.9 | 3.0 | 5.1 | 1.8 | virginica | \n", "\n", "\n" ], "text/plain": [ " sepal_length sepal_width petal_length petal_width species \n", "145 6.7 3.3 5.7 2.5 virginica\n", "146 6.7 3.0 5.2 2.3 virginica\n", "147 6.3 2.5 5.0 1.9 virginica\n", "148 6.5 3.0 5.2 2.0 virginica\n", "149 6.2 3.4 5.4 2.3 virginica\n", "150 5.9 3.0 5.1 1.8 virginica" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "'data.frame':\t150 obs. of 5 variables:\n", " $ sepal_length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...\n", " $ sepal_width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...\n", " $ petal_length: num 1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...\n", " $ petal_width : num 0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...\n", " $ species : Factor w/ 3 levels \"setosa\",\"versicolor\",..: 1 1 1 1 1 1 1 1 1 1 ...\n" ] } ], "source": [ "frame=read.csv(file=\"../../input/iris.csv\", header=TRUE,sep=\",\")\n", "class(frame)\n", "head(frame) #The first few rows.\n", "tail(frame) #The last few rows.\n", "str(frame) #The Structure.\n", "\n" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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speciessepal_width
setosa3.5
setosa3.0
setosa3.2
setosa3.1
setosa3.6
setosa3.9
setosa3.4
setosa3.4
setosa2.9
setosa3.1
setosa3.7
setosa3.4
setosa3.0
setosa3.0
setosa4.0
setosa4.4
setosa3.9
setosa3.5
setosa3.8
setosa3.8
setosa3.4
setosa3.7
setosa3.6
setosa3.3
setosa3.4
setosa3.0
setosa3.4
setosa3.5
setosa3.4
setosa3.2
⋮⋮
virginica3.2
virginica2.8
virginica2.8
virginica2.7
virginica3.3
virginica3.2
virginica2.8
virginica3.0
virginica2.8
virginica3.0
virginica2.8
virginica3.8
virginica2.8
virginica2.8
virginica2.6
virginica3.0
virginica3.4
virginica3.1
virginica3.0
virginica3.1
virginica3.1
virginica3.1
virginica2.7
virginica3.2
virginica3.3
virginica3.0
virginica2.5
virginica3.0
virginica3.4
virginica3.0
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2.7 \\\\\n", "\t virginica & 3.3 \\\\\n", "\t virginica & 3.2 \\\\\n", "\t virginica & 2.8 \\\\\n", "\t virginica & 3.0 \\\\\n", "\t virginica & 2.8 \\\\\n", "\t virginica & 3.0 \\\\\n", "\t virginica & 2.8 \\\\\n", "\t virginica & 3.8 \\\\\n", "\t virginica & 2.8 \\\\\n", "\t virginica & 2.8 \\\\\n", "\t virginica & 2.6 \\\\\n", "\t virginica & 3.0 \\\\\n", "\t virginica & 3.4 \\\\\n", "\t virginica & 3.1 \\\\\n", "\t virginica & 3.0 \\\\\n", "\t virginica & 3.1 \\\\\n", "\t virginica & 3.1 \\\\\n", "\t virginica & 3.1 \\\\\n", "\t virginica & 2.7 \\\\\n", "\t virginica & 3.2 \\\\\n", "\t virginica & 3.3 \\\\\n", "\t virginica & 3.0 \\\\\n", "\t virginica & 2.5 \\\\\n", "\t virginica & 3.0 \\\\\n", "\t virginica & 3.4 \\\\\n", "\t virginica & 3.0 \\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "species | sepal_width | \n", "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n", "| setosa | 3.5 | \n", "| setosa | 3.0 | \n", "| setosa | 3.2 | \n", "| setosa | 3.1 | \n", "| setosa | 3.6 | \n", "| setosa | 3.9 | \n", "| setosa | 3.4 | \n", "| setosa | 3.4 | \n", "| setosa | 2.9 | \n", "| setosa | 3.1 | \n", "| setosa | 3.7 | \n", "| setosa | 3.4 | \n", "| setosa | 3.0 | \n", "| setosa | 3.0 | \n", "| setosa | 4.0 | \n", "| setosa | 4.4 | \n", "| setosa | 3.9 | \n", "| setosa | 3.5 | \n", "| setosa | 3.8 | \n", "| setosa | 3.8 | \n", "| setosa | 3.4 | \n", "| setosa | 3.7 | \n", "| setosa | 3.6 | \n", "| setosa | 3.3 | \n", "| setosa | 3.4 | \n", "| setosa | 3.0 | \n", "| setosa | 3.4 | \n", "| setosa | 3.5 | \n", "| setosa | 3.4 | \n", "| setosa | 3.2 | \n", "| ⋮ | ⋮ | \n", "| virginica | 3.2 | \n", "| virginica | 2.8 | \n", "| virginica | 2.8 | \n", "| virginica | 2.7 | \n", "| virginica | 3.3 | \n", "| virginica | 3.2 | \n", "| virginica | 2.8 | \n", "| virginica | 3.0 | \n", "| virginica | 2.8 | \n", "| virginica | 3.0 | \n", "| virginica | 2.8 | \n", "| virginica | 3.8 | \n", "| virginica | 2.8 | \n", "| virginica | 2.8 | \n", "| virginica | 2.6 | \n", "| virginica | 3.0 | \n", "| virginica | 3.4 | \n", "| virginica | 3.1 | \n", "| virginica | 3.0 | \n", "| virginica | 3.1 | \n", "| virginica | 3.1 | \n", "| virginica | 3.1 | \n", "| virginica | 2.7 | \n", "| virginica | 3.2 | \n", "| virginica | 3.3 | \n", "| virginica | 3.0 | \n", "| virginica | 2.5 | \n", "| virginica | 3.0 | \n", "| virginica | 3.4 | \n", "| virginica | 3.0 | \n", "\n", "\n" ], "text/plain": [ " species sepal_width\n", "1 setosa 3.5 \n", "2 setosa 3.0 \n", "3 setosa 3.2 \n", "4 setosa 3.1 \n", "5 setosa 3.6 \n", "6 setosa 3.9 \n", "7 setosa 3.4 \n", "8 setosa 3.4 \n", "9 setosa 2.9 \n", "10 setosa 3.1 \n", "11 setosa 3.7 \n", "12 setosa 3.4 \n", "13 setosa 3.0 \n", "14 setosa 3.0 \n", "15 setosa 4.0 \n", "16 setosa 4.4 \n", "17 setosa 3.9 \n", "18 setosa 3.5 \n", "19 setosa 3.8 \n", "20 setosa 3.8 \n", "21 setosa 3.4 \n", "22 setosa 3.7 \n", "23 setosa 3.6 \n", "24 setosa 3.3 \n", "25 setosa 3.4 \n", "26 setosa 3.0 \n", "27 setosa 3.4 \n", "28 setosa 3.5 \n", "29 setosa 3.4 \n", "30 setosa 3.2 \n", "⋮ ⋮ ⋮ \n", "121 virginica 3.2 \n", "122 virginica 2.8 \n", "123 virginica 2.8 \n", "124 virginica 2.7 \n", "125 virginica 3.3 \n", "126 virginica 3.2 \n", "127 virginica 2.8 \n", "128 virginica 3.0 \n", "129 virginica 2.8 \n", "130 virginica 3.0 \n", "131 virginica 2.8 \n", "132 virginica 3.8 \n", "133 virginica 2.8 \n", "134 virginica 2.8 \n", "135 virginica 2.6 \n", "136 virginica 3.0 \n", "137 virginica 3.4 \n", "138 virginica 3.1 \n", "139 virginica 3.0 \n", "140 virginica 3.1 \n", "141 virginica 3.1 \n", "142 virginica 3.1 \n", "143 virginica 2.7 \n", "144 virginica 3.2 \n", "145 virginica 3.3 \n", "146 virginica 3.0 \n", "147 virginica 2.5 \n", "148 virginica 3.0 \n", "149 virginica 3.4 \n", "150 virginica 3.0 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "frame[c(\"species\",\"sepal_width\")]" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
sepal_lengthsepal_widthpetal_lengthpetal_widthspeciespetalspetals2
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4.9 3.0 1.4 0.2 setosa0 0
4.7 3.2 1.3 0.2 setosa0 0
4.6 3.1 1.5 0.2 setosa0 0
5.0 3.6 1.4 0.2 setosa0 0
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\n" ], "text/latex": [ "\\begin{tabular}{r|lllllll}\n", " sepal\\_length & sepal\\_width & petal\\_length & petal\\_width & species & petals & petals2\\\\\n", "\\hline\n", "\t 5.1 & 3.5 & 1.4 & 0.2 & setosa & 0 & 0 \\\\\n", "\t 4.9 & 3.0 & 1.4 & 0.2 & setosa & 0 & 0 \\\\\n", "\t 4.7 & 3.2 & 1.3 & 0.2 & setosa & 0 & 0 \\\\\n", "\t 4.6 & 3.1 & 1.5 & 0.2 & setosa & 0 & 0 \\\\\n", "\t 5.0 & 3.6 & 1.4 & 0.2 & setosa & 0 & 0 \\\\\n", "\t 5.4 & 3.9 & 1.7 & 0.4 & setosa & 0 & 0 \\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "sepal_length | sepal_width | petal_length | petal_width | species | petals | petals2 | \n", "|---|---|---|---|---|---|\n", "| 5.1 | 3.5 | 1.4 | 0.2 | setosa | 0 | 0 | \n", "| 4.9 | 3.0 | 1.4 | 0.2 | setosa | 0 | 0 | \n", "| 4.7 | 3.2 | 1.3 | 0.2 | setosa | 0 | 0 | \n", "| 4.6 | 3.1 | 1.5 | 0.2 | setosa | 0 | 0 | \n", "| 5.0 | 3.6 | 1.4 | 0.2 | setosa | 0 | 0 | \n", "| 5.4 | 3.9 | 1.7 | 0.4 | setosa | 0 | 0 | \n", "\n", "\n" ], "text/plain": [ " sepal_length sepal_width petal_length petal_width species petals petals2\n", "1 5.1 3.5 1.4 0.2 setosa 0 0 \n", "2 4.9 3.0 1.4 0.2 setosa 0 0 \n", "3 4.7 3.2 1.3 0.2 setosa 0 0 \n", "4 4.6 3.1 1.5 0.2 setosa 0 0 \n", "5 5.0 3.6 1.4 0.2 setosa 0 0 \n", "6 5.4 3.9 1.7 0.4 setosa 0 0 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "frame['petals']<-0\n", "frame$petals2<-0\n", "head(frame)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": true }, "outputs": [], "source": [ "mean.sepalLenth.setosa<-mean(frame[,'sepal_length'])" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "## Slicing a Dataframe by Column\n", "- Remember the syntax of `df[rows,columns]` \n", "- Using `dataframe$column` provides one way of selecting a column. \n", "- We can also specify the index position: `dataframe[,columnIndex]`\n", "- We can also specify the column name: `dataframe[,columnsName]`" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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  2. 4.9
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  3. 4.7
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  5. 5
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\n" ], "text/latex": [ "\\begin{enumerate*}\n", "\\item 5.1\n", "\\item 4.9\n", "\\item 4.7\n", "\\item 4.6\n", "\\item 5\n", "\\end{enumerate*}\n" ], "text/markdown": [ "1. 5.1\n", "2. 4.9\n", "3. 4.7\n", "4. 4.6\n", "5. 5\n", "\n", "\n" ], "text/plain": [ "[1] 5.1 4.9 4.7 4.6 5.0" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
    \n", "\t
  1. 5.1
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  2. 4.9
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  3. 4.7
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  5. 5
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\n" ], "text/latex": [ "\\begin{enumerate*}\n", "\\item 5.1\n", "\\item 4.9\n", "\\item 4.7\n", "\\item 4.6\n", "\\item 5\n", "\\end{enumerate*}\n" ], "text/markdown": [ "1. 5.1\n", "2. 4.9\n", "3. 4.7\n", "4. 4.6\n", "5. 5\n", "\n", "\n" ], "text/plain": [ "[1] 5.1 4.9 4.7 4.6 5.0" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sepal_length1<-frame$sepal_length #Using Dollar Sign and the column name.\n", "sepal_length2<- frame[,1] #Using the Index Location\n", "sepal_length3<- frame[,'sepal_length']\n", "sepal_length4<- frame[,c('sepal_length','sepal_width')]\n", "\n", "sepal_length1[1:5] #Print the first 5 \n", "sepal_length2[1:5]\n", "sepal_length3[1:5]\n" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "## Selecting Rows\n", "- We can select rows from a dataframe using index position: `dataframe[rowIndex,columnIndex]`. \n", "- Use `c(row1, row2, row3)` to select out specific rows. " ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "20" ], "text/latex": [ "20" ], "text/markdown": [ "20" ], "text/plain": [ "[1] 20" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "3" ], "text/latex": [ "3" ], "text/markdown": [ "3" ], "text/plain": [ "[1] 3" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\n", "
sepal_lengthsepal_widthpetal_lengthpetal_widthspeciespetalspetals2
15.1 3.5 1.4 0.2 setosa0 0
55.0 3.6 1.4 0.2 setosa0 0
65.4 3.9 1.7 0.4 setosa0 0
\n" ], "text/latex": [ "\\begin{tabular}{r|lllllll}\n", " & sepal\\_length & sepal\\_width & petal\\_length & petal\\_width & species & petals & petals2\\\\\n", "\\hline\n", "\t1 & 5.1 & 3.5 & 1.4 & 0.2 & setosa & 0 & 0 \\\\\n", "\t5 & 5.0 & 3.6 & 1.4 & 0.2 & setosa & 0 & 0 \\\\\n", "\t6 & 5.4 & 3.9 & 1.7 & 0.4 & setosa & 0 & 0 \\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "| | sepal_length | sepal_width | petal_length | petal_width | species | petals | petals2 | \n", "|---|---|---|\n", "| 1 | 5.1 | 3.5 | 1.4 | 0.2 | setosa | 0 | 0 | \n", "| 5 | 5.0 | 3.6 | 1.4 | 0.2 | setosa | 0 | 0 | \n", "| 6 | 5.4 | 3.9 | 1.7 | 0.4 | setosa | 0 | 0 | \n", "\n", "\n" ], "text/plain": [ " sepal_length sepal_width petal_length petal_width species petals petals2\n", "1 5.1 3.5 1.4 0.2 setosa 0 0 \n", "5 5.0 3.6 1.4 0.2 setosa 0 0 \n", "6 5.4 3.9 1.7 0.4 setosa 0 0 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "frame2<-frame[1:20,] \n", "frame3<-frame[c(1,5,6),] #This selects out specific rows\n", "nrow(frame2)\n", "nrow(frame3)\n", "frame3" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "## Conditional Statements and Dataframes with Subset\n", "- We can select subsets of a dataframe by putting an equality in the row or subset. \n", "- Subset is also a dataframe. \n", "- Can optionally select columns with the `select = c(col1, col2)`" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
sepal_lengthsepal_widthpetal_lengthpetal_widthspeciespetalspetals2
5.1 3.5 1.4 0.2 setosa0 0
4.9 3.0 1.4 0.2 setosa0 0
4.7 3.2 1.3 0.2 setosa0 0
4.6 3.1 1.5 0.2 setosa0 0
5.0 3.6 1.4 0.2 setosa0 0
5.4 3.9 1.7 0.4 setosa0 0
\n" ], "text/latex": [ "\\begin{tabular}{r|lllllll}\n", " sepal\\_length & sepal\\_width & petal\\_length & petal\\_width & species & petals & petals2\\\\\n", "\\hline\n", "\t 5.1 & 3.5 & 1.4 & 0.2 & setosa & 0 & 0 \\\\\n", "\t 4.9 & 3.0 & 1.4 & 0.2 & setosa & 0 & 0 \\\\\n", "\t 4.7 & 3.2 & 1.3 & 0.2 & setosa & 0 & 0 \\\\\n", "\t 4.6 & 3.1 & 1.5 & 0.2 & setosa & 0 & 0 \\\\\n", "\t 5.0 & 3.6 & 1.4 & 0.2 & setosa & 0 & 0 \\\\\n", "\t 5.4 & 3.9 & 1.7 & 0.4 & setosa & 0 & 0 \\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "sepal_length | sepal_width | petal_length | petal_width | species | petals | petals2 | \n", "|---|---|---|---|---|---|\n", "| 5.1 | 3.5 | 1.4 | 0.2 | setosa | 0 | 0 | \n", "| 4.9 | 3.0 | 1.4 | 0.2 | setosa | 0 | 0 | \n", "| 4.7 | 3.2 | 1.3 | 0.2 | setosa | 0 | 0 | \n", "| 4.6 | 3.1 | 1.5 | 0.2 | setosa | 0 | 0 | \n", "| 5.0 | 3.6 | 1.4 | 0.2 | setosa | 0 | 0 | \n", "| 5.4 | 3.9 | 1.7 | 0.4 | setosa | 0 | 0 | \n", "\n", "\n" ], "text/plain": [ " sepal_length sepal_width petal_length petal_width species petals petals2\n", "1 5.1 3.5 1.4 0.2 setosa 0 0 \n", "2 4.9 3.0 1.4 0.2 setosa 0 0 \n", "3 4.7 3.2 1.3 0.2 setosa 0 0 \n", "4 4.6 3.1 1.5 0.2 setosa 0 0 \n", "5 5.0 3.6 1.4 0.2 setosa 0 0 \n", "6 5.4 3.9 1.7 0.4 setosa 0 0 " ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "'data.frame'" ], "text/latex": [ "'data.frame'" ], "text/markdown": [ "'data.frame'" ], "text/plain": [ "[1] \"data.frame\"" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "50" ], "text/latex": [ "50" ], "text/markdown": [ "50" ], "text/plain": [ "[1] 50" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "5.006" ], "text/latex": [ "5.006" ], "text/markdown": [ "5.006" ], "text/plain": [ "[1] 5.006" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "22" ], "text/latex": [ "22" ], "text/markdown": [ "22" ], "text/plain": [ "[1] 22" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
sepal_lengthsepal_widthpetal_lengthpetal_widthspeciespetalspetals2
15.1 3.5 1.4 0.2 setosa0 0
65.4 3.9 1.7 0.4 setosa0 0
115.4 3.7 1.5 0.2 setosa0 0
155.8 4.0 1.2 0.2 setosa0 0
165.7 4.4 1.5 0.4 setosa0 0
175.4 3.9 1.3 0.4 setosa0 0
\n" ], "text/latex": [ "\\begin{tabular}{r|lllllll}\n", " & sepal\\_length & sepal\\_width & petal\\_length & petal\\_width & species & petals & petals2\\\\\n", "\\hline\n", "\t1 & 5.1 & 3.5 & 1.4 & 0.2 & setosa & 0 & 0 \\\\\n", "\t6 & 5.4 & 3.9 & 1.7 & 0.4 & setosa & 0 & 0 \\\\\n", "\t11 & 5.4 & 3.7 & 1.5 & 0.2 & setosa & 0 & 0 \\\\\n", "\t15 & 5.8 & 4.0 & 1.2 & 0.2 & setosa & 0 & 0 \\\\\n", "\t16 & 5.7 & 4.4 & 1.5 & 0.4 & setosa & 0 & 0 \\\\\n", "\t17 & 5.4 & 3.9 & 1.3 & 0.4 & setosa & 0 & 0 \\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "| | sepal_length | sepal_width | petal_length | petal_width | species | petals | petals2 | \n", "|---|---|---|---|---|---|\n", "| 1 | 5.1 | 3.5 | 1.4 | 0.2 | setosa | 0 | 0 | \n", "| 6 | 5.4 | 3.9 | 1.7 | 0.4 | setosa | 0 | 0 | \n", "| 11 | 5.4 | 3.7 | 1.5 | 0.2 | setosa | 0 | 0 | \n", "| 15 | 5.8 | 4.0 | 1.2 | 0.2 | setosa | 0 | 0 | \n", "| 16 | 5.7 | 4.4 | 1.5 | 0.4 | setosa | 0 | 0 | \n", "| 17 | 5.4 | 3.9 | 1.3 | 0.4 | setosa | 0 | 0 | \n", "\n", "\n" ], "text/plain": [ " sepal_length sepal_width petal_length petal_width species petals petals2\n", "1 5.1 3.5 1.4 0.2 setosa 0 0 \n", "6 5.4 3.9 1.7 0.4 setosa 0 0 \n", "11 5.4 3.7 1.5 0.2 setosa 0 0 \n", "15 5.8 4.0 1.2 0.2 setosa 0 0 \n", "16 5.7 4.4 1.5 0.4 setosa 0 0 \n", "17 5.4 3.9 1.3 0.4 setosa 0 0 " ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
sepal_lengthspecies
15.1 setosa
65.4 setosa
115.4 setosa
155.8 setosa
165.7 setosa
175.4 setosa
\n" ], "text/latex": [ "\\begin{tabular}{r|ll}\n", " & sepal\\_length & species\\\\\n", "\\hline\n", "\t1 & 5.1 & setosa\\\\\n", "\t6 & 5.4 & setosa\\\\\n", "\t11 & 5.4 & setosa\\\\\n", "\t15 & 5.8 & setosa\\\\\n", "\t16 & 5.7 & setosa\\\\\n", "\t17 & 5.4 & setosa\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "| | sepal_length | species | \n", "|---|---|---|---|---|---|\n", "| 1 | 5.1 | setosa | \n", "| 6 | 5.4 | setosa | \n", "| 11 | 5.4 | setosa | \n", "| 15 | 5.8 | setosa | \n", "| 16 | 5.7 | setosa | \n", "| 17 | 5.4 | setosa | \n", "\n", "\n" ], "text/plain": [ " sepal_length species\n", "1 5.1 setosa \n", "6 5.4 setosa \n", "11 5.4 setosa \n", "15 5.8 setosa \n", "16 5.7 setosa \n", "17 5.4 setosa " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "setosa.df <- subset(frame, species == 'setosa')\n", "\n", "head(setosa.df)\n", "class(setosa.df)\n", "nrow(setosa.df)\n", "mean.sepalLenth.setosa<-mean(setosa.df$sepal_length) #This creates a new vector\n", "mean.sepalLenth.setosa\n", "setosa.df.highseptalLength <- subset(setosa.df, sepal_length > mean.sepalLenth.setosa)\n", "nrow(setosa.df.highseptalLength)\n", "head(setosa.df.highseptalLength)\n", "setosa.dfhighseptalLength2 <- subset(setosa.df, sepal_length > mean.sepalLenth.setosa, select = c(sepal_length, species))\n", "head(setosa.dfhighseptalLength2)" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "## Subsetting Rows Using Indices\n", "- Just like pandas, we are using conditional statements to specify specific rows. \n", "- See [here](http://www.ats.ucla.edu/stat/r/faq/subset_R.htm) for good coverage and examples. " ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
sepal_lengthsepal_widthpetal_lengthpetal_widthspeciespetals
15.1 3.5 1.4 0.2 setosa0
24.9 3 1.4 0.2 setosa0
34.7 3.2 1.3 0.2 setosa0
44.6 3.1 1.5 0.2 setosa0
55 3.6 1.4 0.2 setosa0
65.4 3.9 1.7 0.4 setosa0
\n" ], "text/latex": [ "\\begin{tabular}{r|llllll}\n", " & sepal\\_length & sepal\\_width & petal\\_length & petal\\_width & species & petals\\\\\n", "\\hline\n", "\t1 & 5.1 & 3.5 & 1.4 & 0.2 & setosa & 0 \\\\\n", "\t2 & 4.9 & 3 & 1.4 & 0.2 & setosa & 0 \\\\\n", "\t3 & 4.7 & 3.2 & 1.3 & 0.2 & setosa & 0 \\\\\n", "\t4 & 4.6 & 3.1 & 1.5 & 0.2 & setosa & 0 \\\\\n", "\t5 & 5 & 3.6 & 1.4 & 0.2 & setosa & 0 \\\\\n", "\t6 & 5.4 & 3.9 & 1.7 & 0.4 & setosa & 0 \\\\\n", "\\end{tabular}\n" ], "text/plain": [ " sepal_length sepal_width petal_length petal_width species petals\n", "1 5.1 3.5 1.4 0.2 setosa 0\n", "2 4.9 3.0 1.4 0.2 setosa 0\n", "3 4.7 3.2 1.3 0.2 setosa 0\n", "4 4.6 3.1 1.5 0.2 setosa 0\n", "5 5.0 3.6 1.4 0.2 setosa 0\n", "6 5.4 3.9 1.7 0.4 setosa 0" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "'data.frame'" ], "text/latex": [ "'data.frame'" ], "text/markdown": [ "'data.frame'" ], "text/plain": [ "[1] \"data.frame\"" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "50" ], "text/latex": [ "50" ], "text/markdown": [ "50" ], "text/plain": [ "[1] 50" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "5.006" ], "text/latex": [ "5.006" ], "text/markdown": [ "5.006" ], "text/plain": [ "[1] 5.006" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "22" ], "text/latex": [ "22" ], "text/markdown": [ "22" ], "text/plain": [ "[1] 22" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
sepal_lengthsepal_widthpetal_lengthpetal_widthspeciespetals
15.1 3.5 1.4 0.2 setosa0
65.4 3.9 1.7 0.4 setosa0
115.4 3.7 1.5 0.2 setosa0
155.8 4 1.2 0.2 setosa0
165.7 4.4 1.5 0.4 setosa0
175.4 3.9 1.3 0.4 setosa0
\n" ], "text/latex": [ "\\begin{tabular}{r|llllll}\n", " & sepal\\_length & sepal\\_width & petal\\_length & petal\\_width & species & petals\\\\\n", "\\hline\n", "\t1 & 5.1 & 3.5 & 1.4 & 0.2 & setosa & 0 \\\\\n", "\t6 & 5.4 & 3.9 & 1.7 & 0.4 & setosa & 0 \\\\\n", "\t11 & 5.4 & 3.7 & 1.5 & 0.2 & setosa & 0 \\\\\n", "\t15 & 5.8 & 4 & 1.2 & 0.2 & setosa & 0 \\\\\n", "\t16 & 5.7 & 4.4 & 1.5 & 0.4 & setosa & 0 \\\\\n", "\t17 & 5.4 & 3.9 & 1.3 & 0.4 & setosa & 0 \\\\\n", "\\end{tabular}\n" ], "text/plain": [ " sepal_length sepal_width petal_length petal_width species petals\n", "1 5.1 3.5 1.4 0.2 setosa 0\n", "6 5.4 3.9 1.7 0.4 setosa 0\n", "11 5.4 3.7 1.5 0.2 setosa 0\n", "15 5.8 4.0 1.2 0.2 setosa 0\n", "16 5.7 4.4 1.5 0.4 setosa 0\n", "17 5.4 3.9 1.3 0.4 setosa 0" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "setosa.df <- frame[frame$species == \"setosa\",]\n", "head(setosa.df)\n", "class(setosa.df)\n", "nrow(setosa.df)\n", "mean.sepalLenth.setosa<-mean(setosa.df$sepal_length) #This creates a new vector\n", "mean.sepalLenth.setosa\n", "setosa.df.highseptalLength <- setosa.df[setosa.df$sepal_length > mean.sepalLenth.setosa,]\n", "nrow(setosa.df.highseptalLength)\n", "head(setosa.df.highseptalLength)" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "slideshow": { "slide_type": "subslide" } }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
sepal_lengthsepal_widthpetal_lengthpetal_widthspeciespetals
15.1 3.5 1.4 0.2 setosa0
155.8 4.0 1.2 0.2 setosa0
185.1 3.5 1.4 0.3 setosa0
205.1 3.8 1.5 0.3 setosa0
225.1 3.7 1.5 0.4 setosa0
245.1 3.3 1.7 0.5 setosa0
\n" ], "text/latex": [ "\\begin{tabular}{r|llllll}\n", " & sepal\\_length & sepal\\_width & petal\\_length & petal\\_width & species & petals\\\\\n", "\\hline\n", "\t1 & 5.1 & 3.5 & 1.4 & 0.2 & setosa & 0 \\\\\n", "\t15 & 5.8 & 4.0 & 1.2 & 0.2 & setosa & 0 \\\\\n", "\t18 & 5.1 & 3.5 & 1.4 & 0.3 & setosa & 0 \\\\\n", "\t20 & 5.1 & 3.8 & 1.5 & 0.3 & setosa & 0 \\\\\n", "\t22 & 5.1 & 3.7 & 1.5 & 0.4 & setosa & 0 \\\\\n", "\t24 & 5.1 & 3.3 & 1.7 & 0.5 & setosa & 0 \\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "| | sepal_length | sepal_width | petal_length | petal_width | species | petals | \n", "|---|---|---|---|---|---|\n", "| 1 | 5.1 | 3.5 | 1.4 | 0.2 | setosa | 0 | \n", "| 15 | 5.8 | 4.0 | 1.2 | 0.2 | setosa | 0 | \n", "| 18 | 5.1 | 3.5 | 1.4 | 0.3 | setosa | 0 | \n", "| 20 | 5.1 | 3.8 | 1.5 | 0.3 | setosa | 0 | \n", "| 22 | 5.1 | 3.7 | 1.5 | 0.4 | setosa | 0 | \n", "| 24 | 5.1 | 3.3 | 1.7 | 0.5 | setosa | 0 | \n", "\n", "\n" ], "text/plain": [ " sepal_length sepal_width petal_length petal_width species petals\n", "1 5.1 3.5 1.4 0.2 setosa 0 \n", "15 5.8 4.0 1.2 0.2 setosa 0 \n", "18 5.1 3.5 1.4 0.3 setosa 0 \n", "20 5.1 3.8 1.5 0.3 setosa 0 \n", "22 5.1 3.7 1.5 0.4 setosa 0 \n", "24 5.1 3.3 1.7 0.5 setosa 0 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "specific.df <- frame[frame$sepal_length %in% c(5.1,5.8),]\n", "head(specific.df)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Basics\n", "\n", "1. Load the Titanic train.csv data into an R data frame.\n", "2. Calculate the number of rows in the data frame.\n", "3. Calcuated general descriptive statistics for the data frame.\n", "4. Slice the data frame into 2 parts, selecting the first half of the rows. \n", "5. Select just the columns passangerID and whether they survivied or not. " ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "## CREDITS\n", "\n", "Copyright [AnalyticsDojo](http://rpi.analyticsdojo.com) 2016\n", "This work is licensed under the [Creative Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/) license agreement.\n", "Adopted from [Berkley R Bootcamp](https://github.com/berkeley-scf/r-bootcamp-2016).\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] } ], "metadata": { "anaconda-cloud": {}, "celltoolbar": "Slideshow", "kernelspec": { "display_name": "R", "language": "R", "name": "ir" }, "language_info": { "codemirror_mode": "r", "file_extension": ".r", "mimetype": "text/x-r-source", "name": "R", "pygments_lexer": "r", "version": "3.5.1" } }, "nbformat": 4, "nbformat_minor": 2 }