Data 608 - Assignment 1
Natalie Mollaghan
9/8/2018
library(ggplot2)
library(psych)##
## Attaching package: 'psych'## The following objects are masked from 'package:ggplot2':
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## %+%, alphalibrary(dplyr)## Warning: package 'dplyr' was built under R version 3.4.2##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
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## filter, lag## The following objects are masked from 'package:base':
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## intersect, setdiff, setequal, unionPrinciples of Data Visualization and Introduction to ggplot2
I have provided you with data about the 5,000 fastest growing companies in the US, as compiled by Inc. magazine. lets read this in:
And lets preview this data:
## Rank Name Growth_Rate Revenue
## 1 1 Fuhu 421.48 1.179e+08
## 2 2 FederalConference.com 248.31 4.960e+07
## 3 3 The HCI Group 245.45 2.550e+07
## 4 4 Bridger 233.08 1.900e+09
## 5 5 DataXu 213.37 8.700e+07
## 6 6 MileStone Community Builders 179.38 4.570e+07
## Industry Employees City State
## 1 Consumer Products & Services 104 El Segundo CA
## 2 Government Services 51 Dumfries VA
## 3 Health 132 Jacksonville FL
## 4 Energy 50 Addison TX
## 5 Advertising & Marketing 220 Boston MA
## 6 Real Estate 63 Austin TX## Rank Name Growth_Rate
## Min. : 1 (Add)ventures : 1 Min. : 0.340
## 1st Qu.:1252 @Properties : 1 1st Qu.: 0.770
## Median :2502 1-Stop Translation USA: 1 Median : 1.420
## Mean :2502 110 Consulting : 1 Mean : 4.612
## 3rd Qu.:3751 11thStreetCoffee.com : 1 3rd Qu.: 3.290
## Max. :5000 123 Exteriors : 1 Max. :421.480
## (Other) :4995
## Revenue Industry Employees
## Min. :2.000e+06 IT Services : 733 Min. : 1.0
## 1st Qu.:5.100e+06 Business Products & Services: 482 1st Qu.: 25.0
## Median :1.090e+07 Advertising & Marketing : 471 Median : 53.0
## Mean :4.822e+07 Health : 355 Mean : 232.7
## 3rd Qu.:2.860e+07 Software : 342 3rd Qu.: 132.0
## Max. :1.010e+10 Financial Services : 260 Max. :66803.0
## (Other) :2358 NA's :12
## City State
## New York : 160 CA : 701
## Chicago : 90 TX : 387
## Austin : 88 NY : 311
## Houston : 76 VA : 283
## San Francisco: 75 FL : 282
## Atlanta : 74 IL : 273
## (Other) :4438 (Other):2764Think a bit on what these summaries mean. Use the space below to add some more relevant non-visual exploratory information you think helps you understand this data:
## [1] 241160900000## # A tibble: 25 x 2
## # Groups: Industry [25]
## Industry n
## <fctr> <int>
## 1 IT Services 733
## 2 Business Products & Services 482
## 3 Advertising & Marketing 471
## 4 Health 355
## 5 Software 342
## 6 Financial Services 260
## 7 Manufacturing 256
## 8 Consumer Products & Services 203
## 9 Retail 203
## 10 Government Services 202
## # ... with 15 more rows## # A tibble: 25 x 2
## Industry `Revenue by Industry`
## <fctr> <dbl>
## 1 Business Products & Services 26367900000
## 2 IT Services 20681300000
## 3 Health 17863400000
## 4 Consumer Products & Services 14956400000
## 5 Logistics & Transportation 14840500000
## 6 Energy 13771600000
## 7 Construction 13174300000
## 8 Financial Services 13150900000
## 9 Food & Beverage 12911300000
## 10 Manufacturing 12684000000
## # ... with 15 more rows## Industry n Revenue by Industry
## 1 Computer Hardware 44 11885700000
## 2 Energy 109 13771600000
## 3 Food & Beverage 131 12911300000
## 4 Logistics & Transportation 155 14840500000
## 5 Consumer Products & Services 203 14956400000
## 6 Construction 187 13174300000
## 7 Telecommunications 129 7334400000
## 8 Business Products & Services 482 26367900000
## 9 Security 73 3812800000
## 10 Environmental Services 51 2638800000
## 11 Financial Services 260 13150900000
## 12 Retail 203 10257400000
## 13 Health 355 17863400000
## 14 Manufacturing 256 12684000000
## 15 Travel & Hospitality 62 2931600000
## 16 Human Resources 196 9246100000
## 17 Insurance 50 2337900000
## 18 Engineering 74 2532500000
## 19 Media 54 1742400000
## 20 Real Estate 96 2965700000
## 21 Government Services 202 6009100000
## 22 IT Services 733 20681300000
## 23 Software 342 8140600000
## 24 Advertising & Marketing 471 7785000000
## 25 Education 83 1139300000
## Avg. Rev. By Industry
## 1 270129545
## 2 126344954
## 3 98559542
## 4 95745161
## 5 73676847
## 6 70450802
## 7 56855814
## 8 54705187
## 9 52230137
## 10 51741176
## 11 50580385
## 12 50529064
## 13 50319437
## 14 49546875
## 15 47283871
## 16 47173980
## 17 46758000
## 18 34222973
## 19 32266667
## 20 30892708
## 21 29748020
## 22 28214598
## 23 23802924
## 24 16528662
## 25 13726506## # A tibble: 52 x 2
## State `Revenue by State`
## <fctr> <dbl>
## 1 IL 33244300000
## 2 CA 23457900000
## 3 TX 22164200000
## 4 NY 18260400000
## 5 OH 12786600000
## 6 FL 10610300000
## 7 NC 9258500000
## 8 VA 8667700000
## 9 MI 7805800000
## 10 WI 7296600000
## # ... with 42 more rows## # A tibble: 25 x 2
## Industry `Employees By Industry`
## <fctr> <int>
## 1 Human Resources 226980
## 2 Financial Services 47693
## 3 Consumer Products & Services 45464
## 4 Security 41059
## 5 Advertising & Marketing 39731
## 6 Retail 37068
## 7 Construction 29099
## 8 Energy 26437
## 9 Government Services 26185
## 10 Travel & Hospitality 23035
## # ... with 15 more rows## # A tibble: 798 x 3
## # Groups: State [52]
## State Industry n
## <fctr> <fctr> <int>
## 1 CA Advertising & Marketing 91
## 2 VA Government Services 83
## 3 CA IT Services 82
## 4 CA Business Products & Services 69
## 5 VA IT Services 69
## 6 CA Software 65
## 7 NY Advertising & Marketing 57
## 8 TX IT Services 54
## 9 IL IT Services 48
## 10 CA Financial Services 44
## # ... with 788 more rows## # A tibble: 25 x 4
## Industry `Avg. Growth Rate` `Min Growth Rate`
## <fctr> <dbl> <dbl>
## 1 Energy 9.603303 0.35
## 2 Consumer Products & Services 8.776108 0.35
## 3 Real Estate 7.746667 0.35
## 4 Government Services 7.238168 0.35
## 5 Advertising & Marketing 6.225478 0.35
## 6 Retail 6.184729 0.34
## 7 Financial Services 5.435308 0.34
## 8 Software 5.020643 0.35
## 9 Health 4.856394 0.35
## 10 Media 4.374074 0.41
## # ... with 15 more rows, and 1 more variables: `Max Growth Rate` <dbl>## # A tibble: 25 x 4
## Industry `Avg. No. Employees` `Min No. Employees`
## <fctr> <dbl> <dbl>
## 1 Human Resources 1158.0612 4
## 2 Security 562.4521 7
## 3 Travel & Hospitality 371.5323 3
## 4 Engineering 276.1486 11
## 5 Energy 242.5413 2
## 6 Consumer Products & Services 223.9606 1
## 7 Computer Hardware 220.7727 6
## 8 Environmental Services 199.1176 4
## 9 Financial Services 183.4346 5
## 10 Retail 182.6010 2
## # ... with 15 more rows, and 1 more variables: `Max No. Employees` <dbl>Question 1
Create a graph that shows the distribution of companies in the dataset by State (ie how many are in each state). There are a lot of States, so consider which axis you should use. This visualization is ultimately going to be consumed on a ‘portrait’ oriented screen (ie taller than wide), which should further guide your layout choices.
Quesiton 2
Lets dig in on the state with the 3rd most companies in the data set. Imagine you work for the state and are interested in how many people are employed by companies in different industries. Create a plot that shows the average and/or median employment by industry for companies in this state (only use cases with full data, use R’s complete.cases() function.) In addition to this, your graph should show how variable the ranges are, and you should deal with outliers.
Question 3
Now imagine you work for an investor and want to see which industries generate the most revenue per employee. Create a chart that makes this information clear. Once again, the distribution per industry should be shown.
## Industry Employees By Industry Revenue by Industry
## 1 Computer Hardware 9714 11885700000
## 2 Energy 26437 13771600000
## 3 Construction 29099 13174300000
## 4 Consumer Products & Services 45464 14956400000
## 5 Insurance 7339 2337900000
## 6 Retail 37068 10257400000
## 7 Financial Services 47693 13150900000
## 8 Environmental Services 10155 2638800000
## 9 Government Services 26185 6009100000
## 10 Advertising & Marketing 39731 7785000000
## 11 Media 9532 1742400000
## 12 Education 7685 1139300000
## 13 Travel & Hospitality 23035 2931600000
## 14 Engineering 20435 2532500000
## 15 Security 41059 3812800000
## 16 Human Resources 226980 9246100000
## 17 Business Products & Services NA 26367900000
## 18 Food & Beverage NA 12911300000
## 19 Health NA 17863400000
## 20 IT Services NA 20681300000
## 21 Logistics & Transportation NA 14840500000
## 22 Manufacturing NA 12684000000
## 23 Real Estate NA 2965700000
## 24 Software NA 8140600000
## 25 Telecommunications NA 7334400000
## Revenue Per Employee By Industry
## 1 1223563.93
## 2 520921.44
## 3 452740.64
## 4 328972.37
## 5 318558.39
## 6 276718.46
## 7 275740.67
## 8 259852.29
## 9 229486.35
## 10 195942.71
## 11 182794.80
## 12 148249.84
## 13 127267.20
## 14 123929.53
## 15 92861.49
## 16 40735.31
## 17 NA
## 18 NA
## 19 NA
## 20 NA
## 21 NA
## 22 NA
## 23 NA
## 24 NA
## 25 NA