Week2

Synopsis

This is the R Markdown file for week 2.Topics covered in this homework are:

• importing csv files: Artificial Reddit user data
• importing excel files: HUD data regarding 2017 fair market rent
• importing text files: Average daily temperatures for Cincinnati dating back to 1995

The details of the homework can be found in the assignment section of this page: http://uc-r.github.io/data_wrangling/week-2.

Packages Required

The following packages were used in the homework

library(readxl) # for reading xlsx file from desktop
library(gdata)  # for scraping xlsx file from web
#library(DT)     # for displaying results in tabular form

Homeowrk Problems

1. download & import the csv file located at: https://bradleyboehmke.github.io/public/data/reddit.csv

the first five rows are displayed below

structure of file

## 'data.frame':    32754 obs. of  14 variables:
##  $ id               : int  1 2 3 4 5 6 7 8 9 10 ...
##  $ gender           : Factor w/ 2 levels "0","1": 1 1 2 1 2 1 1 1 1 1 ...
##  $ age.range        : Factor w/ 7 levels "18-24","25-34",..: 2 2 1 2 2 2 2 1 3 2 ...
##  $ marital.status   : Factor w/ 6 levels "Engaged","Forever Alone",..: NA NA NA NA NA 4 3 4 4 3 ...
##  $ employment.status: Factor w/ 6 levels "Employed full time",..: 1 1 2 2 1 1 1 4 1 2 ...
##  $ military.service : Factor w/ 2 levels "No","Yes": NA NA NA NA NA 1 1 1 1 1 ...
##  $ children         : Factor w/ 2 levels "No","Yes": 1 1 1 1 1 1 1 1 1 1 ...
##  $ education        : Factor w/ 7 levels "Associate degree",..: 2 2 5 2 2 2 5 2 2 5 ...
##  $ country          : chr  "United States" "United States" "United States" "United States" ...
##  $ state            : chr  "New York" "New York" "Virginia" "New York" ...
##  $ income.range     : Factor w/ 8 levels "$100,000 - $149,999",..: 2 2 8 2 7 2 NA 7 2 7 ...
##  $ fav.reddit       : chr  "getmotivated" "gaming" "snackexchange" "spacedicks" ...
##  $ dog.cat          : Factor w/ 3 levels "I like cats.",..: NA NA NA NA NA 2 2 2 1 1 ...
##  $ cheese           : Factor w/ 11 levels "American","Brie",..: NA NA NA NA NA 3 3 1 10 7 ...

2. now import the above csv file directly from the url provided (without downloading to your local hard drive)

the first five rows are displayed below

structure of file

## 'data.frame':    32754 obs. of  14 variables:
##  $ id               : int  1 2 3 4 5 6 7 8 9 10 ...
##  $ gender           : Factor w/ 2 levels "0","1": 1 1 2 1 2 1 1 1 1 1 ...
##  $ age.range        : Factor w/ 7 levels "18-24","25-34",..: 2 2 1 2 2 2 2 1 3 2 ...
##  $ marital.status   : Factor w/ 6 levels "Engaged","Forever Alone",..: NA NA NA NA NA 4 3 4 4 3 ...
##  $ employment.status: Factor w/ 6 levels "Employed full time",..: 1 1 2 2 1 1 1 4 1 2 ...
##  $ military.service : Factor w/ 2 levels "No","Yes": NA NA NA NA NA 1 1 1 1 1 ...
##  $ children         : Factor w/ 2 levels "No","Yes": 1 1 1 1 1 1 1 1 1 1 ...
##  $ education        : Factor w/ 7 levels "Associate degree",..: 2 2 5 2 2 2 5 2 2 5 ...
##  $ country          : chr  "United States" "United States" "United States" "United States" ...
##  $ state            : chr  "New York" "New York" "Virginia" "New York" ...
##  $ income.range     : Factor w/ 8 levels "$100,000 - $149,999",..: 2 2 8 2 7 2 NA 7 2 7 ...
##  $ fav.reddit       : chr  "getmotivated" "gaming" "snackexchange" "spacedicks" ...
##  $ dog.cat          : Factor w/ 3 levels "I like cats.",..: NA NA NA NA NA 2 2 2 1 1 ...
##  $ cheese           : Factor w/ 11 levels "American","Brie",..: NA NA NA NA NA 3 3 1 10 7 ...

3. download & import the .xlsx file located at: http://www.huduser.gov/portal/datasets/fmr/fmr2017/FY2017_4050_FMR.xlsx

the first five rows are displayed below

structure of file

## Classes 'tbl_df', 'tbl' and 'data.frame':    4769 obs. of  21 variables:
##  $ fips2010         : chr  "2300512300" "6099999999" "6999999999" "0100199999" ...
##  $ fips2000         : chr  NA NA NA "0100199999" ...
##  $ fmr2             : num  1078 677 666 822 977 ...
##  $ fmr0             : num  755 502 411 587 807 501 665 665 491 464 ...
##  $ fmr1             : num  851 506 498 682 847 505 751 751 494 467 ...
##  $ fmr3             : num  1454 987 961 1054 1422 ...
##  $ fmr4             : num  1579 1038 1158 1425 1634 ...
##  $ State            : num  23 60 69 1 1 1 1 1 1 1 ...
##  $ Metro_code       : chr  "METRO38860MM6400" "NCNTY60999N60999" "NCNTY69999N69999" "METRO33860M33860" ...
##  $ areaname         : chr  "Portland, ME HUD Metro FMR Area" "American Samoa" "Northern Mariana Islands" "Montgomery, AL MSA" ...
##  $ county           : num  NA 999 999 1 3 5 7 9 11 13 ...
##  $ CouSub           : chr  "12300" "99999" "99999" "99999" ...
##  $ countyname       : chr  "Cumberland County" "American Samoa" "Northern Mariana Islands" "Autauga County" ...
##  $ county_town_name : chr  "Chebeague Island town" "American Samoa" "Northern Mariana Islands" "Autauga County" ...
##  $ pop2010          : num  341 55519 53883 54571 182265 ...
##  $ acs_2016_2       : num  1109 653 642 788 873 ...
##  $ state_alpha      : chr  "ME" "AS" "MP" "AL" ...
##  $ fmr_type         : num  40 40 40 40 40 40 40 40 40 40 ...
##  $ metro            : num  1 0 0 1 1 0 1 1 0 0 ...
##  $ FMR_PCT_Change   : num  0.972 1.037 1.037 1.043 1.119 ...
##  $ FMR_Dollar_Change: num  -31 24 24 34 104 35 26 26 52 52 ...

4. now import the above .xlsx file directly from the url provided (without downloading to your local hard drive)

the first five rows are displayed below

structure of file

## 'data.frame':    4769 obs. of  21 variables:
##  $ fips2010         : num  2.3e+09 6.1e+09 7.0e+09 1.0e+08 1.0e+08 ...
##  $ fips2000         : num  NA NA NA 1e+08 1e+08 ...
##  $ fmr2             : int  1078 677 666 822 977 671 866 866 621 621 ...
##  $ fmr0             : int  755 502 411 587 807 501 665 665 491 464 ...
##  $ fmr1             : int  851 506 498 682 847 505 751 751 494 467 ...
##  $ fmr3             : int  1454 987 961 1054 1422 839 1163 1163 853 849 ...
##  $ fmr4             : int  1579 1038 1158 1425 1634 958 1298 1298 856 1094 ...
##  $ State            : int  23 60 69 1 1 1 1 1 1 1 ...
##  $ Metro_code       : Factor w/ 2598 levels "METRO10180M10180",..: 451 2592 2594 384 160 625 55 55 626 627 ...
##  $ areaname         : Factor w/ 2598 levels " Santa Ana-Anaheim-Irvine, CA HUD Metro FMR Area",..: 1903 52 1723 1633 571 122 186 186 263 271 ...
##  $ county           : int  NA 999 999 1 3 5 7 9 11 13 ...
##  $ CouSub           : int  12300 99999 99999 99999 99999 99999 99999 99999 99999 99999 ...
##  $ countyname       : Factor w/ 1961 levels "Abbeville County",..: 462 41 1265 92 99 110 163 178 239 249 ...
##  $ county_town_name : Factor w/ 3175 levels "Abbeville County",..: 533 60 2024 136 149 165 254 277 386 401 ...
##  $ pop2010          : int  341 55519 53883 54571 182265 27457 22915 57322 10914 20947 ...
##  $ acs_2016_2       : int  1109 653 642 788 873 636 840 840 569 569 ...
##  $ state_alpha      : Factor w/ 56 levels "AK","AL","AR",..: 24 4 28 2 2 2 2 2 2 2 ...
##  $ fmr_type         : int  40 40 40 40 40 40 40 40 40 40 ...
##  $ metro            : int  1 0 0 1 1 0 1 1 0 0 ...
##  $ FMR_PCT_Change   : num  0.972 1.037 1.037 1.043 1.119 ...
##  $ FMR_Dollar_Change: int  -31 24 24 34 104 35 26 26 52 52 ...

5. go to this University of Dayton webpage http://academic.udayton.edu/kissock/http/Weather/citylistUS.htm scroll down to Ohio and import the Cincinnati (OHCINCIN.txt) file

the first five rows are displayed below

structure of file

## 'data.frame':    7963 obs. of  4 variables:
##  $ V1: int  1 1 1 1 1 1 1 1 1 1 ...
##  $ V2: int  1 2 3 4 5 6 7 8 9 10 ...
##  $ V3: int  1995 1995 1995 1995 1995 1995 1995 1995 1995 1995 ...
##  $ V4: num  41.1 22.2 22.8 14.9 9.5 23.8 31.1 26.9 31.3 31.5 ...