Is there a way to make the legend smaller and the graph larger? I keep getting an extremely large legend with a small graph and I need it to be the opposite.
Here is my code:
ggplot(Metro, aes(x=MedianSalePrice, fill=Region)) +geom_histogram(binwidth = 50)+labs(x="MedianSalePrice")
Here is what I get:
Here is a small sample of the dataset
Region | PeriodEnd | MedianSalePrice | HomesSold | NewListings | Inventory |
---|---|---|---|---|---|
National | March 2014 | 214500 | 8 | 5 | 38 |
National | June 2014 | 264000 | 7 | 8 | 35 |
National | July 2014 | 225550 | 4 | 11 | 39 |
National | August 2014 | 246500 | 8 | 5 | 31 |
National | October 2014 | 232500 | 6 | 5 | 34 |
National | November 2014 | 207500 | 6 | 7 | 33 |
National | January 2015 | 277500 | 4 | 10 | 34 |
National | February 2015 | 234950 | 6 | 3 | 35 |
National | April 2015 | 216300 | 7 | 4 | 29 |
National | July 2015 | 271600 | 10 | 8 | 36 |
National | August 2015 | 176500 | 6 | 12 | 41 |
National | September 2015 | 165000 | 5 | 8 | 42 |
National | October 2015 | 95339 | 2 | 7 | 42 |
National | November 2015 | 235000 | 5 | 8 | 37 |
National | December 2015 | 225000 | 13 | 2 | 28 |
National | February 2016 | 182000 | 2 | 11 | 32 |
National | March 2016 | 200400 | 4 | 10 | 34 |
National | April 2016 | 222500 | 14 | 8 | 28 |
National | May 2016 | 246000 | 7 | 9 | 29 |
National | June 2016 | 256000 | 11 | 19 | 33 |
National | July 2016 | 275000 | 7 | 7 | 34 |
National | August 2016 | 269900 | 5 | 9 | 31 |
National | October 2016 | 222500 | 9 | 3 | 26 |
National | January 2017 | 245000 | 7 | 12 | 26 |
National | February 2017 | 245100 | 7 | 14 | 34 |
National | March 2017 | 257450 | 6 | 12 | 32 |
National | April 2017 | 266750 | 14 | 8 | 30 |
National | May 2017 | 278900 | 7 | 9 | 30 |
National | June 2017 | 250000 | 7 | 6 | 30 |
National | July 2017 | 283500 | 7 | 7 | 30 |
National | January 2018 | 240125 | 4 | 4 | 21 |
National | February 2018 | 258000 | 3 | 6 | 19 |
National | June 2018 | 257500 | 15 | 5 | 18 |
National | July 2018 | 258000 | 9 | 10 | 23 |
National | October 2018 | 277475 | 10 | 9 | 30 |
National | December 2018 | 280350 | 6 | 5 | 20 |
National | January 2019 | 285750 | 4 | 10 | 20 |
National | March 2019 | 268250 | 6 | 9 | 24 |
National | April 2019 | 272000 | 9 | 15 | 31 |
National | July 2019 | 283000 | 9 | 10 | 32 |
National | August 2019 | 278500 | 5 | 4 | 31 |
National | September 2019 | 265000 | 9 | 3 | 24 |
National | October 2019 | 270000 | 11 | 7 | 18 |
National | December 2019 | 234000 | 4 | 2 | 12 |
National | July 2020 | 279900 | 11 | 10 | 12 |
National | September 2016 | 93000 | 10 | 8 | 41 |
National | December 2016 | 128000 | 10 | 11 | 46 |
National | January 2017 | 126250 | 4 | 12 | 49 |
National | February 2017 | 97000 | 7 | 13 | 48 |
National | March 2017 | 131000 | 6 | 11 | 49 |
National | May 2017 | 107500 | 10 | 7 | 42 |
National | June 2017 | 123000 | 7 | 12 | 46 |
National | July 2017 | 95000 | 5 | 5 | 42 |
National | August 2017 | 122125 | 2 | 9 | 47 |
National | November 2017 | 147000 | 7 | 13 | 44 |
National | December 2017 | 140000 | 9 | 11 | 48 |
National | January 2018 | 147000 | 8 | 17 | 51 |
National | February 2018 | 115000 | 7 | 15 | 54 |
National | March 2018 | 128750 | 12 | 15 | 53 |
National | April 2018 | 152000 | 3 | 12 | 55 |
National | May 2018 | 138000 | 8 | 19 | 66 |
National | June 2018 | 146250 | 4 | 5 | 65 |
National | July 2018 | 155000 | 3 | 9 | 62 |
National | August 2018 | 133500 | 9 | 14 | 57 |
National | September 2018 | 115000 | 11 | 12 | 57 |
National | December 2018 | 112750 | 10 | 12 | 49 |
National | January 2019 | 140000 | 8 | 18 | 53 |
National | February 2019 | 124000 | 16 | 12 | 55 |
National | March 2019 | 140750 | 8 | 13 | 54 |
National | April 2019 | 135000 | 13 | 8 | 46 |
National | May 2019 | 147950 | 8 | 12 | 40 |
National | June 2019 | 147000 | 10 | 18 | 47 |
National | July 2019 | 145150 | 10 | 12 | 43 |
National | August 2019 | 140800 | 17 | 11 | 42 |
National | September 2019 | 144451 | 10 | 14 | 43 |
National | October 2019 | 139000 | 13 | 15 | 46 |
National | November 2019 | 149900 | 5 | 11 | 45 |
National | December 2019 | 168000 | 9 | 18 | 52 |
National | January 2020 | 140350 | 16 | 22 | 59 |
National | February 2020 | 163400 | 13 | 21 | 55 |
National | March 2020 | 160000 | 20 | 13 | 51 |
National | April 2020 | 169000 | 7 | 15 | 55 |
National | May 2020 | 163000 | 9 | 19 | 53 |
National | June 2020 | 161500 | 18 | 13 | 48 |
National | July 2020 | 174000 | 9 | 18 | 52 |
National | August 2020 | 139000 | 13 | 15 | 46 |
National | September 2020 | 155500 | 22 | 13 | 36 |
National | October 2020 | 142000 | 17 | 15 | 36 |
National | November 2020 | 154000 | 13 | 18 | 44 |
National | December 2020 | 137400 | 10 | 23 | 48 |
National | January 2021 | 145000 | 8 | 19 | 47 |
National | February 2021 | 139500 | 12 | 23 | 49 |