How to edit a ggplot

[TJ37043]

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

[jrkrideau]

What are you trying to do with this data? It looks like you have 64 categories of data. How much data overall if your small sample has 92 data points?

I just cannot see that a histogram of all those categories is going to be interpretable in a simple histogram. It might make sense to facet by Region but there likely are better ways to graph the data.

Re the sample data you supplied, it is appreciated but a better way to supply it to use the dput() function.
See ?dput. If you have a very large data set then something like head(dput(myfile), 100) will usually supply enough data for us to work with. However in this case we probably need a random sample rather than data from just one Region.

As a very simple step---not that will cure your problem---just get rid of the legend and see what you get

ggplot(Metro, aes(x=MedianSalePrice, fill=Region)) +geom_histogram(binwidth = 50)+
  theme(legend.position = "none")

[smouksassi]

Seems a geo-facet might help but first what questions or comparisons you are after?

[TJ37043]

Thank you for your assistance. I have 6000 data points; I did not post them. However, I changed the font and put the graph in a second window that seemed to work.