Gallo Exercise 9

.gitignore

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Exercise09.Rproj

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Exercise9_Gallo_Script.R

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+# Hayden Gallo
+# Intro to Biocomputing
+# Exercise 09
+
+library(ggplot2)
+
+# Problem 1
+#1. Find some data on two variables that you would expect to be related to each other.
+#These data can come from your own research, your daily life, or the internet.
+#Enter those data into a text file or Excel and then save a text file, and write a script
+#that loads this text file and produces a scatter plot of those two variables that includes a trend line.
+
+baseball_data <- read.table('baseball_data.txt',header = TRUE, sep = '\t')
+
+ggplot(data = baseball_data, aes(x = H, y = R)) + geom_point() + geom_smooth(se = FALSE, method ='lm') +
+        xlab('Hits') + ylab('Runs') + ggtitle('Hits vs. Runs for Professional Baseball Teams')
+
+
+# Problem 2
+# 2. Given the data in “data.txt”. Write a script that generates two figures that sumamrize the data.
+# First, show a barplot of the means of the four populations. Second, show a scatter plot of all of the observations.
+# You may want to “jitter” the points (geom_jitter()) to make it easier to see all of the observations
+# within a population in your scatter plot. Alternatively, you could also try setting the alpha argument
+# in geom_scatterplot() to 0.1. Answer the following questions as a comment in your R script - Do the bar
+# and scatter plots tell you different stories? Why?
+
+data <- read.table('data.txt', header = TRUE, sep = ',')
+
+data.mean <- aggregate(observations ~ region, data, mean)
+
+ggplot(data.mean, aes(x = region, y = observations)) + geom_bar(stat = 'identity') + ggtitle('Mean of Each of the Four Populations')
+
+ggplot(data = data, aes(x = region, y = observations)) + geom_point() + ggtitle('Region vs Observation Value') + geom_jitter()
+
+# Yes, the bar and scatter plots definitely tell different stories. The bar plot shows that the averages
+# of the populations are very close to one another, but based on the scatterplot, the spread of the data
+# for each of the populations is very different, so it shows that the populations are made up of very different
+# observation values but just happen to have means close to one another.

baseball_data.txt

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+Tm	Bat	BatAge	R/G	G	PA	AB	R	H	2B	3B	HR	RBI	SB	CS	BB	SO	BA	OBP	SLG	OPS	OPS+	TB	GDP	HBP	SH	SF	IBB	LOB
+Arizona Diamondbacks	57	26.5	4.33	162	6027	5351	702	1232	262	24	173	658	104	29	531	1341	0.23	0.304	0.385	0.689	95	2061	97	60	31	50	14	1039
+Atlanta Braves	53	27.5	4.87	162	6082	5509	789	1394	298	11	243	753	87	31	470	1498	0.253	0.317	0.443	0.761	111	2443	103	66	1	36	13	1030
+Baltimore Orioles	58	27	4.16	162	6049	5429	674	1281	275	25	171	639	95	31	476	1390	0.236	0.305	0.39	0.695	97	2119	95	83	12	43	10	1095
+Boston Red Sox	54	28.8	4.54	162	6144	5539	735	1427	352	12	155	704	52	20	478	1373	0.258	0.321	0.409	0.731	102	2268	131	63	12	50	23	1133
+Chicago Cubs	64	27.9	4.06	162	6072	5425	657	1293	265	31	159	620	111	37	507	1448	0.238	0.311	0.387	0.698	96	2097	130	84	19	36	16	1100
+Chicago White Sox	44	29.3	4.23	162	6123	5611	686	1435	272	9	149	654	58	10	388	1269	0.256	0.31	0.387	0.698	97	2172	127	73	16	35	9	1117
+Cincinnati Reds	66	29.4	4	162	5978	5380	648	1264	235	18	156	618	58	33	452	1430	0.235	0.304	0.372	0.676	83	2003	127	92	12	33	6	1020
+Cleveland Guardians	50	25.9	4.31	162	6163	5558	698	1410	273	31	127	662	119	27	450	1122	0.254	0.316	0.383	0.699	102	2126	115	81	22	52	36	1156
+Colorado Rockies	43	29.1	4.31	162	6105	5540	698	1408	280	34	149	669	45	20	453	1330	0.254	0.315	0.398	0.713	90	2203	139	61	10	40	10	1113
+Detroit Tigers	53	27.9	3.44	162	5870	5378	557	1240	235	27	110	530	47	24	380	1413	0.231	0.286	0.346	0.632	84	1859	108	58	10	44	8	1015
+Houston Astros	45	29.3	4.55	162	6054	5409	737	1341	284	13	214	715	83	22	528	1179	0.248	0.319	0.424	0.743	111	2293	118	60	9	42	18	1068
+Kansas City Royals	55	27.1	3.95	162	6010	5437	640	1327	247	38	138	613	104	34	460	1287	0.244	0.306	0.38	0.686	93	2064	101	48	20	44	7	1091
+Los Angeles Angels	66	27.9	3.85	162	5977	5423	623	1265	219	31	190	600	77	27	449	1539	0.233	0.297	0.39	0.687	94	2116	95	54	25	25	28	1050
+Los Angeles Dodgers	51	29.6	5.23	162	6247	5526	847	1418	325	31	212	812	98	18	607	1374	0.257	0.333	0.442	0.775	112	2441	85	56	3	53	22	1159
+Miami Marlins	56	28.8	3.62	162	5949	5395	586	1241	248	20	144	554	122	29	436	1429	0.23	0.294	0.363	0.658	86	1961	120	70	4	36	6	1045
+Milwaukee Brewers	51	29.1	4.48	162	6122	5417	725	1271	251	17	219	703	96	30	577	1464	0.235	0.315	0.409	0.724	105	2213	117	80	11	37	25	1102
+Minnesota Twins	61	26.9	4.3	162	6113	5476	696	1356	269	18	178	668	38	17	518	1353	0.248	0.317	0.401	0.718	107	2195	133	62	10	46	11	1126
+New York Mets	61	29.7	4.77	162	6176	5489	772	1422	272	27	171	735	62	22	510	1217	0.259	0.332	0.412	0.744	113	2261	122	112	20	44	25	1158
+New York Yankees	54	30.2	4.98	162	6172	5422	807	1308	225	8	254	764	102	33	620	1391	0.241	0.325	0.426	0.751	113	2311	121	70	14	41	36	1093
+Oakland Athletics	64	28.3	3.51	162	5863	5314	568	1147	249	15	137	537	78	23	433	1389	0.216	0.281	0.346	0.626	82	1837	109	59	22	33	7	969
+Philadelphia Phillies	56	28.1	4.61	162	6077	5496	747	1392	255	29	205	719	105	28	478	1363	0.253	0.317	0.422	0.739	107	2320	116	52	6	44	15	1075
+Pittsburgh Pirates	68	26.3	3.65	162	5912	5331	591	1186	221	29	158	555	89	32	476	1497	0.222	0.291	0.364	0.655	84	1939	96	54	19	32	14	1016
+San Diego Padres	55	28.2	4.35	162	6175	5468	705	1317	275	18	153	682	49	22	574	1327	0.241	0.318	0.382	0.7	104	2087	95	65	17	46	24	1174
+Seattle Mariners	59	27.5	4.26	162	6117	5375	690	1236	229	19	197	663	83	27	596	1397	0.23	0.315	0.39	0.704	106	2094	120	89	9	45	17	1129
+San Francisco Giants	66	30	4.42	162	6117	5392	716	1261	255	18	183	683	64	16	571	1462	0.234	0.315	0.39	0.705	98	2101	109	95	6	53	14	1115
+St. Louis Cardinals	51	28.8	4.77	162	6165	5496	772	1386	290	21	197	739	95	25	537	1226	0.252	0.325	0.42	0.745	114	2309	112	80	5	45	11	1132
+Tampa Bay Rays	61	27	4.11	162	6008	5412	666	1294	296	17	139	634	95	37	500	1395	0.239	0.309	0.377	0.686	100	2041	93	57	7	31	13	1074
+Texas Rangers	55	28	4.36	162	6029	5478	707	1308	224	20	198	670	128	41	456	1446	0.239	0.301	0.395	0.696	98	2166	82	47	10	38	12	1007
+Toronto Blue Jays	51	27.1	4.78	162	6158	5555	775	1464	307	12	200	756	67	35	500	1242	0.264	0.329	0.431	0.76	116	2395	136	55	8	33	13	1111
+Washington Nationals	55	28.7	3.72	162	5998	5434	603	1351	252	20	136	579	75	31	442	1221	0.249	0.31	0.377	0.688	99	2051	140	60	20	37	12	1099
+League Average	50	28.2	4.28	162	6068	5449	694	1322	265	21	174	663	83	27	495	1360	0.243	0.312	0.395	0.706	100	2152	113	68	13	41	16	1087