lmullen · April 15, 2015 18:40
diff --git a/README.md b/README.md
diff --git a/census-1880.csv b/census-1880.csv
diff --git a/census-1890.csv b/census-1890.csv
diff --git a/census-1900.csv b/census-1900.csv
diff --git a/charts.R b/charts.R
 library(ggplot2)
 library(dplyr)
 library(readr)

 # This line loads the data and stores it in a variable. Notice that you can
 # change the file name. These are the files available to you:
 #    census-1890.csv
 #    census-1900.csv
 #    census-1910.csv
 # These all contain state-level information about "nativity," that is,
 # where people were born.
 census <- read_csv("census-1890.csv")

 # These are different ways of seeing what is in the variable you just created.
 glimpse(census)

 # This will create a plot of the absolute numbers: i.e., so many people
 # immigrated from Germany. Notice that you can change the variables and the
 # labels on the plot.
 census %>%
  ggplot(aes(x = STATE, y = born_germany)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "Title",
         x   = "X Label",
         y   = "Y Label")

 # Try transforming the y variable by dividing the number of people born in
 # Germany by the total number of people. That is, we get the percentage of
 # people born in Germany. So ...
 #    y = born_germany / total_population
diff --git a/digital-past-r-lesson.Rproj b/digital-past-r-lesson.Rproj
 Version: 1.0

 RestoreWorkspace: Default
 SaveWorkspace: Default
 AlwaysSaveHistory: Default

 EnableCodeIndexing: Yes
 UseSpacesForTab: Yes
 NumSpacesForTab: 2
 Encoding: UTF-8

 RnwWeave: knitr
 LaTeX: pdfLaTeX

 AutoAppendNewline: Yes
 StripTrailingWhitespace: Yes
diff --git a/hello.R b/hello.R
 # This is a comment. It contains text for humans, not computers. Any line that
 # starts with a # will be a comment.

 # The line below is a command to the computer. Can you guess what it does?
 print("Hello, HIST 390")

 # Notice that the command had two parts:
 #   print()            This is called a "function": it is a verb that does
 #                      something
 #   "Hello, HIST 390"  This is a valeu: it is a noun. The quotation marks
 #                      are important since this is text.

 # Now try running a command that prints your name. Here is a start.
 print("")

 # We can also save values to variables to use them. For example:
 class <- "HIST 390"
 print(class)

 # Now you try it.
 yourname <- ""
 print(yourname)

 # We can do way more complicated things.
 library(historydata)
 plot(us_national_population)
 title("Population of the United States")

 # Three lines and we made a chart! Now on to a real example.
diff --git a/maps.R b/maps.R
 library(maps)
 library(ggplot2)

 # This loads the census data as in the charting example.
 census <- read_csv("census-1890.csv")

 # This joins the map data to the census data. You probably don't want to change
 # it.
 states <- map_data("state")
 census$region <- tolower(census$region)
 states <- states %>%
  left_join(census)


 # This creates a map
 ggplot() +
  geom_map(data = states, map = states,
           aes(x = long,
               y = lat,
               group = group,
               map_id = region,
               fill = born_germany),
           color = "black", size = 0.2) + coord_map() +
  theme_minimal() +
  labs(title = "Title",
       x     = "X Label",
       y     = "Y Label",
       fill  = "Fill label") +
  scale_fill_gradient(low = "white", high = "red")
GISJOIN	YEAR	STATE	region	STATEA	COUNTY	COUNTYA	AREANAME	total_persons	urban_population	white	colored	chinese	indian	born_al	born_ar	born_ca	born_co	born_ct	born_de	born_fl	born_ga	born_il	born_in	born_ia	born_ks	born_ky	born_la	born_me	born_md	born_ma	born_mi	born_ms	born_mn	born_mo	born_ne	born_nv	born_nh	born_nj	born_ny	born_nc	born_oh	born_or	born_pa	born_ri	born_sc	born_tn	born_tx	born_vt	born_va	born_wv	born_wi	born_ak	born_az	born_dakota	born_dc	born_id	born_indian_terr	born_mt	born_nm	born_ut	born_wa	born_wy	born_at_sea	born_state_of_residence	born_africa	born_atlantic_islands	born_austria	born_bohemia	born_british_america	born_central_america	born_china	born_cuba	born_denmark	born_england	born_france	born_germany	born_great_britain	born_holland	born_ireland	born_italy	born_mexico	born_poland	born_portugal	born_russia	born_scotland	born_spain	born_sweden_norway	born_switzerland	born_west_indies
G010	1880	Alabama	Alabama	10			Alabama	1262505	68518	662185	600103	4	213	1014633	863	21	17	266	42	4209	95782	686	785	92	31	2624	1785	171	1889	368	186	13046	43	572	26	0	97	227	1668	23269	1477	1	1199	67	35764	23859	1254	128	24279	72	988	1	4	5	247	2	13	1	5	0	4	2	1	1014633	149	5	121	39	271	1	11	55	69	1004	442	3238	11	27	2966	114	26	47	13	44	426	89	143	173	39
G025	1880	Alaska Territory	Alaska Territory	25			Alaska Territory	33426	0	430	0	0	32996
G045	1880	Arizona Territory	Arizona Territory	45			Arizona Territory	40440	7007	35160	155	1632	3493	130	322	2162	65	130	19	22	169	682	373	320	160	446	123	441	217	564	231	100	32	914	18	112	134	156	1735	90	954	178	812	64	55	308	522	232	349	18	185	1	8166	3	61	80	8	8	1144	1338	24	12	2	8166	3	2	53	7	571	1	1626	2	131	765	276	1110	1	14	1296	104	9330	43	15	25	250	18	151	117	12
G050	1880	Arkansas	Arkansas	50			Arkansas	802525	32020	591531	210666	133	195	39013	436677	168	66	143	64	445	36715	12238	8528	1527	1675	18039	9649	339	1329	374	887	35248	144	29508	107	10	99	270	2290	19727	5254	16	2673	75	15107	87593	10860	189	13292	126	678	0	3	15	155	5	791	8	9	31	9	6	1	436677	17	1	106	68	787	2	121	13	98	1275	369	3620	1	66	2432	132	20	191	2	77	229	6	244	240	8
G060	1880	California	California	60			California	864694	370611	767181	6018	75218	16277	1381	2478	326000	330	3904	473	163	1234	17254	8164	9160	1993	7851	2412	14497	3152	19145	5451	1440	1546	20749	725	2603	3469	3760	43749	1749	17759	3358	15374	1812	969	5609	1981	4681	5906	337	5488	33	369	56	668	211	94	166	297	1131	538	111	40	326000	86	3356	1948	239	18889	188	73548	182	3748	26577	9550	42532	55	694	62962	7537	8648	1026	4705	1013	6465	572	5974	5308	528
G080	1880	Colorado	Colorado	80			Colorado	194327	60961	191126	2435	612	154	452	760	555	26363	1226	232	66	918	12993	5231	7520	4011	3786	416	2619	1047	3638	3654	527	816	12435	932	102	737	1479	15593	846	11759	81	11387	368	203	1961	1043	1568	2441	417	3910	2	13	93	159	24	99	53	9501	241	21	234	5	26363	13	5	453	91	5785	1	601	12	507	10009	825	7012	2	115	8263	335	186	154	12	278	1673	35	2526	551	30
G090	1880	Connecticut	Connecticut	90			Connecticut	622700	260718	610769	11547	129	255	131	10	216	8	398211	190	104	359	813	227	224	76	155	188	2431	834	22643	426	52	140	164	20	2	2047	4067	39172	544	1272	14	3223	8325	299	87	65	3476	1722	35	365	0	4	7	288	2	4	2	10	36	5	1	12	398211	14	79	287	124	16444	11	134	35	428	15860	1079	15627	28	122	70638	879	10	225	165	65	4157	47	2254	680	161
G095	1880	Dakota Territory	Dakota Territory	95			Dakota Territory	135177	9901	133147	401	238	1391	53	60	101	201	527	61	11	70	4528	1669	7823	241	519	90	1494	327	1292	2509	93	8766	1520	633	24	559	402	9135	101	3806	49	4305	159	62	216	108	1315	575	69	11685	0	5	17796	72	25	19	84	35	104	6	74	4	17796	4	53	131	1337	10678	2	237	40	1447	2516	272	5925	0	140	4104	71	17	219	4	6493	940	26	16422	386	14
G100	1880	Delaware	Delaware	100			Delaware	146608	48989	120160	26442	1	5	7	5	22	1	217	110643	15	37	79	55	20	6	45	20	131	9562	264	38	7	15	83	2	9	71	2238	1321	69	96	2	11059	37	64	17	13	76	642	9	53	0	0	1	88	0	0	0	1	0	0	0	0	110643	15	1	22	2	246	0	2	19	36	1484	138	1179	1	10	5791	43	1	8	1	9	285	2	77	48	8
G110	1880	District Of Columbia	District Of Columbia	110			District of Columbia	177624	159871	118006	59596	17	5	300	71	145	18	675	346	122	449	540	533	176	69	509	317	855	24562	1693	338	236	97	316	36	6	564	1107	5952	753	1872	21	5587	209	508	400	134	525	29009	451	227	2	5	6	80702	4	8	0	14	9	10	12	2	80702	9	6	75	16	452	3	24	22	45	1704	293	5055	1	71	7840	244	12	116	13	67	495	35	70	196	84
G120	1880	Florida	Florida	120			Florida	269493	26947	142605	126690	18	180	12023	148	26	14	500	70	173481	32601	538	339	134	64	668	578	502	604	852	215	757	52	204	16	1	248	369	2375	6297	685	13	855	126	18522	833	190	199	3329	38	305	0	5	2	738	1	5	2	4	1	3	47	5	173481	78	291	46	3	446	5	15	2170	259	889	221	978	8	19	652	77	44	26	41	32	216	91	310	43	2793
G130	1880	Georgia	Georgia	130			Georgia	1542180	145090	816906	725133	17	124	17009	545	50	21	531	46	5840	1395214	224	242	51	31	1136	516	292	1459	625	78	1516	36	287	6	0	157	469	2570	24156	514	6	1000	252	50195	10717	584	187	14606	29	167	0	6	5	207	1	10	1	9	2	1	0	10	1395214	129	0	71	33	348	2	24	33	53	1196	295	2956	21	36	4148	82	13	62	6	33	395	44	161	107	77
G165	1880	Idaho Territory	Idaho Territory	165			Idaho Territory	32610	0	29013	53	3379	165	63	279	535	86	106	14	4	88	1142	576	879	308	437	50	381	109	251	199	57	127	1393	153	84	67	98	1269	99	1044	999	804	17	29	309	70	153	336	36	368	0	5	38	22	5992	6	82	7	3205	201	59	0	5992	14	1	18	5	584	2	3366	3	586	2235	142	750	9	10	981	35	50	17	10	17	253	3	599	225	5
G170	1880	Illinois	Illinois	170			Illinois	3077871	940504	3031151	46368	212	140	3319	2470	969	250	9417	1596	164	1947	1709520	91388	16555	4350	61920	2472	7451	12396	20481	12985	3066	2062	39493	1004	82	6582	14636	120199	9279	136884	474	89467	2100	2122	37400	1302	14593	27904	2718	21757	0	17	91	860	20	183	63	82	128	25	37	15	1709520	57	431	2608	13408	34043	8	299	69	6029	60012	8524	235786	202	5012	117343	1764	67	6962	424	1276	15645	243	59385	8881	167
G180	1880	Indiana	Indiana	180			Indiana	1978301	386211	1938798	39228	29	246	892	563	267	75	1837	1593	101	1284	27201	1354565	4590	2136	73928	874	1165	7429	3195	9188	682	537	5688	323	19	879	5448	26506	20884	186391	210	51234	377	1627	10969	431	2211	24538	1988	1784	0	8	25	307	26	36	8	26	47	11	17	3	1354565	11	3	511	306	5569	12	41	11	583	12020	4473	80756	16	1368	25741	198	28	917	39	320	2731	24	3303	3695	41
G190	1880	Iowa	Iowa	190			Iowa	1624615	247427	1614600	9516	33	466	378	532	746	403	5062	939	80	388	102820	59278	737306	3722	12920	515	5783	6169	9378	10616	591	6130	20677	3005	107	4743	6357	82690	3990	120495	198	77357	907	531	5372	402	12297	15531	2521	40380	1	14	650	259	76	54	72	27	394	44	50	8	737306	17	15	1473	10554	21097	5	37	50	6901	25550	2675	88268	91	4743	44061	122	18	403	22	535	6885	38	39145	4587	79
G200	1880	Kansas	Kansas	200			Kansas	996096	104956	952155	43107	19	815	1605	3084	683	634	2791	567	103	1579	106992	77096	55972	233066	32978	1782	3538	4431	5395	13012	3452	2784	60228	4350	82	2088	4631	42779	5709	93396	198	59236	612	899	15649	4057	4914	15336	3644	15016	0	12	132	300	28	685	150	106	126	48	51	4	233066	34	11	1285	2468	12536	53	35	21	1838	16260	1821	28034	11	749	14993	167	58	1200	17	8032	3788	24	12565	2668	41
G210	1880	Kentucky	Kentucky	210			Kentucky	1648690	249923	1377179	271451	10	50	1854	1136	127	20	342	159	90	2171	5675	18445	810	341	1402112	1244	264	2257	797	397	1983	85	5417	39	4	181	710	3745	9738	27115	19	6032	85	1530	54386	741	257	36515	1736	318	2	2	10	213	6	22	9	8	6	7	2	9	1402112	10	8	142	43	1070	3	15	6	73	4494	1512	30413	5	262	18256	370	22	124	2	63	982	16	116	1130	18
G220	1880	Louisiana	Louisiana	220			Louisianna	939946	239390	454954	483655	489	848	23263	4298	87	13	227	105	1572	15172	699	663	104	63	6564	728322	387	4875	641	213	38421	47	2962	8	4	109	249	3038	6202	1576	11	1394	69	9495	5382	7322	135	21321	157	101	0	47	4	390	21	43	2	6	8	3	2	3	728322	270	11	275	24	726	18	449	669	285	2653	9992	17475	8	170	13807	2527	424	164	141	158	659	987	348	674	568
G230	1880	Maine	Maine	230			Maine	648936	146608	646852	1451	8	625	13	17	244	22	517	23	50	65	196	79	95	35	42	58	563015	158	10066	118	22	100	57	18	11	9458	212	1835	48	219	16	522	526	70	30	18	1482	276	8	183	0	1	4	89	3	4	3	1	12	10	1	1	563015	5	29	19	1	37114	0	23	41	273	3999	128	688	5	16	13421	90	0	24	62	54	1397	32	1087	31	86
G240	1880	Maryland	Maryland	240			Maryland	934943	375843	724693	210230	5	15	216	54	143	12	715	8207	128	472	552	406	152	47	422	395	506	762641	1337	220	177	40	372	24	10	177	2354	5733	1232	1942	6	26986	229	663	258	121	340	26754	2397	877	0	3	14	4768	0	9	1	5	2	5	4	9	762641	28	29	401	1169	988	1	11	129	128	6155	620	45481	13	362	21865	477	20	642	29	213	2645	70	285	338	209
G250	1880	Massachusetts	Massachusetts	250			Massachusetts	1783085	1331580	1763782	18697	237	369	143	24	745	105	20574	288	185	557	1747	430	541	146	502	465	68226	1838	1088565	940	120	310	371	57	26	54088	3137	35628	893	2160	43	4775	17258	708	268	123	26943	4766	95	819	1	25	6	680	7	11	5	42	182	12	6	8	1088565	124	2421	308	279	119302	27	314	158	576	48136	2212	16872	89	586	226700	2116	21	681	1161	462	12507	211	5395	604	676
G260	1880	Michigan	Michigan	260			Michigan	1636937	405412	1614560	15100	28	7249	231	95	397	90	6333	642	64	213	9699	18216	2682	892	1732	259	5079	1433	9591	803306	243	859	1416	294	28	3300	7903	229657	1040	77053	44	36064	974	213	764	237	12588	3069	272	10775	0	3	56	215	0	52	16	175	70	66	17	12	803306	17	22	1025	1789	148866	27	163	19	3513	44032	3203	89085	64	17177	43413	555	34	5421	18	1560	10731	39	12932	2474	107
G270	1880	Minnesota	Minnesota	270			Minnesota	780773	148758	776884	1564	25	2300	168	90	183	51	2711	189	35	131	16199	8342	10916	330	2151	220	12511	1001	7223	5539	197	302371	2390	229	14	3593	1862	47006	373	15560	30	15032	729	108	481	97	7869	1901	413	44178	0	1	336	156	8	46	39	20	30	16	18	4	302371	14	8	2607	7759	29631	10	32	6	6071	9598	1351	66592	47	1581	25942	124	6	2218	2	2272	2964	19	101697	2828	32
G280	1880	Mississippi	Mississippi	280			Mississippi	1131597	34581	479398	650291	51	1857	75558	3852	52	14	138	68	1000	29159	890	659	103	33	7844	13809	133	2464	195	68	863185	32	2095	11	1	59	144	1187	23128	1023	8	1071	39	31157	31820	1933	89	28816	212	64	2	0	1	240	0	19	5	4	2	0	2	0	863185	77	0	126	12	309	3	55	11	99	1059	507	2556	5	27	2753	260	39	79	6	76	303	99	358	144	37
G290	1880	Missouri	Missouri	290			Missouri	2168380	545993	2022826	145350	91	113	5358	13752	1222	521	2234	936	239	4030	103290	60094	30564	13305	102799	4699	2108	7421	4765	5351	4507	1347	1268641	2203	95	1269	3497	32126	15925	78938	174	37220	505	2637	72454	4797	2575	54058	2687	6730	0	11	96	717	48	404	94	81	192	35	42	9	1268641	38	9	1655	3342	8685	11	106	58	970	17564	4642	106800	44	1122	48898	1074	84	801	16	340	3641	135	3547	6064	109
G305	1880	Montana Territory	Montana Territory	305			Montana Territory	39159	6987	35385	346	1765	1663	61	45	264	160	135	25	15	98	1548	769	1188	361	712	106	603	254	523	485	63	382	2493	180	55	140	234	2470	146	1841	149	1703	64	77	335	92	260	475	57	783	0	10	172	52	106	9	7225	23	554	65	71	0	7225	3	0	60	25	2481	1	1756	2	190	1495	161	1705	2	24	2408	64	28	32	6	25	324	9	454	171	4
G310	1880	Nebraska	Nebraska	310			Nebraska	452402	61307	449764	2385	18	235	208	270	305	225	1928	267	34	247	45583	20403	34489	2474	4034	317	2133	1704	3524	7853	367	2277	10503	95790	45	1148	2318	29341	809	31800	59	25079	427	160	1560	416	3209	4425	1042	16931	0	8	397	170	24	110	37	113	208	22	194	1	95790	11	17	2346	8858	8622	12	21	6	4511	8831	749	31125	19	753	10133	62	14	1128	7	3281	2230	11	12174	1579	29
G320	1880	Nevada	Nevada	320			Nevada	62266	19353	53556	488	5419	2803	81	108	4004	82	294	41	18	76	1296	509	704	115	578	176	1198	247	1037	569	55	68	1176	58	13732	231	344	3287	97	1603	159	1575	95	52	268	60	414	486	45	599	0	10	4	45	71	6	40	41	800	20	38	1	13732	5	12	162	15	3147	18	5402	3	350	4461	393	2213	15	21	5191	1560	220	64	207	41	671	32	436	709	24
G330	1880	New Hampshire	New Hampshire	330			New Hampshire	346991	104105	346229	685	14	63	20	4	102	13	842	14	18	41	326	47	122	32	47	25	14130	165	20561	142	112	95	65	10	4	242757	178	3739	38	271	1	403	711	35	34	9	15040	213	10	146	0	0	1	46	6	3	3	3	98	13	1	1	242757	3	0	44	10	27142	48	20	4	30	3518	98	789	11	11	13052	32	3	11	19	7	1102	17	210	27	7
G340	1880	New Jersey	New Jersey	340			New Jersey	1131116	615311	1092017	38853	172	74	150	26	236	55	6071	4113	191	493	1140	427	272	104	483	388	1961	4556	6583	627	146	109	442	34	13	1121	725614	94692	650	2409	12	46754	1075	660	240	118	1337	4789	107	426	0	3	11	691	2	10	2	39	14	3	3	14	725614	41	26	864	429	3536	18	196	146	1264	32148	3739	64935	22	4281	93079	1547	65	748	23	301	7633	114	1851	3040	375
G355	1880	New Mexico Territory	New Mexico Territory	355			New Mexico Territory	119565	6635	108721	1015	57	9772	79	182	1131	455	133	17	14	80	607	460	292	337	429	92	117	146	237	132	80	72	883	34	6	49	81	666	52	826	9	693	30	45	252	1027	111	301	21	135	0	52	3	24	5	24	16	101046	18	2	11	0	101046	1	0	15	13	280	0	52	13	23	367	167	729	0	6	795	73	5173	22	8	16	110	12	56	54	7
G360	1880	New York	New York	360			New York	5082871	2868529	5016022	65104	926	819	793	106	1551	239	38662	1247	645	2239	6504	2040	1928	552	1720	2211	7206	7842	42501	7700	526	835	1886	199	52	7380	47266	3556394	2274	11599	76	56155	6252	2696	952	550	31271	12586	293	3683	4	27	36	2259	17	52	30	113	260	31	17	35	3556394	156	137	6530	8748	84182	65	1015	2227	3145	123585	20321	355913	263	8399	499445	15113	237	11999	295	5438	28066	1216	13349	10721	1734
G370	1880	North Carolina	North Carolina	370			North Carolina	1399750	55116	867242	531277	1	1230	642	186	26	6	190	67	185	3338	143	224	29	37	365	129	139	630	336	38	531	8	135	5	2	56	248	889	1344553	257	5	891	77	16121	5194	224	154	19486	154	174	0	1	2	98	2	9	1	1	3	5	8	4	1344553	24	3	10	14	425	7	10	11	58	750	59	950	5	23	611	42	1	18	12	11	408	8	34	67	45
G390	1880	Ohio	Ohio	390			Ohio	3198062	1030769	3117920	79900	112	130	727	294	487	87	9003	1671	111	809	10013	27202	4609	1444	32492	1235	2386	20091	10854	11403	1043	614	3873	342	32	2626	10487	64138	3971	2361437	63	138163	889	968	3770	384	7064	51647	12812	2727	0	19	25	730	21	89	33	68	112	29	21	4	2361437	40	203	1681	6232	16146	10	157	43	642	55318	10136	192597	76	2455	78927	1064	43	2039	38	610	8946	81	1364	11989	191
G410	1880	Oregon	Oregon	410			Oregon	174768	25852	163075	487	9512	1694	238	1058	6011	206	465	74	19	187	7804	5055	6969	1505	2754	158	1453	478	1291	1281	158	828	10754	637	256	345	457	5443	645	6201	67942	3342	111	122	2469	261	644	1835	95	2118	0	13	98	59	355	32	115	20	182	1650	67	5	67942	6	8	317	109	3019	8	9472	5	385	3061	514	5034	64	127	3659	167	40	92	59	379	1129	19	1557	730	25
G420	1880	Pennsylvania	Pennsylvania	420			Pennsylvania	4282891	1783378	4197016	85535	156	184	306	147	552	98	6162	19034	240	730	4129	2591	1814	562	1829	741	3345	38826	10010	2422	294	512	1624	180	38	2026	44843	100490	1427	27502	48	3385693	1645	1159	793	251	3601	20189	5274	1317	0	21	102	2270	19	38	13	43	32	41	26	13	3385693	71	35	2317	1058	12376	29	182	335	945	109549	7949	168426	76	1068	236505	2794	95	3790	175	1040	20735	168	7956	6343	582
G440	1880	Rhode Island	Rhode Island	440			Rhode Island	276531	226618	269939	6488	27	77	21	7	104	7	7825	116	63	123	287	55	62	30	76	62	2846	863	23320	109	29	63	47	15	1	1725	854	6416	170	198	10	1280	152487	140	22	15	1543	1076	30	174	1	1	3	227	1	1	2	1	25	3	1	1	152487	11	185	28	29	18306	10	40	35	55	12667	312	1966	3	51	35281	313	2	97	210	25	3039	65	832	122	109
G450	1880	South Carolina	South Carolina	450			South Carolina	995577	74539	391105	604332	9	131	891	113	11	3	210	21	536	7641	49	37	12	9	194	118	135	437	350	24	430	5	62	2	1	47	175	1070	17297	122	4	429	64	952395	547	110	53	4058	12	136	0	1	2	72	0	1	1	1	1	0	2	0	952395	123	0	46	31	141	1	14	20	60	680	131	2846	4	16	2626	84	1	128	5	29	354	48	68	73	57
G470	1880	Tennessee	Tennessee	470			Tennessee	1542359	115984	1138831	403151	25	352	22200	3867	93	18	253	54	276	19481	2968	2840	370	419	24868	1560	194	1463	519	625	19632	157	3776	21	4	130	377	3082	41918	5035	42	3311	87	11698	1313552	1450	262	38059	165	374	0	9	7	278	3	63	8	8	9	29	21	22	1313552	39	1	111	30	545	7	31	11	98	2258	523	3983	18	66	5975	443	17	212	4	70	516	19	276	1026	24
G480	1880	Texas	Texas	480			Texas	1591749	146795	1197237	393384	136	992	93625	41365	873	182	723	237	3601	61407	19643	9094	2772	2046	34121	37972	867	3168	1568	2148	62835	606	43168	220	30	349	1024	7909	23277	7949	104	5568	193	22124	83158	870705	557	27874	405	1317	0	73	51	331	31	1202	29	546	27	21	24	14	870705	274	10	3474	2669	2472	14	147	71	489	6749	2653	35347	26	228	8103	539	43161	995	74	279	1659	240	2173	1203	154
G495	1880	Utah Territory	Utah Territory	495			Utah Territory	143963	33665	142423	232	501	807	156	51	607	77	238	63	14	116	2230	475	1602	118	409	55	375	116	645	412	146	71	1224	381	349	150	372	2715	218	791	44	1628	53	70	402	122	328	442	17	275	0	58	10	30	258	5	84	13	81716	7	231	0	81716	106	40	22	3	1036	1	502	92	7791	22044	129	885	13	141	1321	138	17	16	4	54	3201	76	4964	1040	7
G500	1880	Vermont	Vermont	500			Vermont	332286	33367	331218	1057	0	11	8	4	74	20	1211	15	13	28	286	64	122	29	28	37	1361	135	8295	238	33	75	50	12	8	11780	262	13733	38	348	5	372	320	24	18	26	251780	137	4	271	1	3	1	33	0	3	12	4	4	1	0	1	251780	6	7	5	4	24620	31	1	3	35	2767	138	396	4	10	11657	30	4	5	4	8	1006	10	78	45	7
G510	1880	Virginia	Virginia	510			Virginia	1512565	189079	880858	631616	6	85	477	110	53	12	418	480	130	695	322	330	139	79	2087	392	346	7942	878	255	420	38	474	10	6	234	1349	5382	22505	1275	23	5541	118	898	4967	332	213	1435124	1641	179	0	4	6	1925	1	17	3	28	4	6	1	0	1435124	8	5	73	21	585	14	13	18	60	2916	289	3759	6	125	4835	281	10	59	22	39	893	34	78	174	73
G535	1880	Washington Territory	Washington Territory	535			Washington Territory	75116	7121	67199	325	3187	4405	73	403	2417	191	228	34	13	93	3228	2027	2846	801	879	82	1882	219	805	745	61	632	3160	363	112	214	229	2981	233	2727	6583	1823	99	43	606	137	312	612	74	1187	0	27	96	52	190	80	86	3	234	19359	32	0	19359	5	2	106	53	2857	2	3166	6	296	1846	245	2198	4	53	2243	71	19	37	26	205	628	10	1228	174	27
G540	1880	West Virginia	West Virginia	540			West Virginia	618457	54050	592537	25886	5	29	51	58	41	13	179	122	23	97	579	759	320	148	4361	106	186	8114	450	119	108	42	589	22	3	94	470	1565	1208	27535	0	18841	40	127	369	75	134	135599	397267	77	0	3	2	256	0	3	5	8	12	3	8	1	397267	2	2	62	34	295	0	9	1	38	2420	230	7029	2	19	6459	48	1	18	0	19	622	3	24	810	6
G550	1880	Wisconsin	Wisconsin	550			Wisconsin	1315497	317204	1309618	2702	16	3161	163	63	233	121	4235	267	49	197	16471	6207	5018	453	1410	231	7861	955	8274	6933	159	5672	1785	351	38	3778	2907	86588	296	20512	65	19099	913	139	693	114	12554	1519	165	693177	0	7	116	126	15	12	21	14	69	9	11	7	693177	29	22	4601	13848	28965	15	60	30	8797	30268	2412	184328	112	5698	41907	253	30	5263	13	312	5770	21	57487	6283	62
G565	1880	Wyoming Territory	Wyoming Territory	565			Wyoming Territory	20789	6152	19437	298	914	140	26	88	116	157	93	26	17	48	1056	492	700	365	305	41	229	186	396	236	40	71	1163	373	33	107	134	1599	95	1174	36	1169	51	21	161	137	178	257	38	338	0	10	43	53	36	16	47	33	451	2	2496	0	2496	7	0	23	10	542	0	913	1	188	1234	61	801	1	16	1093	15	40	14	1	19	432	3	323	49	6
	library(ggplot2)
	library(dplyr)
	library(readr)

	# This line loads the data and stores it in a variable. Notice that you can
	# change the file name. These are the files available to you:
	# census-1890.csv
	# census-1900.csv
	# census-1910.csv
	# These all contain state-level information about "nativity," that is,
	# where people were born.
	census <- read_csv("census-1890.csv")

	# These are different ways of seeing what is in the variable you just created.
	glimpse(census)

	# This will create a plot of the absolute numbers: i.e., so many people
	# immigrated from Germany. Notice that you can change the variables and the
	# labels on the plot.
	census %>%
	ggplot(aes(x = STATE, y = born_germany)) +
	geom_bar(stat = "identity") +
	coord_flip() +
	labs(title = "Title",
	x = "X Label",
	y = "Y Label")

	# Try transforming the y variable by dividing the number of people born in
	# Germany by the total number of people. That is, we get the percentage of
	# people born in Germany. So ...
	# y = born_germany / total_population
	Version: 1.0

	RestoreWorkspace: Default
	SaveWorkspace: Default
	AlwaysSaveHistory: Default

	EnableCodeIndexing: Yes
	UseSpacesForTab: Yes
	NumSpacesForTab: 2
	Encoding: UTF-8

	RnwWeave: knitr
	LaTeX: pdfLaTeX

	AutoAppendNewline: Yes
	StripTrailingWhitespace: Yes
	# This is a comment. It contains text for humans, not computers. Any line that
	# starts with a # will be a comment.

	# The line below is a command to the computer. Can you guess what it does?
	print("Hello, HIST 390")

	# Notice that the command had two parts:
	# print() This is called a "function": it is a verb that does
	# something
	# "Hello, HIST 390" This is a valeu: it is a noun. The quotation marks
	# are important since this is text.

	# Now try running a command that prints your name. Here is a start.
	print("")

	# We can also save values to variables to use them. For example:
	class <- "HIST 390"
	print(class)

	# Now you try it.
	yourname <- ""
	print(yourname)

	# We can do way more complicated things.
	library(historydata)
	plot(us_national_population)
	title("Population of the United States")

	# Three lines and we made a chart! Now on to a real example.
	library(maps)
	library(ggplot2)

	# This loads the census data as in the charting example.
	census <- read_csv("census-1890.csv")

	# This joins the map data to the census data. You probably don't want to change
	# it.
	states <- map_data("state")
	census$region <- tolower(census$region)
	states <- states %>%
	left_join(census)


	# This creates a map
	ggplot() +
	geom_map(data = states, map = states,
	aes(x = long,
	y = lat,
	group = group,
	map_id = region,
	fill = born_germany),
	color = "black", size = 0.2) + coord_map() +
	theme_minimal() +
	labs(title = "Title",
	x = "X Label",
	y = "Y Label",
	fill = "Fill label") +
	scale_fill_gradient(low = "white", high = "red")