5 📚 Summarizing Data

Let’s do some more practice. Download the dca_weather dataset, which gives the minimum and maximum temperatures in Arlington, VA, and also the amount of rainfall each day. This data is taken from NOAA’s Website.

TABLE 5.1: Weather Data for DCA Airport from 1/1/2022 to 6/19/2022
STATION	NAME	year	month	day	TAVG	TMAX	TMIN	AWND	PRCP	SNOW	SNWD
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	1	57	66	53	4.70	0.44	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	2	60	63	46	9.62	0.13	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	3	38	46	25	14.54	0.99	6.9	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	4	30	34	23	5.82	0.00	0.0	7.1
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	5	34	41	27	8.95	0.00	0.0	3.9
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	6	40	44	36	7.61	0.00	0.0	2.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	7	32	36	25	12.30	0.19	2.6	3.1
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	8	27	33	22	7.61	0.00	0.0	1.2
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	9	35	47	30	10.74	0.58	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	10	38	44	28	14.54	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	11	27	30	22	9.84	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	12	32	47	23	9.62	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	13	39	52	31	2.91	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	14	43	50	34	14.76	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	15	29	34	20	12.97	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	16	22	40	17	12.75	0.90	2.6	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	17	37	42	34	17.22	0.02	0.0	1.2
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	18	37	42	30	9.84	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	19	39	55	30	11.41	0.03	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	20	42	46	27	10.51	0.28	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	21	25	27	19	13.42	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	22	24	34	16	7.38	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	23	31	40	24	5.59	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	24	36	41	31	7.83	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	25	39	51	30	9.62	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	26	30	35	24	10.51	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	27	27	36	20	6.26	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	28	34	41	31	6.49	0.12	0.2	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	29	28	33	22	19.69	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	30	24	32	18	6.04	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	1	31	30	39	25	7.61	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	1	32	44	25	4.25	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	2	36	49	29	4.47	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	3	44	57	40	5.37	0.50	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	4	50	62	35	13.20	1.08	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	5	33	35	26	14.99	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	6	29	39	23	4.92	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	7	36	44	32	5.14	0.07	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	8	40	50	31	6.26	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	9	40	54	30	6.93	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	10	48	62	37	7.61	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	11	48	67	33	8.95	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	12	54	62	44	10.51	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	13	39	44	28	10.51	0.05	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	14	29	33	25	10.51	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	15	30	39	21	6.93	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	16	37	54	28	8.50	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	17	54	70	47	14.99	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	18	54	68	31	18.34	0.01	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	19	37	51	26	14.99	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	20	31	43	23	9.17	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	21	44	66	32	7.61	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	22	53	66	42	11.41	0.07	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	23	65	77	42	14.32	0.01	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	24	40	42	33	10.07	0.35	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	25	39	59	33	12.08	0.19	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	26	38	44	33	9.17	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	27	43	56	35	6.49	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	2	28	45	51	36	8.95	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	1	41	55	32	7.83	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	2	51	63	40	5.14	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	3	51	57	35	14.32	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	4	38	48	28	8.05	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	5	45	61	36	6.93	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	6	62	78	50	13.65	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	7	70	80	54	18.12	0.03	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	8	53	54	44	11.86	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	9	44	47	40	8.50	0.77	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	10	44	53	36	5.82	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	11	49	63	38	8.50	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	12	41	50	24	16.11	0.58	0.9	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	13	29	44	21	10.96	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	14	44	61	32	8.05	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	15	53	71	42	7.16	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	16	58	73	45	4.92	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	17	55	61	50	7.61	0.86	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	18	57	74	47	8.28	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	19	65	76	57	13.87	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	20	59	62	50	14.99	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	21	56	71	44	8.28	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	22	59	71	47	5.59	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	23	53	55	49	9.40	0.49	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	24	54	57	51	7.83	0.02	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	25	55	64	49	7.83	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	26	51	54	41	11.63	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	27	42	46	32	16.55	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	28	35	42	28	15.66	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	29	34	48	25	9.84	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	30	45	60	35	6.71	0.02	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	3	31	61	75	51	17.00	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	1	58	65	46	13.87	0.21	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	2	48	58	39	8.72	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	3	52	62	44	12.30	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	4	48	59	39	7.16	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	5	52	56	48	7.38	0.84	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	6	56	62	53	9.62	0.86	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	7	53	54	48	9.62	0.68	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	8	54	65	45	8.28	0.15	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	9	51	58	44	9.62	0.04	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	10	48	56	41	10.96	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	11	51	67	40	6.71	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	12	63	80	53	5.82	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	13	69	86	56	9.62	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	14	75	84	60	14.54	0.03	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	15	62	72	50	9.84	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	16	66	80	59	13.42	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	17	57	59	46	13.87	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	18	46	48	40	11.63	0.91	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	19	46	55	40	13.65	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	20	50	62	41	7.61	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	21	56	68	49	10.74	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	22	64	77	52	5.37	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	23	65	78	53	5.82	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	24	66	82	55	6.93	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	25	61	72	54	8.95	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	26	62	74	57	6.93	0.10	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	27	56	63	43	14.32	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	28	48	60	39	13.42	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	29	54	67	42	6.04	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	4	30	56	68	44	5.82	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	1	59	67	53	5.82	0.13	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	2	64	79	54	4.92	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	3	65	74	58	9.62	0.36	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	4	63	74	57	5.14	0.52	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	5	64	69	58	6.71	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	6	61	64	53	11.18	1.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	7	54	55	47	16.55	1.29	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	8	50	58	44	13.87	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	9	56	71	43	8.28	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	10	62	74	49	10.51	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	11	64	75	51	9.62	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	12	65	75	57	8.50	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	13	67	76	63	7.83	0.14	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	14	69	71	65	4.70	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	15	69	81	63	6.26	0.44	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	16	69	82	64	7.61	0.27	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	17	71	84	57	10.51	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	18	67	75	58	6.93	0.01	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	19	71	86	61	6.49	0.03	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	20	77	89	67	7.61	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	21	83	92	73	8.72	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	22	80	89	69	10.51	1.50	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	23	70	75	62	10.74	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	24	62	64	59	10.07	0.32	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	25	64	72	57	9.84	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	26	66	73	61	5.59	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	27	71	79	66	9.62	0.33	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	28	71	80	63	8.05	0.02	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	29	74	82	63	4.92	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	30	77	88	67	8.50	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	5	31	82	96	71	5.82	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	6	1	85	94	74	6.93	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	6	2	80	89	72	6.71	0.46	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	6	3	73	80	67	9.62	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	6	4	75	86	61	6.26	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	6	5	73	80	64	8.72	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	6	6	72	81	61	8.05	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	6	7	71	80	64	8.50	0.20	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	6	8	77	88	69	5.82	0.02	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	6	9	77	84	67	11.86	0.06	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	6	10	72	83	61	NA	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	6	11	70	73	65	NA	0.07	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	6	12	71	81	67	7.38	0.01	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	6	13	80	94	72	4.70	0.01	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	6	14	79	85	73	7.61	0.04	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	6	15	80	89	70	6.93	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	6	16	79	85	74	11.41	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	6	17	84	99	73	10.96	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	6	18	77	79	67	16.11	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	6	19	70	80	60	14.32	0.00	0.0	0.0
USW00013743	WASHINGTON REAGAN NATIONAL AIRPORT, VA US	2022	6	20	72	NA	NA	NA	NA	NA	NA

5.1 Quantitative Variables: `mean()`, `median()`, `fivenum()`, `IQR()`, and `sd()`

These functions do exactly as they sound, however, you must pass a numeric vector through each of them.

#This will return an error-- since dca_weather 
#has multiple columns, R doesn't know which column you want.
mean(dca_weather)

## Warning in mean.default(dca_weather): argument is not
## numeric or logical: returning NA

## [1] NA

mean(dca_weather$TAVG)

## [1] 53.13

Knowing the average temperature from January to June is pretty useless though– sometimes, you want to filter it by month.

mean(dca_weather$TAVG[dca_weather$month %in% 6] )

## [1] 75.85

If the command looks intimidating, consider the command from inside out.

In the square brackets, you consider only the rows where dca_weather$months is equal to 6. Those pass on a set of rows to dca_weather$TAVG.
Then, you pass only those rows, and select the dca_weather$TAVG data from those rows. That passes on a vector to mean().
Finally, you calculate the mean of all those numbers.

The median() and fivenum() commands work the same.

fivenum(dca_weather$TMIN[dca_weather$month %in% 2])

## [1] 21.0 27.0 32.0 35.5 47.0

median(dca_weather$TMAX[dca_weather$month %in% 5])

## [1] 75

Finally, sd() and IQR() will give you measures of spread.

sd(dca_weather$TMAX[dca_weather$month %in% 3])

## [1] 10.79

IQR(dca_weather$TAVG[dca_weather$month %in% 6])

## [1] 7.25

5.1.1 The dreaded `NA` response

Consider the following code:

sd(dca_weather$TMAX[dca_weather$month %in% 6])

## [1] NA

Why does it return back NA? Well it turns out that if you look examine the data for June… it turns out that there are some NAs within the vector we are trying to process. Any time you perform a mathematical operation with NA in R, R will always return back NA– it’s like a special value that obliterates everything else in its path.

dca_weather[169:171,]

## # A tibble: 3 × 12
##   STATION   NAME   year month   day  TAVG  TMAX  TMIN  AWND
##   <chr>     <chr> <dbl> <dbl> <int> <dbl> <dbl> <dbl> <dbl>
## 1 USW00013… WASH…  2022     6    18    77    79    67  16.1
## 2 USW00013… WASH…  2022     6    19    70    80    60  14.3
## 3 USW00013… WASH…  2022     6    20    72    NA    NA  NA  
## # … with 3 more variables: PRCP <dbl>, SNOW <dbl>,
## #   SNWD <dbl>

At this point, we have a choice to make. Obviously, the data for June 20th wasn’t available when I downloaded it, because I downloaded this data on June 23rd. In this case though, it doesn’t make sense to treat NA as 0, because clearly the temperature wasn’t 0 degrees in June. However, we can still draw conclusions about the data that we have, and so we can tell R to ignore any NAs in the data.

sd(dca_weather$TMAX[dca_weather$month %in% 6], na.rm=TRUE)

## [1] 6.306

Notice that the argument na.rm= is passed into the sd() argument. Try typing ?sd() to read the documentation on this function.

5.2 Categorical Variables: The `table()` function

Let’s say I’m interested in how many elements are in gas, liquid, and solid state at room temperature. Looking at the periodic_table columns, I see that the column that gives me that information is state_at_stp.

table(periodic_table$state_at_stp)

## 
##    Gas Liquid  Solid 
##     11      2     90

You should only use table() for categorical data, because it returns a counts to you. Counting quanatitative variables is meaningless.
The table function takes a single vector, or two vectors, into the function. Do not pass an entire table through table(), or else R will return an error.
The table function provides a count of the number of elements that appear in each state. But as you can see, the ordering is off.

5.3 Making code efficient with piping and dplyr

The following code does the same exact thing as the previous command, using the dyplr package and the piping operator.²

library(dplyr)
dca_weather %>%
  dplyr::filter(month==6) %>%
  dplyr::select(TMAX) %>%
  summarize(average=mean(TMAX, na.rm=TRUE), std_dev=sd(TMAX, na.rm=TRUE))

## # A tibble: 1 × 2
##   average std_dev
##     <dbl>   <dbl>
## 1    84.7    6.31

Although it is one more thing to learn, it is more powerful and sustainable in the long run. In fact, most help guides you’ll see on the internet will use the pipe operator and the dplyr functions filter and `select. Some advantages:

Unlike in base R, where the first command is on the inside, and you work your way out, piping allows you to see the first command on the top.
Piping also passes the dataframe name to the next command, so you don’t need to retype the dataset name each time.
The dplyr::filter() function also makes quick work of selecting only the rows that you need, rather than using a combination of [], %in, and $.
And finally, the summarize command allows you to not just calculate one statistic, but many statistics at once.

FIGURE 5.1: A comparison between Base R commands and dplyr commands.

Finally, dplyr allows us to do more powerful things like the group_by function. Now, we can find the mean, median, and standard deviation of all 6 months with just one command.

library(dplyr)
dca_weather %>%
  dplyr::group_by(month) %>%
  dplyr::select(TMAX) %>%
  summarize(average=mean(TMAX, na.rm=TRUE), median=median(TMAX, na.rm=TRUE), std_dev=sd(TMAX, na.rm=TRUE))

## # A tibble: 6 × 4
##   month average median std_dev
##   <dbl>   <dbl>  <dbl>   <dbl>
## 1     1    42.0   41      9.10
## 2     2    53.1   52.5   11.6 
## 3     3    60.5   61     10.8 
## 4     4    66.6   65      9.97
## 5     5    76.4   75      9.49
## 6     6    84.7   84      6.31

🛠 Vectors and Dataframe Exercises

6 👀 Visualizing One-Variable Data

5 📚 Summarizing Data

5.1 Quantitative Variables: mean(), median(), fivenum(), IQR(), and sd()

5.1.1 The dreaded NA response

5.2 Categorical Variables: The table() function

5.3 Making code efficient with piping and dplyr

5.1 Quantitative Variables: `mean()`, `median()`, `fivenum()`, `IQR()`, and `sd()`

5.1.1 The dreaded `NA` response

5.2 Categorical Variables: The `table()` function