Using RStudio: You may use either the local functions, or the dplyr / data.table packages to perform the following actions (do NOT use any other package for computations for graphing use any package):

1. Create a data.frame object named airQ from the exam1quality excel file (given).

2. Sort the data by the Wind column.

3. Remove any rows for which the Ozone column has a missing value.

4. Remove the Solar.R column and create a new column containing the ratio of Ozone to Wind.

5. For each Temp reading in the original exam1quality data, create a plot of Temp against Ozone only if (Temp>=60). In case where the Ozone reading is not available, do NOT plot that TempOzone pairing. Ensure that all the plots are on the same axis and include a suitable title that indicates the monthfor example, Ozone against Temp for Month X.

6. List the Dates in Month/Day format for all readings where Temp > 65 and Wind > 10.3

7. Create a subset of the original exam1quality data containing just three columns: Month, Day, and Solar.R. The data should only contain data for June and July. Create a new .txt file named solar, and put the data in it.

8. Merge the air and solar datasets together, retaining all records from the air dataset (i.e., similar to a left join).

9. Calculate the median Ozone value by Month for the merged data in the previous step.

Ozone	Solar.R	Wind	Temp	Month	Day
41	190	7.4	67	5	1
36	118	8	72	5	2
12	149	12.6	74	5	3
18	313	11.5	62	5	4
NA	NA	14.3	56	5	5
28	NA	14.9	66	5	6
23	299	8.6	65	5	7
19	99	13.8	59	5	8
8	19	20.1	61	5	9
NA	194	8.6	69	5	10
7	NA	6.9	74	5	11
16	256	9.7	69	5	12
11	290	9.2	66	5	13
14	274	10.9	68	5	14
18	65	13.2	58	5	15
14	334	11.5	64	5	16
34	307	12	66	5	17
6	78	18.4	57	5	18
30	322	11.5	68	5	19
11	44	9.7	62	5	20
1	8	9.7	59	5	21
11	320	16.6	73	5	22
4	25	9.7	61	5	23
32	92	12	61	5	24
NA	66	16.6	57	5	25
NA	266	14.9	58	5	26
NA	NA	8	57	5	27
23	13	12	67	5	28
45	252	14.9	81	5	29
115	223	5.7	79	5	30
37	279	7.4	76	5	31
NA	286	8.6	78	6	1
NA	287	9.7	74	6	2
NA	242	16.1	67	6	3
NA	186	9.2	84	6	4
NA	220	8.6	85	6	5
NA	264	14.3	79	6	6
29	127	9.7	82	6	7
NA	273	6.9	87	6	8
71	291	13.8	90	6	9
39	323	11.5	87	6	10
NA	259	10.9	93	6	11
NA	250	9.2	92	6	12
23	148	8	82	6	13
NA	332	13.8	80	6	14
NA	322	11.5	79	6	15
21	191	14.9	77	6	16
37	284	20.7	72	6	17
20	37	9.2	65	6	18
12	120	11.5	73	6	19
13	137	10.3	76	6	20
NA	150	6.3	77	6	21
NA	59	1.7	76	6	22
NA	91	4.6	76	6	23
NA	250	6.3	76	6	24
NA	135	8	75	6	25
NA	127	8	78	6	26
NA	47	10.3	73	6	27
NA	98	11.5	80	6	28
NA	31	14.9	77	6	29
NA	138	8	83	6	30
135	269	4.1	84	7	1
49	248	9.2	85	7	2
32	236	9.2	81	7	3
NA	101	10.9	84	7	4
64	175	4.6	83	7	5
40	314	10.9	83	7	6
77	276	5.1	88	7	7
97	267	6.3	92	7	8
97	272	5.7	92	7	9
85	175	7.4	89	7	10
NA	139	8.6	82	7	11
10	264	14.3	73	7	12
27	175	14.9	81	7	13
NA	291	14.9	91	7	14
7	48	14.3	80	7	15
48	260	6.9	81	7	16
35	274	10.3	82	7	17
61	285	6.3	84	7	18
79	187	5.1	87	7	19
63	220	11.5	85	7	20
16	7	6.9	74	7	21
NA	258	9.7	81	7	22
NA	295	11.5	82	7	23
80	294	8.6	86	7	24
108	223	8	85	7	25
20	81	8.6	82	7	26
52	82	12	86	7	27
82	213	7.4	88	7	28
50	275	7.4	86	7	29
64	253	7.4	83	7	30
59	254	9.2	81	7	31
39	83	6.9	81	8	1
9	24	13.8	81	8	2
16	77	7.4	82	8	3
78	NA	6.9	86	8	4
35	NA	7.4	85	8	5
66	NA	4.6	87	8	6
122	255	4	89	8	7
89	229	10.3	90	8	8
110	207	8	90	8	9
NA	222	8.6	92	8	10
NA	137	11.5	86	8	11
44	192	11.5	86	8	12
28	273	11.5	82	8	13
65	157	9.7	80	8	14
NA	64	11.5	79	8	15
22	71	10.3	77	8	16
59	51	6.3	79	8	17
23	115	7.4	76	8	18
31	244	10.9	78	8	19
44	190	10.3	78	8	20
21	259	15.5	77	8	21
9	36	14.3	72	8	22
NA	255	12.6	75	8	23
45	212	9.7	79	8	24
168	238	3.4	81	8	25
73	215	8	86	8	26
NA	153	5.7	88	8	27
76	203	9.7	97	8	28
118	225	2.3	94	8	29
84	237	6.3	96	8	30
85	188	6.3	94	8	31
96	167	6.9	91	9	1
78	197	5.1	92	9	2
73	183	2.8	93	9	3
91	189	4.6	93	9	4
47	95	7.4	87	9	5
32	92	15.5	84	9	6
20	252	10.9	80	9	7
23	220	10.3	78	9	8
21	230	10.9	75	9	9
24	259	9.7	73	9	10
44	236	14.9	81	9	11
21	259	15.5	76	9	12
28	238	6.3	77	9	13
9	24	10.9	71	9	14
13	112	11.5	71	9	15
46	237	6.9	78	9	16
18	224	13.8	67	9	17
13	27	10.3	76	9	18
24	238	10.3	68	9	19
16	201	8	82	9	20
13	238	12.6	64	9	21
23	14	9.2	71	9	22
36	139	10.3	81	9	23
7	49	10.3	69	9	24
14	20	16.6	63	9	25
30	193	6.9	70	9	26
NA	145	13.2	77	9	27
14	191	14.3	75	9	28
18	131	8	76	9	29
20	223	11.5	68	9	30