Consider the data below is csv file. Do the Volume part.

ID	Date	AveragePrice	Volume	4046	4225
0	########	1.33	64236.62	1036.74	54454.85
1	########	1.35	54876.98	674.28	44638.81
2	########	0.93	118220.2	794.7	109149.7
3	########	1.08	78992.15	1132	71976.41
4	########	1.28	51039.6	941.48	43838.39
5	########	1.26	55979.78	1184.27	48067.99
6	########	0.99	83453.76	1368.92	73672.72
7	########	0.98	109428.3	703.75	101815.4
8	########	1.02	99811.42	1022.15	87315.57
9	########	1.07	74338.76	842.4	64757.44
10	########	1.12	84843.44	924.86	75595.85
11	########	1.28	64489.17	1582.03	52677.92
12	########	1.31	61007.1	2268.32	49880.67
13	########	0.99	106803.4	1204.88	99409.21
14	########	1.33	69759.01	1028.03	59313.12
15	########	1.28	76111.27	985.73	65696.86
16	9/6/2015	1.11	99172.96	879.45	90062.62
17	########	1.07	105693.8	689.01	94362.67
18	########	1.34	79992.09	733.16	67933.79
19	########	1.33	80043.78	539.65	68666.01
20	8/9/2015	1.12	111140.9	584.63	100961.5
21	8/2/2015	1.45	75133.1	509.94	62035.06

a) Write a python function without using any libraries (pandas, NumPy, etc.) that takes a variable name in the form of string ("Volume") from the csv file given below, reads into memory the values for that variable and calculates the mean using statistic module. Mean_SM=calculate MeanSM("Volume") b) Write a python function without using any libraries (pandas, NumPy, etc.) that takes a variable name in the form of string ("Volume"), reads into memory the values for that variable and calculates the standard deviation using statistic module. STD_SM=calculateSTDSM("Volume") c) Repeat a and b, but instead using statistic module, write your own code to calculate mean and standard deviation. Mean_OC=calculate MeanOc("Volume") STD_OC=calculateSTDOC("Volume") d) Repeat a and b, but your functions must be memoryless you can hold in memory only single value from the file at any given time. e) Write test code to demonstrate that means and std are the same all three techniques