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CSCE 121H - Fall 2019
Project 2 - Histogram
due: Fri, 9/27/19, 8:00am
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Write a C++ program that reads a list of numbers in from a file,
prints out some statistics (count, range, mean, standard deviation),
and then prints a histogram of the values in ASCII.
The histogram should span between the min and max of the values,
and have 20 evenly spaced bins (for now).

The filename should be given on the command-line.
Assume it has one value on each line.

Do the calculation of the statistics yourself; don't use library functions.

Since the input file could have an arbitrary number of values, you
will have to store them in a dynamic data structure, like a vector.
An important part of this program is setting up an array or similar
data structure to count how many items are in each bin (try to do 
this in one pass).

Here is an example of running on daily temperatures over 3 days in the summer for BCS.
  hourly weather data: https://w1.weather.gov/data/obhistory/KCLL.html

> histo wx.dat
num_vals: 72
mean:     84.6806
std_dev:  5.91097
range:    77 - 95
 77.00 -  77.90: ****
 77.90 -  78.80: ************
 78.80 -  79.70: ***
 79.70 -  80.60: ***
 80.60 -  81.50: ********
 81.50 -  82.40: *****
 82.40 -  83.30: **
 83.30 -  84.20: **
 84.20 -  85.10: ***
 85.10 -  86.00: 
 86.00 -  86.90: *
 86.90 -  87.80: ****
 87.80 -  88.70: *
 88.70 -  89.60: ******
 89.60 -  90.50: **
 90.50 -  91.40: ***
 91.40 -  92.30: **
 92.30 -  93.20: ***
 93.20 -  94.10: ***
 94.10 -  95.00: *****


Get your own data:

examples:
  daily temperature in BCS in a given month
  aggie football scores over last couple years (or all NCAA games)
  stock price of Google (GOOG) over the last year
  exam grade distribution for students in a class

Note: if you have a table of interesting data, you might be able to
open it as a spreadsheet delete the other columns and save the
column of interest as a text file.


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Optional:

1. Add a command line flag to specify the number of bins.

2. Other options might be the starting value, the bin size.

3. If the total number of observations is very large (like > 10,000), you
might want to divide the counts by a scaling factor, so the output doesn't
have too many asterisks.

4. If your input file has multiple columns (separated by tab or space), then
allow the user to indicate which column to read.