In your final program:
Comments are required in the following locations:
At the top of the source code comment your name and a short program description.
Comment the purpose of each variable neatly aligned to the right side.
Comment major sections of code such as input, processing, and output.
Program Design: Your program is a professional document and must be neat and easy to read. All programs should follow the listed specifications.
Comments should be aligned and entered in a consistent fashion
Blank lines should be added to aid readability
Code within blocks should be indented
Comments should not contain spelling mistakes
Variables names should be meaningful
Define functions and data structures where necessary
Optimize your code: least possible number of lines to produce the output
Error handling: you should handle all the possible error conditions and invalid inputs
SIE507 – Information Systems Programming November 26th, 2022
Option 1: Standard Project
Consider the dataset provided:US_births_1994_2014_ monthly.csv(This dataset contains the number of births in the United States from 1994–2014 - arranged monthly)
Write a python program to:
Read the dataset from the .csv file to an appropriate Numpy array.(2%)
Based on the dataset, calculate and report the most appropriate descriptive statistics (e.g., min, max, mean, standard deviation, median, etc.). Format your output to be aligned and consistent.
(2%)
Classify the dataset in multiple ways (note: original dataset is already classified monthly): yearly, decennially (every 10 years), and based on each month (e.g., data for January from all the years, similarly for 12-months). Use appropriate Numpy data structures to store the classified data (yearly, decennially, for 12 months).(5%)
Visualize your data with basic graphs: select at least two suitable chart types (e.g., bar, line, scatter, pie, box, etc.), and plot your graphs in different ways under each classification(6%)
After visualizing the data in multiple ways, what are the hidden features, data points, or trends you can find?
Briefly explain your analysis, observations, and findings:(5%)
What are your overall conclusions?
What are your recommendations or predictions?
What are some new things that you learned from the dataset once you visualized the data
in different ways? What surprised you?
Did you notice any hidden information or patterns from the data and/or graphs?
Can you think of any innovative ways to plot the data/findings?
textfile
year
month
births
1994
1
320705
2
301327
3
339736
4
317392
5
330295
6
329737
7
345862
8
352173
9
339223
10
330172
11
319397
12
326748
1995
316013
295094
328503
309119
334543
329805
340873
350737
339103
330012
310817
314970
1996
314283
301763
322581
312595
325708
318525
345162
346317
336348
336346
309397
322469
1997
317211
291541
321212
314230
330331
321867
346506
339122
333600
328657
307282
329335
1998
319340
298711
329436
319758
330519
327091
348651
344736
343384
332790
313241
333896
1999
319182
297568
332939
316889
328526
332201
349812
351371
349409
332980
315289
333251
2000
330108
317377
340553
317180
341207
341206
348975
360080
347609
343921
333811
336787
2001
335198
303534
338684
323613
344017
331085
351047
361802
342564
344074
323746
326569
2002
330674
303977
331505
324432
339007
327588
357669
359417
348814
345814
318573
334256
2003
329803
307248
336920
330106
346754
337425
364226
360103
359644
354048
320094
343579
2004
339077
321348
352379
339079
343248
350876
365380
361835
362895
355048
342359
353339
2005
337478
314890
355121
338060
351736
356576
363196
376467
370354
351161
342182
354720
2006
345976
324435
362520
334587
360901
363615
373445
394199
381204
373685
357976
362611
2007
360521
331617
365888
342981
367491
363486
384861
396355
372774
375272
359335
360203
2008
361868
343354
355484
351344
359835
353430
380707
379046
373625
363420
328905
359719
2009
342975
321122
352571
341822
349831
351620
373491
364795
367694
353059
325247
346764
2010
328120
306393
343448
329137
332651
338966
349648
354727
355887
341767
330984
344247
2011
324845
301927
334439
317225
330667
341637
349841
364194
350662
333132
326107
332232
2012
320661
308262
328123
310118
333908
330785
351472
365501
344333
349973
329306
328426
2013
327352
294882
323629
314847
332868
322868
352495
356879
341676
344285
322157
339399
2014
329962
300899
326267
322329
336504
327680
357476
356066
350497
344471
318655
339726
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