# CSCI 1100 | Computer Science 1 Homework 7

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## Description

CSCI 1100 | Computer Science 1 Homework 7
Dictionaries
Homework Overview
This homework is worth 110 points toward your overall homework grade and is due Thursday
November 10, 2016 at 11:59:59 pm. It consists of one single program called hw7.py that
assumes the presence of a data le called tempdata.json.
The data set for this homework comes from NOAA (National Oceanic and Atmospheric Admin-
istration). It contains temperature data from Troy, NY from 1956 until June of 2015, measured
at Hudson River Lock and Dam (you can see it for yourself here: http://www.google.com/maps/
place/42.75,-73.68333).
The data set is given to you in a le called tempdata.json in JSON format, which can be read in
its entirety with the following three lines of code:
import json
if __name__ == ‘__main__’:
You might remember the JSON format from our Lecture 13 notes, http://www.cs.rpi.edu/
call, the variable data is a list of dictionaries. Each dictionary in the list contains climate values
for a single month and year. For example:
>>> print data[0]
{u’MMNT’: -9999, u’TPCP’: -9999, u’MMXT’: -9999, u’DX32′: 0, u’MNTM’: 0, u’DT90′: 0,
u’EMNT’: 51, u’MXSD’: -9999, u’DT32′: 0, u’month’: 7, u’DP05′: -9999, u’year’: 1956,
u’DSNW’: -9999, u’DP01′: -9999, u’TSNW’: -9999, u’DP10′: -9999, u’DT00′: 0, u’EMXT’:
-9999}
>>> print(‘{}/{}’.format(data[0][‘month’], data[0][‘year’]))
7/1956
In order to understand this better you might write a simple for loop that goes through all the
dictionaries in the data list and prints out the month and year of each.
Each attribute of each dictionary is a climate measurement for a given year and month. The
u before each attribute name indicates that these are strings encoded in Unicode, for example
u MMNT . Your code may or may not print out the u, but in either case, you may safely ignore it
and treat these strings as any regular string.
Here is the list of attributes each dictionary has and their meaning:
month: Month of year (1-12)
year: Year
EMNT: Extreme minimum daily temperature
EMXT: Extreme maximum daily temperature
MMNT: Monthly Mean minimum temperature
MMXT: Monthly Mean maximum temperature
MNTM: Monthly mean temperature
MXSD: Maximum snow depth
TPCP: Total precipitation
TSNW: Total snow fall
DT00: Number days with minimum temperature less than or equal to 0.0 F
DT32: Number days with minimum temperature less than or equal to 32.0 F
DT90: Number days with maximum temperature greater than or equal 90.0 F
DX32: Number days with maximum temperature less than or equal to 32.0 F
DP01: Number of days with greater than or equal to 0.1 inch of precipitation
DP05: Number of days with greater than or equal to 0.5 inch of precipitation
DP10: Number of days with greater than or equal to 1.0 inch of precipitation
DSNW: Number days with snow depth > 1 inch.
Note that some values are missing, especially for older data. In this case, you have a special value
(-9999). You are expected to disregard any value that is -9999.
Problem Description
Write a program that reads in a year in the interval 1956 through 2015 inclusive (you may assume
this input is correct) and nds the data for every month in this year to print out the following
information:
 Top 3 months and associated values for:
{ highest maximum temperature (EMXT)
{ lowest minimum temperature (EMNT)
{ highest number of days with maximum temperature above 90 (DT90)
{ highest number of days with maximum temperature below 32 (DX32)
{ highest total precipitation (TPCP)
{ lowest total precipitation (TPCP)
{ highest snow depth (TSNW)
{ lowest snow depth (TSNW)
All values should be printed as oats with one decimal point {:.1f}.
If there are three or fewer valid values, then print that there is not enough data. (For example,
snow depth in 1956.)
Ties should be broken using the month. For maximum values such as highest maximum
temperature, the tie-breaking month will be sorted in descending order from 12 down to 1
and for minimum values such as lowest minimum temperature the tie-breaking month will be
sorted in ascending order from 1 up to 12. Note that if you store your value/month pairs as
a list of tuples or a list of lists, this is the default sort behavior and you will not have to do
any additional work to get the sort order correct. See the example for snow depth in 2014 at
the end of this write up for an example of the expected ordering.
 Average of mean temperature across di erent months in the year (MNTM)
{ Overall average (average of all months for the chosen year for MNTM)
{ Average for the rst 6 months of the year (MNTM)
{ Average for the last 6 months of the year (MNTM)
If there are three or fewer valid data values for any one of these then print Not enough data.
 A histogram of overall average temperatures in 3 month intervals, i.e. months 1-3, 4-6, 7-9,
and 10-12. If there are fewer than two months in an interval, then print Not enough data.
A histogram prints a single * for each value in the average, excluding partial values. For
example, 54 *’s will be output for an average temperature of 54.7.
Expected output
Below you can see the expected functioning of this program with the le we gave you (note: we
might change the le in the homework submission server):
For the year 2014
Enter a year (1956-2015) => 2014
2014
Temperatures
———————————————————————-
Highest max value => 7: 92.0, 6: 91.0, 9: 90.0
Lowest min value => 1: -9.0, 2: -7.0, 3: 1.0
Highest days with max >= 90 => 7: 3.0, 9: 2.0, 6: 1.0
Highest days with max <= 32 => 2: 20.0, 1: 18.0, 3: 9.0
Precipitation
———————————————————————-
Highest total => 7: 5.8, 6: 5.6, 12: 5.0
Lowest total => 9: 0.9, 4: 1.9, 11: 2.1
Highest snow depth => 2: 24.6, 1: 12.6, 12: 5.8
Lowest snow depth => 5: 0.0, 6: 0.0, 7: 0.0
Average temperatures
———————————————————————-
Overall: 48.3
First 6 months: 40.9
Last 6 months: 55.7
Temperature histograms
———————————————————————-
01-03: ***********************
04-06: **********************************************************
07-09: *********************************************************************
10-12: ******************************************
For the year 1956
Enter a year (1956-2015) => 1956
1956
Temperatures
———————————————————————-
Highest max value => 8: 92.0, 9: 88.0, 10: 83.0
Lowest min value => 12: 5.0, 11: 15.0, 10: 27.0
Highest days with max >= 90 => 8: 3.0, 12: 0.0, 11: 0.0
Highest days with max <= 32 => 12: 4.0, 11: 2.0, 10: 0.0
Precipitation
———————————————————————-
Highest total => 9: 5.0, 11: 2.4, 12: 2.3
Lowest total => 8: 1.1, 10: 1.4, 12: 2.3
Highest snow depth => Not enough data
Lowest snow depth => Not enough data
Average temperatures
———————————————————————-
Overall: 42.3
First 6 months: Not enough data
Last 6 months: 42.3
Temperature histograms
———————————————————————-
01-03: Not enough data
04-06: Not enough data
07-09: ******************************************
10-12: *****************************************
Hints: (1) There are 70 – s in every dashed line. (2) Investigate use of the rjust string method
to print things like the 01 month string.
Suggestions
It appears that there are many things to compute, but it is actually the same thing for many
di erent keys of the same list of dictionaries. The trick is to gure out what functions are needed
and how they can be used over and over again to do closely related things by changing the function
call parameters. You might write functions to do a number of things:
 Gather values from data for a key and a year. (Note that data should be passed as a
parameter.) Return these values in a list or a dictionary
 Compute various statistics from these gathered values.
 Compute and output average temperatures. Can this be called three times?
 Compute and output a histogram. Can this be called four times?
 Anything else? Some combination of the above?
If you are thoughtful and thorough in thinking through your use of functions you might nd yourself
only writing 100 lines of Python code or even fewer to solve this problem.