Question

In the lectures about lists we have seen some Python code examples that involve the processing of lists containing weather statistics. The original source of the values shown in the slides was taken from part of the Environment Canada website that serves up historical data:

http://climate.weather.gc.ca/historical_data/search_historic_data_e.html
  
Data can be provied by that website using the Comma Separated Value (CSV) format which is stored in text files normally using a CSV suffix. We will not work directly with such files in this part of the assignment, but instead will work with pre-packaged strings.

In the code cell below are:
* two global variables which each corresponding to a list of strings, ```WEATHER_LIST_01``` and ```WEATHER_LIST_02```. Each list contains the comma-separated values for a single month's weather measurements;
* a nearly empty function called ```compute_month_stats()``` which you are to complete for this part of the assignment; and
* a ```main()``` function that calls ```compute_month_stats()```.

The docstring comment for ```compute_month_stats()``` describes the format of each string, and also describes what the function must compute. Note that the function which you are to complete ***must not produce output to the console*** (*i.e.*, must not call ```print()```). If the function is correctly written, the output of the program when ```WEATHER_LIST_01``` is given as the argument to the function will be:

```
4,23.1,-8.0,91.0,14
5,26.3,4.1,1.8,0
```

As part of your solution you will need to use string-to-list functions such as ```split()```, as well as ```for``` loops and various kinds of ```if``` statements (and many other kinds of Python elements, too). You may use code from lecture slides but you **must** include a comment indicating which slides were used.

And here are some additional important notes:
1. Please remember that strings are not integers or floats. You may need to call ```int()```, ```float()```, and ```str()``` as appropriate.
1. The data from Environment Canada is not necessarily always complete as equipment at measurement stations often malfunctions. Data provided to you has been cleaned up such that you need not worry about handling errors in the data. That is, the keen-eyed among you will notice that there may be fewer strings in a list than there are days in a month. ***Therefore your solution must not make any assumptions about the number of days in a month.***
1. ***You are not permitted to ```import``` modules into your solution (*i.e.*, submitted solutions may not use ```re```, ```pandas```, ```itertools```, etc.). The only exception is the ```sys``` module.***

WEATHER_LIST_01=['2017,04,01,4.7,-5.4,0.0', '2017,04,02,0.6,-2.5,5.6', '2017,04,03,2.2,-2.9,0.0', '2017,04,04,6.8,-3.7,0.0', '2017,04,05,2.8,-1.3,0.0', '2017,04,06,6.8,-0.1,18.4', '2017,04,07,11.6,2.7,27.3', '2017,04,08,7.5,1.1,0.0', '2017,04,09,9.1,1.2,0.0', '2017,04,10,11.3,0.3,0.0', '2017,04,11,23.1,3.5,0.0', '2017,04,12,14.2,1.7,0.0', '2017,04,13,14.5,2.0,0.0', '2017,04,14,11.1,1.7,0.0', '2017,04,15,15.0,1.9,0.0', '2017,04,16,17.9,3.1,0.0', '2017,04,17,10.9,-1.2,0.2', '2017,04,18,5.3,-6.2,0.0', '2017,04,19,5.0,-8.0,0.0', '2017,04,20,2.7,-3.3,0.0', '2017,04,21,10.6,-2.8,0.0', '2017,04,22,6.0,-3.9,5.5', '2017,04,23,4.9,-0.1,3.4', '2017,04,24,14.9,0.4,0.0', '2017,04,25,12.6,-2.5,0.0', '2017,04,26,10.8,3.9,9.4', '2017,04,27,15.3,9.6,19.0', '2017,04,28,15.6,8.5,2.2', '2017,04,29,20.4,5.8,0.0', '2017,04,30,11.3,3.4,0.0']
WEATHER_LIST_02=['2015,05,01,18.0,9.0,0.0', '2015,05,02,16.0,4.1,0.0', '2015,05,04,17.6,5.3,0.0', '2015,05,05,16.2,6.1,0.4', '2015,05,07,19.6,4.5,0.0', '2015,05,08,22.8,5.5,0.0', '2015,05,09,22.5,7.0,0.0', '2015,05,10,18.8,8.1,0.0', '2015,05,11,16.8,10.3,0.0', '2015,05,12,17.5,10.8,0.0', '2015,05,13,16.8,10.5,0.0', '2015,05,14,16.8,9.2,1.2', '2015,05,15,19.9,7.3,0.0', '2015,05,16,18.5,10.6,0.0', '2015,05,17,19.2,9.6,0.0', '2015,05,18,21.3,9.2,0.0', '2015,05,19,22.9,9.2,0.0', '2015,05,20,22.4,7.9,0.0', '2015,05,21,22.3,8.3,0.0', '2015,05,22,18.9,9.8,0.2', '2015,05,23,18.5,8.8,0.0', '2015,05,24,18.5,9.4,0.0', '2015,05,25,15.6,8.1,0.0', '2015,05,26,19.7,9.4,0.0', '2015,05,27,21.4,9.0,0.0', '2015,05,28,23.5,9.1,0.0', '2015,05,29,26.3,9.9,0.0', '2015,05,30,22.5,8.8,0.0', '2015,05,31,20.5,7.7,0.0']

def compute_month_stats(data):
"""
function: compute_month_stats
  
Given a list of strings containing weather data for one month,
compute summary statistics for that month (maximimum temperature,
minimum temperature, number of days with freezing temperatures,
total precipitation) and return all this as a tuple.

Input parameter:
----------------
  
* data: A list of strings where each string contains one day's
weather measurements. All of the data in the list is from a
single month. The values are separated by commas, and each day's
string has the same number of values. The order of these values
is: year, month, day, high temp (Celsius), low temp (Celsius),
and precipitation (mm).
  
Output:
-------
* There is no output to the console from this function.
  
Return value:
-------------
A tuple with five values is returned. The values are: the month
number corresponding to the data, the maximum high temperature,
the minimum low temperature, the total precipitation for the
month (rounded to one decimal place), and the number of days
having freezing or below-freezing temperatures (i.e., 0.0 C or
lower).
"""
  
return(0,0,0,0,0)
  

def main():
weather_data = [WEATHER_LIST_01, WEATHER_LIST_02]
  
for month_data in weather_data:
stats = compute_month_stats(month_data)
for val in stats[:-1]:
print(val, ",", sep="", end="")
print(stats[-1])
  
main()

Output:

4,23.1,-8.0,91.0,14
5,26.3,4.1,1.8,0

Answer 1

Here is the completed code for this problem. Comments are included, go through it, learn how things work and let me know if you have any doubts or if you need anything to change. If you are satisfied with the solution, please rate the answer. Thanks

#code

WEATHER_LIST_01 = ['2017,04,01,4.7,-5.4,0.0', '2017,04,02,0.6,-2.5,5.6', '2017,04,03,2.2,-2.9,0.0',

                   '2017,04,04,6.8,-3.7,0.0', '2017,04,05,2.8,-1.3,0.0', '2017,04,06,6.8,-0.1,18.4',

                   '2017,04,07,11.6,2.7,27.3', '2017,04,08,7.5,1.1,0.0', '2017,04,09,9.1,1.2,0.0',

                   '2017,04,10,11.3,0.3,0.0', '2017,04,11,23.1,3.5,0.0', '2017,04,12,14.2,1.7,0.0',

                   '2017,04,13,14.5,2.0,0.0', '2017,04,14,11.1,1.7,0.0', '2017,04,15,15.0,1.9,0.0',

                   '2017,04,16,17.9,3.1,0.0', '2017,04,17,10.9,-1.2,0.2', '2017,04,18,5.3,-6.2,0.0',

                   '2017,04,19,5.0,-8.0,0.0', '2017,04,20,2.7,-3.3,0.0', '2017,04,21,10.6,-2.8,0.0',

                   '2017,04,22,6.0,-3.9,5.5', '2017,04,23,4.9,-0.1,3.4', '2017,04,24,14.9,0.4,0.0',

                   '2017,04,25,12.6,-2.5,0.0', '2017,04,26,10.8,3.9,9.4', '2017,04,27,15.3,9.6,19.0',

                   '2017,04,28,15.6,8.5,2.2', '2017,04,29,20.4,5.8,0.0', '2017,04,30,11.3,3.4,0.0']

WEATHER_LIST_02 = ['2015,05,01,18.0,9.0,0.0', '2015,05,02,16.0,4.1,0.0', '2015,05,04,17.6,5.3,0.0',

                   '2015,05,05,16.2,6.1,0.4', '2015,05,07,19.6,4.5,0.0', '2015,05,08,22.8,5.5,0.0',

                   '2015,05,09,22.5,7.0,0.0', '2015,05,10,18.8,8.1,0.0', '2015,05,11,16.8,10.3,0.0',

                   '2015,05,12,17.5,10.8,0.0', '2015,05,13,16.8,10.5,0.0', '2015,05,14,16.8,9.2,1.2',

                   '2015,05,15,19.9,7.3,0.0', '2015,05,16,18.5,10.6,0.0', '2015,05,17,19.2,9.6,0.0',

                   '2015,05,18,21.3,9.2,0.0', '2015,05,19,22.9,9.2,0.0', '2015,05,20,22.4,7.9,0.0',

                   '2015,05,21,22.3,8.3,0.0', '2015,05,22,18.9,9.8,0.2', '2015,05,23,18.5,8.8,0.0',

                   '2015,05,24,18.5,9.4,0.0', '2015,05,25,15.6,8.1,0.0', '2015,05,26,19.7,9.4,0.0',

                  '2015,05,27,21.4,9.0,0.0', '2015,05,28,23.5,9.1,0.0', '2015,05,29,26.3,9.9,0.0',

                   '2015,05,30,22.5,8.8,0.0', '2015,05,31,20.5,7.7,0.0']

def compute_month_stats(data):

    """

    function: compute_month_stats

    Given a list of strings containing weather data for one month,

    compute summary statistics for that month (maximimum temperature,

    minimum temperature, number of days with freezing temperatures,

    total precipitation) and return all this as a tuple.

    Input parameter:

    ----------------

    * data: A list of strings where each string contains one day's

    weather measurements. All of the data in the list is from a

    single month. The values are separated by commas, and each day's

    string has the same number of values. The order of these values

    is: year, month, day, high temp (Celsius), low temp (Celsius),

    and precipitation (mm).

    Output:

    -------

    * There is no output to the console from this function.

    Return value:

    -------------

    A tuple with five values is returned. The values are: the month

    number corresponding to the data, the maximum high temperature,

    the minimum low temperature, the total precipitation for the

    month (rounded to one decimal place), and the number of days

    having freezing or below-freezing temperatures (i.e., 0.0 C or

    lower).

    """

    #declaring all needed variables

    month=0

    max_hi_temp=None

    min_low_temp=None

    total_precip=0

    num_days_freezing=0

    #validating length

    if len(data)>0:

        #extracting month from the first record

        #{splitting by comma, taking element at index 1, converting to int}

        month=int(data[0].split(',')[1])

        #looping through each day in data

        for day in data:

            #splitting by comma

            fields=day.split(',')

            #finding hi temperature (value at index 3, converted to float)

            hi_temp=float(fields[3])

            #finding low temperature

            low_temp=float(fields[4])

            #finding precipitation

            precip=float(fields[5])

            #if max_hi_temp is not initialized or is less than hi_temp

            #updating max_hi_temp

            if max_hi_temp==None or max_hi_temp<hi_temp:

                max_hi_temp=hi_temp

            # if min_low_temp is not initialized or is greater than low_temp

            # updating min_low_temp

            if min_low_temp==None or min_low_temp>low_temp:

                min_low_temp=low_temp

            #adding precip to total precipitation

            total_precip+=precip

            #if low temp is less than or equal to 0, incrementing num_days_freezing

            if low_temp<=0:

                num_days_freezing+=1

        #returning a tuple containing everything, (total_precip rounded to 2 places)

        return (month,max_hi_temp,min_low_temp,round(total_precip,2),num_days_freezing)

    return None # data is empty

def main():

    weather_data = [WEATHER_LIST_01, WEATHER_LIST_02]

    for month_data in weather_data:

        stats = compute_month_stats(month_data)

        for val in stats[:-1]:

            print(val, ",", sep="", end="")

        print(stats[-1])

main()

#output

4,23.1,-8.0,91.0,14

5,26.3,4.1,1.8,0