Python 字典排序和打印

Question

I have a file with mountains and their height and their mountains ranges. I have to extract from the csv file containing these data, the mountains ranges which each heights (as there is fewer mountains for each ranges in the csv), and I also have to count how many time each range appears. Then my program should print the 2 first mountain ranges and their heights

Here the guidelines:

Rewrite your function to use the collections module's Counter to count how many times each mountain range is mentioned. Each row contains a mountain, its height, and the range it is part of. The ranges are still in the 3rd column of the mountains.csv file. You can use more than one function if you want.

        with open('mountains.csv', 'r') as handle:
            for line in handle:

Shishapangma,8027,Himalayas,

Answer 1

I tried to modify your code as little as possible based on the other comments. This should achieve what you are looking for using your existing function/code.

from collections import Counter
from collections import defaultdict
from statistics import mean

def mountain_ranges(filename):
    ranges = Counter()
    heights = defaultdict(list)  
    msg = "The average height of {} is {} meters."
    err_msg = "Error: File doesn't exist or is unreadable."
    dictionary = {}

    try:
        with open('mountains.csv', 'r') as handle:
            for line in handle:
                mnt, height, range_, _ = line.strip().split(',')
                ranges[range_] += 1
                heights[range_].append(int(height))

    except IOError:
        print(err_msg)
    print("The two most common ranges are:\n")
    print([r[0] for r in ranges.most_common(2)])

    for range_ in heights:
        print(msg.format(range_, mean(heights[range_])))

Answer 2

You add all key/value -pairs in dictionary to your ranges and heights variables every time you handle a line in csv file.

Try like this:

with open('mountains.csv', 'r') as handle:
    for line in handle:
        key = line.replace('"', '').strip()
        k = key.split(",")
        # You always overwrited value here...
        # dictionary[k[2]] = k[1]
        if k[2] not in dictionary:
             dictionary[k[2]] = []
        dictionary[k[2]].append(k[1])
    # moved these loops out of upper for-loop
    for key, value in dictionary.items():
        ranges[key] += 1  
    for key, value in dictionary.items():
        heights[key].append(value)

And to get rid of that check if key exists use defaultdict from collections

Answer 3

It is easier to use the csv module to read data like this. Since order is meaningful, use a list:

import csv
with open('mountains.csv') as f:
    data=[[mtn,int(height),range] for (mtn,height,range,_) in csv.reader(f)]

# the extra _ is because you have an extra blank field in your example 
# from the trailing ,

Or, if you cannot use csv, in this simple case, you can replicate the function like this:

with open('mountain.csv') as f:
    data=[[mtn,int(height),rng] 
             for (mtn,height,rng,_) in (line.split(',') for line in f)]

That is it: Then you have the data needed to answer all other questions:

print(data)

[['Mount Everest', 8848, 'Himalayas'], ['K2', 8611, 'Karakoram'], 
 ['Kangchenjunga', 8586, 'Himalayas'], ['Lhotse', 8516, 'Himalayas'], 
 ['Makalu', 8485, 'Himalayas'], ['Cho Oyu', 8201, 'Himalayas'], 
 ['Dhaulagiri', 8167, 'Himalayas'], ['Manaslu', 8163, 'Himalayas'], 
 ['Nanga Parbat', 8126, 'Himalayas'], ['Annapurna', 8091, 'Himalayas'], 
 ['Gasherbrum I', 8080, 'Karakoram'], ['Broad Peak', 8051, 'Karakoram'], 
 ['Gasherbrum II', 8035, 'Karakoram'], ['Shishapangma', 8027, 'Himalayas']]

from collections import Counter 
print(Counter(row[2] for row in data))

# prints Counter({'Himalayas': 10, 'Karakoram': 4})

print(f'Average height of all mountains: {sum(row[1] for row in data)/len(data)}')

# prints "Average height of all mountains: 8284.785714285714"

And by range:

for rng, cnt in (Counter(row[2] for row in data).items()):
    print(f'Average for {rng}: {sum(row[1] for row in data if row[2]==rng)/cnt}')   

Prints:

Average for Himalayas: 8321.0
Average for Karakoram: 8194.25

Answer 4

You could try something like this:

from collections import Counter
from collections import defaultdict
from collections import OrderedDict
from statistics import mean   # this also exists in numpy if you prefer
# define your dicts inside the function, so they can be re-used each time it is called.


def mountain_ranges(filename):
    ranges = Counter()
    heights = defaultdict(list)
    msg = "The height of {} is {} meters."
    err_msg = "Error: File doesn't exist or is unreadable."
    dictionary = {}

    temp_list = []
    try:
        with open('mountains.csv', 'r') as handle:


            for row in handle:
                temp_list.append(row.split(','))

            for item in temp_list:
                    ranges[item[2].rstrip()] += 1  
                    heights[item[2].rstrip()].append(item[1]) 


    except IOError:
        print(err_msg)
    ranges = OrderedDict(ranges.most_common(2))
    print(ranges)
    print(heights)

Output:

OrderedDict([('Himalayas', 10), ('Karakoram', 4)])
defaultdict(<class 'list'>, {'Himalayas': ['8848', '8586', '8516', '8485', '8201', '8167', '8163', '8126', '8091', '8027'], 'Karakoram': ['8611', '8080', '8051', '8035']})