Python：将一个列表的索引与另一个列表进行比较，将第二个列表的值附加到第一个列表

Question

I have a .csv file as follows (snippet).

Country,Year,GDP ($US),Population
Angola,2002,11431738368,10760510
Angola,2005,32810672128,11706954
Antigua and Barbuda,2002,714677760,67448
Antigua and Barbuda,2005,875751360,68722
Argentina,2002,1.02E+11,38331121
Argentina,2005,1.83E+11,39537943
Armenia,2002,2376335104,3013818
Armenia,2005,4902779392,2982904
...

I need to find the five lowest GDP/Pop countries for 2002, then find their corresponding GDP/Pop values in 2005, then compute the difference and the percent difference. There are blanks for either GDP or Population values for some records, which I omit.

So far I used

import csv
import operator

data = open('file.csv')
read_data = csv.reader(data)

thisthing = []
for line in read_data:
#find 2002 GDP/Pop, omit blanks, append to list
    if line[7] == '2002' and line[8] != ' ' and line[9] != ' ':
        thisthing.append([line[0], (float(line[8])/(int(line[9])))])

thisthing.sort(key=operator.itemgetter(1))

This produces a list which print line by line as follows (Country, GDP/Pop):

['Burma (Myanmar)', 69.07171351277908]
['Burundi', 89.45864552423431]
['Congo (Dem. Rep.)', 99.23033109735835]
['Ethiopia', 109.33326343550823]
['Eritrea', 142.8576737907048]
['Guinea-Bissau', 151.110429668747]
['Afghanistan', 159.7524117568956]
['Malawi', 159.7614709537829]
['Sierra Leone', 174.6506490278577]

I want to now iterate back through 'read_data', using the country name in 'thisthing' as a conditional along with my blank prevention conditional

and line[8] != ' ' and line[9] != ' ':

to select and append the 2005 GDP/Pop to 'thisthing'

I have no idea where to begin doing that, and I have been stuck here for about a week now...any help would be most appreciated.

Answer 1

try this!!

import csv 
import operator

data = open('file.csv') read_data = csv.reader(data)

data_2002 = {}
data_2005 = {}

thisthing = [["country", "2002%", "2005%"]] 

for line in read_data:
    try: 
        gdp = float(line[8])/(int(line[9]))
        if line[7] == '2002' and line[8] != ' ' and line[9] != ' ':
            data_2002[line[0]] = gdp

        elif line[7] == '2005' and line[8] != ' ' and line[9] != ' ':
            data_2002[line[0]] = gdp
    except KeyError:
        print line[0]
        continue

for country in data_2002:
    thisthing.append([country, data_2002[country], data_2005[country]])

print thisthing

Answer 2

Using this as read_data :

[['Country', 'Year', 'GDP ($US)', 'Population'],
 ['Angola', '2002', '11431738368', '10760510'],
 ['Angola', '2005', '32810672128', '11706954'],
 ['Antigua and Barbuda', '2002', '714677760', '67448'],
 ['Antigua and Barbuda', '2005', '875751360', '68722'],
 ['Argentina', '2002', '1.02E+11', '38331121'],
 ['Argentina', '2005', '1.83E+11', '39537943'],
 ['Armenia', '2002', '2376335104', '3013818'],
 ['Armenia', '2005', '4902779392', '2982904']]

We don't want the first line:

read_data = read_data[1:]

If you use a csv.read object for read_data do:

next(read_data)

Actually, the code is robust enough to iterate over all lines because we skip the lines with exceptions caused by converting a string into a number that doesn't work , ie 'GDP ($US)' and 'Population' . But it is still good practice to show our intention to skip the first line. Because we all know: Explicit is better than implicit.

We use a defaultdict to avoid testing at first insert of year:

import collections
data = collections.defaultdict(dict)

for line in read_data:
    try:
        gdp = float(line[2]) / float(line[3])
    # Make sure this exception catches what you want.
    except (ValueError, ZeroDivisionError):
        continue
    data[line[0]][line[1]] = gdp

Now we get this for data :

{'Angola': {'2002': 1062.3788619684383, '2005': 2802.6651619200006},
 'Antigua and Barbuda': {'2002': 10595.981496856837,
                         '2005': 12743.391635866245},
 'Argentina': {'2002': 2661.023140961622, '2005': 4628.465370593508},
 'Armenia': {'2002': 788.4799626254804, '2005': 1643.6262756025671}}

We need to rearrange to get to your list:

list_data = []
for key, value in data.items():
    list_data.append([key] + [value[year] for year in sorted(value.keys())])

Result:

[['Antigua and Barbuda', 10595.981496856837, 12743.391635866245],
 ['Argentina', 2661.023140961622, 4628.465370593508],
 ['Angola', 1062.3788619684383, 2802.6651619200006],
 ['Armenia', 788.4799626254804, 1643.6262756025671]]

This solution works for any number of years and puts in them the chronological order.

EDIT

As it turns out, the data contains more than two years. I you don't want all years. Change the last section to include only the years you explicitly want:

list_data = []
for key, value in data.items():
    list_data.append([key] + [value[year] for year in ('2002', '2005')])

EDIT2

Small modification if year is missing as requested by the OP:

list_data = []
for key, value in data.items():
    list_data.append([key] + [value.get(year, 0) for year in ('2002', '2005')])

This puts in 0 if the year is missing. Use any suitable other value to indicate missing values.

EDIT3

Another variation as requested by the OP. No append if no value:

list_data = []
for key, value in data.items():
    list_data.append([key] + [value.get(year) for year in ('2002', '2005')
                              if value.get(year) is not None])