Question

我一直在尝试从此csv文件中提取数据并以某种方式组织它，以便可以更清楚地查看数据。目的是创建2个词典。一种用于保存来自csv中列出的区域的数据。另一个保存来自csv国家的数据。我在遍历数据时遇到麻烦。csv文件开始首先列出所有区域。直到“ ID”列达到第4位时，这些国家才开始成立，因此我需要组织这些帮助。到目前为止，我有这个。但是我仍然需要帮助根据地区和国家进行组织。链接到csv文件是： https://docs.google.com/document/d/1v68_QQX7Tn96l-b0LMO9YZ4ZAn_KWDMUJboa6LEyPr8/edit?usp=sharing

import csv

f = open('dph_SYB60_T03_Population Growth, Fertility and Mortality Indicators.csv')

reader = csv.DictReader(f)

data_by_region = {}
data_by_country = {}
answers = []


for line in reader:
  #Collects all the region names
  regions = line['Region/Country/Area'] 
  # Gets All the Years
  years = line['Year']
  # print(regions)



  if regions not in data_by_region:
    data_by_region[regions] = {}

Answer 1

也许这会有所帮助：

import csv

f = open('dph_SYB60_T03_Population Growth, Fertility and Mortality Indicators.csv', encoding='utf-8-sig')

reader = csv.DictReader(f)

data_by_region = {}
data_by_country = {}
answers = []

for line in reader:
    # Collects all the region names
    regions = line['Region/Country/Area']
    # Gets All the Years
    years = line['Year']
    # print(regions)

    if regions not in data_by_region:
        data_by_region[regions] = [line]
    else:
        data_by_region[regions].append(line)

# print data count group by regions.
for region, data_list in data_by_region.items():
    print('{:>30s}: {} rows.'.format(region, len(data_list)))

输出：

 Total, all countries or areas: 21 rows.
                        Africa: 18 rows.
               Northern Africa: 21 rows.
            Sub-Saharan Africa: 21 rows.
                Eastern Africa: 18 rows.
                 Middle Africa: 18 rows.
               Southern Africa: 18 rows.
                Western Africa: 18 rows.
              Northern America: 18 rows.
...

Answer 2

python具有内置功能groupby，可帮助您对数据进行分组，但是它需要您使用组密钥对列表进行排序，因此，如果要按Region/Country/Area进行分组，则需要对其进行排序第一。以下代码段应有助于快速将数据分组。

import csv
import itertools

def csv_iter(filepath):
    with open(filepath, mode="r", encoding="utf-8-sig") as f:
        reader = csv.DictReader(f)
        yield from reader

def main():
    filepath = "dph_SYB60_T03_Population Growth, Fertility and Mortality Indicators.csv"
    data_list = sorted(csv_iter(filepath), key=lambda x: x.get("Region/Country/Area", ""))
    for g, v in itertools.groupby(data_list, key=lambda x: x.get("Region/Country/Area", "")):
        print("{}: {}".format(g, len(list(v))))

if __name__ == "__main__":
    main()

输出：

Afghanistan: 21
Africa: 18
Albania: 21
Algeria: 21
American Samoa: 9
Andorra: 6
Angola: 21
Anguilla: 9
Antigua and Barbuda: 18
Argentina: 21
......

但是有一个与您对数据的理解有关的问题，并非所有区域ID都小于4，例如，Northern Africa的ID为15，因此您不能通过ID区分不同的地区和国家/地区，您需要找到所有名称并构建地区和国家/地区列表，然后才能区分一行是属于地区还是国家/地区。

CSV文件数据组织（结构化数据）

2 个答案: