从csv文件中以嵌套的字典格式分别计数男性和女性
从csv文件中以嵌套的字典格式分别计数男性和女性
提问于 2021-06-14 20:58:22
这段代码运行良好，并以这种格式打印结果。
我需要像这样的嵌套字典格式的结果。
data = {
'year': {
'male': {'Q1': 1, 'Q2': 1, 'Q3': 1, 'Q4': 1, },
'female': { 'Q1': 1, 'Q2': 1, 'Q3': 1, 'Q4': 1, }
}
}代码：
import csv
results = {'males': {}, 'females': {}}
with open('1000 Records.csv') as csv_file:
csv_reader = csv.reader(csv_file)
for row in csv_reader:
year_of_joining = int(row[17])
quarter_of_joining = row[15]
gender = 'males' if row[5] == 'M' else 'females'
if year_of_joining not in results[gender]:
results[gender][year_of_joining] = {f'Q{i + 1}': 0 for i in range(4)}
results[gender][year_of_joining][quarter_of_joining] += 1
years = list(results['males'].keys()) + list(results['females'].keys())
years = sorted(list(set(years)))
for year in years:
count = [results['males'].get(year, 0), results['females'].get(year, 0)]
print("Male's and Female's: %s: %s" % (year, count))回答 3
Stack Overflow用户
回答已采纳
发布于 2021-06-15 01:13:26
这是一个有效的解决方案：
import csv
import collections
data= {}
with open('1000 Records.csv') as csv_file:
csv_reader = csv.reader(csv_file)
for row in csv_reader:
year_of_joining = int(row[17])
quarter_of_joining = row[15]
gender = 'male' if row[5] == 'M' else 'female'
if year_of_joining not in data:
data[year_of_joining]={'male': {f'Q{i + 1}': 0 for i in range(4)}, 'female': {f'Q{i + 1}': 0 for i in range(4)}}
data[year_of_joining][gender][quarter_of_joining] += 1
data = collections.OrderedDict(sorted(data.items())) # sorting
for year in data:
print("Male's and Female's: %s: %s" % (year, data[year]))上面代码中唯一的区别是它给出的输出格式略有不同，但我怀疑这可能是您首先想要的：
Male's and Female's: 1993: {'male': {'Q1': 0, 'Q2': 0, 'Q3': 0, 'Q4': 1}, 'female': {'Q1': 0, 'Q2': 0, 'Q3': 0,
'Q4': 0}}
Male's and Female's: 1998: {'male': {'Q1': 0, 'Q2': 0, 'Q3': 0, 'Q4': 1}, 'female': {'Q1': 0, 'Q2': 0, 'Q3': 0,
'Q4': 0}}
Male's and Female's: 1999: {'male': {'Q1': 0, 'Q2': 1, 'Q3': 1, 'Q4': 0}, 'female': {'Q1': 0, 'Q2': 0, 'Q3': 0,
'Q4': 1}}
Male's and Female's: 2001: {'male': {'Q1': 0, 'Q2': 0, 'Q3': 0, 'Q4': 0}, 'female': {'Q1': 1, 'Q2': 0, 'Q3': 0,
'Q4': 0}}
Male's and Female's: 2003: {'male': {'Q1': 0, 'Q2': 0, 'Q3': 0, 'Q4': 0}, 'female': {'Q1': 0, 'Q2': 0, 'Q3': 0,
'Q4': 1}}如果没有，请让我知道，我会修改它。
Stack Overflow用户
发布于 2021-06-15 00:06:30
你已经很接近了。在你的for year in years之外，保留一个字典来存储每年计数的运行结果：
data = {}
for year in years:
data[year] = {'male':results['males'].get(year, 0),
'female':results['females'].get(year, 0)}Stack Overflow用户
发布于 2021-06-15 01:19:02
我在本应“正常工作”的代码中遇到了一些错误，因此我也修复了这些错误，并在此过程中对其进行了一些优化。下面是使用我为测试目的创建的简单示例CSV文件的结果：
import csv
from pprint import pprint
#YOJ, QOJ, GEN = 17, 15, 3
YOJ, QOJ, GEN = 0, 1, 2 # For testing since no sample CSV provided.
results = {'males': {}, 'females': {}}
with open('1000 Records.csv') as csv_file:
for row in csv.reader(csv_file):
year_of_joining = int(row[YOJ])
quarter_of_joining = int(row[QOJ])
gender = 'males' if row[GEN] == 'M' else 'females'
if year_of_joining not in results[gender]:
results[gender][year_of_joining] = {f'Q{i + 1}': 0 for i in range(4)}
QOJ_key = f'Q{quarter_of_joining+1}' # Convert to dict key format.
results[gender][year_of_joining][QOJ_key] += 1
years = sorted(results['males'].keys() | results['females'].keys())
data = {year: {'males': results['males'][year],
'females': results['females'][year]}
for year in years}
pprint(data, sort_dicts=False)示例输出：
{1980: {'males': {'Q1': 0, 'Q2': 1, 'Q3': 1, 'Q4': 0},
'females': {'Q1': 0, 'Q2': 0, 'Q3': 1, 'Q4': 0}},
1981: {'males': {'Q1': 0, 'Q2': 0, 'Q3': 1, 'Q4': 0},
'females': {'Q1': 0, 'Q2': 0, 'Q3': 0, 'Q4': 2}}}页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/67970674
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