从文件中读取和获取包含数字和单词的数据集

Question

我正在尝试从文件中获取城市、州，然后获取指示区域的数字。然后，我需要对具有相同城市和州的另一个文件执行相同的操作，其中的数字表示人口，并以相同的格式创建人口密度文件。我不明白我应该如何去做这件事

我是 py 新手，没有很多编码经验，所以这就是我到目前为止所拥有的

这是人口txt文件：

Calico, California         12
Rhyolite, Nevada           3
Goldfield, Arizona         30
St. Elmo, Colorado         6
Terlingua, Texas           100
Virginia City, Montana     10
Nevada City, Montana       12
Bodie, California          45
Cahawba, Alabama           22
Kennecott, Alaska          2
Bannack, Montana           233
South Pass City, Wyoming   43
Centralia, Pennsylvania    6
Thurmond, West Virginia    55
Glenrio, Texas             1
Glenrio, New Mexico        1
Bulowville, Florida        54

这里是区域txt文件：

Calico, California         2
Rhyolite, Nevada           3
Goldfield, Arizona         12
St. Elmo, Colorado         4
Terlingua, Texas           10
Virginia City, Montana     15
Nevada City, Montana       6
Bodie, California          100
Cahawba, Alabama           20
Kennecott, Alaska          300
Bannack, Montana           23
South Pass City, Wyoming   3
Centralia, Pennsylvania    6
Thurmond, West Virginia    50
Glenrio, Texas             1
Glenrio, New Mexico        1
Bulowville, Florida        60

我知道我需要做一些事情：

OpenFile = open( Population.txt', 'r')

for EachLine in OpenFile:
    Split = EachLine.strip.split("   ")
    #some sort of append to a list but with the first part of split in one list and the number
    # nested in that  list

OpenFile.close()

Answer 1

考虑将您的任务分解为步骤并为每个步骤创建辅助函数：

from pathlib import Path


def read_data(filename: Path) -> dict[str, int]:
  """Reads data from a given filename and parses it into a dictionary.
  
  Expected file only has lines with 'City, State' followed by whitespace and a integer.

  Args:
    filename (Path): The path to the file to read.

  Returns:
    A dictionary where keys are 'City, State' and values are integers.
  """
  data = {}
  with open(filename, 'r') as file:
    for line in file:
      line = line.strip()
      if line:
        parts = line.rsplit(' ', 1)
        name = parts[0].strip()
        number = int(parts[1])
        data[name] = number
  return data


def calculate_density(population_data: dict[str, int],
                      area_data: dict[str, int]) -> dict[str, float]:
  """Calculates the population density by dividing the population by the area.

  Args:
    population_data: A dictionary of populations keyed by 'City, State'.
    area_data: A dictionary of areas keyed by 'City, State'.

  Returns:
    A dictionary of population densities keyed by 'City, State'.
  """
  return {
    city_state: population / area_data[city_state]
    for city_state, population in population_data.items()
    if city_state in area_data
  }


def write_data(filename: Path, data: dict[str, float]) -> None:
  """Writes data dict to a file after sorting, with each key-value pair on a new line.

  Args:
    filename: The path to the file where data will be written.
    data: The data to write, where each key-value pair is a line.
  """
  with open(filename, 'w') as file:
    for key, value in sorted(data.items()):
      file.write(f"{key} {value:.2f}\n")


def main() -> None:
  """Entry point of script."""
  write_data(filename=Path('density.txt'),
             data=calculate_density(
                 population_data=read_data(Path('population.txt')),
                 area_data=read_data(Path('area.txt')),
             ))


if __name__ == '__main__':
  main()

输出

density.txt

：

Bannack, Montana 10.13
Bodie, California 0.45
Bulowville, Florida 0.90
Cahawba, Alabama 1.10
Calico, California 6.00
Centralia, Pennsylvania 1.00
Glenrio, New Mexico 1.00
Glenrio, Texas 1.00
Goldfield, Arizona 2.50
Kennecott, Alaska 0.01
Nevada City, Montana 2.00
Rhyolite, Nevada 1.00
South Pass City, Wyoming 14.33
St. Elmo, Colorado 1.50
Terlingua, Texas 10.00
Thurmond, West Virginia 1.10
Virginia City, Montana 0.67