从 csv 文件中提取用户输入的特定列的数据（无熊猫）

Question

我需要一个代码帮助，该代码从我拥有的大型 csv 文件中获取用户想要的特定列的输入。 在他们自己输入他们想要的列之后，他们还必须输入 integer 输入。 integer 输入将为他们提供该列的最低出现次数的结果。 例如，如果他们键入：hospital_name, "5"，它将向他们显示 5 个不同的医院（该列下至少有 50 个不同的医院名称），这些医院的数量最少。 我将编写一个示例输入和 output：

输入您想要的列：hospital_name 输入您想要的最低结果数：3

output 可能如下所示：

                      400 births are tied to Gains Hospital                                                                            
                      347 births are tied to Petri Hospital 
                      200 births are tied to Brit Hospital 

整个 csv 是关于出生的报告，因此您必须计算每个项目在每列中出现的次数并报告（最低计数）

我已经使用“with”阅读了我的 csv 文件

我无法使循环连接所有这些。 我知道用户输入本身将是 input() 和 int(input())，但这并没有将我连接回 csv 文件。

Answer 1

代码

import csv

column_name = input('Which column: ').upper()
number_lowest = int(input('How many lowest: '))

# Calculate births by specified column name
with open("data.csv", "r") as f:
  reader = csv.DictReader(f, skipinitialspace=True, delimiter=",")
  births_count = {}
  for d in reader:
    # Use column_name as key
    # accumulate births for this key
    if not d[column_name] in births_count:
      births_count[d[column_name]] = 0
    births_count[d[column_name]] += 1 # since each row is a different birth

# Find number_lowest lowest births
lowest_births = {}
for i in range(number_lowest):
  # By looping number_lowest times, 
  # we find this many lowest values
  if len(births_count) > 0:
    # find lowest births
    lowest_val = 1e37 # just use a large number
                      # that we know actual
                      # count will be less than

    lowest_name = ""
    for name, value in births_count.items():
      if value < lowest_val:
        lowest_val = value
        lowest_name = name

    # Add to lowest births
    lowest_births[lowest_name] = lowest_val

    # remove from births_count
    # this reduces count of items in dictionary
    del births_count[lowest_name]
  else:
    break  # births_count is empty

# Output results
for name, births in lowest_births.items():
  print(f"{births} births are tied to {name} {column_name.title()}")

测试

用逗号分隔的 CSV 数据组成三列：出生、医院、位置

File: data.csv

HOSPITAL_NAME,BIRTH_DAY, BIRTH_YEAR, BIRTH_WEIGHT
Gains,1/14,2015,8.5 lbs
Mayo Clinic,2/11,2018,6.5 lbs
Gains,1/15,2016,8.9 lbs
Stanford Health Care,2/15,2016,7.4 lbs
Mayo Clinic,11/10,2018,7.3 lbs
Gains,1/09,2011,7.5 lbs
John Hopkins,12/23,2012,6.9 lbs
Massachusetts General,9/14,2001,8.3 lbs
Stanford Health Care,8/17,2005,7.6 lbs
Massachusetts General,7/18,2016,8.7 lbs
John Hopkins,3/11,2017,7.2 lbs
Massachusetts General,4/16,2014,7.4 lbs
Northwestern Memorial,10/12,2012,8.3 lbs
UCLA Medical Center,9/19,2011,8.1 lbs
Petri,11/21,2003,7.5 lbs
UCSF Medical Center,2/15,2004,7.9 lbs

示例运行：

Which column: hospital_name
How many lowest: 5
HOSPITAL_NAME
1 births are tied to Northwestern Memorial Hospital_Name
1 births are tied to UCLA Medical Center Hospital_Name
1 births are tied to Petri Hospital_Name
1 births are tied to UCSF Medical Center Hospital_Name
2 births are tied to Mayo Clinic Hospital_Name

使用插入排序更新 Find Max

import csv

# Source: https://www.geeksforgeeks.org/python-program-for-insertion-sort/
def insertionSort(arr): 
  " Inplace location sort "
  # Traverse through 1 to len(arr) 
  for i in range(1, len(arr)): 
    key = arr[i] 
    # Move elements of arr[0..i-1], that are 
    # greater than key, to one position ahead 
    # of their current position 
    j = i-1
    while j >=0 and key < arr[j] : 
            arr[j+1] = arr[j] 
            j -= 1
    arr[j+1] = key

def find_maxs_by_sort(data, number):
  """ Finds extreems of mins or max's 
      depending upn bLowest flag
  """

  # Get list of key, value pairs as tuples of (value, key)
  tuple_list = []
  for k, v in data.items():
    tuple_list.append((v, k))

  # Sort will be in ascending order
  # Does an inplace sort
  # insertSort also works on array of tuples
  # Will sort by v since it's first in the each tuple
  insertionSort(tuple_list)

  # Place sorted tuples back as a dictionary
  # tuples are sorted by [(v1, k1), (v2, k2), ...]
  # We start at the end and work backwards since sort is
  # in ascending order
  n = len(tuple_list)
  results = {}
  for i in range(n-1, n - number - 1, -1):
    v, k = tuple_list[i]
    results[k] = v

  return results

for i in range(3):
  # To do this 3 times
  column_name = input('Which column: ').upper()
  number = int(input('How many maxs: '))

  with open("data.csv", "r") as f:
    reader = csv.DictReader(f, skipinitialspace=True, delimiter=",")
    births_count = {}
    for d in reader:
      # Use column_name as key
      # accumulate births for this key
      if not d[column_name] in births_count:
        births_count[d[column_name]] = 0
      births_count[d[column_name]] += 1 # since each row is a different birth

  # find max
  max_births = find_maxs_by_sort(births_count, number)

  # Output results
  for name, births in max_births.items():
    print(f"\t{births} births are tied to {name} {column_name.title()}")