我需要代码方面的帮助，该代码从我拥有的大型csv文件中获取用户输入的他们想要的特定列。在他们自己键入所需的列后，他们还必须键入整数输入。该整数输入将为他们提供该列出现次数最少的结果数。例如，如果他们输入：hospital_name"5"，它将向他们显示 5 家不同的医院(该列下至少有 50 家不同的医院名称(，这些医院的计数与他们并列最低。我将编写一个示例输入和输出：
键入所需的列：hospital_name 输入您想要的最低结果数：3
输出可能如下所示：
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的次数并报告(大多数计数较低(
我已经使用"with"读取了我的csv文件
我在制作连接所有这些的循环时遇到麻烦。 我知道用户输入本身将是input((和int(input(((，但这并不能将我连接回csv文件。
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
由逗号分隔的CSV数据组成，包含三列：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
运行示例：
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
使用插入排序更新查找最大值
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()}")