在我的代码中，用户输入一个文本文件。文本文件包含4列，行数将随加载的文本文件而变化，因此代码必须是通用的。从文本文件生成的数组的第一列包含一种动物类型，第二列是它在字段中的X位置，第三列是它的Y位置，第四列是字段中的动物Z位置。加载数据如果你不想按照链接到数据图片，这里是加载数据的代码和返回的数组的副本：
#load the data
emplaced_animals_data = np.genfromtxt('animal_data.txt', skip_header = 1, dtype = str)
print(type(emplaced_animals_data))
print(emplaced_animals_data)
[['butterfly' '1' '1' '3']
['butterfly' '2' '2' '3']
['butterfly' '3' '3' '3']
['dragonfly' '4' '1' '1']
['dragonfly' '5' '2' '1']
['dragonfly' '6' '3' '1']
['cat' '4' '4' '2']
['cat' '5' '5' '2']
['cat' '6' '6' '2']
['cat' '7' '8' '3']
['elephant' '8' '9' '3']
['elephant' '9' '10' '4']
['elephant' '10' '10' '4']
['camel' '10' '11' '5']
['camel' '11' '6' '5']
['camel' '12' '5' '6']
['camel' '12' '3' '6']
['bear' '13' '13' '7']
['bear' '5' '15' '7']
['bear' '4' '10' '5']
['bear' '6' '9' '2']
['bear' '15' '13' '1']
['dog' '1' '3' '9']
['dog' '2' '12' '8']
['dog' '3' '10' '1']
['dog' '4' '8' '1']]
数据加载后，数据中总会有两种动物我们不想知道，所以我从第一列中删除了这些动物的名称，但我不确定如何从整行中删除数据。我如何将数据的选择从动物类型扩展到其位置，并为不想要的动物删除它？我已经包含了一些图像来显示我目前所做的工作的输出。移除不需要的动物
#Removes unwanted animals from list
print('Original list:', emplaced_animals_data[:,0])
all_the_animals = list(emplaced_animals_data[:,0])
Butterfly = set('butterfly')
Dragonfly = set('dragonfly')
for i in range(0, len(emplaced_animals_data)):
for animal in all_the_animals:
if Butterfly == set(animal):
all_the_animals.remove(animal)
if Dragonfly == set(animal):
all_the_animals.remove(animal)
print('Updated list:', words)
接下来，我想取剩下的动物，将每只动物及其位置数据排序到自己的数组中，该数组将保存为一些变量，但目前我只能将动物类型排序到它们自己的数组。我该如何扩展我对动物的选择，以纳入它们的位置，并根据动物类型将动物和它们的位置保存到自己的阵列中？动物分组
#Groups all of the items with the same name together
setofanimals = set(all_the_animals)
animal_groups = {}
for one in setofanimals:
ids = [one for i in emplaced_animals_data[:,0] if i == one]
animal_groups.update({one:ids})
for one in animal_groups:
print(one, ":", animal_groups[one])
我的最终目标是能够绘制每种动物的每次出现，而不管加载的文本文件是什么。
这是我正在处理的数据，从Excel电子表格中复制，我将其保存为文本文件：
数据
以下函数应该可以实现这一点。您输入的txt可以是任意长度的，两个函数都会根据所述列表中包含的动物来删除或选择动物列表：
import numpy as np
# note that my delimiter is a tab, which might be different from yours
emplaced_animals = np.genfromtxt('animals.txt', skip_header=1, dtype=str, delimiter=' ')
listed_animals = ['cat', 'dog', 'bear', 'camel', 'elephant']
def get_specific_animals_from(list_of_all_animals, specific_animals):
"""get a list only containing rows of a specific animal"""
list_of_specific_animals = np.array([])
for specific_animal in specific_animals:
for animal in list_of_all_animals:
if animal[0] == specific_animal:
list_of_specific_animals = np.append(list_of_specific_animals, animal, 0)
return list_of_specific_animals
def delete_specific_animals_from(list_of_all_animals, bad_animals):
"""
delete all rows of bad_animal in provided list
takes in a list of bad animals e.g. ['dragonfly', 'butterfly']
returns list of only desired animals
"""
all_useful_animals = list_of_all_animals
positions_of_bad_animals = []
for n, animal in enumerate(list_of_all_animals):
if animal[0] in bad_animals:
positions_of_bad_animals.append(n)
if len(positions_of_bad_animals):
for position in sorted(positions_of_bad_animals, reverse=True):
# reverse is important
# without it, list positions change as you delete items
all_useful_animals = np.delete(all_useful_animals, (position), 0)
return all_useful_animals
emplaced_animals = delete_specific_animals_from(emplaced_animals, ['dragonfly', 'butterfly'])
list_of_elephants = get_specific_animals_from(emplaced_animals, ['elephant'])
list_of_needed_animals = get_specific_animals_from(emplaced_animals, listed_animals)
我不知道这是否正是你想要的，但请看一看。首先，对于您的评论，您可能必须将分隔符更改为","或";"。该代码经过测试，与逗号分隔的文本文件配合使用效果良好
输入(.txt(：
Animals,Xlocation,Ylocation,Zlocation
butterfly,1,1,3
butterfly,2,2,3
butterfly,3,3,3
dragonfly,4,1,1
dragonfly,5,2,1
dragonfly,6,3,1
cat,4,4,2
cat,5,5,2
cat,6,6,2
cat,7,8,3
elephant,8,9,3
elephant,9,10,4
elephant,10,10,4
camel,10,11,5
camel,11,6,5
camel,12,5,6
camel,12,3,6
bear,13,13,7
bear,5,15,7
bear,4,10,5
bear,6,9,2
bear,15,13,1
dog,1,3,9
dog,2,12,8
dog,3,10,1
dog,4,8,1
代码：
def main():
result = readFile("C:\Users\Desktop\animals.txt")
# Array of animals to remove from main list
to_remove = ["butterfly", "dragonfly"]
# returns a new list with all rows except the 'to_remove animals'
useful_animals = [one for one in result if one["Animals"] not in to_remove]
cats = get_animal_group(useful_animals, "cat")
camels = get_animal_group(useful_animals, "camel")
# returns a new list with all rows where animals_list match given animal
def get_animal_group(animal_list, animal):
return [one for one in animal_list if one["Animals"] == animal]
def readFile(path):
# From this you get a list of dict which is much easier to handle
result = pandas.read_csv(path, encoding="utf-8",
usecols=["Animals", "Xlocation", "Ylocation", "Zlocation"]).to_dict("records")
return result
输出：
# for animal in useful_animals:
{'Animals': 'cat', 'Xlocation': 4, 'Ylocation': 4, 'Zlocation': 2.0}
{'Animals': 'cat', 'Xlocation': 5, 'Ylocation': 5, 'Zlocation': 2.0}
{'Animals': 'cat', 'Xlocation': 6, 'Ylocation': 6, 'Zlocation': 2.0}
{'Animals': 'cat', 'Xlocation': 7, 'Ylocation': 8, 'Zlocation': 3.0}
{'Animals': 'elephant', 'Xlocation': 8, 'Ylocation': 9, 'Zlocation': 3.0}
{'Animals': 'elephant', 'Xlocation': 9, 'Ylocation': 10, 'Zlocation': 4.0}
{'Animals': 'elephant', 'Xlocation': 10, 'Ylocation': 10, 'Zlocation': 4.0}
{'Animals': 'camel', 'Xlocation': 10, 'Ylocation': 11, 'Zlocation': 5.0}
{'Animals': 'camel', 'Xlocation': 11, 'Ylocation': 6, 'Zlocation': 5.0}
{'Animals': 'camel', 'Xlocation': 12, 'Ylocation': 5, 'Zlocation': 6.0}
{'Animals': 'camel', 'Xlocation': 12, 'Ylocation': 3, 'Zlocation': 6.0}
{'Animals': 'bear', 'Xlocation': 13, 'Ylocation': 13, 'Zlocation': 7.0}
{'Animals': 'bear', 'Xlocation': 5, 'Ylocation': 15, 'Zlocation': 7.0}
{'Animals': 'bear', 'Xlocation': 4, 'Ylocation': 10, 'Zlocation': 5.0}
{'Animals': 'bear', 'Xlocation': 6, 'Ylocation': 9, 'Zlocation': 2.0}
{'Animals': 'bear', 'Xlocation': 15, 'Ylocation': 13, 'Zlocation': 1.0}
{'Animals': 'dog', 'Xlocation': 1, 'Ylocation': 3, 'Zlocation': 9.0}
{'Animals': 'dog', 'Xlocation': 2, 'Ylocation': 12, 'Zlocation': 8.0}
{'Animals': 'dog', 'Xlocation': 3, 'Ylocation': 10, 'Zlocation': 1.0}
{'Animals': 'dog', 'Xlocation': 4, 'Ylocation': 8, 'Zlocation': 1.0}
# for cat in cats:
{'Animals': 'cat', 'Xlocation': 4, 'Ylocation': 4, 'Zlocation': 2.0}
{'Animals': 'cat', 'Xlocation': 5, 'Ylocation': 5, 'Zlocation': 2.0}
{'Animals': 'cat', 'Xlocation': 6, 'Ylocation': 6, 'Zlocation': 2.0}
{'Animals': 'cat', 'Xlocation': 7, 'Ylocation': 8, 'Zlocation': 3.0}
如果您还有其他问题，请随时询问(评论(
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