英文:
Create numpy array from panda daataframe inside a For loop
问题
以下是翻译好的代码部分：
让我们假设我有以下的数据框：
data = {"Names": ["Ray", "John", "Mole", "Smith", "Jay", "Marc", "Tom", "Rick"],
"Sports": ["Soccer", "Judo", "Tenis", "Judo", "Tenis","Soccer","Judo","Tenis"]}
我想要使用一个循环，对于每个独特的运动项目，我可以获取一个包含参与该运动项目的人的numpy数组。在伪代码中，可以解释为：
for unique sport in sports:
nArray = 包含练习该运动的人的numpy数组
---------
对nArray执行某些操作
-------
请注意，代码中的伪代码部分没有被翻译，只有注释和字符串被翻译。
英文:
Lets say that i have the following dataframe:
data = {"Names": ["Ray", "John", "Mole", "Smith", "Jay", "Marc", "Tom", "Rick"],
"Sports": ["Soccer", "Judo", "Tenis", "Judo", "Tenis","Soccer","Judo","Tenis"]}
I want to have a for loop like that for each unique Sport i am able to retrieve a numpy array containing the Names of people playing that sport. In pseudo code that can be explainded as
for unique sport in sports:
nArray= numpy array of names of people practicing sport
---------
Do something with nArray
-------
答案1
得分: 0
使用 GroupBy.apply 与 np.array：
df = pd.DataFrame(data)
s = df.groupby('Sports')['Names'].apply(np.array)
print (s)
Sports
Judo [John, Smith, Tom]
Soccer [Ray, Marc]
Tenis [Mole, Jay, Rick]
Name: Names, dtype: object
for sport, name in s.items():
print (name)
['John' 'Smith' 'Tom']
['Ray' 'Marc']
['Mole' 'Jay' 'Rick']
英文:
Use GroupBy.apply with np.array:
df = pd.DataFrame(data)
s = df.groupby('Sports')['Names'].apply(np.array)
print (s)
Sports
Judo [John, Smith, Tom]
Soccer [Ray, Marc]
Tenis [Mole, Jay, Rick]
Name: Names, dtype: object
for sport, name in s.items():
print (name)
['John' 'Smith' 'Tom']
['Ray' 'Marc']
['Mole' 'Jay' 'Rick']
答案2
得分: 0
一种方法是
df = pd.DataFrame(data)
for sport in df.Sports.unique():
list_of_names = list(df[df.Sports == sport].Names)
data = np.array(list_of_names)
英文:
one way to go
df = pd.DataFrame(data)
for sport in df.Sports.unique():
list_of_names = list(df[df.Sports == sport].Names)
data = np.array(list_of_names)
答案3
得分: 0
import numpy as np
import pandas as pd
data = {"Names": ["Ray", "John", "Mole", "Smith", "Jay", "Marc", "Tom", "Rick"],
"Sports": ["Soccer", "Judo", "Tenis", "Judo", "Tenis", "Soccer", "Judo", "Tenis"]}
df = pd.DataFrame(data)
unique_sports = df['Sports'].unique()
for sport in unique_sports:
uniqueNames = np.array(df[df['Sports'] == sport]['Names'])
print(uniqueNames)
Result:
['Mole' 'Jay' 'Rick']
英文:
You can do by pandas library for get list array of sport persons name.
import numpy as np
import pandas as pd
data = {"Names": ["Ray", "John", "Mole", "Smith", "Jay", "Marc", "Tom", "Rick"],
"Sports": ["Soccer", "Judo", "Tenis", "Judo", "Tenis","Soccer","Judo","Tenis"]}
df = pd.DataFrame(data)
unique_sports = df['Sports'].unique()
for sport in unique_sports:
uniqueNames = np.array(df[df['Sports'] == sport]['Names'])
print(uniqueNames)
Result :
['Mole' 'Jay' 'Rick']
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