字典元组中的索引 python

Question

I have a tuple which its elements are dictionaries. ie

tuple=({"code":101,"assignment":'math',"credits":2},
       {"code":102,"assignment":'physics',"credits":3},
       {"code":103,"assignment":'chemistry',"credits":2},
       {"code":104,"assignment":'biology',"credits":5},
       {"code":105,"assignment":'science',"credits":1}

Then I want to check how many credits each student has, but first I would like to have a list the index where each code is

student1=[101,103]
student2=[102,104,105]

So I would like have

student1list=[1,3]
student1credits=4
student2list=[2,4,5]
student2credits=9

I can get those credits with 2 for like this

s1=[]
for i in range(len(student1)) :
  for j in range(len(tuple)) :
    if  student1[i]==tuple[j]['code'] :
      s1.append(tuple[j]['credits'])

student1credits=0
for k in range(len(s1)):
  student1credits=student1credits+s1[k]

print(student1credits)

But no idea of how to get the indexes

Answer 1

This feels like something where pandas would help out a lot.

import pandas as pd

tuple=({"code":101,"assignment":'math',"credits":2},
{"code":102,"assignment":'physics',"credits":3},
{"code":103,"assignment":'chemistry',"credits":2},
{"code":104,"assignment":'biology',"credits":5},
{"code":105,"assignment":'science',"credits":1})

my_data = pd.DataFrame(tuple)

my_data.head()

	code	assignment	credits
0	101	math	2
1	102	physics	3
2	103	chemistry	2
3	104	biology	5
4	105	science	1

Look up the codes for a student

student1=[101,103]
keep = my_data.code.isin(student1)
my_data[keep]

	code	assignment	credits
0	101	math	2
2	103	chemistry	2

Get just the index

student1=[101,103]
keep = my_data.code.isin(student1)
my_data[keep].index.values

array([0, 2], dtype=int64)

ps: Sorry, these index start at 0 instead of 1...hope that is ok. :)

An Extension...

Let's store our student-class relationship in pandas too, and do the look up/sum of credits.

student_class_relationships = pd.DataFrame(
    {'student_id': [1, 1, 2, 2, 2], 
     'code': [101, 102, 103, 104, 105]}
)

my_data \
    .merge(student_class_relationships, on='code') \
    .groupby('student_id') \
    .agg({'credits': 'sum'})

student_id	credits
1	5
2	8

Answer 2

You can use list comprehension with enumerate .

tuple_credits = ({"code":101,"assignment":'math',"credits":2},{"code":102,"assignment":'physics',"credits":3},{"code":103,"assignment":'chemistry',"credits":2},{"code":104,"assignment":'biology',"credits":5},{"code":105,"assignment":'science',"credits":1})

code_to_idx = {x['code']: i for i, x in enumerate(tuple_credits)}

def idx_and_credits(student):
    idx = [code_to_idx[c] for c in student]
    cred = sum(tuple_credits[i]['credits'] for i in idx)
    return idx, cred

student1list, student1credits = idx_and_credits([101, 103])
student2list, student2credits = idx_and_credits([101, 103, 101, 105])

print(student1list, student1credits) # [0, 2] 4
print(student2list, student2credits) # [0, 2, 0, 4] 7

In Python, index starts with 0, so student1list would be [0, 2] instead of [1, 3] . Also I renamed tuple to tuple_credits , as tuple is a built-in function.