I'm using python3 and and i have data set. That contains the following data. I'm trying to get the desire value from this data list. I have tried many ways but unable to figure out how to do that.
slots_data = [
{
"id":551,
"user_id":1,
"time":"199322002",
"expire":"199322002"
},
{
"id":552,
"user_id":1,
"time":"199322002",
"expire":"199322002"
},
{
"id":525,
"user_id":3,
"time":"199322002",
"expire":"199322002"
},
{
"id":524,
"user_id":3,
"time":"199322002",
"expire":"199322002"
},
{
"id":553,
"user_id":1,
"time":"199322002",
"expire":"199322002"
},
{
"id":550,
"user_id":2,
"time":"199322002",
"expire":"199322002"
}
]
# Desired output
# [
# {"user_id":1,"slots_ids":[551,552,553]}
# {"user_id":2,"slots_ids":[550]}
# {"user_id":3,"slots_ids":[524,525]}
# ]
I have tried in the following way and obviously this is not correct. I couldn't figure out the solution of this problem :
final_list = []
for item in slots_data:
obj = obj.dict()
obj = {
"user_id":item["user_id"],
"slot_ids":item["id"]
}
final_list.append(obj)
print(set(final_list))
CodePudding user response：
The other answer added here has a nice solution, but here's one without using pandas:
users = {}
for item in slots_data:
# Check if we've seen this user before,
if item['user_id'] not in users:
# if not, create a new entry for them
users[item['user_id']] = {'user_id': item['user_id'], 'slot_ids': []}
# Add their slot ID to their dictionary
users[item['user_id']]['slot_ids'].append(item['id'])
# We only need the values (dicts)
output_list = list(users.values())
CodePudding user response：
I would say try using pandas to group the user id's together and convert it back to a dictionary
pd.DataFrame(slots_data).groupby('user_id')['id'].agg(list).reset_index().to_dict('records')
[{'user_id': 1, 'id': [551, 552, 553]},
{'user_id': 2, 'id': [550]},
{'user_id': 3, 'id': [525, 524]}]
CodePudding user response：
thriough just simple loop way
>>> result = {}
>>> for i in slots_data:
... if i['user_id'] not in result:
... result[i['user_id']] = []
... result[i['user_id']].append(i['id'])
...
>>> output = []
>>> for i in result:
... dict_obj = dict(user_id=i, slots_id=result[i])
... output.append(dict_obj)
...
>>> output
[{'user_id': 1, 'slots_id': [551, 552, 553]}, {'user_id': 3, 'slots_id': [525, 524]}, {'user_id': 2, 'slots_id': [550]}]
CodePudding user response：
You can use the following to get it done. Purely Python. Without any dependencies.
slots_data = [
{
"id":551,
"user_id":1,
"time":"199322002",
"expire":"199322002"
},
{
"id":552,
"user_id":1,
"time":"199322002",
"expire":"199322002"
},
{
"id":525,
"user_id":3,
"time":"199322002",
"expire":"199322002"
},
{
"id":524,
"user_id":3,
"time":"199322002",
"expire":"199322002"
},
{
"id":553,
"user_id":1,
"time":"199322002",
"expire":"199322002"
},
{
"id":550,
"user_id":2,
"time":"199322002",
"expire":"199322002"
}
]
user_wise_slots = {}
for slot_detail in slots_data:
if not slot_detail["user_id"] in user_wise_slots:
user_wise_slots[slot_detail["user_id"]] = {
"user_id": slot_detail["user_id"],
"slot_ids": []
}
user_wise_slots[slot_detail["user_id"]]["slot_ids"].append(slot_detail["id"])
print(user_wise_slots.values())
CodePudding user response：
Lots of good answers here.
If I was doing this, I would base my answer on setdefault and/or collections.defaultdict that can be used in a similar way. I think the defaultdict version is very readable but if you are not already importing collections you can do without it.
Given your data:
slots_data = [
{
"id":551,
"user_id":1,
"time":"199322002",
"expire":"199322002"
},
{
"id":552,
"user_id":1,
"time":"199322002",
"expire":"199322002"
},
#....
]
You can reshape it into your desired output via:
reshaped = {}
for slot in slots_data:
reshaped.setdefault(slot["user_id"],{ # return the value for this key if it exists...
"user_id": slot["user_id"], # otherwise set it to a default value and return it
"slots_ids":[]
})["slots_ids"].append(slot["id"]) # given the returned value, append our new data to the sub-key
## Now the sub-key lists can be sorted in-place via
for slot in reshaped.values():
slot["slots_ids"].sort()
print(list(reshaped.values()))
Giving you:
[
{'user_id': 1, 'slots_ids': [551, 552, 553]},
{'user_id': 3, 'slots_ids': [524, 525]},
{'user_id': 2, 'slots_ids': [550]}
]
If you need the items in the main list also sorted in "key" order for some reason you can also tack on:
reshaped = sorted(reshaped.values(),key=lambda x: x["user_id"])
print(reshaped)
That will give you:
[
{'user_id': 1, 'slots_ids': [551, 552, 553]},
{'user_id': 2, 'slots_ids': [550]},
{'user_id': 3, 'slots_ids': [524, 525]}
]
CodePudding user response：
This can be made in a using listcomprehension:
final_list = [{"user_id": user_id, "id":sorted([slot["id"] for slot in slots_data if slot["user_id"] == user_id])} for user_id in sorted(set([slot["user_id"] for slot in slots_data]))]
A more verbose and better formatted version of the same code:
all_user_ids = [slot["user_id"] for slot in slots_data]
unique_user_ids = sorted(set(all_user_ids))
final_list = [
{
"user_id": user_id,
"id": sorted([slot["id"] for slot in slots_data if slot["user_id"] == user_id])
}
for user_id in unique_user_ids]
Explanation:
- get all the user ids with list comprehension
- get the unique user ids by creating a set
- create the final list of dictionaries using list comprehension.
- each field
idis of itself a list with list comprehension. We get the id of the slot, and only add it to the list, if the user ids match
CodePudding user response：
Using pandas you can easily achieve the result. First install pandas if you don't have as follow
pip install pandas
import pandas as pd
df = pd.DataFrame(slots_data) #create dataframe
df1 = df.groupby("user_id")['id'].apply(list).reset_index(name="slots_ids") #groupby on user_id and combine elements of id in list and give the column name is slots_ids
final_slots_data = df1.to_dict('records') # convert dataframe into a list of dictionary
final_slots_data
Output:
[{'user_id': 1, 'slots_ids': [551, 552, 553]},
{'user_id': 2, 'slots_ids': [550]},
{'user_id': 3, 'slots_ids': [525, 524]}]