Welcome to OGeek Q&A Community for programmer and developer-Open, Learning and Share
Welcome To Ask or Share your Answers For Others

Categories

0 votes
485 views
in Technique[技术] by (71.8m points)

python - From Nested Dictionary to CSV File

I have nested dictionary (with length > 70.000):

users_item = {
    "sessionId1": {
        "12345645647": 1.0, 
        "9798654": 5.0 

    },         
    "sessionId2":{
        "3445657657": 1.0

    },
    "sessionId3": {
        "87967976": 5.0, 
        "35325626436": 1.0, 
        "126789435": 1.0, 
        "72139856": 5.0      
    },
    "sessionId4": {
        "4582317": 1.0         
    }
......
}

I want create CSV file from my nested dictionary, my result will look like:

sessionId1 item rating
sessionId1 item rating
sessionId2 item rating
sessionId3 item rating
sessionId3 item rating
sessionId3 item rating
sessionId3 item rating
.......

I found this post: Convert Nested Dictionary to CSV Table

It's similar to my question but it's not working when I try all answers, pandas library run out of memory

How I can make CSV file with my data?

See Question&Answers more detail:os

与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…
Welcome To Ask or Share your Answers For Others

1 Reply

0 votes
by (71.8m points)
for session, ratings in users_item.items():
    for rating, value in ratings.items():
        print("{} {}".format(session, value))

Output:

sessionId3 5.0
sessionId3 1.0
sessionId3 5.0
sessionId3 1.0
sessionId1 5.0
sessionId1 1.0
sessionId4 1.0
sessionId2 1.0

Note that a dict (user_items) has no order. So unless you specify the order of rows using some other way, the ouput will be in the order the dict uses internally.

Edit: This approach has no problems with a file containing 70k entries.

Edit: If you want to write to a CSV file, use the csv module or just pipe the output to a file.


与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…
OGeek|极客中国-欢迎来到极客的世界,一个免费开放的程序员编程交流平台!开放,进步,分享!让技术改变生活,让极客改变未来! Welcome to OGeek Q&A Community for programmer and developer-Open, Learning and Share
Click Here to Ask a Question

...