{ "id": 309093, "title": "Dealing with Datasize.", "url": "/competitions/h-and-m-personalized-fashion-recommendations/discussion/309093", "author_name": "", "post_date": "2022-02-21T20:24:10.658212100Z", "votes": 2, "comment_count": 4, "views": 0, "content": "

Hello everyone.
\nI was really looking forward the competition, however, after pre-processing the data and merging three files into one and after a few engineered columns i have a massive csv file of 14 GB.
\nI cant load the file in PC as I only have 16GB of RAM. Cant do it on google colab as well.
\nAny ideas as to how can I get around the problem.

", "messages": [ { "id": "1700311", "postDate": "02/21/2022 20:24:10", "content": "

Hello everyone.
\nI was really looking forward the competition, however, after pre-processing the data and merging three files into one and after a few engineered columns i have a massive csv file of 14 GB.
\nI cant load the file in PC as I only have 16GB of RAM. Cant do it on google colab as well.
\nAny ideas as to how can I get around the problem.

", "rawMarkdown": "Hello everyone. \nI was really looking forward the competition, however, after pre-processing the data and merging three files into one and after a few engineered columns i have a massive csv file of 14 GB.\nI cant load the file in PC as I only have 16GB of RAM. Cant do it on google colab as well.\nAny ideas as to how can I get around the problem.", "votes": null }, { "id": "1700318", "postDate": "02/21/2022 20:28:39", "content": "

Here are few discussions/comments that should help:
\nhttps://www.kaggle.com/c/h-and-m-personalized-fashion-recommendations/discussion/308635
\nhttps://www.kaggle.com/c/h-and-m-personalized-fashion-recommendations/discussion/307288 (general tips section)
\nhttps://www.kaggle.com/c/h-and-m-personalized-fashion-recommendations/discussion/308810

\n

In general, when you have a question, if you sort the discussions by \"most votes\", you'll often find that your question has been discussed already.

", "rawMarkdown": "Here are few discussions/comments that should help:\nhttps://www.kaggle.com/c/h-and-m-personalized-fashion-recommendations/discussion/308635\nhttps://www.kaggle.com/c/h-and-m-personalized-fashion-recommendations/discussion/307288 (general tips section)\nhttps://www.kaggle.com/c/h-and-m-personalized-fashion-recommendations/discussion/308810\n\nIn general, when you have a question, if you sort the discussions by \"most votes\", you'll often find that your question has been discussed already.", "votes": null }, { "id": "1700372", "postDate": "02/21/2022 22:21:45", "content": "

Thanks for the tip, will check before posting.

", "rawMarkdown": "Thanks for the tip, will check before posting.", "votes": null }, { "id": "1700373", "postDate": "02/21/2022 22:22:04", "content": "

I shared a notebook recently about that : https://www.kaggle.com/souamesannis/tips-to-work-efficiently-with-the-dataset

", "rawMarkdown": "I shared a notebook recently about that : https://www.kaggle.com/souamesannis/tips-to-work-efficiently-with-the-dataset", "votes": null }, { "id": "1700378", "postDate": "02/21/2022 22:39:48", "content": "

Thanks. This will do great for me.

", "rawMarkdown": "Thanks. This will do great for me.", "votes": null } ], "comments": [ { "id": 1700318, "author_name": "jacob34", "author_url": "", "post_date": "02/21/2022 20:28:39", "content": "

Here are few discussions/comments that should help:
\nhttps://www.kaggle.com/c/h-and-m-personalized-fashion-recommendations/discussion/308635
\nhttps://www.kaggle.com/c/h-and-m-personalized-fashion-recommendations/discussion/307288 (general tips section)
\nhttps://www.kaggle.com/c/h-and-m-personalized-fashion-recommendations/discussion/308810

\n

In general, when you have a question, if you sort the discussions by \"most votes\", you'll often find that your question has been discussed already.

", "votes": null, "replies": [ { "id": 1700372, "author_name": "sourabhpatel", "author_url": "", "post_date": "02/21/2022 22:21:45", "content": "

Thanks for the tip, will check before posting.

", "votes": null, "replies": [] } ] }, { "id": 1700373, "author_name": "souamesannis", "author_url": "", "post_date": "02/21/2022 22:22:04", "content": "

I shared a notebook recently about that : https://www.kaggle.com/souamesannis/tips-to-work-efficiently-with-the-dataset

", "votes": null, "replies": [ { "id": 1700378, "author_name": "sourabhpatel", "author_url": "", "post_date": "02/21/2022 22:39:48", "content": "

Thanks. This will do great for me.

", "votes": null, "replies": [] } ] } ], "raw_markdown_by_id": { "1700311": "Hello everyone. \nI was really looking forward the competition, however, after pre-processing the data and merging three files into one and after a few engineered columns i have a massive csv file of 14 GB.\nI cant load the file in PC as I only have 16GB of RAM. Cant do it on google colab as well.\nAny ideas as to how can I get around the problem.", "1700318": "Here are few discussions/comments that should help:\nhttps://www.kaggle.com/c/h-and-m-personalized-fashion-recommendations/discussion/308635\nhttps://www.kaggle.com/c/h-and-m-personalized-fashion-recommendations/discussion/307288 (general tips section)\nhttps://www.kaggle.com/c/h-and-m-personalized-fashion-recommendations/discussion/308810\n\nIn general, when you have a question, if you sort the discussions by \"most votes\", you'll often find that your question has been discussed already.", "1700372": "Thanks for the tip, will check before posting.", "1700373": "I shared a notebook recently about that : https://www.kaggle.com/souamesannis/tips-to-work-efficiently-with-the-dataset", "1700378": "Thanks. This will do great for me." }, "source": "meta" }