Hello Guys, could you please let us a way to open the downloaded PARQUET files in our PC. Or is there any other way to open them in Kaggle itself?
", "messages": [ { "id": "3225378", "postDate": "06/16/2025 10:10:42", "content": "Hello Guys, could you please let us a way to open the downloaded PARQUET files in our PC. Or is there any other way to open them in Kaggle itself?
", "rawMarkdown": "Hello Guys, could you please let us a way to open the downloaded PARQUET files in our PC. Or is there any other way to open them in Kaggle itself?", "votes": null }, { "id": "3225404", "postDate": "06/16/2025 10:48:55", "content": "Use pandas, pd.read_parquet this should work. :)
", "rawMarkdown": "Use pandas, pd.read_parquet this should work. :)", "votes": null }, { "id": "3225503", "postDate": "06/16/2025 13:52:40", "content": "Thank you for your suggestion. Also, can't we download it as .csv? (Any conversion)
", "rawMarkdown": "Thank you for your suggestion. Also, can't we download it as .csv? (Any conversion)", "votes": null }, { "id": "3225534", "postDate": "06/16/2025 14:15:24", "content": "You can load it with pd.read_parquet then save df to csv with pd.to_csv.
", "rawMarkdown": "You can load it with pd.read_parquet then save df to csv with pd.to_csv.", "votes": null }, { "id": "3226825", "postDate": "06/18/2025 06:18:59", "content": "If you have conda install in your PC then you can do these things:
\nthen you can read the datasets using df = pd.read_parquet('train.parquet')
\n** HOPE THIS HELPS YOU **
", "rawMarkdown": "If you have conda install in your PC then you can do these things:\n\n1. You can add fastparquet to your env ( cmd>> conda install fastparquet)\n2. If you want to install it on your jupyter notebook use(cmd >> pip install fastparquet [OR] !pip install fastparquet)\n\nthen you can read the datasets using df = pd.read_parquet('train.parquet')\n\n** HOPE THIS HELPS YOU **", "votes": null }, { "id": "3226963", "postDate": "06/18/2025 10:05:05", "content": "You can open Parquet files both on your PC and within Kaggle Notebooks pretty easily.
\n On Kaggle:
\nJust use pandas:
\nimport pandas as pd
\ndf = pd.read_parquet('/kaggle/input/your-file.parquet')
\ndf.head()
On your PC:
\nIf you have Python installed:
\npip install pandas pyarrow
\nThen:
\nimport pandas as pd
\ndf = pd.read_parquet('your-file.parquet')
You can also convert to CSV if you prefer Excel, but that’s less efficient.
\nHope that helps!
Thanks mate. It's truly helpful.
", "rawMarkdown": "Thanks mate. It's truly helpful.", "votes": null }, { "id": "3226976", "postDate": "06/18/2025 10:17:59", "content": "Sure. Thanks for the suggestion. 😊
", "rawMarkdown": "Sure. Thanks for the suggestion. 😊", "votes": null } ], "comments": [ { "id": 3225404, "author_name": "aryamanvaishya", "author_url": "", "post_date": "06/16/2025 10:48:55", "content": "Use pandas, pd.read_parquet this should work. :)
", "votes": null, "replies": [ { "id": 3225503, "author_name": "venkytheknown", "author_url": "", "post_date": "06/16/2025 13:52:40", "content": "Thank you for your suggestion. Also, can't we download it as .csv? (Any conversion)
", "votes": null, "replies": [ { "id": 3225534, "author_name": "liondude", "author_url": "", "post_date": "06/16/2025 14:15:24", "content": "You can load it with pd.read_parquet then save df to csv with pd.to_csv.
", "votes": null, "replies": [ { "id": 3226976, "author_name": "venkytheknown", "author_url": "", "post_date": "06/18/2025 10:17:59", "content": "Sure. Thanks for the suggestion. 😊
", "votes": null, "replies": [] } ] } ] } ] }, { "id": 3226825, "author_name": "mahboobbiswas", "author_url": "", "post_date": "06/18/2025 06:18:59", "content": "If you have conda install in your PC then you can do these things:
\nthen you can read the datasets using df = pd.read_parquet('train.parquet')
\n** HOPE THIS HELPS YOU **
", "votes": null, "replies": [] }, { "id": 3226963, "author_name": "sanketpai", "author_url": "", "post_date": "06/18/2025 10:05:05", "content": "You can open Parquet files both on your PC and within Kaggle Notebooks pretty easily.
\n On Kaggle:
\nJust use pandas:
\nimport pandas as pd
\ndf = pd.read_parquet('/kaggle/input/your-file.parquet')
\ndf.head()
On your PC:
\nIf you have Python installed:
\npip install pandas pyarrow
\nThen:
\nimport pandas as pd
\ndf = pd.read_parquet('your-file.parquet')
You can also convert to CSV if you prefer Excel, but that’s less efficient.
\nHope that helps!
Thanks mate. It's truly helpful.
", "votes": null, "replies": [] } ] } ], "raw_markdown_by_id": { "3225378": "Hello Guys, could you please let us a way to open the downloaded PARQUET files in our PC. Or is there any other way to open them in Kaggle itself?", "3225404": "Use pandas, pd.read_parquet this should work. :)", "3225503": "Thank you for your suggestion. Also, can't we download it as .csv? (Any conversion)", "3225534": "You can load it with pd.read_parquet then save df to csv with pd.to_csv.", "3226825": "If you have conda install in your PC then you can do these things:\n\n1. You can add fastparquet to your env ( cmd>> conda install fastparquet)\n2. If you want to install it on your jupyter notebook use(cmd >> pip install fastparquet [OR] !pip install fastparquet)\n\nthen you can read the datasets using df = pd.read_parquet('train.parquet')\n\n** HOPE THIS HELPS YOU **", "3226963": "You can open Parquet files both on your PC and within Kaggle Notebooks pretty easily.\n On Kaggle:\nJust use pandas:\nimport pandas as pd\ndf = pd.read_parquet('/kaggle/input/your-file.parquet')\ndf.head()\n\n\n On your PC:\nIf you have Python installed:\npip install pandas pyarrow\nThen:\nimport pandas as pd\ndf = pd.read_parquet('your-file.parquet')\n\nYou can also convert to CSV if you prefer Excel, but that’s less efficient.\nHope that helps!", "3226974": "Thanks mate. It's truly helpful.", "3226976": "Sure. Thanks for the suggestion. 😊" }, "source": "meta" }