Unable to unzip train.csv.zip.\nHas anyone faced this problem ?
", "messages": [ { "id": "466553", "postDate": "02/05/2019 15:58:22", "content": "Unable to unzip train.csv.zip.\nHas anyone faced this problem ?
", "rawMarkdown": "Unable to unzip train.csv.zip.\nHas anyone faced this problem ?", "votes": null }, { "id": "466601", "postDate": "02/05/2019 17:10:54", "content": "While the file appears as a .zip in the competition's Data Tab, when your kernel loads, Kaggle automatically extracts it and adds it's contents to your file-system. In most cases, a .zip of CSVs will end up being provided to the kernal as a single CSV. You can check what is available in your kernel by running from os import listdir; print(listdir(\"../input\")) which should result in the following output: ['test', 'train.csv', 'sample_submission.csv'] which includes train.csv, the file you're looking for. If we follow along with Harshit Holmes's notebook for this competition (published in this competition's Kernel Tab) we can see that the training data can be imported via the following code:
\nimport pandas as pd
\nimport numpy as np\ntrain = pd.read_csv('../input/train.csv', dtype={'acoustic_data': np.int16, 'time_to_failure': np.float32})\n
Hope that helps!
", "rawMarkdown": "While the file appears as a .zip in the competition's [Data Tab](https://www.kaggle.com/c/LANL-Earthquake-Prediction/data), when your kernel loads, Kaggle automatically extracts it and adds it's contents to your file-system. In most cases, a .zip of CSVs will end up being provided to the kernal as a single CSV. You can check what is available in your kernel by running `from os import listdir; print(listdir(\"../input\"))` which should result in the following output: `['test', 'train.csv', 'sample_submission.csv']` which includes *train.csv*, the file you're looking for. If we follow along with [Harshit Holmes](https://www.kaggle.com/harshitholmes)'s [notebook](https://www.kaggle.com/harshitholmes/testing-each-every-regressor-with-own-instances) for this competition (published in this competition's [Kernel Tab](https://www.kaggle.com/c/LANL-Earthquake-Prediction/kernels)) we can see that the training data can be imported via the following code: \n\n```\nimport pandas as pd \nimport numpy as np\ntrain = pd.read_csv('../input/train.csv', dtype={'acoustic_data': np.int16, 'time_to_failure': np.float32})\n```\n\nHope that helps!", "votes": null }, { "id": "467206", "postDate": "02/06/2019 16:20:27", "content": "Thanks a lot for your answer, Alec.
\n\nI still have a problem.\nI download LANL-Earthquake-Prediction.zip, by clicking on 'Download All'.\nMaybe this does not work.
", "rawMarkdown": "Thanks a lot for your answer, Alec.\n\nI still have a problem.\nI download LANL-Earthquake-Prediction.zip, by clicking on 'Download All'.\nMaybe this does not work.", "votes": null }, { "id": "467252", "postDate": "02/06/2019 17:46:31", "content": "You have to be a bit more specific for us to help you. What operating system do you use? Which program do you use to unzip? What do the log files say?\nIt would also be useful if the organizers published the checksum of the file to be sure that the downloaded copy is uncorrupted. Perhaps that can be achieved by using the Kaggle API, I don't know.
\n\nBy the way: you don't really have to download the data, you may also analyze it by writing your own private Kaggle kernel, which is then executed in the Kaggle cloud.
", "rawMarkdown": "You have to be a bit more specific for us to help you. What operating system do you use? Which program do you use to unzip? What do the log files say?\nIt would also be useful if the organizers published the checksum of the file to be sure that the downloaded copy is uncorrupted. Perhaps that can be achieved by using the Kaggle API, I don't know.\n\nBy the way: you don't really have to download the data, you may also analyze it by writing your own private Kaggle kernel, which is then executed in the Kaggle cloud.", "votes": null }, { "id": "467636", "postDate": "02/07/2019 13:05:11", "content": "@Daniel Gerigk\nI use a Mac, with macOS High Sierra.\nTo unzip, I use the tool provided by default (\"Utilitaire d'archive\", in French).\nI've got the message : \"impossible to uncompress LANL-Earthquake-Prediction.zip. (Error 2 : unexacting file or folder)\"\n(something like that, I translated it).\nI'm going to follow your advice and create my own private Kernel.\nThanks a lot.
", "rawMarkdown": "Daniel Gerigk\nI use a Mac, with macOS High Sierra.\nTo unzip, I use the tool provided by default (\"Utilitaire d'archive\", in French).\nI've got the message : \"impossible to uncompress LANL-Earthquake-Prediction.zip. (Error 2 : unexacting file or folder)\"\n(something like that, I translated it).\nI'm going to follow your advice and create my own private Kernel.\nThanks a lot.", "votes": null }, { "id": "467666", "postDate": "02/07/2019 14:28:29", "content": "If you use a Kaggle kernel directly linked to the Competition (or Dataset), it'll automatically have the data loaded in and will deal with .zip files for you.
", "rawMarkdown": "If you use a Kaggle kernel directly linked to the Competition (or Dataset), it'll automatically have the data loaded in and will deal with .zip files for you.", "votes": null }, { "id": "467720", "postDate": "02/07/2019 16:08:57", "content": "Yes, thank you both.\nIt goes well with a Kaggle kernel.
", "rawMarkdown": "Yes, thank you both.\nIt goes well with a Kaggle kernel.", "votes": null }, { "id": "470301", "postDate": "02/12/2019 18:17:53", "content": "When I click on the file in the finder in Mojave it runs the archive utility, and, all the way at the end it fails with Error 2, no such file or directory. Is that what you see?
\n\nThe solution that has always worked for me in this case is to run unzip on the command line (from a Terminal). This works fine.
\n\nI think that MacOS's archive utility is unhappy with zip files over 2G.
\n\n$ unzip all.zip \nArchive: all.zip\n inflating: sample_submission.csv
\n inflating: test.zip
\n inflating: train.csv
\n$
Yes, that was the same for me.\nI will try your solution.\nThanks a lot.
", "rawMarkdown": "Yes, that was the same for me.\nI will try your solution.\nThanks a lot.", "votes": null } ], "comments": [ { "id": 466601, "author_name": "alecthekulak", "author_url": "", "post_date": "02/05/2019 17:10:54", "content": "While the file appears as a .zip in the competition's Data Tab, when your kernel loads, Kaggle automatically extracts it and adds it's contents to your file-system. In most cases, a .zip of CSVs will end up being provided to the kernal as a single CSV. You can check what is available in your kernel by running from os import listdir; print(listdir(\"../input\")) which should result in the following output: ['test', 'train.csv', 'sample_submission.csv'] which includes train.csv, the file you're looking for. If we follow along with Harshit Holmes's notebook for this competition (published in this competition's Kernel Tab) we can see that the training data can be imported via the following code:
\nimport pandas as pd
\nimport numpy as np\ntrain = pd.read_csv('../input/train.csv', dtype={'acoustic_data': np.int16, 'time_to_failure': np.float32})\n
Hope that helps!
", "votes": null, "replies": [] }, { "id": 467206, "author_name": "massenet", "author_url": "", "post_date": "02/06/2019 16:20:27", "content": "Thanks a lot for your answer, Alec.
\n\nI still have a problem.\nI download LANL-Earthquake-Prediction.zip, by clicking on 'Download All'.\nMaybe this does not work.
", "votes": null, "replies": [ { "id": 467252, "author_name": "danjel", "author_url": "", "post_date": "02/06/2019 17:46:31", "content": "You have to be a bit more specific for us to help you. What operating system do you use? Which program do you use to unzip? What do the log files say?\nIt would also be useful if the organizers published the checksum of the file to be sure that the downloaded copy is uncorrupted. Perhaps that can be achieved by using the Kaggle API, I don't know.
\n\nBy the way: you don't really have to download the data, you may also analyze it by writing your own private Kaggle kernel, which is then executed in the Kaggle cloud.
", "votes": null, "replies": [] } ] }, { "id": 467636, "author_name": "massenet", "author_url": "", "post_date": "02/07/2019 13:05:11", "content": "@Daniel Gerigk\nI use a Mac, with macOS High Sierra.\nTo unzip, I use the tool provided by default (\"Utilitaire d'archive\", in French).\nI've got the message : \"impossible to uncompress LANL-Earthquake-Prediction.zip. (Error 2 : unexacting file or folder)\"\n(something like that, I translated it).\nI'm going to follow your advice and create my own private Kernel.\nThanks a lot.
", "votes": null, "replies": [ { "id": 467666, "author_name": "alecthekulak", "author_url": "", "post_date": "02/07/2019 14:28:29", "content": "If you use a Kaggle kernel directly linked to the Competition (or Dataset), it'll automatically have the data loaded in and will deal with .zip files for you.
", "votes": null, "replies": [] } ] }, { "id": 467720, "author_name": "massenet", "author_url": "", "post_date": "02/07/2019 16:08:57", "content": "Yes, thank you both.\nIt goes well with a Kaggle kernel.
", "votes": null, "replies": [] }, { "id": 470301, "author_name": "edoneel", "author_url": "", "post_date": "02/12/2019 18:17:53", "content": "When I click on the file in the finder in Mojave it runs the archive utility, and, all the way at the end it fails with Error 2, no such file or directory. Is that what you see?
\n\nThe solution that has always worked for me in this case is to run unzip on the command line (from a Terminal). This works fine.
\n\nI think that MacOS's archive utility is unhappy with zip files over 2G.
\n\n$ unzip all.zip \nArchive: all.zip\n inflating: sample_submission.csv
\n inflating: test.zip
\n inflating: train.csv
\n$
Yes, that was the same for me.\nI will try your solution.\nThanks a lot.
", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "466553": "Unable to unzip train.csv.zip.\nHas anyone faced this problem ?", "466601": "While the file appears as a .zip in the competition's [Data Tab](https://www.kaggle.com/c/LANL-Earthquake-Prediction/data), when your kernel loads, Kaggle automatically extracts it and adds it's contents to your file-system. In most cases, a .zip of CSVs will end up being provided to the kernal as a single CSV. You can check what is available in your kernel by running `from os import listdir; print(listdir(\"../input\"))` which should result in the following output: `['test', 'train.csv', 'sample_submission.csv']` which includes *train.csv*, the file you're looking for. If we follow along with [Harshit Holmes](https://www.kaggle.com/harshitholmes)'s [notebook](https://www.kaggle.com/harshitholmes/testing-each-every-regressor-with-own-instances) for this competition (published in this competition's [Kernel Tab](https://www.kaggle.com/c/LANL-Earthquake-Prediction/kernels)) we can see that the training data can be imported via the following code: \n\n```\nimport pandas as pd \nimport numpy as np\ntrain = pd.read_csv('../input/train.csv', dtype={'acoustic_data': np.int16, 'time_to_failure': np.float32})\n```\n\nHope that helps!", "467206": "Thanks a lot for your answer, Alec.\n\nI still have a problem.\nI download LANL-Earthquake-Prediction.zip, by clicking on 'Download All'.\nMaybe this does not work.", "467252": "You have to be a bit more specific for us to help you. What operating system do you use? Which program do you use to unzip? What do the log files say?\nIt would also be useful if the organizers published the checksum of the file to be sure that the downloaded copy is uncorrupted. Perhaps that can be achieved by using the Kaggle API, I don't know.\n\nBy the way: you don't really have to download the data, you may also analyze it by writing your own private Kaggle kernel, which is then executed in the Kaggle cloud.", "467636": "Daniel Gerigk\nI use a Mac, with macOS High Sierra.\nTo unzip, I use the tool provided by default (\"Utilitaire d'archive\", in French).\nI've got the message : \"impossible to uncompress LANL-Earthquake-Prediction.zip. (Error 2 : unexacting file or folder)\"\n(something like that, I translated it).\nI'm going to follow your advice and create my own private Kernel.\nThanks a lot.", "467666": "If you use a Kaggle kernel directly linked to the Competition (or Dataset), it'll automatically have the data loaded in and will deal with .zip files for you.", "467720": "Yes, thank you both.\nIt goes well with a Kaggle kernel.", "470301": "When I click on the file in the finder in Mojave it runs the archive utility, and, all the way at the end it fails with Error 2, no such file or directory. Is that what you see?\n\nThe solution that has always worked for me in this case is to run unzip on the command line (from a Terminal). This works fine.\n\nI think that MacOS's archive utility is unhappy with zip files over 2G.\n\n$ unzip all.zip \nArchive: all.zip\n inflating: sample_submission.csv \n inflating: test.zip \n inflating: train.csv \n$", "470973": "Yes, that was the same for me.\nI will try your solution.\nThanks a lot." }, "source": "meta" }