![\"\"](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2Fb8654a95eb162990c781ed835884b6a6%2FUntitled.png?generation=1572599829112314&alt=media\")
Despite having my EDA kernel I want to share some more plots.
\n\nThose are plots of each building's daily mean energy consumption by a meter type. Separately for each building. Yeas, it is a lot of images.
\n\nAnd as you know there are 1449 different buildings in the dataset, so plotting them in a kernel causes it to freeze. So I have rendered all of this images and leaving a links to them, so you can download them to assess and analyze.
\n\nHere is and example of how this plots look like:
\n\n
By the way on the example of building 1302 you can see why month feature might be useful. Meter 3 have non-zero reading only on winter-spring months and only zeroes during summer months. So this is, most likely, a heating.
\n\nLink to the images. Click to download.
\n\nDespite having my EDA kernel I want to share some more plots.
\n\nThose are plots of each building's daily mean energy consumption by a meter type. Separately for each building. Yeas, it is a lot of images.
\n\nAnd as you know there are 1449 different buildings in the dataset, so plotting them in a kernel causes it to freeze. So I have rendered all of this images and leaving a links to them, so you can download them to assess and analyze.
\n\nHere is and example of how this plots look like:
\n\n
By the way on the example of building 1302 you can see why month feature might be useful. Meter 3 have non-zero reading only on winter-spring months and only zeroes during summer months. So this is, most likely, a heating.
\n\nLink to the images. Click to download.
\n\nThis is great! Thanks for sharing! Are there any buildings that stand out?
", "rawMarkdown": "This is great! Thanks for sharing! Are there any buildings that stand out?", "votes": null }, { "id": "663340", "postDate": "11/01/2019 20:39:55", "content": "There are plenty of them.
", "rawMarkdown": "There are plenty of them.", "votes": null }, { "id": "663451", "postDate": "11/02/2019 03:57:52", "content": "awesome thanks for sharing! ππ
", "rawMarkdown": "awesome thanks for sharing! ππ", "votes": null }, { "id": "663614", "postDate": "11/02/2019 12:25:57", "content": "π Do you see a common theme among buildings with weird behaviors? It seems that there are some power outages and/or meter malfunctions in some buildings. Our team mostly did analysis on the meters and sites.
", "rawMarkdown": "π Do you see a common theme among buildings with weird behaviors? It seems that there are some power outages and/or meter malfunctions in some buildings. Our team mostly did analysis on the meters and sites.", "votes": null }, { "id": "664261", "postDate": "11/03/2019 12:14:25", "content": "Amazing & Awesome\nThanks for Sharing...!! @nroman
", "rawMarkdown": "Amazing & Awesome\nThanks for Sharing...!! @nroman", "votes": null }, { "id": "666062", "postDate": "11/05/2019 17:24:54", "content": "I have created three notebooks capturing the absolute value of the meter reading for all the buildings across. Tried to create one notebook initially, but it was not getting rendered at all. Hopefully, it would be helpful.
\n\nhttps://www.kaggle.com/c/ashrae-energy-prediction/discussion/115850
", "rawMarkdown": "I have created three notebooks capturing the absolute value of the meter reading for all the buildings across. Tried to create one notebook initially, but it was not getting rendered at all. Hopefully, it would be helpful. \n\nhttps://www.kaggle.com/c/ashrae-energy-prediction/discussion/115850", "votes": null }, { "id": "671973", "postDate": "11/13/2019 11:48:37", "content": "Thanks for Sharingβ¦!!
", "rawMarkdown": "Thanks for Sharingβ¦!!", "votes": null }, { "id": "690606", "postDate": "12/08/2019 21:09:38", "content": "Amazing!!
", "rawMarkdown": "Amazing!!", "votes": null }, { "id": "702067", "postDate": "12/24/2019 08:09:47", "content": "Really helpful. Thanks @nroman π
", "rawMarkdown": "Really helpful. Thanks @nroman π", "votes": null }, { "id": "702204", "postDate": "12/24/2019 11:42:55", "content": "did you perform clustering analysis on building and build validation strategies based on identified clusters?
", "rawMarkdown": "did you perform clustering analysis on building and build validation strategies based on identified clusters?", "votes": null }, { "id": "702230", "postDate": "12/24/2019 12:31:20", "content": "No, I wasn't doing any clustering-based analysis.
", "rawMarkdown": "No, I wasn't doing any clustering-based analysis.", "votes": null } ], "comments": [ { "id": 663325, "author_name": "carlolepelaars", "author_url": "", "post_date": "11/01/2019 20:06:28", "content": "This is great! Thanks for sharing! Are there any buildings that stand out?
", "votes": null, "replies": [ { "id": 663340, "author_name": "nroman", "author_url": "", "post_date": "11/01/2019 20:39:55", "content": "There are plenty of them.
", "votes": null, "replies": [] }, { "id": 663614, "author_name": "carlolepelaars", "author_url": "", "post_date": "11/02/2019 12:25:57", "content": "π Do you see a common theme among buildings with weird behaviors? It seems that there are some power outages and/or meter malfunctions in some buildings. Our team mostly did analysis on the meters and sites.
", "votes": null, "replies": [] } ] }, { "id": 663451, "author_name": "marquis08", "author_url": "", "post_date": "11/02/2019 03:57:52", "content": "awesome thanks for sharing! ππ
", "votes": null, "replies": [] }, { "id": 664261, "author_name": "veeralakrishna", "author_url": "", "post_date": "11/03/2019 12:14:25", "content": "Amazing & Awesome\nThanks for Sharing...!! @nroman
", "votes": null, "replies": [] }, { "id": 666062, "author_name": "arnabbiswas1", "author_url": "", "post_date": "11/05/2019 17:24:54", "content": "I have created three notebooks capturing the absolute value of the meter reading for all the buildings across. Tried to create one notebook initially, but it was not getting rendered at all. Hopefully, it would be helpful.
\n\nhttps://www.kaggle.com/c/ashrae-energy-prediction/discussion/115850
", "votes": null, "replies": [] }, { "id": 671973, "author_name": "chanhu", "author_url": "", "post_date": "11/13/2019 11:48:37", "content": "Thanks for Sharingβ¦!!
", "votes": null, "replies": [] }, { "id": 690606, "author_name": "flyingpiggy", "author_url": "", "post_date": "12/08/2019 21:09:38", "content": "Amazing!!
", "votes": null, "replies": [] }, { "id": 702067, "author_name": "vishnurapps", "author_url": "", "post_date": "12/24/2019 08:09:47", "content": "Really helpful. Thanks @nroman π
", "votes": null, "replies": [] }, { "id": 702204, "author_name": "projdev", "author_url": "", "post_date": "12/24/2019 11:42:55", "content": "did you perform clustering analysis on building and build validation strategies based on identified clusters?
", "votes": null, "replies": [ { "id": 702230, "author_name": "nroman", "author_url": "", "post_date": "12/24/2019 12:31:20", "content": "No, I wasn't doing any clustering-based analysis.
", "votes": null, "replies": [] } ] } ], "raw_markdown_by_id": { "662975": "Despite having my [EDA kernel](https://www.kaggle.com/nroman/eda-for-ashrae) I want to share some more plots. \n\nThose are plots of each building's daily mean energy consumption by a meter type. Separately for each building. Yeas, it is a lot of images.\n\nAnd as you know there are 1449 different buildings in the dataset, so plotting them in a kernel causes it to freeze. So I have rendered all of this images and leaving a links to them, so you can download them to assess and analyze.\n\nHere is and example of how this plots look like:\n\n\n\nBy the way on the example of building 1302 you can see why month feature might be useful. Meter 3 have non-zero reading only on winter-spring months and only zeroes during summer months. So this is, most likely, a heating.\n\nLink to the images. Click to download.\n\n* [building_id from 0 to 99](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2F9776a8565b44f289a909120821526731%2F0-99.png?generation=1572520895032852&alt=media)\n* [building_id from 100 to 199](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2Fa8a263eb9d35e26163cec66bd721e37c%2F100-199.png?generation=1572521357706276&alt=media)\n* [building_id from 200 to 299](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2F58ff392c105f6a01e596445873f745b4%2F200-299.png?generation=1572521796971791&alt=media)\n* [building_id from 300 to 399](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2Fee532a85419e1aa6d7e390735f5dc0db%2F300-399.png?generation=1572522561682454&alt=media)\n* [building_id from 400 to 499](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2F2b92d4a5ab96023ddbe07882a2eb9daa%2F400-499.png?generation=1572523460019602&alt=media)\n* [building_id from 500 to 599](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2F4a3ac754309da7033e82b0eda92ad841%2F500-599.png?generation=1572523803045516&alt=media)\n* [building_id from 600 to 699](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2Ff9ad5389d2ab4110cd56ed1da3ef4a3a%2F600-699.png?generation=1572524735838758&alt=media)\n* [building_id from 700 to 799](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2F8e202bdb496c9d0f4a7f0431400dd076%2F700-799.png?generation=1572525134582055&alt=media)\n* [building_id from 800 to 899](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2F65b62204686ef8a302a8e622df6011a2%2F800-899.png?generation=1572525465188308&alt=media)\n* [building_id from 900 to 999](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2Fd9da022dfc4ec834799a2e502089067e%2F900-999.png?generation=1572534498140152&alt=media)\n* [building_id from 1000 to 1099](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2F0a631a7ebc3ab15b090de367e41dd076%2F1000-1099.png?generation=1572597569272577&alt=media)\n* [building_id from 1100 to 1199](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2Fcf53766a294bf809b2f251e90592188c%2F1100-1199.png?generation=1572532340945059&alt=media)\n* [building_id from 1200 to 1299](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2Fa2db31ed4bb149c955beb445a7c33294%2F1200-1299.png?generation=1572598287764301&alt=media)\n* [building_id from 1300 to 1399](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2F371a6fd89326968d4913cc9fd8315f6e%2F1300-1399.png?generation=1572599105374855&alt=media)\n* [building_id from 1400 to 1448](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2F75c83cccc4ec440c695ec4faa35187f3%2F1400-1448.png?generation=1572599024652763&alt=media)", "663325": "This is great! Thanks for sharing! Are there any buildings that stand out?", "663340": "There are plenty of them.", "663451": "awesome thanks for sharing! ππ", "663614": "π Do you see a common theme among buildings with weird behaviors? It seems that there are some power outages and/or meter malfunctions in some buildings. Our team mostly did analysis on the meters and sites.", "664261": "Amazing & Awesome\nThanks for Sharing...!! @nroman", "666062": "I have created three notebooks capturing the absolute value of the meter reading for all the buildings across. Tried to create one notebook initially, but it was not getting rendered at all. Hopefully, it would be helpful. \n\nhttps://www.kaggle.com/c/ashrae-energy-prediction/discussion/115850", "671973": "Thanks for Sharingβ¦!!", "690606": "Amazing!!", "702067": "Really helpful. Thanks @nroman π", "702204": "did you perform clustering analysis on building and build validation strategies based on identified clusters?", "702230": "No, I wasn't doing any clustering-based analysis." }, "source": "meta" }![building_id from 0 to 99](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2F9776a8565b44f289a909120821526731%2F0-99.png?generation=1572520895032852&alt=media\"){kind=link}
![building_id from 100 to 199](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2Fa8a263eb9d35e26163cec66bd721e37c%2F100-199.png?generation=1572521357706276&alt=media\"){kind=link}
![building_id from 200 to 299](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2F58ff392c105f6a01e596445873f745b4%2F200-299.png?generation=1572521796971791&alt=media\"){kind=link}
![building_id from 300 to 399](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2Fee532a85419e1aa6d7e390735f5dc0db%2F300-399.png?generation=1572522561682454&alt=media\"){kind=link}
![building_id from 400 to 499](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2F2b92d4a5ab96023ddbe07882a2eb9daa%2F400-499.png?generation=1572523460019602&alt=media\"){kind=link}
![building_id from 500 to 599](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2F4a3ac754309da7033e82b0eda92ad841%2F500-599.png?generation=1572523803045516&alt=media\"){kind=link}
![building_id from 600 to 699](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2Ff9ad5389d2ab4110cd56ed1da3ef4a3a%2F600-699.png?generation=1572524735838758&alt=media\"){kind=link}
![building_id from 700 to 799](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2F8e202bdb496c9d0f4a7f0431400dd076%2F700-799.png?generation=1572525134582055&alt=media\"){kind=link}
![building_id from 800 to 899](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2F65b62204686ef8a302a8e622df6011a2%2F800-899.png?generation=1572525465188308&alt=media\"){kind=link}
![building_id from 900 to 999](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2Fd9da022dfc4ec834799a2e502089067e%2F900-999.png?generation=1572534498140152&alt=media\"){kind=link}
![building_id from 1000 to 1099](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2F0a631a7ebc3ab15b090de367e41dd076%2F1000-1099.png?generation=1572597569272577&alt=media\"){kind=link}
![building_id from 1100 to 1199](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2Fcf53766a294bf809b2f251e90592188c%2F1100-1199.png?generation=1572532340945059&alt=media\"){kind=link}
![building_id from 1200 to 1299](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2Fa2db31ed4bb149c955beb445a7c33294%2F1200-1299.png?generation=1572598287764301&alt=media\"){kind=link}
![building_id from 1300 to 1399](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2F371a6fd89326968d4913cc9fd8315f6e%2F1300-1399.png?generation=1572599105374855&alt=media\"){kind=link}
![building_id from 1400 to 1448](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1696976%2F75c83cccc4ec440c695ec4faa35187f3%2F1400-1448.png?generation=1572599024652763&alt=media\"){kind=link}