Data analysis part 2 #173
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Data analysis part 2 #173
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qwandor
reviewed
Apr 22, 2021
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| ## Looking at the data | ||
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| The data will be split into different csv files, split by different data types.According to your setup, there will be up to 5 files: |
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You're missing a space after the fullstop.
qwandor
reviewed
Apr 22, 2021
| - homie_enum | ||
| - homie_color: contains rgb values for the smart lights | ||
| - homie_float: contains all metrics stored as floats (temperature) | ||
| - homie_integer: contains all metrics stored as integers (humidity %, battery level %) |
qwandor
reviewed
Apr 22, 2021
| - homie_float: contains all metrics stored as floats (temperature) | ||
| - homie_integer: contains all metrics stored as integers (humidity %, battery level %) | ||
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| Here, we want to focus on the csvs containing floats and integers, as they contain the temperature/humdity data. Useful columns: |
qwandor
reviewed
Apr 22, 2021
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| Here, we want to focus on the csvs containing floats and integers, as they contain the temperature/humdity data. Useful columns: | ||
| - time: since epoch (unix epoch 1970). pandas handles this for us. | ||
| device_id |
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I guess this should also be a list entry.
qwandor
reviewed
Apr 22, 2021
| - node_type: =="Mijia sensor" to select only the temperature/humidity sensor data | ||
| - node_name: nickname for the sensor (e.g., "living room") | ||
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| There are between 4 and 10 data points per sensor per minute, depending on how often a sensor gets polled (~ 10K data points in a 24h period for a given sensor) |
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Depending on the min_update_period_seconds in mijia-homie.toml, really.
alsuren
reviewed
Apr 23, 2021
| @@ -7,7 +7,9 @@ | |||
| "outputs": [], | |||
| "source": [ | |||
| "import pandas as pd \n", | |||
| "import plotly.express as px\n" | |||
| "import plotly.express as px\n", | |||
| "from sklearn.preprocessing import StandardScaler\n", | |||
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hrm. I'm getting an error here. Trying to debug now.
ModuleNotFoundError Traceback (most recent call last)
<ipython-input-2-186f7a1512d6> in <module>
1 import pandas as pd
2 import plotly.express as px
----> 3 from sklearn.preprocessing import StandardScaler
4 from sklearn.decomposition import PCA
ModuleNotFoundError: No module named 'sklearn'
alsuren
reviewed
Apr 23, 2021
| @@ -10,6 +10,7 @@ ipykernel = "^5.5.3" | |||
| pandas = "^1.2.4" | |||
| plotly = "^4.14.3" | |||
| nbstripout = "^0.3.9" | |||
| sklearn = "^0.0" | |||
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https://pypi.org/project/sklearn/ says to use scikit-learn instead.
vscode also decided that it wanted to install notebook when I tried things out on a fresh virtualenv, but I can make a patch for that as a separate PR.
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