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How to effectively work with multiple time series data collected on daily basis?
How to deal with time series which change in seasonality or other patterns?Combining parameters for Douglas-Peucker SimplificationHow to cluster multiple time-series from one data frameHandling time series data with gapsHow to train Syllables instead of phones using HTK?Detecting voice in a noisy environmentCalculating correlation of slightly out of sync dataInteractive dashboard for time series dataPrediction based on more dataframesPython Time series: extracting features on a rolling window basis
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I am currently trying to preprocess data collected from vehicles and I am new to working with these file types (in mdf format). The other issue is, there are a few separate files for the data collected each day the vehicle was used and this was collected over a few years. Within these files, there are parameters that are collected in different timestamp formats (either every 10ms or 100ms etc). I am not sure yet which parameters will be needed for me to build any statistical model so at the moment, what I am trying to do is to first combine the files collected each day and then think of how best to match the timestamps to create same length dataframes. I am curious to know if anyone has experience dealing with this kind of data arrangements and any advice on what are the ideal approaches to use to look for patterns across these datasets to gain some understanding about the features it has.
python data-mining bigdata visualization data-science-model
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Py_MelPy_Mel
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I am currently trying to preprocess data collected from vehicles and I am new to working with these file types (in mdf format). The other issue is, there are a few separate files for the data collected each day the vehicle was used and this was collected over a few years. Within these files, there are parameters that are collected in different timestamp formats (either every 10ms or 100ms etc). I am not sure yet which parameters will be needed for me to build any statistical model so at the moment, what I am trying to do is to first combine the files collected each day and then think of how best to match the timestamps to create same length dataframes. I am curious to know if anyone has experience dealing with this kind of data arrangements and any advice on what are the ideal approaches to use to look for patterns across these datasets to gain some understanding about the features it has.
python data-mining bigdata visualization data-science-model
asked 2 hours ago
Py_MelPy_Mel
61
New contributor
Py_Mel is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
I am currently trying to preprocess data collected from vehicles and I am new to working with these file types (in mdf format). The other issue is, there are a few separate files for the data collected each day the vehicle was used and this was collected over a few years. Within these files, there are parameters that are collected in different timestamp formats (either every 10ms or 100ms etc). I am not sure yet which parameters will be needed for me to build any statistical model so at the moment, what I am trying to do is to first combine the files collected each day and then think of how best to match the timestamps to create same length dataframes. I am curious to know if anyone has experience dealing with this kind of data arrangements and any advice on what are the ideal approaches to use to look for patterns across these datasets to gain some understanding about the features it has.
python data-mining bigdata visualization data-science-model
asked 2 hours ago
Py_MelPy_Mel
61
New contributor
Py_Mel is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
I am currently trying to preprocess data collected from vehicles and I am new to working with these file types (in mdf format). The other issue is, there are a few separate files for the data collected each day the vehicle was used and this was collected over a few years. Within these files, there are parameters that are collected in different timestamp formats (either every 10ms or 100ms etc). I am not sure yet which parameters will be needed for me to build any statistical model so at the moment, what I am trying to do is to first combine the files collected each day and then think of how best to match the timestamps to create same length dataframes. I am curious to know if anyone has experience dealing with this kind of data arrangements and any advice on what are the ideal approaches to use to look for patterns across these datasets to gain some understanding about the features it has.
python data-mining bigdata visualization data-science-model
python data-mining bigdata visualization data-science-model
asked 2 hours ago
Py_MelPy_Mel
61
New contributor
Py_Mel is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 2 hours ago
Py_MelPy_Mel
61
New contributor
Py_Mel is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 2 hours ago
Py_MelPy_Mel
61
New contributor
Py_Mel is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 2 hours ago
Py_MelPy_Mel
61
asked 2 hours ago
Py_MelPy_Mel
61
61
New contributor
Py_Mel is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Py_Mel is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
Py_Mel is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
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