How do concatenate over many datasets?
$begingroup$
I am working on a project where I would like to take two timeseries datasets and train a machine learning model. Say for example, APPL stock performance and MSFT. These are two different excel spreadsheets. Each includes historical stock information (historical prices) for the last 5 years. Each trading day is a new "sample." In this case how can I treat each stock as an individual sample?
ie.
Price
4/19/20 100 (Apple)
64 (MSFT)
4/18/20 101 (APPL)
45 (MSFT)
See my problem? Each sample has two samples. How should I deal with this. Ideally, I could construct a dataset with 100 different stocks.
machine-learning pandas machine-learning-model
New contributor
$endgroup$
add a comment |
$begingroup$
I am working on a project where I would like to take two timeseries datasets and train a machine learning model. Say for example, APPL stock performance and MSFT. These are two different excel spreadsheets. Each includes historical stock information (historical prices) for the last 5 years. Each trading day is a new "sample." In this case how can I treat each stock as an individual sample?
ie.
Price
4/19/20 100 (Apple)
64 (MSFT)
4/18/20 101 (APPL)
45 (MSFT)
See my problem? Each sample has two samples. How should I deal with this. Ideally, I could construct a dataset with 100 different stocks.
machine-learning pandas machine-learning-model
New contributor
$endgroup$
add a comment |
$begingroup$
I am working on a project where I would like to take two timeseries datasets and train a machine learning model. Say for example, APPL stock performance and MSFT. These are two different excel spreadsheets. Each includes historical stock information (historical prices) for the last 5 years. Each trading day is a new "sample." In this case how can I treat each stock as an individual sample?
ie.
Price
4/19/20 100 (Apple)
64 (MSFT)
4/18/20 101 (APPL)
45 (MSFT)
See my problem? Each sample has two samples. How should I deal with this. Ideally, I could construct a dataset with 100 different stocks.
machine-learning pandas machine-learning-model
New contributor
$endgroup$
I am working on a project where I would like to take two timeseries datasets and train a machine learning model. Say for example, APPL stock performance and MSFT. These are two different excel spreadsheets. Each includes historical stock information (historical prices) for the last 5 years. Each trading day is a new "sample." In this case how can I treat each stock as an individual sample?
ie.
Price
4/19/20 100 (Apple)
64 (MSFT)
4/18/20 101 (APPL)
45 (MSFT)
See my problem? Each sample has two samples. How should I deal with this. Ideally, I could construct a dataset with 100 different stocks.
machine-learning pandas machine-learning-model
machine-learning pandas machine-learning-model
New contributor
New contributor
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asked 21 mins ago
QFIIQFII
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QFII is a new contributor. Be nice, and check out our Code of Conduct.
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