Pandas Dataframe to tensor

Question

I have a dataframe with 3 columns (a date index, a price and a string symbol). It looks like that:

Date	Price	Symbol
2019-01-02	39.480000	AAPL
2019-01-02	101.120003	MSFT
2019-01-02	62.023998	TSLA
2019-01-03	35.547501	AAPL
2019-01-03	97.400002	MSFT
2019-01-03	60.071999	TSLA

I'm looking for some panda/pytorch/python syntactic sugar to turn that into a tensor/matrix that will be:

[ [ 39.480000, 101.120003, 62.023998], [35.547501, 97.400002, 60.071999]]

With the number length of the first dimension will be the number of unique dates, and the length of the second will be the number of unique symbols. I'm guaranteed to have exactly 3 symbols per date and I want that each row of my matrix follow the same order for its columns (e.g always AAPL, MSFT, TSLA).

Now, that is very easy with some for loops, but I'm looking for something more "pythonic"

End genocide - save Gaza · Accepted Answer · 2021-03-23 16:13:40Z

2

You can groupby the date column, convert the groups of Price to numpy arrays, and then convert this series to a tensor:

import torch
import pandas as pd

prices = df.groupby(['Date'])['Price'].apply(np.array)
my_tensor = torch.tensor(prices)

answered Mar 23, 2021 at 16:13

End genocide - save Gaza

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