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Is there an easier way to load an excel file directly into a Numpy array?
I have looked at the numpy.genfromtxt autoloading function from numpy documentation but it doesn't load excel files directly.
array = np.genfromtxt("Stats.xlsx")
ValueError: Some errors were detected !
Line #3 (got 2 columns instead of 1)
Line #5 (got 5 columns instead of 1)
......
Right now I am using using openpyxl.reader.excel to read the excel file and then append to numpy 2D arrays. This seems to be inefficient.
Ideally I would like to have to excel file directly loaded to numpy 2D array.
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Python NumPy read CSV into 2d NumPy arraytxt() and open() functions to load a CSV file into a 2Dimension NumPy Array. Call open file to open the CSV text file Use numpy. loadtxt( CSV file, delimiter) with the file as the result of the previous step and delimiter as “,” to return the data in a two-dimensional NumPy.
Honestly, if you're working with heterogeneous data (as spreadsheets are likely to contain) using a pandas.DataFrame is a better choice than using numpy directly.
While pandas is in some sense just a wrapper around numpy, it handles heterogeneous data very very nicely. (As well as a ton of other things... For "spreadsheet-like" data, it's the gold standard in the python world.)
If you decide to go that route, just use pandas.read_excel.
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