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For classical numpy dtypes in pandas, this should be more efficient than forcing slices + dicts
Spotted in Prophet
Desired syntax:
import narwhals as nw import numpy as np import pandas as pd arr = np.zeros([[1,2,3], [4,5,6]]) df = nw.from_2d_array(arr, column_names=['a', 'b', 'c'])
It should also be possible to pass in dtype as an argument - if not passed, it'll be autoinferred
dtype
import narwhals as nw import numpy as np import pandas as pd arr = np.zeros([[1,2,3], [4,5,6]]) df = nw.from_2d_array(arr, column_names=['a', 'b', 'c'], dtype=nw.Float64)
The text was updated successfully, but these errors were encountered:
Should this emulate polars.from_numpy with the extra namespace argument?
polars.from_numpy
namespace
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yup good shout!
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For classical numpy dtypes in pandas, this should be more efficient than forcing slices + dicts
Spotted in Prophet
Desired syntax:
It should also be possible to pass in
dtype
as an argument - if not passed, it'll be autoinferredThe text was updated successfully, but these errors were encountered: