module fastdata.pandas2numpy
¶
Short summary¶
module cpyquickhelper.fastdata.pandas2numpy
Fast data manipulations.
Functions¶
function |
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Converts a dataframe into a numpy.array without copying. pandas is merging consecutive columns sharing … |
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Converts a dataframe into a list of a list of tuple (column name, :epkg:`numpy:array`) without copying. pandas … |
Documentation¶
Fast data manipulations.
- cpyquickhelper.fastdata.pandas2numpy.df2array(df, check=True)¶
Converts a dataframe into a numpy.array without copying. pandas is merging consecutive columns sharing the same type into one memory block. The function can be used only if the data is stored in one block and one type as a consequence.
- Parameters:
df – dataframe
check – verifies the operation can be done (True) or skip verification (False)
- Returns:
See data member, _data.
See also
- cpyquickhelper.fastdata.pandas2numpy.df2arrays(df, sep=',', check=True)¶
Converts a dataframe into a list of a list of tuple (column name, :epkg:`numpy:array`) without copying. pandas is merging consecutive columns sharing the same type into one memory block. That’s what the function extracts
- Parameters:
df – dataframe
check – verifies the operation can be done (True) or skip verification (False)
sep – columns separator
- Returns:
a list of tuple
(column, array)
Example:
<<<
from pandas import DataFrame from cpyquickhelper.fastdata import df2arrays df = DataFrame([dict(a=3.4, b=5.6, c="e"), dict(a=3.5, b=5.7, c="r")]) arr = df2arrays(df) print(arr)
>>>
[('a,b', array([[3.4, 3.5], [5.6, 5.7]])), ('c', array([['e', 'r']], dtype=object))]
See also