I would like to be able to pull out an arbitrary row, such as the 4th row, and get an array so that I can send it through another function.
What would be the easiest way to do this?
Since Pandas data is stored internally as Numpy arrays, you can extract the Numpy representation directly.
Use pd.Series.to_numpy
method:
df.iloc[3].to_numpy() # output 4th row as Numpy array
Use pd.Series.values
property:
df.iloc[3].values # output 4th row as Numpy array
Just remember that if your dataframe contains multiple types, the dtype
of the row-wise Numpy array may become object
. This will lead to inefficiencies in subsequent operations.
# Dummy DataFrame
df = pd.DataFrame({'col1': [1,2,3], 'col2': [4,5,6]})
# Extract second row (index: 1)
df.iloc[1].values
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