'data' must have a single column, not '(ncol)'

Package:

pandas

30911

Exception Class:

ValueError

Raise code

""" 
        Fill: 0.0
        IntIndex
        Indices: array([], dtype=int32)
        """
        length, ncol = data.shape

        if ncol != 1:
            raise ValueError(f"'data' must have a single column, not '{ncol}'")

        # our sparse index classes require that the positions be strictly
        # increasing. So we need to sort loc, and arr accordingly.
        data = data.tocsc()
        data.sort_indices()
        arr = data.data
        idx = data.indices

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Links to the raise (1)

https://github.com/pandas-dev/pandas/blob/b3e335254f46a526ee3ce9bb757eac4011d9d1fe/pandas/core/arrays/sparse/array.py#L492

Ways to fix

This happens when the function pandas,arrays.SparseArray.from_spmatrix() is given a sparse matrix with columns greater than one.

How to reproduce it:

import scipy.sparse
import pandas as pd

# Notice here that `mat` has 2 columns and 4 rows.
mat = scipy.sparse.coo_matrix((4, 2))
result = pd.arrays.SparseArray.from_spmatrix(mat)
print(result)

Output error:

---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-3-bbeedda2bc3e> in <module>()  3   4 mat = scipy.sparse.coo_matrix((4, 2)) ----> 5 result = pd.arrays.SparseArray.from_spmatrix(mat)  6 print(result) 
/usr/local/lib/python3.7/dist-packages/pandas/core/arrays/sparse/array.py in from_spmatrix(cls, data)  486   487 if ncol != 1: --> 488 raise ValueError(f"'data' must have a single column, not '{ncol}'")  489   490 # our sparse index classes require that the positions be strictly 
ValueError: 'data' must have a single column, not '2'

Fixed version of the code:

import scipy.sparse
import pandas as pd


mat = scipy.sparse.coo_matrix((4, 1))
result = pd.arrays.SparseArray.from_spmatrix(mat)
print(result)

Output:

[0.0, 0.0, 0.0, 0.0] 
Fill: 0.0 IntIndex 
Indices: array([], dtype=int32)

May 05, 2022

kellemnegasi 29.0k

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