Pandas pivot to sparse

from scipy.sparse import csr_matrix
from pandas.api.types import CategoricalDtype

person_c = CategoricalDtype(sorted(frame.person.unique()), ordered=True)
thing_c = CategoricalDtype(sorted(frame.thing.unique()), ordered=True)

row = frame.person.astype(person_c).cat.codes
col = frame.thing.astype(thing_c).cat.codes
sparse_matrix = csr_matrix((frame["count"], (row, col)), \
                           shape=(person_c.categories.size, thing_c.categories.size))

>>> sparse_matrix
<3x4 sparse matrix of type '<class 'numpy.int64'>'
     with 6 stored elements in Compressed Sparse Row format>

>>> sparse_matrix.todense()
matrix([[0, 1, 0, 1],
        [1, 0, 0, 1],
        [1, 0, 1, 0]], dtype=int64)


dfs = pd.SparseDataFrame(sparse_matrix, \
                         index=person_c.categories, \
                         columns=thing_c.categories, \
                         default_fill_value=0)
>>> dfs
        a   b   c   d
 him    0   1   0   1
  me    1   0   0   1
 you    1   0   1   0

Source: stackoverflow.com

Similar codes

1 vote354 views2 answers
How to get unique value of all columns in pandas
Python
1 vote316 views1 answer
Python sort array by value
Python
10 votes334 views2 answers
Adding static file and its usage in Django
Python
1 vote322 views1 answer
Flask clear session
Python
8 votes362 views4 answers
Count unique values numpy
Python
0 vote273 views1 answer
Pandas select data by column value
Python
0 vote336 views1 answer
SimpleITK interpolation
Python
0 vote344 views1 answer
Try and exception
Python
0 vote316 views1 answer
Store in a variable the ocntent of a file python
Python
0 vote312 views1 answer
How to change array of arrays to simpe array
Python