FIX: revert change to lib.pyx

Author: hexgnu

pandas/_libs/lib.pyx

@@ -59,14 +59,8 @@ def memory_usage_of_objects(ndarray[object, ndim=1] arr):
  cdef Py_ssize_t i, n
  cdef int64_t s = 0
 
- # The problem here is that... 
- # A SparseArray of size 1 that has fill_value = the only value
- # will cause this
-
- # n = 1
- # 
  n = len(arr)
- for i in range(n):
+ for i from 0 <= i < n:
  s += arr[i].__sizeof__()
  return s
 
@@ -137,10 +131,10 @@ def fast_unique_multiple(list arrays):
  dict table = {}
  object val, stub = 0
 
- for i in range(k):
+ for i from 0 <= i < k:
  buf = arrays[i]
  n = len(buf)
- for j in range(n):
+ for j from 0 <= j < n:
  val = buf[j]
  if val not in table:
  table[val] = stub
@@ -164,10 +158,10 @@ def fast_unique_multiple_list(list lists):
  dict table = {}
  object val, stub = 0
 
- for i in range(k):
+ for i from 0 <= i < k:
  buf = lists[i]
  n = len(buf)
- for j in range(n):
+ for j from 0 <= j < n:
  val = buf[j]
  if val not in table:
  table[val] = stub
@@ -206,7 +200,7 @@ def fast_unique_multiple_list_gen(object gen, bint sort=True):
 
  for buf in gen:
  n = len(buf)
- for j in range(n): 
+ for j from 0 <= j < n:
  val = buf[j]
  if val not in table:
  table[val] = stub
@@ -836,15 +830,15 @@ def count_level_2d(ndarray[uint8_t, ndim=2, cast=True] mask,
  if axis == 0:
  counts = np.zeros((max_bin, k), dtype='i8')
  with nogil:
- for i in range(n):
- for j in range(n):
+ for i from 0 <= i < n:
+ for j from 0 <= j < k:
  counts[labels[i], j] += mask[i, j]
 
  else: # axis == 1
  counts = np.zeros((n, max_bin), dtype='i8')
  with nogil:
- for i in range(n):
- for j in range(k):
+ for i from 0 <= i < n:
+ for j from 0 <= j < k:
  counts[i, labels[j]] += mask[i, j]
 
  return counts