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CLN: Removed Unnecessary Conditionals in groupby_helper #19734

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Merged
merged 1 commit into from
Feb 18, 2018
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CLN: Removed Unnecessary Conditionals in groupby_helper #19734

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176 changes: 47 additions & 129 deletions pandas/_libs/groupby_helper.pxi.in
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Original file line number Diff line number Diff line change
Expand Up @@ -56,36 +56,19 @@ def group_add_{{name}}(ndarray[{{dest_type2}}, ndim=2] out,

with nogil:

if K > 1:

for i in range(N):
lab = labels[i]
if lab < 0:
continue

counts[lab] += 1
for j in range(K):
val = values[i, j]

# not nan
if val == val:
nobs[lab, j] += 1
sumx[lab, j] += val

else:

for i in range(N):
lab = labels[i]
if lab < 0:
continue
for i in range(N):
lab = labels[i]
if lab < 0:
continue

counts[lab] += 1
val = values[i, 0]
counts[lab] += 1
for j in range(K):
val = values[i, j]

# not nan
if val == val:
nobs[lab, 0] += 1
sumx[lab, 0] += val
nobs[lab, j] += 1
sumx[lab, j] += val

for i in range(ncounts):
for j in range(K):
Expand Down Expand Up @@ -119,33 +102,19 @@ def group_prod_{{name}}(ndarray[{{dest_type2}}, ndim=2] out,
N, K = (<object> values).shape

with nogil:
if K > 1:
for i in range(N):
lab = labels[i]
if lab < 0:
continue

counts[lab] += 1
for j in range(K):
val = values[i, j]

# not nan
if val == val:
nobs[lab, j] += 1
prodx[lab, j] *= val
else:
for i in range(N):
lab = labels[i]
if lab < 0:
continue
for i in range(N):
lab = labels[i]
if lab < 0:
continue

counts[lab] += 1
val = values[i, 0]
counts[lab] += 1
for j in range(K):
val = values[i, j]

# not nan
if val == val:
nobs[lab, 0] += 1
prodx[lab, 0] *= val
nobs[lab, j] += 1
prodx[lab, j] *= val

for i in range(ncounts):
for j in range(K):
Expand Down Expand Up @@ -231,31 +200,18 @@ def group_mean_{{name}}(ndarray[{{dest_type2}}, ndim=2] out,
N, K = (<object> values).shape

with nogil:
if K > 1:
for i in range(N):
lab = labels[i]
if lab < 0:
continue

counts[lab] += 1
for j in range(K):
val = values[i, j]
# not nan
if val == val:
nobs[lab, j] += 1
sumx[lab, j] += val
else:
for i in range(N):
lab = labels[i]
if lab < 0:
continue
for i in range(N):
lab = labels[i]
if lab < 0:
continue

counts[lab] += 1
val = values[i, 0]
counts[lab] += 1
for j in range(K):
val = values[i, j]
# not nan
if val == val:
nobs[lab, 0] += 1
sumx[lab, 0] += val
nobs[lab, j] += 1
sumx[lab, j] += val

for i in range(ncounts):
for j in range(K):
Expand Down Expand Up @@ -670,43 +626,24 @@ def group_max_{{name}}(ndarray[{{dest_type2}}, ndim=2] out,
N, K = (<object> values).shape

with nogil:
if K > 1:
for i in range(N):
lab = labels[i]
if lab < 0:
continue

counts[lab] += 1
for j in range(K):
val = values[i, j]

# not nan
{{if name == 'int64'}}
if val != {{nan_val}}:
{{else}}
if val == val and val != {{nan_val}}:
{{endif}}
nobs[lab, j] += 1
if val > maxx[lab, j]:
maxx[lab, j] = val
else:
for i in range(N):
lab = labels[i]
if lab < 0:
continue
for i in range(N):
lab = labels[i]
if lab < 0:
continue

counts[lab] += 1
val = values[i, 0]
counts[lab] += 1
for j in range(K):
val = values[i, j]

# not nan
{{if name == 'int64'}}
if val != {{nan_val}}:
{{else}}
if val == val and val != {{nan_val}}:
{{endif}}
nobs[lab, 0] += 1
if val > maxx[lab, 0]:
maxx[lab, 0] = val
nobs[lab, j] += 1
if val > maxx[lab, j]:
maxx[lab, j] = val

for i in range(ncounts):
for j in range(K):
Expand Down Expand Up @@ -744,43 +681,24 @@ def group_min_{{name}}(ndarray[{{dest_type2}}, ndim=2] out,
N, K = (<object> values).shape

with nogil:
if K > 1:
for i in range(N):
lab = labels[i]
if lab < 0:
continue

counts[lab] += 1
for j in range(K):
val = values[i, j]

# not nan
{{if name == 'int64'}}
if val != {{nan_val}}:
{{else}}
if val == val and val != {{nan_val}}:
{{endif}}
nobs[lab, j] += 1
if val < minx[lab, j]:
minx[lab, j] = val
else:
for i in range(N):
lab = labels[i]
if lab < 0:
continue
for i in range(N):
lab = labels[i]
if lab < 0:
continue

counts[lab] += 1
val = values[i, 0]
counts[lab] += 1
for j in range(K):
val = values[i, j]

# not nan
{{if name == 'int64'}}
if val != {{nan_val}}:
{{else}}
if val == val and val != {{nan_val}}:
{{endif}}
nobs[lab, 0] += 1
if val < minx[lab, 0]:
minx[lab, 0] = val
nobs[lab, j] += 1
if val < minx[lab, j]:
minx[lab, j] = val

for i in range(ncounts):
for j in range(K):
Expand Down