Skip to content

added pandas day alias to fix problem when using hercules with resolutions < 1 month #323

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Nov 28, 2019
Merged

added pandas day alias to fix problem when using hercules with resolutions < 1 month #323

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
7 changes: 6 additions & 1 deletion python/labours/modes/burndown.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -328,7 +328,7 @@ def load_burndown(
)
daily[(last - start).days :] = 0
# Resample the bands
aliases = {"year": "A", "month": "M"}
aliases = {"year": "A", "month": "M", "day": "D"}
resample = aliases.get(resample, resample)
periods = 0
date_granularity_sampling = [start]
Expand All @@ -343,6 +343,11 @@ def load_burndown(
return load_burndown(
header, name, matrix, "month", report_survival=False
)
elif resample == "M":
print("too loose resampling - by month, trying by day")
return load_burndown(
header, name, matrix, "day", report_survival=False
)
else:
raise ValueError("Too loose resampling: %s. Try finer." % resample)
date_range_sampling = pandas.date_range(
Expand Down