Replace deprecated applymap() and use two decimal places for formatting #1743
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Additional details and impacted files@@ Coverage Diff @@
## main #1743 +/- ##
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Coverage 94.17% 94.17%
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Files 66 66
Lines 4170 4170
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Hits 3927 3927
Misses 243 243 ☔ View full report in Codecov by Sentry. |
| @@ -184,7 +184,7 @@ def get_context_data(self, **kwargs): | |||
| "headcount_data": headcount_data_frame.pivot( | |||
| index="start_date", values="headcount", columns="organization" | |||
| ) | |||
| .applymap("{:.0f}".format) | |||
| .map("{:.0f}".format) | |||
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shouldn't this be :.2 for consistency as well?
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I originally made a commit to change it to :.2f but it seems like it's used to display the headcount within the data table on the route utilization/analytics, I may have assumed incorrectly that head count was going to be a whole number. That's an easy enough change if we'd like it to be that way.
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I think that this one is a whole number and so 0 decimal places is correct.
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Thanks y'all! You are right, 0 decimal places is correct here. Merge at will!
| @@ -184,7 +184,7 @@ def get_context_data(self, **kwargs): | |||
| "headcount_data": headcount_data_frame.pivot( | |||
| index="start_date", values="headcount", columns="organization" | |||
| ) | |||
| .applymap("{:.0f}".format) | |||
| .map("{:.0f}".format) | |||
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I think that this one is a whole number and so 0 decimal places is correct.
Description
This attempts to resolve #1642
Additional information
Include any of the following (as necessary):
For a project view (/projects/{pk_id}), we were previously formatting the total hours in the data table using
:.0f, I've updated that to format using:.2finstead. This seems to correctly stop truncating hours and the test suite passes.The original ticket also mentions
DataTable.applymap()being deprecated and replaced byDataTable.map(). I found thatDataTable.map()was already being used in the utilization/analytics.py file but the terminal complained aboutDataTable.applymap()in utilization/views.py on line 187, I've replacedDataTable.applymap()withDataTable.map()and that didn't seem to upset anything.