This document is intended to be read on github. Some of what appears below does not render properly on other websites such as pypi.org.
This assumes you have Python installed (and pip, which comes with Python unless you have a very old Python distribution). At a command prompt (e.g., cmd or Powershell in Windows, terminal in Linux or Mac), type
pip install aggie-unterprise
If you don't want to install Python or write Python code, some functionality is available through a downloadable standalone program.
This is an example of a useful summary of research grant funds:
| Project Name | Expenses | Salary | Travel | Supplies | Fringe | Fellowship | Indirect | Balance | Budget |
|---|---|---|---|---|---|---|---|---|---|
| INDIRECT COST RETURN | $0.00 | $0.00 | $0.00 | $0.00 | $0.00 | $0.00 | $0.00 | $904.00 | $904.00 |
| DISCRETIONARY FUNDS | $0.00 | $0.00 | $0.00 | $0.00 | $0.00 | $0.00 | $0.00 | $2,500.00 | $2,500.00 |
| NSF Engineering DNA and RNA | $61,316.61 | $34,800.00 | $0.00 | $133.40 | $3,263.70 | $0.00 | $23,119.51 | $318,683.39 | $380,000.00 |
| NSF CAREER Chemical Computation | $468,000.72 | $211,746.21 | $33,334.25 | $8,847.54 | $58,519.35 | $5,166.81 | $150,386.56 | $17,180.28 | $485,181.00 |
| REU CAREER Chemical Computation | $44,062.63 | $43,180.29 | $0.00 | $0.00 | $882.34 | $0.00 | $0.00 | $18,750.37 | $62,813.00 |
| DOE Office of Science Basic Energy | $15,045.49 | $8,642.86 | $0.00 | $0.00 | $760.57 | $0.00 | $5,642.06 | $51,372.51 | $66,418.00 |
AggieEnterprise is a software system used by UC Davis, whose purpose is bury this useful information beneath mountains of gibberish, resulting in a spreadsheet filled with useless trash like this:
The aggie_unterprise Python package helps you, the AGGIE, to UNdo this enTERPRISing feat. It sifts through the trash to find the important data related to your grants.
Suppose you have generated a spreadsheet from AggieEnterprise named 2024-8-1.xlsx following these instructions. The following code:
from aggie_unterprise import Summary
summary = Summary.from_file('2024-8-1.xlsx')
print(f'Totals for {summary.month()} {summary.year()}')
print(summary)will print something like this:
Totals for August 2024
╭────────────────────────────────────┬─────────────┬─────────────┬────────────┬────────────┬────────────┬──────────────┬─────────────┬─────────────┬─────────────╮
│ Project Name │ Expenses │ Salary │ Travel │ Supplies │ Fringe │ Fellowship │ Indirect │ Balance │ Budget │
├────────────────────────────────────┼─────────────┼─────────────┼────────────┼────────────┼────────────┼──────────────┼─────────────┼─────────────┼─────────────┤
│ INDIRECT COST RETURN │ $0.00 │ $0.00 │ $0.00 │ $0.00 │ $0.00 │ $0.00 │ $0.00 │ $904.00 │ $904.00 │
│ DISCRETIONARY FUNDS │ $0.00 │ $0.00 │ $0.00 │ $0.00 │ $0.00 │ $0.00 │ $0.00 │ $2,500.00 │ $2,500.00 │
│ NSF Engineering DNA and RNA │ $61,316.61 │ $34,800.00 │ $0.00 │ $133.40 │ $3,263.70 │ $0.00 │ $23,119.51 │ $318,683.39 │ $380,000.00 │
│ NSF CAREER Chemical Computation │ $468,000.72 │ $211,746.21 │ $33,334.25 │ $8,847.54 │ $58,519.35 │ $5,166.81 │ $150,386.56 │ $17,180.28 │ $485,181.00 │
│ REU CAREER Chemical Computation │ $44,062.63 │ $43,180.29 │ $0.00 │ $0.00 │ $882.34 │ $0.00 │ $0.00 │ $18,750.37 │ $62,813.00 │
│ DOE Office of Science Basic Energy │ $15,045.49 │ $8,642.86 │ $0.00 │ $0.00 │ $760.57 │ $0.00 │ $5,642.06 │ $51,372.51 │ $66,418.00 │
╰────────────────────────────────────┴─────────────┴─────────────┴────────────┴────────────┴────────────┴──────────────┴─────────────┴─────────────┴─────────────╯
The table summarizes expenses, broken down by type of expense, remaining balance, and original total budget, for each grant. These are the totals since the start of each grant.
Since we sometimes care about monthly spending, we may want to know the differences between months, to indicate for instance, how much money was spent during July (e.g., $800 total spent by August - $600 total spent by July = $200 spent during July). The method Summary.diff_table gives this information:
from aggie_unterprise import Summary
summary_aug = Summary.from_file('2024-8-1.xlsx')
summary_jul = Summary.from_file('2024-7-1.xlsx')
print(f'Difference between {summary_aug.month()} and {summary_jul.month()}')
print(summary_aug.diff_table(summary_jul))Difference between August and July
╭────────────────────────────────────┬────────────┬────────────┬───────────┬────────────┬───────────┬──────────────┬────────────┬─────────────╮
│ Project Name │ Expenses │ Salary │ Travel │ Supplies │ Fringe │ Fellowship │ Indirect │ Balance │
├────────────────────────────────────┼────────────┼────────────┼───────────┼────────────┼───────────┼──────────────┼────────────┼─────────────┤
│ INDIRECT COST RETURN │ $0.00 │ $0.00 │ $0.00 │ $0.00 │ $0.00 │ $0.00 │ $0.00 │ $0.00 │
│ DISCRETIONARY FUNDS │ $0.00 │ $0.00 │ $0.00 │ $0.00 │ $0.00 │ $0.00 │ $0.00 │ $0.00 │
│ NSF Engineering DNA and RNA │ $32,401.41 │ $18,300.00 │ $0.00 │ $13.40 │ $1,811.70 │ $0.00 │ $12,276.31 │ -$32,401.41 │
│ NSF CAREER Chemical Computation │ $14,347.87 │ $5,275.73 │ $3,504.27 │ $2,458.96 │ $100.24 │ -$3,826.31 │ $6,834.98 │ $62,178.13 │
│ REU CAREER Chemical Computation │ $0.00 │ $0.00 │ $0.00 │ $0.00 │ $0.00 │ $0.00 │ $0.00 │ $0.00 │
│ DOE Office of Science Basic Energy │ $0.00 │ $0.00 │ $0.00 │ $0.00 │ $0.00 │ $0.00 │ $0.00 │ $0.00 │
╰────────────────────────────────────┴────────────┴────────────┴───────────┴────────────┴───────────┴──────────────┴────────────┴─────────────╯
In the diff table, one would normally expect each entry under Balance (which represents a change in balance from July to August) to be the negative of the entry under Expenses (total amount of expenses between July and August), as in the project "NSF Engineering DNA and RNA". However, sometimes a grant agency will deposit new funds in between the dates (as happened in the "NSF CAREER Chemical Computation" entry above), so the change in balance and change in expenses are not always negatives of each other.
You can also render the tables in Markdown in a Jupyter notebook, so they will appear similar to the first table shown at the top of this document. When you print/stringify a Summary, it calls a method called table (so f'{summary}' is equivalent to f'{summary.table()}'), which, along with the method diff_table, can take the tablefmt argument with value 'github' to render the table appropriately for Markdown ('github' means "GitHub-flavored Markdown", which Jupyter can render nicely):
from aggie_unterprise import Summary, summary_diff_table, summary_table
summary_aug = Summary.from_file('2024-8-5.xlsx')
summary_jul = Summary.from_file('2024-7-11.xlsx')
from IPython.display import display, Markdown
display(Markdown(f"""\
### Totals for {summary_aug.month()}
{summary_aug.table(tablefmt='github')}
### Totals for {summary_jul.month()}
{summary_jul.table(tablefmt='github')}
### Difference between {summary_aug.month()} and {summary_jul.month()}
{summary_aug.diff_table(summary_jul, tablefmt='github')}
"""))In general, you can pass any value to tablefmt that the tabulate package expects in its function tabulate: https://github.com/astanin/python-tabulate?tab=readme-ov-file#table-format.
Finally, you can customize a bit how to clean up project names. They are taken either from the column "Project Name" in the spreadsheet for sponsored (external) grant, or the column "Task/Subtask Name" for internal funds (e.g., startup grants or indirect cost return), since the project names for internal grants tend to be identical (for the CS department for me, they are all named "David Doty ENGR COMPUTER SCIENCE PPM Only").
To clean up the project names, you can specify two arguments to the Summary.from_file method: substrings_to_clean and suffixes_to_clean. Any substring appearing in substrings_to_clean will be removed, for example if I set substrings_to_clean=['CS', 'Doty'], it will change the project name "CS NSF Engineering DNA and RNA Doty K302325F33" to "NSF Engineering DNA and RNA K302325F33". Anything in suffixes_to_clean will be removed, not only that substring, but the entire rest of the name. For instance, if I set suffixes_to_clean=['K3023'], it will change "NSF Engineering DNA and RNA K302325F33" to "NSF Engineering DNA and RNA".
I personally use them like this:
suffixes = ['K3023', 'DOTY DEFAULT PROJECT 13U00']
substrings = ['Doty', 'CS ']
summary_aug = Summary.from_file('2024-8-1.xlsx', substrings_to_clean=substrings, suffixes_to_clean=suffixes)due to the particular manner in which someone mashed their palm against the keyboard to generate the alien-looking project names of my own grants (e.g. "CS NSF DNA and RNA Partic Support Doty K3023EDRNA"), but you will want to customize according to the shape of your SPO representative's palm.
If you do not want to install Python or write Python code, there is a standalone command-line program called aggie-report that can do some basic tasks. There are pre-compiled versions of aggie-report you can download:
- Windows (save with file name
aggie-report.exe) - Linux (save with file name
aggie-report) - macOS (save with file name
aggie-report)
Open a command prompt in the directory where you saved the file.
On Mac (respectively Linux), type mv aggie-report-mac aggie-report to rename the file to aggie-report (respectively mv aggie-report-linux aggie-report on Linux).
On Mac and Linux, type chmod +x aggie-report (after renaming the file to aggie-report) to make the program executable.
On Mac, you must then type xattr -d com.apple.quarantine ./aggie-report to enable the program to run.
Run aggie-report -h to see all the options.
Alternately, you can install Python, then install the package by typing pip install aggie_unterprise. After doing this, you will have a program named aggie-report you can use from any directory:
$ aggie-report -d reports
Assuming you have a subdirectory reports of your current directory with your AggieEnterprise reports in it, this will print to the screen a summary of each report, as well as a summary of differences between adjacent-in-creation-time reports. It sorts them in descending order of the date they were produced (so prints the latest one first).
The other options are as follows, but in case this documentation gets outdated, run aggie-report -h to see the latest options:
usage: aggie-report [-h] [-d DIRECTORY | -f FILE [FILE ...]] [-o OUTFILE] [-nd | -ni]
[-s] [-sb SUBSTRING [SUBSTRING ...]] [-sf SUFFIX [SUFFIX ...]]
[-sbf SUBSTRINGS_FILE] [-sff SUFFIXES_FILE]
Processes reports generated by AggieEnterprise to summarize the useful data in them.
By default it sorts the files by the date they were generated (according to cell A3
inside the spreadsheet file), and in that order going backwards (so latest file is
processed first), summarizes each file, as well as summarizing differences between
adjacent files. If run with no arguments like this: `C:\reports> aggie-report`
(or if you are using the Python script, `C:\reports> python aggie_report.py`)
it will process all the .xlsx files in the current directory and print the results to
the screen. Command line arguments can be used to customize this; type
`aggie_report -h` to see all the options.
options:
-h, --help show this help message and exit
-d DIRECTORY, --directory DIRECTORY
directory to search for .xlsx files generated by AggieEnterprise.
All .xlsx files are processed; to process only some files,
list them explicitly after the flag -f. If neither -d nor -f
is given, all .xlsx files in the current directory are processed.
This option is mutually exclusive with -f.
-f FILE [FILE ...], --files FILE [FILE ...]
List of one or more .xlsx files generated by AggieEnterprise.
To specify that all .xlsx files in a directory should be
processed, use the -d option. This option is mutually exclusive
with -d.
-o OUTFILE, --outfile OUTFILE
Name of file to print output; if not specified, print output to
the screen.
-nd, --no-diffs If specified, do not include differences between adjacent files
in the output. This option is mutually exclusive with -ni.
-ni, --no-individual If specified, do not include summaries for individual files.
This option is mutually exclusive with -nd.
-s, --sort-increasing-by-date
If specified, sort the files by date in increasing order instead
of the default, which is to sort by date in decreasing order.
--sb SUBSTRING [SUBSTRING ...], --substrings SUBSTRING [SUBSTRING ...]
List of substrings to remove from the project name. This can
help clean up ugly project names like "NSF CAREER K20304932"
by specifying substring "K20304932", which would change the
project name to "NSF CAREER".
--sf SUFFIX [SUFFIX ...], --suffixes SUFFIX [SUFFIX ...]
List of substrings to remove from the project name, as well
as the entire suffix from there to the end. This can help
clean up ugly project names like "NSF CAREER K302777" and
"NSF Small K302999" by specifying substring "K302", which
would change these project names "NSF CAREER" and "NSF
Small".
--sbf SUBSTRINGS_FILE, --substrings-file SUBSTRINGS_FILE
Filename containing substrings (separated by whitespace or
newlines) to remove from the project name. This is like the
-sb option, but reads the substrings from a file so that you
do not have to type them all out at the command line and can
reuse them in multiple runs.
--ssf SUFFIXES_FILE, --suffixes-file SUFFIXES_FILE
Filename containing substrings (separated by whitespace or
newlines) to remove from the project name, as well as the
entire suffix from there to the end. This is like the -sf
option, but reads the substrings from a file so that you do
not have to type them all out at the command line and can
reuse them in multiple runs.