simpandas
A couple of Pandas DataFrame and Series subclasses, extended to work with units and to deal with column names following the style of eclipse simulator outputs.
This package is under development and is regularly updated. Back-compatibility is intended to be maintained when possible.
Version: 0.93.0 | Python: ≥3.7 (≥3.8 recommended) | Pandas: 1.3.0 - 3.x
What Contains This Package
It is powered by other packages, like NumPy, seaborn and unyts and further own methods, to be able to deal with tables of quantities and facilitate common manipulations of time-dependent data.
Key Features
- Unit-aware DataFrames and Series: Automatic unit tracking and conversion using unyts
- Pandas 1.3-3.x compatible: Compatibility wrappers avoid pandas 2.x/3.x deprecation paths while retaining support for pandas 1.3+
- Enhanced I/O: Read/write Excel, CSV, and JSON files with unit metadata preservation
- Expanded pandas wrapper coverage:
ffill,bfill,pct_change,asfreq,combine_first,isin,compare,swaplevel,align,update,resample, andbetweennow return Sim types where applicable - Time-series utilities: Built-in methods for daily, monthly, yearly aggregations
- Eclipse-style simulator support: Handle column naming conventions from reservoir simulators
- Eclipse/OPM summary round-trip: Read/write
.SMSPEC+.UNSMRYfiles withto_summary/read_summaryand optionalOPMorECLIPSEnaming style - Schedule import: Read
WCONHIST,WCONINJH,WCONPRODandWCONINJEEclipse schedule records with inferred FIELD or METRIC units; each row carries the date set bySTART/DATES/TIME/TSTEP - CMG SR3 support: Read/write CMG
.sr3files (IMEX, GEM, STARS) withread_sr3/write_sr3(requiresh5py)
Installation
To install from pypi.org:
pip install simpandas
To upgrade to the latest version:
pip install --upgrade simpandas
Requirements
- pandas ≥1.3.0, <4.0.0
- numpy
- matplotlib
- seaborn
- unyts ≥1.0.0
- schedule_reader ≥0.7.15 (for Eclipse schedule imports; use the latest version for the strict Eclipse date parsing)
- h5py (optional, for CMG SR3 files)
- openpyxl (for Excel support)
- xlsxwriter (for Excel writing)
- packaging (for version detection)
Quick Start
from simpandas import SimDataFrame, SimSeries, read_csv, read_json
# Create a DataFrame with units
df = SimDataFrame(
{'velocity': [1, 2, 3], 'temperature': [25, 30, 35]},
units={'velocity': 'm/s', 'temperature': 'degC'}
)
# Units are preserved through operations
result = df * 2
print(df.get_units()) # Access unit information
# Read CSV/JSON with units
df = read_csv('data.csv', units=0) # units in row 0 after the header
df = read_json('data.json') # restores units from SimPandas JSON
Compatibility Notes
Pandas Compatibility
Version 0.93.0 supports pandas 1.3.0 through the 3.x series. Compatibility wrappers avoid deprecated pandas copy arguments where pandas Copy-on-Write supersedes them. GroupBy.apply() excludes grouping columns on pandas 2.2+ to match pandas' forward behavior, while retaining the legacy call signature on older supported versions.
Selection Semantics
With Eclipse-style column names, a string can select a semantic column group. For example, sdf['WOPR'] selects columns such as WOPR:WELL-1 and WOPR:WELL-2 in their original column order. Exact column names always take precedence; strings that do not resolve to a column or name pattern can resolve to date-like index labels.
Python Version
- Minimum: Python 3.7
- Recommended: Python 3.8 or higher
Breaking Changes in v0.84.0
The writters module has been renamed to writers (correcting spelling). For backward compatibility:
# Deprecated (still works with warning):
from simpandas.writters import write_excel
# New (recommended):
from simpandas.writers import write_excel
Maintenance Updates (September 2026)
- Added wrappers for missing pandas methods in
SimBasicsto preserve metadata through more operations. - Added
_SimResampleProxyandresample()support on bothSimDataFrameandSimSeries. - Fixed filter parsing infrastructure by wiring
common.filters.key_to_string(...)correctly fromSimSeries.filter()andSimDataFrame.filter(). - Added
as_dict()andfrom_dict()forSimSerieswithunytsinstance support. - Fixed
KeyErrorin__setitem__when re-assigning columns and preserved existing units. - Added regression coverage in
test/test_bugfix_dca.py. - Resolved ambiguous string selection between name-pattern columns and datetime indexes without pandas indexing warnings.
- Added pandas 3.x compatibility for
replace,set_index,concat,rename,align,astype, andGroupBy.apply(). - Updated schedule-reader string normalization for pandas 3.x dtype-selection behavior.
Release 0.93.0 (October 2026)
- Added
read_sr3/write_sr3for CMG SR3 files, tested with two real examples from sr3_reader (MIT). - Fixed
read_schedule: dates are repeated for every record until the nextDATES/TIME/TSTEP, parsed asDD MMM YYYY [HH:MM:SS.SSSS], and rows are returned sorted by date.WCONPRODandWCONINJEare now read too.
Documentation
For detailed documentation, examples, and API reference, see:
- USER_MANUAL.md - Comprehensive user manual for classes, functions, and modules
- docs/USER_GUIDE.md - Shorter quick-start guide
- DEVELOPER_MANUAL.md - Internal architecture and contributor-focused technical notes
- CONTRIBUTING.md - Contribution workflow and release checklist
- CHANGELOG.md - Version history and migration guides
- WHATS_NEW.md - Highlights for the current release
- simpandas_demo.ipynb - Interactive examples and tutorials
- test/ - Comprehensive test suite with usage examples
API At A Glance
from simpandas import (
SimDataFrame, SimSeries, SimIndex, ColumnUnits, concat,
read_excel, read_csv, read_json, read_hdf5, read_parquet,
read_summary, read_sr3, read_schedule, read_vdb,
)
from simpandas.index import SimIndex
from simpandas.writers.xlsx import write_excel
from simpandas.writers.schedule import write_schedule
from simpandas.writers.summary import write_summary
Contributing
Contributions are welcome! Please ensure:
- Code passes all tests:
pytest test/ - Follow existing code style
- Add tests for new features
- Update documentation as needed
Testing
Run the test suite:
cd simpandas
pytest test/ -v
License
See LICENSE file for details.
Author
Martín Carlos Araya martinaraya@gmail.com
Changelog
See CHANGELOG.md for detailed version history.
Metadata
Release files for simpandas 0.93.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| simpandas-0.93.0.tar.gz | 238.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| simpandas-0.93.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 460.7 kB
Release files / simpandas-0.93.0.tar.gz
| Download URL | simpandas-0.93.0.tar.gz |
|---|---|
| Size | 238.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
c6676124f5587cccc0b3ec55912393a5af5a3ff66a0813a584923ce59d4a3dd2
|
|
BLAKE2b-256 checksum How to use checksums |
64ce8afeb274fcb9277bcbd45e4c8d5f18e7b1c3e00029d21474aeb2644fc32a
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.14.0
|
Release files / simpandas-0.93.0-py3-none-any.whl
| Download URL | simpandas-0.93.0-py3-none-any.whl |
|---|---|
| Size | 222.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
b940b9fb2be392a1cfcc38c90f5293ba3d48daf93b64cfc3f5054c7665bc98ef
|
|
BLAKE2b-256 checksum How to use checksums |
3d05ea52edf9315bc5544d4355ad6c69689d8219d5914db938f50e1c51c5fb6d
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.14.0
|