# GoodData Pandas
This package contains a thin layer that utilizes gooddata-sdk and allows you to conveniently create pandas series and
data frames from the computations done against semantic model in your [GoodData.CN](https://www.gooddata.com/developers/cloud-native/) workspace.
See [DOCUMENTATION](https://gooddata-pandas.readthedocs.io/en/latest/) for more details.
## Requirements
- GoodData.CN installation; either running on your cloud
infrastructure or the free Community Edition running on your workstation
- Python 3.9 or newer
## Installation
Run the following command to install the `gooddata-pandas` package on your system:
pip install gooddata-pandas
## Example
Create an indexed and a not-indexed series:
```python
from gooddata_pandas import GoodPandas
# GoodData.CN host in the form of uri eg. "http://localhost:3000"
host = "http://localhost:3000"
# GoodData.CN user token
token = "some_user_token"
# initialize the adapter to work on top of GD.CN host and use the provided authentication token
gp = GoodPandas(host, token)
workspace_id = "demo"
series = gp.series(workspace_id)
# create indexed series
indexed_series = series.indexed(index_by="label/label_id", data_by="fact/measure_id")
# create non-indexed series containing just the values of measure sliced by elements of the label
non_indexed = series.not_indexed(data_by="fact/measure_id", granularity="label/label_id")
```
## Bugs & Requests
Please use the [GitHub issue tracker](https://github.com/gooddata/gooddata-python-sdk/issues) to submit bugs
or request features.
## Changelog
Consult [Github releases](https://github.com/gooddata/gooddata-python-sdk/releases) for a released versions
and list of changes.
Raw data
{
"_id": null,
"home_page": null,
"name": "gooddata-pandas",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.9.0",
"maintainer_email": null,
"keywords": "gooddata, pandas, series, data, frame, data_frame, analytics, headless, business, intelligence, headless-bi, cloud, native, semantic, layer, sql, metrics",
"author": "GoodData",
"author_email": "support@gooddata.com",
"download_url": "https://files.pythonhosted.org/packages/24/15/e7498a01ffd520f6c0bd752328ea1c4b7de988079ea05e0edd94ab78d003/gooddata_pandas-1.49.0.tar.gz",
"platform": null,
"description": "# GoodData Pandas\n\nThis package contains a thin layer that utilizes gooddata-sdk and allows you to conveniently create pandas series and\ndata frames from the computations done against semantic model in your [GoodData.CN](https://www.gooddata.com/developers/cloud-native/) workspace.\n\nSee [DOCUMENTATION](https://gooddata-pandas.readthedocs.io/en/latest/) for more details.\n\n## Requirements\n\n- GoodData.CN installation; either running on your cloud\n infrastructure or the free Community Edition running on your workstation\n\n- Python 3.9 or newer\n\n## Installation\n\nRun the following command to install the `gooddata-pandas` package on your system:\n\n pip install gooddata-pandas\n\n## Example\n\nCreate an indexed and a not-indexed series:\n\n```python\nfrom gooddata_pandas import GoodPandas\n\n# GoodData.CN host in the form of uri eg. \"http://localhost:3000\"\nhost = \"http://localhost:3000\"\n# GoodData.CN user token\ntoken = \"some_user_token\"\n# initialize the adapter to work on top of GD.CN host and use the provided authentication token\ngp = GoodPandas(host, token)\n\nworkspace_id = \"demo\"\nseries = gp.series(workspace_id)\n\n# create indexed series\nindexed_series = series.indexed(index_by=\"label/label_id\", data_by=\"fact/measure_id\")\n\n# create non-indexed series containing just the values of measure sliced by elements of the label\nnon_indexed = series.not_indexed(data_by=\"fact/measure_id\", granularity=\"label/label_id\")\n```\n\n## Bugs & Requests\n\nPlease use the [GitHub issue tracker](https://github.com/gooddata/gooddata-python-sdk/issues) to submit bugs\nor request features.\n\n## Changelog\n\nConsult [Github releases](https://github.com/gooddata/gooddata-python-sdk/releases) for a released versions\nand list of changes.\n",
"bugtrack_url": null,
"license": "MIT",
"summary": "GoodData Cloud to pandas",
"version": "1.49.0",
"project_urls": {
"Documentation": "https://gooddata-pandas.readthedocs.io/en/v1.49.0",
"Source": "https://github.com/gooddata/gooddata-python-sdk"
},
"split_keywords": [
"gooddata",
" pandas",
" series",
" data",
" frame",
" data_frame",
" analytics",
" headless",
" business",
" intelligence",
" headless-bi",
" cloud",
" native",
" semantic",
" layer",
" sql",
" metrics"
],
"urls": [
{
"comment_text": null,
"digests": {
"blake2b_256": "33ce39f1726b4d5ffcda6b0b1e08d2f209e68da703dfee095999c21442943615",
"md5": "e9b53c33d499bb4273ec804451c902d7",
"sha256": "96ec54ee94d6dd1544b71fc4aba1c998ead305e285ac879794720d5cfa0600f6"
},
"downloads": -1,
"filename": "gooddata_pandas-1.49.0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "e9b53c33d499bb4273ec804451c902d7",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.9.0",
"size": 49855,
"upload_time": "2025-08-21T13:50:13",
"upload_time_iso_8601": "2025-08-21T13:50:13.954675Z",
"url": "https://files.pythonhosted.org/packages/33/ce/39f1726b4d5ffcda6b0b1e08d2f209e68da703dfee095999c21442943615/gooddata_pandas-1.49.0-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "2415e7498a01ffd520f6c0bd752328ea1c4b7de988079ea05e0edd94ab78d003",
"md5": "d821d25d832a9f25720fb9b0349b313b",
"sha256": "6ff30e51e4c413e984ed0c73f96efc5b82d94e2e36f95160d08fb977eb4b1041"
},
"downloads": -1,
"filename": "gooddata_pandas-1.49.0.tar.gz",
"has_sig": false,
"md5_digest": "d821d25d832a9f25720fb9b0349b313b",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.9.0",
"size": 47415,
"upload_time": "2025-08-21T13:50:18",
"upload_time_iso_8601": "2025-08-21T13:50:18.015160Z",
"url": "https://files.pythonhosted.org/packages/24/15/e7498a01ffd520f6c0bd752328ea1c4b7de988079ea05e0edd94ab78d003/gooddata_pandas-1.49.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2025-08-21 13:50:18",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "gooddata",
"github_project": "gooddata-python-sdk",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "gooddata-pandas"
}