# 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/39/ec/228aa1c0df5f0c404212c9b06e5b354cab92119ff8814e67d925ed95f37a/gooddata_pandas-1.33.0.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": "1.33.0",
"project_urls": {
"Documentation": "https://gooddata-pandas.readthedocs.io/en/v1.33.0",
"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": "",
"digests": {
"blake2b_256": "88121724a54bdb4b8af165e16841f2e577d9c6f7adf29fdf6c3176bb34196f65",
"md5": "7ca8e873c87cb3fc275940ec7e8e297b",
"sha256": "97b56761e149ed8ee220ca3550db8df078f97ad5a4159abaa12df7fb6a8eb4f1"
},
"downloads": -1,
"filename": "gooddata_pandas-1.33.0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "7ca8e873c87cb3fc275940ec7e8e297b",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.9.0",
"size": 48739,
"upload_time": "2024-12-12T12:30:41",
"upload_time_iso_8601": "2024-12-12T12:30:41.889564Z",
"url": "https://files.pythonhosted.org/packages/88/12/1724a54bdb4b8af165e16841f2e577d9c6f7adf29fdf6c3176bb34196f65/gooddata_pandas-1.33.0-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "39ec228aa1c0df5f0c404212c9b06e5b354cab92119ff8814e67d925ed95f37a",
"md5": "eb669e86d945af291b7eb4c04ad5ac59",
"sha256": "3cdb693cba9b58709bec3c14914ca09b2e82671cd1a5bba5dd9ca882f7ebe1ad"
},
"downloads": -1,
"filename": "gooddata_pandas-1.33.0.tar.gz",
"has_sig": false,
"md5_digest": "eb669e86d945af291b7eb4c04ad5ac59",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.9.0",
"size": 46536,
"upload_time": "2024-12-12T12:30:47",
"upload_time_iso_8601": "2024-12-12T12:30:47.043456Z",
"url": "https://files.pythonhosted.org/packages/39/ec/228aa1c0df5f0c404212c9b06e5b354cab92119ff8814e67d925ed95f37a/gooddata_pandas-1.33.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-12-12 12:30:47",
"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"
}