# catnet
[](https://doi.org/10.5281/zenodo.14031788)
## What catnet does
`catnet` is a Python package that allows for transforming tabular data into a network structure. `catnet` can identify the coexistence of variables and categories in literature reviews and other tables and create a network dataframe that can be exported into a format that can be taken by other packages such as `networkx` and applications such as [Gephi](https://gephi.org/).
`catnet` is a Python package designed to facilitate the creation and analysis of category networks. Whether you’re working with literature review tables or other structured data, `catnet` empowers researchers and analysts to build insightful networks that reveal relationships and patterns within their categories. Streamline your data exploration and enhance your analytical capabilities with catnet!
## How to install catnet
To install this package run:
`python -m pip install git+https://github.com/CamiBetancur/catnet/)`
## Get started using catnet
To be able to use `catnet` you need to format your dataframe in one of the following ways:
### 1. **"Long" format**
"Long" format refers to data that has a column for describing a categorical variable (`var_col`) and an identifier column (`id_col`) that identifies to which entity that variable belongs to. For example, in a literature review, a long dataframe that could be used by catnet could look like this (note that the column names `id_col` and `var_col` do not necessarily need to be named `id_col` and `var_col`):
| id_col | var_col | other_data_cols |
| ------ | ------------------ | --------------- |
| doc_01 | Health | ... |
| doc_01 | Water access | ... |
| doc_01 | Water quality | ... |
| doc_02 | Health | ... |
| doc_02 | Energy generation | ... |
| ... | ... | ... |
Datasets in "long" format can be transformed into networks by using the `catnet.from_long_df()` function. For more information, you can look at the [Examples Jupyter Notebook](https://github.com/CamiBetancur/catnet/blob/main/Examples.ipynb) or the [Examples Markdown file](https://github.com/CamiBetancur/catnet/blob/main/Examples.md).
### 2. **"Same cell" format**
Dataframes in the "same cell" format contain a list of categories insid the same cell. The identifier colum (`id_col`) marks different documents/observations, while the categorical variable column (`var_col`) contains the lists of categories.
| id_col | var_col | other_data_cols |
| ------ | ------------------ | --------------- |
| doc_01 | Health; Water | ... |
| | access; Water | |
| | quality | |
| doc_02 | Health; Energy | ... |
| | generation | |
| ... | ... | ... |
Datasets in the "same cell" format can be transformed into networks by using the `catnet.from_same_cell()` function. For more information, you can look at the [Examples Jupyter Notebook](https://github.com/CamiBetancur/catnet/blob/main/Examples.ipynb) or the [Examples Markdown file](https://github.com/CamiBetancur/catnet/blob/main/Examples.md).
## How to cite catnet
### APA 7
>Betancur Jaramillo, J. C. (2024). _catnet source code (Version 0.1.0)_ [source code]. [https://github.com/CamiBetancur/catnet/](https://github.com/CamiBetancur/catnet/).
### BibTex
```
@misc{Betancur_2024,
title={catnet v0.1.0},
url={https://github.com/CamiBetancur/catnet},
publisher={Stockholm Environment Institute},
author={Betancur Jaramillo, Juan Camilo},
year={2024}}
```
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"description": "# catnet\n[](https://doi.org/10.5281/zenodo.14031788)\n\n## What catnet does\n`catnet` is a Python package that allows for transforming tabular data into a network structure. `catnet` can identify the coexistence of variables and categories in literature reviews and other tables and create a network dataframe that can be exported into a format that can be taken by other packages such as `networkx` and applications such as [Gephi](https://gephi.org/).\n\n`catnet` is a Python package designed to facilitate the creation and analysis of category networks. Whether you\u2019re working with literature review tables or other structured data, `catnet` empowers researchers and analysts to build insightful networks that reveal relationships and patterns within their categories. Streamline your data exploration and enhance your analytical capabilities with catnet!\n\n## How to install catnet\nTo install this package run:\n\n`python -m pip install git+https://github.com/CamiBetancur/catnet/)`\n\n## Get started using catnet\n\nTo be able to use `catnet` you need to format your dataframe in one of the following ways:\n\n### 1. **\"Long\" format**\n\"Long\" format refers to data that has a column for describing a categorical variable (`var_col`) and an identifier column (`id_col`) that identifies to which entity that variable belongs to. For example, in a literature review, a long dataframe that could be used by catnet could look like this (note that the column names `id_col` and `var_col` do not necessarily need to be named `id_col` and `var_col`):\n\n| id_col | var_col | other_data_cols |\n| ------ | ------------------ | --------------- |\n| doc_01 | Health | ... |\n| doc_01 | Water access | ... |\n| doc_01 | Water quality | ... |\n| doc_02 | Health | ... |\n| doc_02 | Energy generation | ... |\n| ... | ... | ... |\n\nDatasets in \"long\" format can be transformed into networks by using the `catnet.from_long_df()` function. For more information, you can look at the [Examples Jupyter Notebook](https://github.com/CamiBetancur/catnet/blob/main/Examples.ipynb) or the [Examples Markdown file](https://github.com/CamiBetancur/catnet/blob/main/Examples.md).\n\n### 2. **\"Same cell\" format**\nDataframes in the \"same cell\" format contain a list of categories insid the same cell. The identifier colum (`id_col`) marks different documents/observations, while the categorical variable column (`var_col`) contains the lists of categories.\n\n| id_col | var_col | other_data_cols |\n| ------ | ------------------ | --------------- |\n| doc_01 | Health; Water | ... |\n| | access; Water | |\n| | quality | |\n| doc_02 | Health; Energy | ... |\n| | generation | |\n| ... | ... | ... |\n\nDatasets in the \"same cell\" format can be transformed into networks by using the `catnet.from_same_cell()` function. For more information, you can look at the [Examples Jupyter Notebook](https://github.com/CamiBetancur/catnet/blob/main/Examples.ipynb) or the [Examples Markdown file](https://github.com/CamiBetancur/catnet/blob/main/Examples.md).\n\n## How to cite catnet\n\n### APA 7\n\n>Betancur Jaramillo, J. C. (2024). _catnet source code (Version 0.1.0)_ [source code]. [https://github.com/CamiBetancur/catnet/](https://github.com/CamiBetancur/catnet/). \n\n### BibTex\n\n```\n@misc{Betancur_2024, \n title={catnet v0.1.0}, \n url={https://github.com/CamiBetancur/catnet}, \n publisher={Stockholm Environment Institute}, \n author={Betancur Jaramillo, Juan Camilo}, \n year={2024}} \n```",
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