<p align="center">
<img src="https://i.imgur.com/4TfRxmI.png" alt="ctrldf"></img>
<br/>
<a href="https://www.python.org/"><img src="https://img.shields.io/badge/python-3670A0?style=plastic&logo=python&logoColor=ffdd54"></img></a>
<a href="https://streamlit.io/"><img src="https://img.shields.io/badge/-Streamlit-61DAFB?style=plastic&logo=streamlit"></img></a>
<a href="https://matplotlib.org/"><img src="https://img.shields.io/badge/Matplotlib-%23ffffff.svg?style=plastic&logo=matplotlib&logoColor=black"></img></a>
<a href="https://numpy.org/doc/stable/index.html"><img src="https://img.shields.io/badge/numpy-%23013243.svg?style=plastic&logo=numpy&logoColor=white"></img></a>
<a href="https://pandas.pydata.org/docs/index.html"><img src="https://img.shields.io/badge/pandas-%23150458.svg?style=plastic&logo=pandas&logoColor=white"></img></a>
<a href="http://opensource.org/licenses/MIT"><img src="https://img.shields.io/badge/License-MIT-yellow.svg?style=plastic"></img></a>
</a>
<br/>
<a href="#Documentation">Documentation</a> ·
<a href="https://github.com/joshjetson/SCDF/issues">Report a Bug</a> ·
<a href="#Demo">Demo</a> .
<a href="https://github.com/joshjetson/SCDF/issues">Request Feature</a> ·
<a href="https://github.com/joshjetson/SCDF/pulls">Send a Pull Request</a>
</p>
## Controller DF
[]()
<i>A python library which creates a simple and easy to use data frame controller.
Using this library, along with streamlit and minimal (*included*) code, anyone can spin up a web app which allows you to control, manipulate and display a data set quickly and easily.
</i>
## Demo
<table>
<tr>
<td>
<center>
<img src="/pics/exgif.gif"></img>
- Quick column metrics
<img src="/pics/ex1.gif"></img>
- Rapid column filter
<img src="/pics/ex3.png"></img>
- Instant type based column widgets
<img src="/pics/ex2.png"></img>
</center>
</table>
</tr>
</td>
## Installation
```
$ pip install streamlit-controllerDF
```
## Getting started
<i>After you pip install the module</i>
<ins>
**Batteries included method:**
</ins>
<details><summary>Quick start</summary>
>
> - `Copy the included test_code.py`
> - `Rename the file to your projects name`
> ~~~
> $ streamlit run your_project.py
> ~~~
> - `Drag and drop csv file`
> - `Enjoy!`
</details>
<ins>
**Batteries excluded method:**
</ins>
<details><summary>Module only</summary>
> ~~~
> import streamlit_controllerDF as sc
> ~~~
> - `see documentation for usage`
</details>
## Documentation
<table>
<tr>
<td>
**class streamlit_controllerDF.Widgets(dataframe, omit_columns=list())**
> Parameters:
>> - dataframe: A pandas data frame
>>> - *Two-dimensional, size-mutable, potentially heterogeneous tabular data.*
>> - omit_columns: A list of column names to be excluded
>>> - *The column names must be exact*
#### Example
```
import streamlit_controllerDF as sc
import pandas as pd
mydf = pd.read_csv('mycsv.csv')
ctrldf = sc.Widgets(mydf,omit_columns=['Engine_Size', 'Year'])
```
**method streamlit_controllerDF.Widgets.metrics()**
> Parameters:
>> - *None*
#### Example
```
import streamlit_controllerDF as sc
import pandas as pd
mydf = pd.read_csv('mycsv.csv')
ctrldf = sc.Widgets(mydf,omit_columns=['Engine_Size', 'Year'])
ctrldf.metrics()
```
</table>
</tr>
</td>
## Limitations
- *This library is currently limited to support only files under 20MB*
- *Due to browser limitations only 12000 rows of data can be viewed at a time*
## To Do
*This library is the base of a much larger project.*
- [ ] Create a chart method which will populate various charts automatically
- [ ] Create a model method which will populate various ML models automatically
- [ ] Add support for automated api data import
- [ ] Add support for relational and non relational data bases
- [ ] Add support for automated queries
- [ ] Add support for big data
- [ ] Create large file size detection and implement chunking automatically
- [ ] Migrate from Pandas to Dask
- [ ] After Dask migration remove file size limitation
Thank you for viewing my project
sincerely
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"description": "<p align=\"center\">\n <img src=\"https://i.imgur.com/4TfRxmI.png\" alt=\"ctrldf\"></img>\n <br/>\n <a href=\"https://www.python.org/\"><img src=\"https://img.shields.io/badge/python-3670A0?style=plastic&logo=python&logoColor=ffdd54\"></img></a>\n <a href=\"https://streamlit.io/\"><img src=\"https://img.shields.io/badge/-Streamlit-61DAFB?style=plastic&logo=streamlit\"></img></a>\n <a href=\"https://matplotlib.org/\"><img src=\"https://img.shields.io/badge/Matplotlib-%23ffffff.svg?style=plastic&logo=matplotlib&logoColor=black\"></img></a>\n <a href=\"https://numpy.org/doc/stable/index.html\"><img src=\"https://img.shields.io/badge/numpy-%23013243.svg?style=plastic&logo=numpy&logoColor=white\"></img></a>\n <a href=\"https://pandas.pydata.org/docs/index.html\"><img src=\"https://img.shields.io/badge/pandas-%23150458.svg?style=plastic&logo=pandas&logoColor=white\"></img></a>\n <a href=\"http://opensource.org/licenses/MIT\"><img src=\"https://img.shields.io/badge/License-MIT-yellow.svg?style=plastic\"></img></a>\n </a>\n\n \n <br/>\n <a href=\"#Documentation\">Documentation</a> \u00b7\n <a href=\"https://github.com/joshjetson/SCDF/issues\">Report a Bug</a> \u00b7\n <a href=\"#Demo\">Demo</a> .\n <a href=\"https://github.com/joshjetson/SCDF/issues\">Request Feature</a> \u00b7\n <a href=\"https://github.com/joshjetson/SCDF/pulls\">Send a Pull Request</a>\n\n</p>\n\n## Controller DF\n\n[]()\n\n<i>A python library which creates a simple and easy to use data frame controller.\nUsing this library, along with streamlit and minimal (*included*) code, anyone can spin up a web app which allows you to control, manipulate and display a data set quickly and easily.\n</i>\n\n## Demo\n\n<table>\n<tr>\n<td>\n<center>\n\n<img src=\"/pics/exgif.gif\"></img>\n\n- Quick column metrics\n\n <img src=\"/pics/ex1.gif\"></img>\n\n- Rapid column filter\n\n <img src=\"/pics/ex3.png\"></img>\n\n- Instant type based column widgets\n\n <img src=\"/pics/ex2.png\"></img>\n</center>\n\n</table>\n</tr>\n</td>\n\n## Installation\n\n```\n$ pip install streamlit-controllerDF\n```\n\n## Getting started\n\n<i>After you pip install the module</i>\n\n<ins>\n\n**Batteries included method:**\n\n</ins>\n\n<details><summary>Quick start</summary>\n\n>\n> - `Copy the included test_code.py`\n> - `Rename the file to your projects name`\n> ~~~\n> $ streamlit run your_project.py \n> ~~~\n> - `Drag and drop csv file`\n> - `Enjoy!`\n\n</details>\n\n<ins>\n\n**Batteries excluded method:**\n\n</ins>\n\n<details><summary>Module only</summary>\n\n> ~~~\n> import streamlit_controllerDF as sc\n> ~~~\n> - `see documentation for usage`\n\n\n</details>\n\n## Documentation\n\n<table>\n<tr>\n<td>\n\n**class streamlit_controllerDF.Widgets(dataframe, omit_columns=list())**\n\n\n> Parameters:\n>> - dataframe: A pandas data frame\n>>> - *Two-dimensional, size-mutable, potentially heterogeneous tabular data.*\n>> - omit_columns: A list of column names to be excluded\n>>> - *The column names must be exact*\n\n#### Example\n```\nimport streamlit_controllerDF as sc\nimport pandas as pd\n\nmydf = pd.read_csv('mycsv.csv')\n\nctrldf = sc.Widgets(mydf,omit_columns=['Engine_Size', 'Year'])\n```\n\n**method streamlit_controllerDF.Widgets.metrics()**\n\n> Parameters:\n>> - *None*\n\n#### Example\n```\nimport streamlit_controllerDF as sc\nimport pandas as pd\n\nmydf = pd.read_csv('mycsv.csv')\n\nctrldf = sc.Widgets(mydf,omit_columns=['Engine_Size', 'Year'])\n\nctrldf.metrics()\n```\n\n</table>\n</tr>\n</td>\n\n## Limitations\n- *This library is currently limited to support only files under 20MB*\n- *Due to browser limitations only 12000 rows of data can be viewed at a time*\n\n## To Do\n*This library is the base of a much larger project.*\n- [ ] Create a chart method which will populate various charts automatically\n- [ ] Create a model method which will populate various ML models automatically\n- [ ] Add support for automated api data import\n- [ ] Add support for relational and non relational data bases\n- [ ] Add support for automated queries\n- [ ] Add support for big data\n- [ ] Create large file size detection and implement chunking automatically\n- [ ] Migrate from Pandas to Dask\n- [ ] After Dask migration remove file size limitation\n\nThank you for viewing my project\nsincerely\n",
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