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90 changes: 83 additions & 7 deletions docs/assets/css/style.css
Original file line number Diff line number Diff line change
Expand Up @@ -139,15 +139,26 @@ body {
box-shadow: 0px 2px 4px rgba(0, 0, 0, 0.05);
}

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background-color: white;
width: 60%;
border: 1px solid #ccc;
Expand All @@ -162,7 +173,8 @@ pre > code.language-python {
display: block;
overflow-x: auto;
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}
*/
/*
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Expand Down Expand Up @@ -230,7 +242,7 @@ pre > code.language-python {
*/


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font-family: monospace; /* Gives the text a code-like appearance */
Expand All @@ -247,7 +259,7 @@ pre > code.language-python {

.flex-container {
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width: 100%;
Expand Down Expand Up @@ -476,4 +488,68 @@ th {
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60 changes: 40 additions & 20 deletions docs/index.md
Original file line number Diff line number Diff line change
Expand Up @@ -7,42 +7,62 @@ title: CoderData

<!-- # Cancer Omics and Drug Experiment Response Data (`coderdata`) Python Package -->

### Introduction
## Introduction
CoderData is a cancer benchmark data package developed in Python and R.
There are two aspects of this package, the backend build section and the user facing python package.
The build section is a github workflow that generates four cancer datasets in a format that is easy for users and algorithms to ingest.
The python package allows users to easily download the data, load it into python and reformat it as desired.

### Installation and Usage
##### Bash / Command Line
## Installation and Usage
### Installation

To install coderdata, simply run the following command in your terminal:
Assuming `python>=3.9` is installed on the system, simply run the following command in the terminal to install the most recent release of the coderdata API:

```bash
pip install coderdata
$ pip install coderdata
```

##### Bash / Command line
To download datasets, simply run the following command in your terminal. Remove the prefix argument if you'd like to install all datasets.
### Bash / Command line
A full list of available datasets can be retrieved via:
```sh
$ coderdata --list
```

To download datasets, simply run the following command in your terminal substituting `<DATASET>` with the desired dataset (e.g. `beataml`). To download all datasets use `--name all`.

```bash
coderdata download --prefix hcmi
$ coderdata download --name <DATASET>
```

##### Python
To download, load, and call datasets in python, simply run the following commands.

<div class="code-box">
<p>import coderdata as cd </p>
<p>cd.download_data_by_prefix('hcmi')</p>
<p>hcmi_data = cd.DatasetLoader('hcmi')</p>
<p>hcmi_data.transcriptomics</p>
</div>
### Python

To download, load, and call datasets in python, simply run the following commands.

```python
>>> import coderdata as cd
>>> cd.download(name='beataml')
>>> beataml = cd.load('beataml')
>>> beataml.experiments
source improve_sample_id improve_drug_id study time time_unit dose_response_metric dose_response_value
0 synapse 3907 SMI_11123 BeatAML 72 hrs fit_auc 0.0564
1 synapse 3907 SMI_11211 BeatAML 72 hrs fit_auc 0.9621
2 synapse 3907 SMI_12192 BeatAML 72 hrs fit_auc 0.1691
3 synapse 3907 SMI_12254 BeatAML 72 hrs fit_auc 0.4245
4 synapse 3907 SMI_12469 BeatAML 72 hrs fit_auc 0.7397
... ... ... ... ... ... ... ... ...
233775 synapse 3626 SMI_7110 BeatAML 72 hrs dss 0.0000
233776 synapse 3626 SMI_7590 BeatAML 72 hrs dss 0.0000
233777 synapse 3626 SMI_8159 BeatAML 72 hrs dss 0.1946
233778 synapse 3626 SMI_8724 BeatAML 72 hrs dss 0.0000
233779 synapse 3626 SMI_987 BeatAML 72 hrs dss 0.7165

[233780 rows x 8 columns]
```

View our [Usage](pages/usage.md) page for full instructions.
For more indepth instructions view our [Usage](pages/usage.md) page.


### Datasets
## Datasets

<table>
<thead>
Expand Down Expand Up @@ -171,7 +191,7 @@ View our [Usage](pages/usage.md) page for full instructions.
</div> -->


### Data Overview
## Data Overview

<div class="flex-container">
<div class="flex-item">
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