barplots 1.2.1
Python package to easily make barplots from multi-indexed dataframes.
License: MIT

# Barplots

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Python package to easily make barplots from multi-indexed dataframes.

## How do I install this package?

As usual, just download it using pip:

```shell
pip install barplots
```

## Documentation

Most methods, in particular those exposed to user usage, are provided with docstrings. Consider reading these docstrings to learn about the most recent updates to the library.

## Examples of the DataFrame structure

The dataframe to be provided to the barplots library may look like the following:

| miss_rate  | fall_out | mcc       | evaluation_type | unbalance | graph_name                 | normalization_name |
|------------|----------|-----------|-----------------|-----------|----------------------------|--------------------|
| 0.0332031  | 0.705078 | 0.353357  | train           | 10        | AlligatorSinensis           | Traditional        |
| 0.240234   | 0.478516 | 0.289591  | train           | 1         | CanisLupus                  | Right Laplacian     |
| 0.0253906  | 0.931641 | 0.101643  | train           | 100       | AlligatorSinensis           | Right Laplacian     |
| 0.121094   | 0.699219 | 0.220219  | train           | 10        | HomoSapiens                 | Traditional        |
| 0.0136719  | 0.292969 | 0.722095  | test            | 1         | CanisLupus                  | Right Laplacian     |
| 0.0605469  | 0.90625  | 0.0622185 | test            | 10        | AmanitaMuscariaKoideBx008    | Traditional        |
| 0.0078125  | 0.4375   | 0.614287  | train           | 100       | AmanitaMuscariaKoideBx008    | Traditional        |
| 0.171875   | 0.869141 | -0.0572194| train           | 100       | AlligatorSinensis           | Traditional        |
| 0.0859375  | 0.810547 | 0.150206  | train           | 10        | MusMusculus                 | Right Laplacian     |
| 0.0273438  | 0.646484 | 0.415357  | test            | 10        | MusMusculus                 | Right Laplacian     |

Specifically, in this example, we may create bar plots for the features **Miss rate**, **fallout**, and **Matthew Correlation Coefficient** by grouping on the `evaluation_type`, `unbalance`, `graph_name`, and `normalization_name` columns.

An example CSV file can be seen [here](https://github.com/LucaCappelletti94/barplots/blob/master/tests/test_case.csv).

## Usage examples

Here follows a set of examples of common usages. Basically, every graph shows either the same data or a mean based on the provided group by indices. Choose whatever representation is best for visualizing your data, as one is not necessarily better than another for every dataset.

> **Note**: The data used in the following examples are **randomly generated** for testing purposes. **DO NOT** consider these values as valid results for experiments using the same labels (cell lines, etc.), which are only used to show possible usages.

For every example, the considered dataframe `df` is loaded as follows:

```python
import pandas as pd

df = pd.read_csv("tests/test_case.csv")
```

Also, for every example, the `custom_defaults` used to sanitize the labels specific to the dataset is:

```python
custom_defaults = {
    "P": "promoters",
    "E": "enhancers",
    "A": "active ",
    "I": "inactive ",
    "+": " and ",
    "": "anything",
    "Validation": "val"
}
```

### Horizontal Example A

In the following example, we will plot the bars horizontally, rotating the group labels by 90 degrees, and displaying the bar labels as a shared legend.

```python
from barplots import barplots
import pandas as pd

df = pd.read_csv("tests/test_case.csv")
custom_defaults = {
    "P": "promoters",
    "E": "enhancers",
    "A": "active ",
    "I": "inactive ",
    "+": " and ",
    "": "anything",
    "Validation": "val"
}

barplots(
    df,
    groupby=["task", "model"],
    orientation="horizontal",
    show_legend=True,
    minor_rotation=90,
    custom_defaults=custom_defaults
)
```

Result can be seen [here](https://github.com/LucaCappelletti94/barplots/blob/master/examples/1/horizontal_legend_minor_rotation_val_auroc.png?raw=true).

### Horizontal Example B

In this example, we will plot the top index as multiple subplots with horizontal bars, rotating the group labels by 90 degrees, and displaying the bar labels as a shared legend.

```python
from barplots import barplots
import pandas as pd

df = pd.read_csv("tests/test_case.csv")
custom_defaults = {
    "P": "promoters",
    "E": "enhancers",
    "A": "active ",
    "I": "inactive ",
    "+": " and ",
    "": "anything",
    "Validation": "val"
}

barplots(
    df,
    groupby=["cell_line", "task", "model"],
    orientation="horizontal",
    show_legend=True,
    subplots=True,
    minor_rotation=90,
    custom_defaults=custom_defaults
)
```

![Horizontal Example B](https://github.com/LucaCappelletti94/barplots/blob/master/examples/1/horizontal_legend_subplots_minor_rotation_val_auroc.png?raw=true)

### Horizontal Example C

In this example, we will plot horizontal bars, rotating the top group labels by 90 degrees, and displaying the bar labels as minor ticks.

```python
from barplots import barplots
import pandas as pd

df = pd.read_csv("tests/test_case.csv")
custom_defaults = {
    "P": "promoters",
    "E": "enhancers",
    "A": "active ",
    "I": "inactive ",
    "+": " and ",
    "": "anything",
    "Validation": "val"
}

barplots(
    df,
    groupby=["task", "model"],
    orientation="horizontal",
    show_legend=False,
    major_rotation=90,
    custom_defaults=custom_defaults
)
```

Result can be seen [here](https://github.com/LucaCappelletti94/barplots/blob/master/examples/1/horizontal_major_rotation_val_auroc.png?raw=true).

### Horizontal Example D

In this example, we will plot the top index as multiple subplots with horizontal bars, rotating the group labels by 90 degrees, and displaying the bar labels as minor ticks.

```python
from barplots import barplots
import pandas as pd

df = pd.read_csv("tests/test_case.csv")
custom_defaults = {
    "P": "promoters",
    "E": "enhancers",
    "A": "active ",
    "I": "inactive ",
    "+": " and ",
    "": "anything",
    "Validation": "val"
}

barplots(
    df,
    groupby=["cell_line", "task", "model"],
    orientation="horizontal",
    show_legend=False,
    major_rotation=90,
    subplots=True,
    custom_defaults=custom_defaults
)
```

![Horizontal Example D](https://github.com/LucaCappelletti94/barplots/blob/master/examples/1/horizontal_subplots_major_rotation_val_auroc.png?raw=true)

### Vertical Example A

In this example, we will plot the bars vertically and display the bar labels as a shared legend.

```python
from barplots import barplots
import pandas as pd

df = pd.read_csv("tests/test_case.csv")
custom_defaults = {
    "P": "promoters",
    "E": "enhancers",
    "A": "active ",
    "I": "inactive ",
    "+": " and ",
    "": "anything",
    "Validation": "val"
}

barplots(
    df,
    groupby=["task", "model"],
    orientation="vertical",
    show_legend=True,
    custom_defaults=custom_defaults
)
```

Result can be seen [here](https://github.com/LucaCappelletti94/barplots/blob/master/examples/1/vertical_legend_val_auroc.png).

### Vertical Example B

In this example, we will plot the top index as multiple subplots with vertical bars, displaying the bar labels as a shared legend.

```python
from barplots import barplots
import pandas as pd

df = pd.read_csv("tests/test_case.csv")
custom_defaults = {
    "P": "promoters",
    "E": "enhancers",
    "A": "active ",
    "I": "inactive ",
    "+": " and ",
    "": "anything",
    "Validation": "val"
}

barplots(
    df,
    groupby=["cell_line", "task", "model"],
    orientation="vertical",
    show_legend=True,
    subplots=True,
    custom_defaults=custom_defaults
)
```

![Vertical Example B](https://github.com/LucaCappelletti94/barplots/blob/master/examples/1/vertical_legend_subplots_val_auroc.png)

### Vertical Example C

In this example, we will plot vertical bars, rotating the minor group labels by 90 degrees, and displaying the bar labels as minor ticks.

```python
from barplots import barplots
import pandas as pd

df = pd.read_csv("tests/test_case.csv")
custom_defaults = {
    "P": "promoters",
    "E": "enhancers",
    "A": "active ",
    "I": "inactive ",
    "+": " and ",
    "": "anything",
    "Validation": "val"
}

barplots(
    df,
    groupby=["task", "model"],
    orientation="vertical",
    show_legend=False,
    minor_rotation=90,
    custom_defaults=custom_defaults
)
```

Result can be seen [here](https://github.com/LucaCappelletti94/barplots/blob/master/examples/1/vertical_minor_rotation_val_auroc.png).

### Vertical Example D

In this example, we will plot the top index as multiple subplots with vertical bars, rotating the minor group labels by 90 degrees, and displaying the bar labels as minor ticks.

```python
from barplots import barplots
import pandas as pd

df = pd.read_csv("tests/test_case.csv")
custom_defaults = {
    "P": "promoters",
    "E": "enhancers",
    "A": "active ",
    "I": "inactive ",
    "+": " and ",
    "": "anything",
    "Validation": "val"
}

barplots(
    df,
    groupby=["cell_line", "task", "model"],
    orientation="vertical",
    show_legend=False,
    minor_rotation=90,
    subplots=True,
    custom_defaults=custom_defaults
)
```

![Vertical Example D](https://github.com/LucaCappelletti94/barplots/blob/master/examples/1/vertical_subplots_minor_rotation_val_auroc.png)