https://github.com/lucacappelletti94/barplots
Python package to easily make barplots from multi-indexed dataframes.
https://github.com/lucacappelletti94/barplots
Last synced: about 1 month ago
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Python package to easily make barplots from multi-indexed dataframes.
- Host: GitHub
- URL: https://github.com/lucacappelletti94/barplots
- Owner: LucaCappelletti94
- License: mit
- Created: 2019-11-07T18:07:43.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2024-10-28T15:34:33.000Z (7 months ago)
- Last Synced: 2025-04-16T03:21:04.430Z (about 2 months ago)
- Language: Python
- Homepage:
- Size: 95.2 MB
- Stars: 7
- Watchers: 1
- Forks: 2
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
- License: LICENSE
Awesome Lists containing this project
README
# Barplots
[](https://pypi.org/project/barplots/)
[](https://pepy.tech/project/barplots)
[](https://github.com/LucaCappelletti94/barplots/blob/master/LICENSE)
[](https://github.com/LucaCappelletti94/barplots/actions)
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 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
)
```
### 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 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
)
```
