Metadata-Version: 2.1
Name: radarplt
Version: 2.2.2
Summary: 
Home-page: https://github.com/jdkern11/radar_plot.git
Author: jdkern11
Author-email: josephdanielkern@gmail.com
Requires-Python: >=3.9,<3.13
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Requires-Dist: matplotlib (>=3.6.3,<4.0.0)
Requires-Dist: pandas (>=1.4.4)
Project-URL: Repository, https://github.com/jdkern11/radar_plot.git
Description-Content-Type: text/markdown

# Radar plot
This package creates radar plots. It can generate typical radar plots and 
plot ranges of values.

- [Data formatting](#data-formatting)
- [Basic usage](#basic-usage)
- [Chaning ranges](#changing-ranges)
- [Chaning labels](#changing-labels)
- [Plotting target ranges](#plotting-target-ranges)

![example 0](https://raw.githubusercontent.com/jdkern11/radar_plot/main/images/example_0.png)

## Data formatting
Data you want to plot must have a tidy format. For instance, if I wanted to plot
three properties (let's say prop1, prop2, and prop3 with values 
12, 3.5, and 42 respectively) then you should load a csv file into a pandas 
dataframe that has the following format:

| property | value | item  |
| -------- | ----- | ----- |
| prop1    | 12.0  | item1 |
| prop2    | 3.5   | item1 |
| prop3    | 42    | item1 |

If you wanted to plot several items (e.g., item1, item2, and item3)
with different values for the properties, then format the data like this:

| property | value | item  |
| -------- | ----- | ----- |
| prop1    | 12.0  | item1 |
| prop2    | 3.5   | item1 |
| prop3    | 42    | item1 |
| prop1    | 14.0  | item2 |
| prop2    | 4.0   | item2 |
| prop3    | 36    | item2 |
| prop1    | 15    | item3 |
| prop2    | 2     | item3 |
| prop3    | 40    | item3 |

## Basic Usage
Following [that formatting scheme](#data-formatting), you can plot the data as follows
```Python
import pandas as pd
import matplotlib.pyplot as plt
import radarplt

# see tables above
df = pd.read_csv('example_data.csv')
fig, ax = radarplt.plot(
    df,
    label_column="property",
    value_column="value",
    hue_column="item",
)
legend = ax.legend(loc=(0.9, 0.95))
plt.tight_layout()
plt.show()
```
Resulting in the following image
![example 1 plotted](https://raw.githubusercontent.com/jdkern11/radar_plot/main/images/example_1.png)

Additional lines are plotted at the .25, .50, and .75 marks on the image. The value at the
.25 and .75 line for each property is labeled and values increase/decrease linearly
between these points. For instance, the 0.5 mark for property 2 would be 4, the 1 
mark would be 6 and the 0 mark would be 2.

### Changing Ranges 
Let's say you don't like that the prop2 ranges from 1 to 6. To change
these value ranges create a dictionary of the ranges you want for each property and 
pass it to the function via the `value_ranges` parameter.
For instance: 
```Python
import pandas as pd
import matplotlib.pyplot as plt
import radarplt

value_ranges = {
  "prop1": [0, 20],
  "prop2": [0, 5],
  "prop3": [0, 50],
}

# see tables above
df = pd.read_csv('example_data.csv')
fig, ax = radarplt.plot(
    df,
    label_column="property",
    value_column="value",
    hue_column="item",
    value_ranges=value_ranges,
)
legend = ax.legend(loc=(0.9, 0.95))
plt.tight_layout()
plt.show()
```
Resulting in the following image
![example 2 plotted](https://raw.githubusercontent.com/jdkern11/radar_plot/main/images/example_2.png)

### Changing labels
If you don't want the labels for the properties to be the property names, 
you can change those as well with the `plot_labels` parameter.

```Python
import pandas as pd
import matplotlib.pyplot as plt
import radarplt

value_ranges = {
  "prop1": [0, 20],
  "prop2": [0, 5],
  "prop3": [0, 50],
}

plot_labels = {
  "prop1": "$\sigma^{2}$",
  "prop2": "Property 2 (seconds)",
  "prop3": "p3"
}

# see tables above
df = pd.read_csv('example_data.csv')
fig, ax = radarplt.plot(
    df,
    label_column="property",
    value_column="value",
    hue_column="item",
    value_ranges=value_ranges,
    plot_labels=plot_labels,
    # can change fontsize of the numbers in the plot
    tick_fontsize=12
)
legend = ax.legend(loc=(0.9, 0.95))
plt.tight_layout()
plt.show()
```
Resulting in the following image
![example 3 plotted](https://raw.githubusercontent.com/jdkern11/radar_plot/main/images/example_3.png)

### Plotting target ranges
If you want to see if your items' values fall within a certain range, you 
can add those ranges as well
```Python
import pandas as pd
import matplotlib.pyplot as plt
import radarplt

target_ranges = {
  "prop1": [10, 20],
  "prop2": [0, 2],
  "prop3": [25, 35]
}

value_ranges = {
  "prop1": [0, 20],
  "prop2": [0, 5],
  "prop3": [0, 50],
}

plot_labels = {
  "prop1": "$\sigma^{2}$",
  "prop2": "Property 2 (seconds)",
  "prop3": "p3"
}

# see tables above
df = pd.read_csv('example_data.csv')
fig, ax = radarplt.plot(
    df,
    label_column="property",
    value_column="value",
    hue_column="item",
    value_ranges=value_ranges,
    plot_labels=plot_labels,
    target_ranges=target_ranges
    # note, you can also change the radar plot target linewidth
    target_linewidth=2
)
legend = ax.legend(loc=(0.9, 0.95))
plt.tight_layout()
plt.show()
```

Resulting in the following image
![example 4 plotted](https://raw.githubusercontent.com/jdkern11/radar_plot/main/images/example_4.png)

