radarplt 2.0.1

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Radar plot

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

• Data formatting
• Basic usage
• Chaning ranges
• Chaning labels
• Plotting target ranges

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, you can plot the data as follows

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

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:

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

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.

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,
)
legend = ax.legend(loc=(0.9, 0.95))
plt.tight_layout()
plt.show()

Resulting in the following image

Plotting target ranges

If you want to see if your items' values fall within a certain range, you can add those ranges as well

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
)
legend = ax.legend(loc=(0.9, 0.95))
plt.tight_layout()
plt.show()

Resulting in the following image