Examples¶
Usage with Pandas¶
The Pandas library offers many tools for importing and processing data. Here is an example of using Paxplot to plot data in a Pandas DataFrame. We will use the tradeoff dataset included in Paxplot, but the workflow is fairly generic.
import pandas as pd
import matplotlib.pyplot as plt
import paxplot
# Import data
path_to_data = paxplot.datasets.tradeoff()
df = pd.read_csv(path_to_data)
cols = df.columns
# Create figure
paxfig = paxplot.pax_parallel(n_axes=len(cols))
paxfig.plot(df.to_numpy())
# Add labels
paxfig.set_labels(cols)
# Add colorbar
color_col = 0
paxfig.add_colorbar(
ax_idx=color_col,
cmap='viridis',
colorbar_kwargs={'label': cols[color_col]}
)
plt.show()
Highlight Solutions¶
Another common workflow with parallel plots is to add a colorbar to a subset of data. This is particularly common when showing nondominated subsets of a dataset in multi-objective optimization problems.
import pandas as pd
import matplotlib.pyplot as plt
import paxplot
# Import data
path_to_data = paxplot.datasets.tradeoff()
df = pd.read_csv(path_to_data)
cols = df.columns
# Split data
df_highlight = df[df['A'] < 20]
df_grey = df[df['A'] >= 20]
# Create figure
paxfig = paxplot.pax_parallel(n_axes=len(cols))
paxfig.plot(df_highlight.to_numpy())
# Add colorbar for highlighted
color_col = 0
paxfig.add_colorbar(
ax_idx=color_col,
cmap='viridis',
colorbar_kwargs={'label': cols[color_col]}
)
# Add grey data
paxfig.plot(
df_grey.to_numpy(),
line_kwargs={'alpha': 0.5, 'color': 'grey', 'zorder': 0}
)
# Add labels
paxfig.set_labels(cols)
plt.show()
