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573a558 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 | import pandas as pd
import plotly.graph_objects as go
def generate_three_features_parcats_plot(dataFrame: pd.DataFrame, true_column: str, true_column_label: str,
n_landscapes_column: str, n_landscapes_label: str, family_column: str,
family_label: str, title: str, color_dict: dict[int, str],
height: float = 1200, width: float = 2400) -> go.Figure:
'''
Returns a parallel categories plots of a plants' subset (e.g. bordering/transition plants)
regarding the number of landscapes it is present and the plant families which consist it.
Parameters:
------------------------------------------------------------------------------------------------------------
dataFrame: Name of a pandas DataFrame(two-dimensional, size-mutable, potentially heterogeneous tabular data)
true_column: Name of the dataFrame's column, of which the True values will be explored
true_column_label: Label for the true_column dimension
n_landscapes_column: Name of the dataFrame's column referring to the number of landscapes, where the
plants are present
n_landscapes_label: Label for the number of landscapes dimension
family_column: Name of the dataFrame's column referring to the plant families
family_label: Label for the plant families dimension
title: Title of the parallel categories plot
color_dict: Custom dictionary for the feature, containing the colors for each landscape
height: Height of the plot; default is 1200
width: Width of the plot; default is 2400
------------------------------------------------------------------------------------------------------------
'''
# Filter the data
df2 = dataFrame[dataFrame[true_column] == True]
# Create dimensions
n_present_landscapes_dim = go.parcats.Dimension(
values = df2[n_landscapes_column],
categoryorder = "category ascending", label = n_landscapes_label)
bordering_dim = go.parcats.Dimension(
values = df2[true_column], label = true_column_label)
family_dim = go.parcats.Dimension(
values = df2[family_column], label = family_label)
# Create Parcats trace with assigned colors
parcats_trace = go.Parcats(
dimensions = [bordering_dim, n_present_landscapes_dim, family_dim],
line = {"color" : df2[n_landscapes_column].map(color_dict)},
hoveron = "category", hoverinfo = "count+probability",
labelfont = {"size" : 20, "family" : "Times"},
tickfont = {"size" : 18, "family" : "Times"},
arrangement = "freeform")
# Create layout
layout = go.Layout(
height = height,
width = width,
title = dict(text = title, font = dict(family = "Times New Roman", size = 28)),
margin = dict(l = 100, r = 150, b = 100, t = 100))
# Create figure
fig = go.Figure(data = [parcats_trace], layout = layout)
return fig |