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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 | import pandas as pd
import plotly.graph_objects as go
def generate_scatterplot(dataFrame: pd.DataFrame, x_value: str, y_value: str, id_column: str, title: str,
height: float = 1200, width: float = 1600) -> go.Figure:
'''
Returns a scatterplot, where points refer to each species, showing the height features of each species.
Parameters:
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dataFrame: Name of a pandas DataFrame(two-dimensional, size-mutable, potentially heterogeneous tabular data)
x_value: Name of the dataFrame's column to be used as the X values
y_value: Name of the dataFrame's column to be used as the Y values
id_column: Name of the dataFrame's column to be used as the id column (plant species) of the plot
title: Title of the scatterplot
height: Height of the plot; default is 1200
width: Width of the plot; default is 1600
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'''
# Extract relevant columns for x and y axes
x_values = dataFrame[x_value]
y_values = dataFrame[y_value]
plant_species = dataFrame[id_column]
# Create a scatterplot
fig = go.Figure()
fig.add_trace(
go.Scatter(
x = x_values,
y = y_values,
mode = "markers",
text = plant_species,
marker = dict(color = "#AA9486", size = 8, opacity = 0.6), # Customize marker color and size
hoverinfo = "text+x+y")) # Display plant species on hover
# Create scatterplot's layout
fig.update_layout(
height = height,
width = width,
title = dict(text = title, font = dict(size = 28, family = "Times New Roman")),
yaxis = dict(title = y_value, titlefont = dict(size = 20, family = "Times New Roman"), tickfont = dict(size = 18, family = "Times New Roman")),
xaxis = dict(title = x_value, titlefont = dict(size = 20, family = "Times New Roman"), tickfont = dict(size = 18, family = "Times New Roman")))
return fig
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