Reputation: 359
In a dataframe, columns A and B are categorical data, while columns X and Y is numerical and continuous. How can I use plotly to draw a parallel coordinates+categories plot such that the first two y-axis corresponding to A and B are categorical, and the latter two corresponding to X and Y are numerical?
For example, consider the following data:
df = pd.DataFrame({'A':['a','a','b','b'],
'B':['1','2','1','2'],
'X':[5.3,6.7,3.1,0.8],
'Y':[0.4,0.6,3.6,4.8]})
I tried plotly.express.parallel_categories
. But this treats all numerical values as categories. On the other hand, plotly.express.parallel_coordinates
omits categorical columns.
Upvotes: 1
Views: 325
Reputation: 914
You can first convert categorical data to numerical data and then use the plotly.express.parallel_coordinates
function to plot the graph.
Because plotly.express.parallel_coordinates
is mainly used to process numerical data, while plotly.express.parallel_categories
is used to process categorical data.
Example:
import pandas as pd
import plotly.express as px
df = pd.DataFrame({'A': ['a', 'a', 'b', 'b'],
'B': ['1', '2', '1', '2'],
'X': [5.3, 6.7, 3.1, 0.8],
'Y': [0.4, 0.6, 3.6, 4.8]})
#Convert categorical data to numerical data
df['A_cat'] = df['A'].astype('category').cat.codes
df['B_cat'] = df['B'].astype('category').cat.codes
# Draw parallel coordinate plot
fig = px.parallel_coordinates(df,
dimensions=['A_cat', 'B_cat', 'X', 'Y'],
labels={'A_cat': 'A', 'B_cat': 'B', 'X': 'X', 'Y': 'Y'},
color="X",
color_continuous_scale=px.colors.diverging.Tealrose,
color_continuous_midpoint=2)
# Update the chart layout to show the original category labels
fig.update_layout(
xaxis=dict(
tickvals=[0, 1, 2, 3],
ticktext=['A', 'B', 'X', 'Y']
)
)
fig.show()
Upvotes: 1