I am aware catboost gives nice interactive chart for calculated feature statistics using the api
model.cal_feature_statistics, I was wondering If we can include this chart in
Streamlit has different chart api (https://docs.streamlit.io/en/stable/api.html#display-charts) such as
streamlit.altair_chart etc, but I was unable to wrap the catboost output plot in streamlit.
Does anybody have idea how to wrap the chart in streamlit.
%%writefile app.py # Ref: https://docs.streamlit.io/en/stable/api.html#display-charts # imports import numpy as np import pandas as pd import seaborn as sns import sklearn from sklearn import datasets import catboost as cb import streamlit as st import streamlit.components.v1 as stc # load the data data = datasets.load_boston() X = data.data y = data.target features = data.feature_names # modelling model = cb.CatBoostRegressor(verbose=0) model.fit(X,y) # chart feature_name = 'sqft_living' dict_stats = model.calc_feature_statistics(X, y, 0) # 0 means first feature # streamlit st.header("catboost feature statistics") st.plotly_chart(dict_stats)
Run the app
streamlit run app.py