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import marimo
__generated_with = "0.11.4"
app = marimo.App(width="medium")
@app.cell
def _(mo):
mo.md("""# Exploration on Smartphone Consumer Trends in India""")
return
@app.cell(hide_code=True)
def _():
import marimo as mo
import polars as pl
dataset_raw = pl.read_csv("dataset/diabetes_binary_health_indicators_BRFSS2015.csv")
dataset_raw.head()
return dataset_raw, mo, pl
@app.cell
def _(dataset_raw):
dataset_priors = dataset_raw.select(["Diabetes_binary", "HighBP", "HighChol", "Stroke", "HeartDiseaseorAttack"])
dataset_priors.head()
return (dataset_priors,)
@app.cell
def _():
from sklearn.naive_bayes import BernoulliNB
from sklearn.metrics import accuracy_score, confusion_matrix, classification_report
from sklearn.model_selection import train_test_split
return (
BernoulliNB,
accuracy_score,
classification_report,
confusion_matrix,
train_test_split,
)
if __name__ == "__main__":
app.run()
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