decisiontree

import json
import pandas as pd
with open('A.json', 'r',encoding='UTF-8') as f:
  data=json.load(f)

import seaborn as sns
import matplotlib.pyplot as plt
import matplotlib.font_manager as fm

plt.rc('font', family='NanumGothicCoding'_
sns.set(font="Malgun Gothic', rc={"aes.unicode_minus":False}, style='white')
df=pd.read_json("A.json")

sns.countplot(x="Address1", data=df)



from sklearn.tree import DecisionTreeClassifier

dt=DecisionTreeClassifier(random_state=1001, max_depth=5)

dt_model=dt.fit(X_train, y_train)

y_pred=dt.predict(X_valid)

from sklearn.metrics import mean_squared_error
dt_mae=mean_squared_error(y_valid, y_pred)
dt_mae