application_vnd.jupyter.stderr_output_1.png
import pandas as pd

df_train = pd.read_csv('/kaggle/input/house-prices-advanced-regression-techniques/train.csv')
df_train.shape

idsUnique = len(set(df_train.Id))
idsTotal = df_train.shape[0]
idsDupli = idsTotal - idsUnique
df_train.drop('Id', axis=1, inplace=True)

df_train = df_train[df_train.GrLivArea < 4000]

def find_cat(dataframe):
    cat_vars = []
    for name in dataframe.columns:
        if dataframe[name].dtype.name == 'object':
            cat_vars.append(name)
    return cat_vars
non_cat_vars = list(df_train.select_dtypes(exclude='object').columns)

cat_vars = find_cat(df_train)
print(cat_vars)