Victor Phan
29 lines
1009 B
Python
29 lines
1009 B
Python
import pandas as pd
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import numpy as np
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df = pd.read_excel('Data_VN_filter_v5.xlsx')
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target_vars = ['Donation']
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numeric_vars = ['Income', 'MEAN RES', 'MEAN CES', 'MEAN DES'] + ['Park', 'Residential', 'Garden', 'Rooftop', 'Recreation', 'Agriculture', 'Nature']
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categorical_vars = ['Gender', 'Career', 'Literacy', 'Frequency', 'Distance', 'Time', 'Transportation']
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for col in categorical_vars:
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df[col] = df[col].astype(str)
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all_vars = target_vars + numeric_vars + categorical_vars
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df_subset = df[all_vars].dropna()
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df_sample = df_subset.sample(n=200, random_state=42)
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X = pd.get_dummies(df_sample[numeric_vars + categorical_vars], drop_first=True, dtype=float)
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y = df_sample['Donation'].astype(float)
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print("Zero variance columns:")
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zero_var = X.columns[X.var() == 0]
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print(zero_var.tolist())
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print("\nCross tab checks (looking for 0 counts):")
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for col in X.columns:
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crosstab = pd.crosstab(X[col], y)
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if (crosstab == 0).any().any():
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print(f"{col} has 0-cells!")
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print(crosstab)
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