text_html_output_1.png
import numpy as np

import numpy as np # linear algebra

import pandas as pd

import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

health_data = pd.read_csv('../input/Big_Cities_Health_Data_Inventory.csv')

health_data = health_data.drop(columns=['BCHC Requested Methodology', 'Source', 'Methods', 'Notes'])

health_data.columns

health_data.isna().sum()

categorical_cols = health_data.select_dtypes(exclude=np.number).columns

categorical_cols = categorical_cols.drop(['Indicator', 'Place'])

encoded_cols = pd.get_dummies(health_data[categorical_cols])

final_data = pd.concat([encoded_cols, health_data['Value']], axis=1)

final_data.info()