import pandas as pd
us_state_abbrev = ['AL', 'AK', 'AZ', 'AR', 'CA', 'CO', 'CT', 'DE', 'DC',
    'FL', 'GA', 'HI', 'ID', 'IL', 'IN', 'IA', 'KS', 'KY', 'LA', 'ME', 'MD',
    'MA', 'MI', 'MN', 'MS', 'MO', 'MT', 'NE', 'NV', 'NH', 'NJ', 'NM', 'NY',
    'NC', 'ND', 'OH', 'OK', 'OR', 'PA', 'RI', 'SC', 'SD', 'TN', 'TX', 'UT',
    'VT', 'VA', 'WA', 'WV', 'WI', 'WY']
df = pd.DataFrame()
for i in us_state_abbrev:
    df_i = pd.read_html('https://www.walkscore.com/' + i)[0]
    df_i['State'] = i
    df = pd.concat([df, df_i])
print(df.head())
df.to_csv('walk.csv')

d79bed14e63e46ef8cf6efdbe97e757a299a8983
<mask token>

<mask token>
for i in us_state_abbrev:
    df_i = pd.read_html('https://www.walkscore.com/' + i)[0]
    df_i['State'] = i
    df = pd.concat([df, df_i])
print(df.head())
df.to_csv('walk.csv')

<mask token>
us_state_abbrev = ['AL', 'AK', 'AZ', 'AR', 'CA', 'CO', 'CT', 'DE', 'DC',
    'FL', 'GA', 'HI', 'ID', 'IL', 'IN', 'IA', 'KS', 'KY', 'LA', 'ME', 'MD',
    'MA', 'MI', 'MN', 'MS', 'MO', 'MT', 'NE', 'NV', 'NH', 'NJ', 'NM', 'NY',
    'NC', 'ND', 'OH', 'OK', 'OR', 'PA', 'RI', 'SC', 'SD', 'TN', 'TX', 'UT',
    'VT', 'VA', 'WA', 'WV', 'WI', 'WY']
df = pd.DataFrame()
for i in us_state_abbrev:
    df_i = pd.read_html('https://www.walkscore.com/' + i)[0]
    df_i['State'] = i
    df = pd.concat([df, df_i])
print(df.head())
df.to_csv('walk.csv')

import pandas as pd
us_state_abbrev = ['AL', 'AK', 'AZ', 'AR', 'CA', 'CO', 'CT', 'DE', 'DC',
    'FL', 'GA', 'HI', 'ID', 'IL', 'IN', 'IA', 'KS', 'KY', 'LA', 'ME', 'MD',
    'MA', 'MI', 'MN', 'MS', 'MO', 'MT', 'NE', 'NV', 'NH', 'NJ', 'NM', 'NY',
    'NC', 'ND', 'OH', 'OK', 'OR', 'PA', 'RI', 'SC', 'SD', 'TN', 'TX', 'UT',
    'VT', 'VA', 'WA', 'WV', 'WI', 'WY']
df = pd.DataFrame()
for i in us_state_abbrev:
    df_i = pd.read_html('https://www.walkscore.com/' + i)[0]
    df_i['State'] = i
    df = pd.concat([df, df_i])
print(df.head())
df.to_csv('walk.csv')
