import numpy as np
import pandas as pd
import os
import folium
from folium import plugins
import seaborn as sns
import matplotlib.pyplot as plt
import plotly.express as px
for dirname, _, filenames in os.walk('/kaggle/input'):
    for filename in filenames:
        print(os.path.join(dirname, filename))
data0=pd.read_csv('../input/fast-food-restaurants-across-us/Fast_Food_Restaurants_US.csv')
data0
print(data0.columns.tolist())
"""
### Fast Food Restaurant Ranknig
"""
data2a=data0[['name']]
data2a['number']=1
data2a=data2a.groupby('name',as_index=False).sum()
data2a=data2a.sort_values('number',ascending=False)
data2a
fig = px.bar(data2a[0:30], x='name', y='number',title="Fast Food Restaurant Ranknig")
fig.show()
"""
### Subway Ranknig by City
"""
data2b=data0[data0['name']=='Subway'][['city']]
data2b['number']=1
data2b=data2b.groupby('city',as_index=False).sum()
data2b=data2b.sort_values('number',ascending=False)
data2b
fig = px.bar(data2b[0:30], x='city', y='number',title="Subway Ranknig by City")
fig.show()
"""
### Location of Subway in Chicago 
"""
data3=data0[data0['name']=='Subway'][data0['city']=='Chicago'][['latitude','longitude']]
data3=data3.fillna('N')
data3
eq_map = folium.Map(location=[41.9,-87.7],tiles='Stamen Terrain',zoom_start=10.0,min_zoom=2.0)
eq_map.add_child(plugins.HeatMap(data3))
eq_map