You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 bike_share_1
【Schema】
# Table: station
[
(id:INTEGER, Primary Key, Examples: [2, 3, 4]),
(name:TEXT, Examples: [San Jose Diridon Caltrain Station]),
(lat:REAL, Examples: [37.329732, 37.330698, 37.333988]),
(long:REAL, Examples: [-121.90178200000001, -121.888979, -121.894902]),
(dock_count:INTEGER, Examples: [27, 15, 11]),
(city:TEXT, Examples: [San Jose, Redwood City, Mountain View]),
(installation_date:TEXT, Examples: [8/6/2013, 8/5/2013, 8/7/2013])
]
# Table: status
[
(station_id:INTEGER, Examples: [2, 3, 4]),
(bikes_available:INTEGER, Examples: [2, 3, 4]),
(docks_available:INTEGER, Examples: [25, 24, 23]),
(time:TEXT, Examples: [2013/08/29 12:06:01, 2013/08/29 12:07:01, 2013/08/29 12:08:01])
]
# Table: trip
[
(id:INTEGER, Primary Key, Examples: [4069, 4073, 4074]),
(duration:INTEGER, Examples: [174, 1067, 1131]),
(start_date:TEXT, Examples: [8/29/2013 9:08, 8/29/2013 9:24, 8/29/2013 9:25]),
(start_station_name:TEXT, Examples: [2nd at South Park]),
(start_station_id:INTEGER, Examples: [64, 66, 22]),
(end_date:TEXT, Examples: [8/29/2013 9:11, 8/29/2013 9:42, 8/29/2013 9:43]),
(end_station_name:TEXT, Examples: [2nd at South Park]),
(end_station_id:INTEGER, Examples: [64, 69, 22]),
(bike_id:INTEGER, Examples: [288, 321, 317]),
(subscription_type:TEXT, Examples: [Subscriber, Customer]),
(zip_code:INTEGER, Examples: [94114, 94703, 94115])
]
# Table: weather
[
(date:TEXT, Examples: [8/29/2013, 8/30/2013, 8/31/2013]),
(max_temperature_f:INTEGER, Examples: [74, 78, 71]),
(mean_temperature_f:INTEGER, Examples: [68, 69, 64]),
(min_temperature_f:INTEGER, Examples: [61, 60, 57]),
(max_dew_point_f:INTEGER, Examples: [61, 57, 60]),
(mean_dew_point_f:INTEGER, Examples: [58, 56, 60]),
(min_dew_point_f:INTEGER, Examples: [56, 54, 53]),
(max_humidity:INTEGER, Examples: [93, 90, 87]),
(mean_humidity:INTEGER, Examples: [75, 70, 68]),
(min_humidity:INTEGER, Examples: [57, 50, 49]),
(max_sea_level_pressure_inches:REAL, Examples: [30.07, 30.05, 30.0]),
(mean_sea_level_pressure_inches:REAL, Examples: [30.02, 30.0, 29.96]),
(min_sea_level_pressure_inches:REAL, Examples: [29.97, 29.93, 29.92]),
(max_visibility_miles:INTEGER, Examples: [10, 9, 8]),
(mean_visibility_miles:INTEGER, Examples: [10, 9, 8]),
(min_visibility_miles:INTEGER, Examples: [10, 7, 6]),
(max_wind_Speed_mph:INTEGER, Examples: [23, 29, 26]),
(mean_wind_speed_mph:INTEGER, Examples: [11, 13, 15]),
(max_gust_speed_mph:INTEGER, Examples: [28, 35, 31]),
(precipitation_inches:TEXT, Examples: [0, 0.23, T]),
(cloud_cover:INTEGER, Examples: [4, 2, 6]),
(events:TEXT, Examples: [Fog, Rain, Fog-Rain]),
(wind_dir_degrees:INTEGER, Examples: [286, 291, 284]),
(zip_code:TEXT, Examples: [94107, 94063, 94301])
]

    【Question】
    What is the average coldest temperature for the zip code of 94301 and what stations are within the zip code? Include the latitude and longitude as well. coldest temperature refers to min_temperature_f; average coldest temperature refers = AVG(min_temperature_f); stations refers to name; latitude refers to lat; longitude refers to long;

    【Evidence】
    coldest temperature refers to min_temperature_f; average coldest temperature refers = AVG(min_temperature_f); stations refers to name; latitude refers to lat; longitude refers to long;

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT AVG(T3.min_temperature_f), T1.long, T1.lat FROM station AS T1 INNER JOIN trip AS T2 ON T2.start_station_name = T1.name INNER JOIN weather AS T3 ON T3.zip_code = T2.zip_code WHERE T3.zip_code = 94301