def get_nearest_station(my_latitude: float, my_longitude: float,stations: List['Station']) -> int:"""Return the id of the station from stations that is nearest to thelocation given by my_latidute and my_longitude.In the case of a tie, return the ID of the last station in stations withthat distance.Preconditions: len(stations) > 1» get_nearest_station(43.671134, -79.325164, SAMPLE_STATIONS)7571» get_nearest_station(43.674312, -79.299221, SAMPLE_STATIONS)7486II II || # A set of constants, each representing a list index for station information.ID = 0%3DNAME1%3DLATITUDE2%3DLONGITUDE= 3САРАСІTY= 4BIKES_AVAILABLEDOCKS_AVAILABLE56.'SMART'NO_KIOSK# For use in the get_lat_lon_distance helper functionEARTH_RADIUS6371# SAMPLE DATA TO USE IN DOCSTRING EXAMPLESSAMPLE_STATIONS%3D[7090, 'Danforth Ave / Lamb Ave',43.681991, -79.329455, 15, 4, 10],[7486, 'Gerrard St E / Ted Reeve Dr',43.684261, -79.299332, 24, 5, 19],[7571, 'Highfield Rd / Gerrard St E43.671685, -79.325176, 19, 14, 5]]SMART',HANDOUT_STATIONS[7000, 'Ft. York / Capreol Crt.',43.639832, -79.395954, 31, 20, 11],[7001, 'Lower Jarvis St SMART / The Esplanade',43.647992, -79.370907, 15, 5, 10]]

def get_nearest_station(my_latitude: float, my_longitude: float, stations: List['Station']) -> int: """'Return the id of the station from stations that is nearest to the location given by my_latidute and my_longitude. In the case of a tie, return the ID of the last station in stations with that distance. Preconditions: len(stations) > 1 » get_nearest_station(43.671134, -79.325164, SAMPLE_STATIONS) 7571 » get_nearest_station(43.674312, -79.299221, SAMPLE_STATIONS) 7486

def get_nearest_station(my_latitude: float, my_longitude: float, stations: List['Station']) -> int: """'Return the id of the station from stations that is nearest to the location given by my_latidute and my_longitude. In the case of a tie, return the ID of the last station in stations with that distance. Preconditions: len(stations) > 1 » get_nearest_station(43.671134, -79.325164, SAMPLE_STATIONS) 7571 » get_nearest_station(43.674312, -79.299221, SAMPLE_STATIONS) 7486

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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def get_nearest_station(my_latitude: float, my_longitude: float, stations: List['Station']) -> int: "''Return the id of the station from stations that is nearest to the location given by my_latidute and my_longitude. In the case of a tie, return the ID of the last station in stations with that distance. Preconditions: len(stations) > 1 » get_nearest_station(43.671134, -79.325164, SAMPLE_STATIONS) 7571 » get_nearest_station(43.674312, -79.299221, SAMPLE_STATIONS) 7486
The following code will #define N_ROW 10 #define N_COL 10 int row; double sum=0, table[N_ROW][N_COL]; sum = 0; for (row = 0; row < N_ROW; row++) sum += table[row][1] sum the values of the column with an index of 1. sum the values of the row with an index of 1. sum the values of the row with an index of N_ROW. none of the others sum the values of the first column in the array.
complete the docstring using the information provided:
MySQL Workbench Will the following select statements work? If the queries don’t work, explain why and then correct them.a-) SELECT NAME, EMPLOYEE_ID, SALARYFROM EMPLOYEE_TBL E, EMPLOYEE_PAY_TBL EPWHERE EMPLOYEE_ID = EMPLOYEE_ID AND NAME LIKE '%MITH';b-) SELECT E.NAME, E.EMPLOYEE_ID, EP.SALARYFROM EMPLOYEE_TBL E, EMPLOYEE_PAY_TBL EPWHERE NAME LIKE '%MITH';c-) SELECT E.NAME, E.EMPLOYEE_ID, EP.SALARYFROM EMPLOYEE_TBL E, EMPLOYEE_PAY_TBL EPWHERE E.EMPLOYEE_ID = EP.EMPLOYEE_ID AND E.NAME LIKE '%MITH';d-) SELECT ENAME, COUNT(*)FROM EMPWHERE ENAME = '&NAME'ORDER BY ENAME;e-) SELECT DEPT_ID, COUNT(*)FROM EMPGROUP BY DEPT_IDHAVING ENAME='ALIYE';f-) SELECT F_NAME, L_NAMEWHERE F_NAME LIKE '%A'FROM EMP, DEPT;g-) SELECT NAME, SALARYFROM DEPT, EMPWHERE DEPT.ID = EMP.ID AND SUM(SALARY);
def get_nearest_station(my_latitude: float, my_longitude: float, stations: List['Station']) -> int: """Return the id of the station from stations that is nearest to the location given by my_latidute and my_longitude. In the case of a tie, return the ID of the last station in stations with that distance. Preconditions: len(stations) > 1 >>> get_nearest_station(43.671134, -79.325164, SAMPLE_STATIONS) 7571 >>> get_nearest_station(43.674312, -79.299221, SAMPLE_STATIONS) 7486 """
Use Python Code Your task is : Number of reported COVID-19 deaths by country. (Use pandas to read the csv table. Example : df = pd.read_csv('Covid19Deaths.csv') then do the code using the dataframe) COVID-19 Deaths table (csv): Province/State Country/Region Lat Long ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## 2/1/2020 2/2/2020 2/3/2020 2/4/2020 2/5/2020 2/6/2020 2/7/2020 2/8/2020 2/9/2020 ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## 3/1/2020 3/2/2020 3/3/2020 3/4/2020 3/5/2020 3/6/2020 3/7/2020 3/8/2020 3/9/2020 ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## 4/1/2020 4/2/2020 4/3/2020 4/4/2020 4/5/2020 4/6/2020 4/7/2020 Afghanistan 33 65 0 0 0 0 0 0 0 0…
The InstantRide Driver Relationship team wants to learn how many travels each driver has done in the month of October. You need to send them the DRIVER_ID, and two calculated columns: DAY and RIDES. The DAY column is calculated using the DAY() function with the TRAVEL_START_TIME as the argument. The RIDES column is calculated by using the COUNT() function to determine the number of rides given for each day. Filter the results with the MONTH function.
nycflights13::flights Q4<- flights %>%filter(carrier == "JFK") %>%summarise(average_dist = mean(distance)%>%summarise(max_dist = max(average_dist))%>%group_by(Q4, month, day)%>%head(Q4[order(dat$month),(dat$day),(dat$max_dist)],n=5) *not pictured, I did upload, tidy verse, dplyr, and the nycflights13 libraries. Error: Incomplete expression: Q4<- flights %>% filter(carrier == "JFK") %>% summarise(average_dist = mean(distance)%>% summarise(max_dist = max(average_dist))%>% group_by(Q4, month, day)%>% head(Q4[order(dat$month),(dat$day),(dat$max_dist)],n=5) RStudio Question: I can't figure out what is wrong with my code. Could someone take a look at it? See below for what I am trying to do, my code and my error output. I am trying to find what 5 days of the year had the highest mean distance from JFK airport, using the nycflights13 library. I want to format it in month, day, andvmean distance.
Dictionary vegetables_info contains key-value pairs that represent the grade received by each vegetable item in an inspection. Dictionary grade_scale contains key-value pairs that represent the meaning of each grade. String vegetables_name is read from input. Complete the following tasks: Use pop() to remove vegetables_name from vegetables_info and assign vegetables_num with the value returned. Any string that is not a key in vegetables_info has the default value 0. Assign patient_grade with the value associated with key vegetables_num in grade_scale. Any number that is not a key in grade_scale has default value 'not reported'.
individual characters using their 0-based index. Hint: You will need to do this for checking all the rules. However, when you access a character .
complete the doctring using the information below: