The file for plant$\_$data looks something like the picture shown. Write this code in python.

$\backslash$table$[[,$A$,B,C,D,E,F,$G$,H$#use the csv library to read Atmosphere Temperature, Soil Temperature, Atmosphere Humidity and Soil Humidity from Plant$\_$Data.csv$.$ Don't forget to close your file at the end!

#$1.$Create a function to read each variable into a dictionary using the csv$.$DictReader$()$ function

#$2.$Inside of that same function, use a for loop to append each of the value pairs for each category to an empty list

#$3.$Pass these lists to another function that will calculate the averages if the values in each list $($Hint: Make sure your data is the correct data type$)$

#$4.$Use the function to return these averages to the main$().$ Display the $4$ average values inside main$()$ with $2$ digit precision.

import csv

from statistics import mean

def read$\_$to$\_$list$()$:

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with open$(\text{'}\text{'}\text{'}$PATH TO DATA'$\text{'}\text{'})$ as csvfile:

#create dictionary with key value pairs foratm tep, atm hum, soil hum and soil temp

reader $=$ csv$.$DictReader$($csvfile$)$

#create empty lists for values for each month $(7$ key value pairs$)$

atm$\_$temp$\_$avg $=[]$

soil$\_$temp$\_$avg $=[]$

atm$\_$hum$\_$avg $=[]$

soil$\_$hum$\_$avg $=[]$

#append each value pair of dictionary to list

for i in reader:

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return $????$

def calc$\_$avgs$(????)$:

#convert hum and temp values to floats

average$\_$atm$\_$temp $=0$

average$\_$soil$\_$temp $=0$

average$\_$atm$\_$hum $=0$

average$\_$soil$\_$hum $=0$

#convert hum and temp values to floats

#average$\_$atm$\_$temp $=$ mean$($map$($float$,$ atm$\_$temp$\_$avg$))$

for j in a$\_$t:

average$\_$atm$\_$temp $???$

average$\_$atm$\_$temp $/=$ len$($a$\_$t$)$

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for $...???$

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for...???

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for...???

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return $????$

# Main function

def main$()$:

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$????=$ read$\_$to$\_$list$()$

$????=$ calc$\_$avgs$(????)$

#show total averages

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print$(????)$

print$(????)$

print$(????)$

print$(????)$

#call main to kick it off

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$????$