The code must be done in python, The information will be given in the picture shown. Thank you.

#You will find the two data sets that have the highest correlation $($either negitive or positive$)$ and then plot the data using a scatter plot.

#Then using the seaborn library, plot the regression line of the data.

#$1.$Create a function to read each colmn of Atmosphere Temperature, Soil Temperature, Atmosphere Humidity and Soil Humidity using the $.$values method from the numpy library.

#$2.$Pass the $.$values to a second function that will calculate and display the correlation coefficient of the two highest correlation values to the console.

#Choose any correlation method you wish. Good examples can be found in the second resrouce listed above. $($there will be one negative and one positive correlation$)$

#$($HINT: You may need to test different combinations to get the best correlations. i$.$e$.$ Atm Hum vs Soil Hum, Atm Temp vs Soil Hum...etc.$)*$

#$3.$Pass the $.$values to a third function that will display a $2$ scatter plots of the two data sets with a properly fit regression line.

#Label the plots with the appropriate title and label the x$-$axis and y$-$axis as well. Display the plots to the console and also include code to save the file to Plant$\_$Corr.pdf$.$

#$4.$Create the main$()$ function which calls all three functions. Don't forget to call main to kick it off!

import pandas as pd

import numpy as np

from matplotlib import pyplot as plt

from scipy.stats import spearmanr as spr

import seaborn as sns

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

# Open the plant$\_$data file for reading.

# Read all the lines from the file.

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plant$\_$file $=$ pd$.$read$\_$csv$(????)$

#create column value lists for plotting

atm$\_$temp $=$ plant$\_$file$[\text{'}$Atmosphere Temp'$].$values

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return $????$

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def corr$\_$calc$(?,?,?,?)$:

#correlation calculation

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# Print the result

print$($f$"\backslash$t$\backslash$tCorrelation: $\{$result:$\mathrm{.}0\%\}\backslash$t$\backslash$t$\backslash$tCorrelation: $\{$result$2$:$\mathrm{.}0\%\}")$

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def plot$\_$me$(?,?,?,?)$:

#plot the data points and regression lines for neg and pos correlation

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plt$.$tight$\_$layout$()$

plt$.$savefig$(\text{'}$drive$/$My Drive$/$Colab Notebooks$/$NEWEST $207/$Plant$\_$Corr.pdf$\text{'})$

plt$.$show$()$

# Create the main function.

def main$()$:

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

corr$\_$calc$(????)$

plot$\_$me$(????)$

# Call main function to kick it off!

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$????$