[Python] Change .shp polygon color based on .csv single cell value

I have a pyplot with three .shp polygons as sublots. I would like to change the color of each polygon based on the values from a .csv file of 3 columns and 2 rows (headers and values). I would like to run each polygon through 2 thresholds. For example, >5= yellow, >10= Red, else blue. I intend to automate the .csv, so the polygons change colors based on the values in the .csv file. I have tried conditional arguments but not get anything to work.

import geopandas as gpd
import matplotlib.pyplot as plt
import pandas as pd
import csv


gdf1 = gpd.read_file("FDRA_1.shp")
gdf2 = gpd.read_file("FDRA_2.shp")
gdf3 = gpd.read_file("FDRA_3.shp")`

row = 2; col = 1
with open("Valley_Index.csv") as f:
reader = csv.reader(f)
for i in range(row):
row = next(reader)
VIndex = row[col - 1]
threshold1=5


fig, ax = plt.subplots()

for i in VIndex:
color = 'coral' if VIndex > threshold1 else 'blue'
ax.fill(x, y, color=color)

gdf1.plot(ax=ax, color='blue', edgecolor='black')


gdf2.plot(ax=ax, color='red', edgecolor='black')


gdf3.plot(ax=ax, color='green', edgecolor='black')


plt.title('Multiple Polygons')
plt.xlabel('Longitude')
plt.ylabel('Latitude')


plt.show()

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