# Imports
from matplotlib import pyplot as plt
import pandas as pd

# Load the data
data = pd.read_csv('series-161224_2.csv')

# Define the start and end index for your data range
start = 0
end = 120

# Slice the data for x and y
x = data['Title'][start:end]
y = data['Gross Domestic Product: Quarter on Quarter growth: CVM SA %'][start:end]

# Create a figure with custom size
plt.figure(figsize=(18, 6))

colors = ['yellow', 'green', 'blue', 'red']  # List of colors to cycle through

for i in range(start, end, 4):
    # Ensure the range doesn't exceed the total number of data points
    plt.axvspan(i, min(i + 4, end), color=colors[(i // 4) % len(colors)], alpha=0.3)

"""
ideas: 
highlight the years where GDP growth rate was > 2% with green in the n-th quarter
highlight the years where GDP growth rate was negative in the n-th quarter 
average the GDP growth rate and merge them into a single value 

then do further research into what contributed to the rise in certain years or what contributed to drops

etc. 

"""

# Plot the data
plt.plot(x, y)

# Rotate X-axis labels and shrink font size
plt.xticks(rotation=90, fontsize=8)

# Show the plot
plt.show()