import warnings
warnings.filterwarnings("ignore")

# This hides warnings so they do not distract us.

# Import Matplotlib and pyplot
import matplotlib.pyplot as plt

# 'plt' is a short name for pyplot, the main part of Matplotlib used for making plots.

# Our first plot: a simple line
plt.plot([1, 2, 3, 4], [10, 20, 25, 30])
plt.title("A simple line plot")
plt.xlabel("X axis")
plt.ylabel("Y axis")
plt.show()

import pandas as pd

# Data setup
url = "https://raw.githubusercontent.com/jbrownlee/Datasets/master/shampoo.csv"
data = pd.read_csv(url)
print("Shape of the data:", data.shape)
print("First few rows:")
print(data.head())

# Let us plot the shampoo sales over time
plt.figure(figsize=(8, 4))
plt.plot(data["Month"], data["Sales"])
plt.title("Monthly Shampoo Sales")
plt.xlabel("Month")
plt.ylabel("Sales")
plt.xticks(rotation=45)
plt.tight_layout()
plt.show()

# A custom plot with markers and color
plt.plot(data["Month"], data["Sales"], color="green", marker="o", linestyle="--")
plt.title("Shampoo Sales with Custom Style")
plt.xlabel("Month")
plt.ylabel("Sales")
plt.xticks(rotation=45)
plt.tight_layout()
plt.show()

# Adding a legend
plt.plot(data["Month"], data["Sales"], color="purple", label="Shampoo Sales")
plt.title("Shampoo Sales with a Legend")
plt.xlabel("Month")
plt.ylabel("Sales")
plt.legend()
plt.xticks(rotation=45)
plt.tight_layout()
plt.show()

# Bar plot: comparing sales across months
plt.bar(data["Month"], data["Sales"], color="skyblue")
plt.title("Sales as a Bar Chart")
plt.xlabel("Month")
plt.ylabel("Sales")
plt.xticks(rotation=45)
plt.tight_layout()
plt.show()

# Check for missing data
missing = data.isnull().sum()
print("Missing values per column:")
print(missing)

# Highlight the highest month of sales
max_idx = data["Sales"].idxmax()
highlight_month = data.loc[max_idx, "Month"]
highlight_sales = data.loc[max_idx, "Sales"]

plt.plot(data["Month"], data["Sales"], label="Sales")
plt.scatter([highlight_month], [highlight_sales], color="red", zorder=5, label="Highest")
plt.title("Highlighting Highest Sales Month")
plt.xlabel("Month")
plt.ylabel("Sales")
plt.legend()
plt.xticks(rotation=45)
plt.tight_layout()
plt.show()

# Save your plot as an image file
plt.figure(figsize=(8,4))
plt.plot(data["Month"], data["Sales"], marker="o")
plt.title("Shampoo Sales")
plt.xlabel("Month")
plt.ylabel("Sales")
plt.xticks(rotation=45)
plt.tight_layout()
plt.savefig("shampoo_sales_plot.png")
plt.close()
print("Plot saved as shampoo_sales_plot.png")

# Input: Let us ask the user for a line color
color = input("What color should the sales line be? For example, blue or orange: ")
plt.plot(data["Month"], data["Sales"], color=color, marker="o")
plt.title("Sales with Your Chosen Color")
plt.xlabel("Month")
plt.ylabel("Sales")
plt.xticks(rotation=45)
plt.tight_layout()
plt.show()

# Adding grid lines
plt.plot(data["Month"], data["Sales"], marker="o")
plt.title("Sales with Grid Lines")
plt.xlabel("Month")
plt.ylabel("Sales")
plt.grid(True)
plt.xticks(rotation=45)
plt.tight_layout()
plt.show()

# Comparing two data series
import numpy as np
data["Random"] = np.random.randint(50, 200, size=len(data))
plt.plot(data["Month"], data["Sales"], marker="o", label="Sales")
plt.plot(data["Month"], data["Random"], marker="x", label="Random Numbers", linestyle=":")
plt.title("Comparing Two Series")
plt.xlabel("Month")
plt.ylabel("Value")
plt.legend()
plt.xticks(rotation=45)
plt.tight_layout()
plt.show()

# Mini-project Part 1: draw both sales and average sales
avg_sales = data["Sales"].mean()
plt.plot(data["Month"], data["Sales"], marker="o", label="Monthly Sales")
plt.hlines(avg_sales, xmin=0, xmax=len(data)-1, colors="red", linestyles="dotted", label="Average Sales")
plt.title("Monthly Sales vs Average")
plt.xlabel("Month")
plt.ylabel("Sales")
plt.legend()
plt.xticks(rotation=45)
plt.tight_layout()
plt.show()

# Mini-project Part 2: highlight months above average
above_avg = data["Sales"] > avg_sales
plt.plot(data["Month"], data["Sales"], marker="o", label="Sales")
plt.scatter(data["Month"][above_avg], data["Sales"][above_avg], color="orange", label="Above Average")
plt.hlines(avg_sales, xmin=0, xmax=len(data)-1, colors="red", linestyles="dotted", label="Average")
plt.title("Highlighting Months Above Average")
plt.xlabel("Month")
plt.ylabel("Sales")
plt.legend()
plt.xticks(rotation=45)
plt.tight_layout()
plt.show()

# Troubleshooting: if the plot does not show
print("Did you forget plt.show() or made a typo in the column name?")

# Recap: What did we learn?
print("You learned to make line and bar plots, customize them, and work with real data using Matplotlib!")