# Import the tools we will use
import warnings; warnings.filterwarnings("ignore")
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

# Let us see some data to practice plotting
tips = sns.load_dataset("tips")

print("Shape of data:", tips.shape)
tips.head()

# Create a bar plot: Average tip by day
plt.figure(figsize=(6,4))
sns.barplot(data=tips, x="day", y="tip")
plt.title("Average Tip by Day")
plt.show()

# You can quickly see differences by adding color
plt.figure(figsize=(6,4))
sns.barplot(data=tips, x="day", y="tip", hue="sex")
plt.title("Average Tip by Day and Gender")
plt.show()

# Count the number of bills for each day
plt.figure(figsize=(6,4))
sns.countplot(data=tips, x="day")
plt.title("Number of Bills by Day")
plt.show()

# Count plot can also use hue for a second category
plt.figure(figsize=(6,4))
sns.countplot(data=tips, x="day", hue="smoker")
plt.title("Bills by Day and Smoking Status")
plt.show()

# Swarm plot: Each dot is a tip value for that day
plt.figure(figsize=(6,4))
sns.swarmplot(data=tips, x="day", y="tip")
plt.title("All Tips by Day - Swarm Plot")
plt.show()

# We can color the dots using another category
plt.figure(figsize=(6,4))
sns.swarmplot(data=tips, x="day", y="tip", hue="sex")
plt.title("Swarm Plot by Day and Gender")
plt.show()

# Try your own: Count plot for time of day
plt.figure(figsize=(6,4))
sns.countplot(data=tips, x="time")
plt.title("Lunch vs Dinner Counts")
plt.show()

# Mini-project: Which gender tips more at lunch vs dinner?
plt.figure(figsize=(7,5))
sns.barplot(data=tips, x="time", y="tip", hue="sex", ci=None)
plt.title("Average Tip Amount by Meal and Gender")
plt.show()

# Practice: Swarm plot of total bill by gender
plt.figure(figsize=(7,5))
sns.swarmplot(data=tips, x="sex", y="total_bill", palette="Accent")
plt.title("Swarm Plot of Total Bill by Gender")
plt.show()

# Challenge: Try making a bar plot with another dataset using input()!
csv_url = input("Paste a CSV url (or press Enter to skip): ")
if csv_url:
    your_data = pd.read_csv(csv_url)
    print("Columns:", list(your_data.columns))
    x = input("Column for X axis: ")
    y = input("Column for Y axis (average height): ")
    plt.figure(figsize=(6,4))
    sns.barplot(data=your_data, x=x, y=y)
    plt.title("Your Bar Plot")
    plt.show()
else:
    print("No data loaded. Try again later!")