import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

# Create data
data = pd.DataFrame({
    'Animal': ['Rhino', 'Giraffe', 'Lion'],
    'Weight': [3000, 1200, 250]
})

# Sort by Weight descending
data = data.sort_values('Weight', ascending=False)

# Set seaborn style without gridlines
sns.set_theme(style="white")  # 'white' style removes most gridlines

# Column chart
plt.figure(figsize=(8,6))
bars = sns.barplot(x='Animal', y='Weight', data=data, color="#D44803")

# Add data labels
for bar in bars.patches:
    height = bar.get_height()
    bars.annotate(f'{int(height)}',
                  xy=(bar.get_x() + bar.get_width()/2, height),
                  xytext=(0, 5),
                  textcoords="offset points",
                  ha='center', va='bottom', fontsize=12)

plt.title('Column Chart: Animal Weights with PikBioStat')
plt.xlabel('Animal')
plt.ylabel('Weight (kg)')
sns.despine(left=True, bottom=True)  # removes top/left/bottom spines
plt.show()

# Bar chart
plt.figure(figsize=(8,6))
bars = sns.barplot(x='Weight', y='Animal', data=data, color="#D44803")

# Add data labels
for bar in bars.patches:
    width = bar.get_width()
    bars.annotate(f'{int(width)}',
                  xy=(width, bar.get_y() + bar.get_height()/2),
                  xytext=(5, 0),
                  textcoords="offset points",
                  ha='left', va='center', fontsize=12)

plt.title('Bar Chart: Animal Weights with PikBioStat')
plt.xlabel('Weight (kg)')
plt.ylabel('Animal')
sns.despine(left=True, bottom=True)
plt.show()