Getting Started with Pandas DataFrames
After exploring Pandas Series, today I dived into DataFrames — the backbone of Pandas and data analysis.
🔹 Creating a DataFrame
import pandas as pd
data = {
"Name": ["Alice", "Bob", "Charlie"],
"Age": [25, 30, 35],
"City": ["NY", "LA", "Chicago"]
}
df = pd.DataFrame(data)
print(df)
✅ Output:
Name Age City
0 Alice 25 NY
1 Bob 30 LA
2 Charlie 35 Chicago
🔹 Fun Facts about DataFrames
• They’re like Excel sheets in Python 📝
• Built on NumPy arrays → super fast
• Support powerful operations: filtering, grouping, merging, pivoting
• Widely used in data science, finance, ML, and business analytics
✨ Reflection
DataFrames are where Python starts feeling like a real data playground. Excited to explore filtering and analysis next! 🚀
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