Tutorial
Easy to learn syntax Massive ecosystem of libraries Strong community support Versatile - from web to ML
**Pandas**: DataFrames, data cleaning **NumPy**: Numerical computing
**Matplotlib**: Basic plots **Seaborn**: Statistical visualizations **Plotly**: Interactive charts
**Scikit-learn**: Classical ML **TensorFlow/PyTorch**: Deep learning
1. Python basics (2-3 weeks) 2. NumPy & Pandas (2-3 weeks) 3. Visualization (2 weeks) 4. Scikit-learn (4-6 weeks) 5. Practice projects
Python for Data Science: Your Complete Getting Started Guide
Dr. Anand Gupta•Data Science Educator
5 March 2026
10 min read
Introduction
Python is the most popular language for data science. This guide will take you from zero to analyzing your first dataset.
Why Python for Data Science?
Essential Libraries
Data Manipulation
Visualization
Machine Learning
Your First Analysis
Step 1: Setup
```python
import pandas as pd
import matplotlib.pyplot as plt
```
Step 2: Load Data
```python
df = pd.read_csv('your_data.csv')
```
Step 3: Explore
```python
print(df.head())
print(df.describe())
```
Step 4: Visualize
```python
plt.figure(figsize=(10, 6))
df['column'].hist()
plt.show()
```
Learning Path
Conclusion
Python opens doors to data science. Start small, practice daily, and build real projects.
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