Python Data Analysis Lab: Experimentation and Exploration

python is a powerful programming language that is widely used for data analysis. This lab is designed to allow you to explore various aspects of Python data analysis through a series of experiments. Through these hands-on exercises, you'll develop a deep understanding of fundamental concepts in data processing, visualization, and modeling.

Experiment 1: Data Loading and Exploration

• Importing and manipulating CSV files
• Exploring Data Structures using NumPy and pandas
• Calculate basic statistics such as mean and standard deviation
• Filtering and Sorting Data to identify patterns

Experiment 2: Data Visualization

• Use Matplotlib to create line graphs, histograms and scatter plots
• Customize visualization appearance, including color, line width, and labels
• Use Seaborn to create more advanced visualizations such as heat maps and cluster plots

Experiment 3: Data Preprocessing

• Missing value processing, including deletion, filling and interpolation
• Outlier detection and exclusion
• Data normalization and scaling to improve modeling performance

Experiment 4: Machine Learning Modeling

• Understand the basic principles of supervised learning and unsupervised learning
Train and evaluate linear regression, logistic regression, and decision tree models using Scikit-learn
• Optimize model parameters and improve prediction accuracy

Experiment 5: Time Series Analysis

Loading and processing time series data
Using Pandas and Statsmodels to draw time series graphs
Identify trends, seasonality and periodicity in time series

Experiment 6: Text Analysis

Use Natural Language Toolkit (NLTK) to process text data
Perform word frequency analysis, stemming and sentiment analysis
Exploring text classification and topic modeling

in conclusion

These experiments provide hands-on experience and let you explore the power of Python data analysis. By completing these exercises, you will master the core concepts of data loading, exploration, visualization, preprocessing, modeling, and text analysis. These skills will provide you with a solid foundation for success in a variety of data analysis projects.

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