🚀 Python Data Aggregation Tutorial

Data aggregation is a core skill in data analysis! Let's explore how to efficiently process and summarize data using Python.

🔍 Key Libraries for Data Aggregation

• Pandas (首选工具)
  

  

  Python_Pandas

  import pandas as pd
  df.groupby('category').mean()
  

• NumPy (数值计算基础)
  

  

  Numerical_Computation

  np.sum(data, axis=1)
  

• Dask (处理大数据集)
  

  

  Parallel_Computing

  dask.dataframe.from_pandas(df).mean()
  

📊 Practical Examples

1. Summarizing sales data
   Use df.pivot_table() to create summary statistics.

2. Time-series aggregation
   Resample data with df.resample() for daily/weekly trends.

3. Custom aggregation functions
   Combine transform() and agg() for advanced operations.

📚 Expand Your Knowledge

Want to dive deeper? Check out our Python Data Analysis Guide for comprehensive tutorials on data manipulation and visualization.