技能档案

Pandas / NumPy

此技能定义了各角色和级别的期望。

Machine Learning & AI Classical Machine Learning

角色数

包含此技能的角色

级别数

结构化成长路径

必要要求

其余 5 个可选

Machine Learning & AI

Classical Machine Learning

2026/2/22

选择当前级别并对比期望。下方卡片显示晋升所需掌握的内容。

各级别期望

表格展示从初级到首席的技能深度变化。点击行查看详情。

角色	必要性	描述
Data Scientist		Works with pandas DataFrame for loading, cleaning, and analyzing data. Performs basic operations: filtering, grouping, aggregation, merge/join. Uses numpy for mathematical operations and array manipulation. Builds pivot tables and descriptive statistics.

角色	必要性	描述
Data Scientist		Efficiently works with large datasets via pandas: chunked processing, dtype optimization, multi-index. Applies numpy vectorized operations for high-performance computing. Uses pandas profiling for automated EDA.

角色	必要性	描述
Data Scientist		Designs high-performance data processing pipelines with pandas/numpy. Applies advanced techniques: Cython extensions, numba JIT compilation for numpy. Optimizes memory footprint through chunked processing and memory-mapped arrays for out-of-core computing.

角色	必要性	描述
Data Scientist		Defines data handling standards for the data science team. Establishes shared data processing utilities and best practices. Coordinates migration from pandas to distributed frameworks (Dask, Polars, Spark) when needed.

角色	必要性	描述
Data Scientist		Shapes data processing stack strategy for the organization. Defines when to use pandas vs Polars vs Spark for different scales. Evaluates emerging tools and their fit for the organization's data science workflow.

Junior 1 要求

Data Scientist

Works with pandas DataFrame for loading, cleaning, and analyzing data. Performs basic operations: filtering, grouping, aggregation, merge/join. Uses numpy for mathematical operations and array manipulation. Builds pivot tables and descriptive statistics.

Middle 1 要求

Data Scientist

Efficiently works with large datasets via pandas: chunked processing, dtype optimization, multi-index. Applies numpy vectorized operations for high-performance computing. Uses pandas profiling for automated EDA.

Senior 1 要求

Data Scientist

Designs high-performance data processing pipelines with pandas/numpy. Applies advanced techniques: Cython extensions, numba JIT compilation for numpy. Optimizes memory footprint through chunked processing and memory-mapped arrays for out-of-core computing.

Lead / Staff 1 要求

Data Scientist

Defines data handling standards for the data science team. Establishes shared data processing utilities and best practices. Coordinates migration from pandas to distributed frameworks (Dask, Polars, Spark) when needed.

Principal 1 要求

Data Scientist

Shapes data processing stack strategy for the organization. Defines when to use pandas vs Polars vs Spark for different scales. Evaluates emerging tools and their fit for the organization's data science workflow.

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