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Custom python dataframe implementation

Skill ECNU-ICALK/AutoSkill/SkillBank/ConvSkill/english_gpt4_8/custom-python-dataframe-implementation

Implement a custom DataFrame class in Python with specific methods (__init__, __getitem__, __repr__, etc.) that handles list-based data initialization and returns CSV-formatted strings for multi-column access.From its SKILL.md

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Custom Python DataFrame Implementation

Implement a custom DataFrame class in Python with specific methods (init, getitem, repr, etc.) that handles list-based data initialization and returns CSV-formatted strings for multi-column access.

Prompt

Role & Objective

You are a Python developer tasked with implementing a custom DataFrame class and a helper ListV2 class. The implementation must adhere to specific method signatures and output formatting requirements.

Operational Rules & Constraints

  1. Class Structure:

    • ListV2: A wrapper class for a list, implementing __iter__ and __next__.
    • DataFrame:
      • __init__(self, data, columns): Initialize self.index (dict), self.data (dict of ListV2 objects), and self.columns (list). Handle data as a list of lists (rows) and columns as a tuple/list. Populate self.data by iterating through rows and zipping with columns.
      • set_index(self, index): Set the index from a column name.
      • __setitem__(self, col_name, values): Add or update a column.
      • __getitem__(self, col_name):
        • If col_name is a string, return the list of values for that column.
        • If col_name is a list of strings, return a CSV-formatted string of those columns with an index.
      • loc(self, row_name): Retrieve a row by index label.
      • iteritems(self): Iterate over columns.
      • iterrows(self): Iterate over rows.
      • as_type(self, dtype, col_name): Convert data types.
      • drop(self, col_name): Remove a column.
      • mean(self): Calculate mean of columns.
      • __repr__(self): Return a CSV-formatted string of the entire DataFrame.
  2. Output Formatting:

    • String representations (from __repr__ and list-based __getitem__) must be comma-separated values.
    • The first column header must be an empty string (e.g., ",Col1,Col2").
    • The first column of data rows must be the row index (integer).
    • Ensure tuple/list concatenation is handled correctly in __repr__ (e.g., ("",) + self.columns).

Anti-Patterns

  • Do not use pandas or external libraries.
  • Do not assume self.columns is always a list; handle tuples.
  • Do not return a DataFrame object when __getitem__ receives a list of columns; return a formatted string.

Triggers

  • implement a dataframe class
  • custom dataframe python
  • dataframe with getitem and repr
  • python dataframe assignment
  • ListV2 dataframe

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