aevri/pandas

Analysis updated 2026-07-18 · repo last pushed 2014-12-03

PythonAudience · dataComplexity · 2/5DormantLicenseSetup · easy

Mindmap

mindmap
  root((repo))
    What it does
      Organizes tabular data
      Cleans messy data
      Reads and writes files
    Tech stack
      Python
      NumPy
      DataFrames
    Use cases
      Sales data analysis
      Research data cleaning
      Dashboard metrics
    Audience
      Data analysts
      Scientists
      Founders building dashboards
    Notable features
      Series and DataFrames
      Automatic alignment
      CSV Excel database IO

mindmap root((repo)) What it does Organizes tabular data Cleans messy data Reads and writes files Tech stack Python NumPy DataFrames Use cases Sales data analysis Research data cleaning Dashboard metrics Audience Data analysts Scientists Founders building dashboards Notable features Series and DataFrames Automatic alignment CSV Excel database IO

What do people build with it?

USE CASE 1

Load a CSV of sales transactions and group them by region to find top performers.

USE CASE 2

Combine data from multiple experiments and clean up inconsistencies before analysis.

USE CASE 3

Transform raw event logs into metrics for a dashboard.

USE CASE 4

Read from and write to CSVs, Excel files, or databases in a few lines of code.

What is it built with?

PythonNumPy

How does it compare?

	aevri/pandas	0xallam/my-recipe	0xhassaan/nn-from-scratch
Stars	—	—	0
Language	Python	Python	Python
Last pushed	2014-12-03	2022-11-22	—
Maintenance	Dormant	Dormant	—
Setup difficulty	easy	moderate	moderate
Complexity	2/5	2/5	4/5
Audience	data	general	developer

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · easy Time to first run · 5min

Install via pip, works best alongside NumPy and matplotlib for full data workflows.

Copy-paste prompts

Prompt 1

Show me how to load a CSV file into a pandas DataFrame and filter rows by a condition.

Prompt 2

Help me group and summarize sales data by region using pandas.

Prompt 3

Explain the difference between a pandas Series and a DataFrame with an example.

Prompt 4

Walk me through merging two datasets and handling missing values with pandas.

Prompt 5

Show me how pandas works alongside matplotlib and NumPy in a typical data analysis workflow.

Frequently asked questions

What is pandas?

A Python library that brings spreadsheet-like tables into code, making it easy to clean, filter, merge, and analyze real-world messy data.

What language is pandas written in?

Mainly Python. The stack also includes Python, NumPy.

Is pandas actively maintained?

Dormant — no commits in 2+ years (last push 2014-12-03).

How hard is pandas to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is pandas for?

Mainly data.

Open on GitHub → Explain another repo

This repo across BitVibe Labs

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