Skip to main content

automated_data_analysis

An automated data analysis pipeline package for efficient data processing and cleaning.

Features

  • Automated data loading (CSV/Excel)
  • Duplicate removal
  • Smart missing value handling
  • Data format validation
  • Statistical analysis
  • Data accuracy checks
  • Comprehensive terminal reporting

Check out the example script for more details.

Usage Parameters

analyze_data() :

  • file_path : Path to CSV/Excel file

  • fill_strategy (optional) : Dictionary specifying filling strategies for columns

  • stats_columns (optional) : List of columns for statistical analysis

  • stats (optional) : List of statistics to calculate (default: ['mean', 'median', 'std', 'min', 'max'])

Dependency :

  • pandas>=1.0.0
  • numpy>=1.18.0
  • openpyxl>=3.0.0

Installation

pip install automated_data_analysis

Metadata

Release files for automated-data-analysis 1.1.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for automated-data-analysis 1.1.1
File Size Uploaded Provenance
automated_data_analysis-1.1.1.tar.gz 4.9 kB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for automated-data-analysis 1.1.1
File Interpreter ABI Platform
automated_data_analysis-1.1.1-py3-none-any.whl Python 3 none any Details

Total release size: 12.3 kB

Release files / automated_data_analysis-1.1.1.tar.gz

Download URL automated_data_analysis-1.1.1.tar.gz
Size 4.9 kB
Tags Source
SHA-256 checksum
How to use checksums
9613dbbc7eeb1a526031c98163dccc110373234d1aea331921422520ef5fad43
BLAKE2b-256 checksum
How to use checksums
8ab3aaff8041f0c0f708167e41111fff634c43ad6d25358c0a83d6795f8802f3
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.13.1

Release files / automated_data_analysis-1.1.1-py3-none-any.whl

Download URL automated_data_analysis-1.1.1-py3-none-any.whl
Size 7.4 kB
Tags Python 3
SHA-256 checksum
How to use checksums
df2cccb77a201404dd8f9a62386c18940bdb61a0e797e0fa3c1f1aae9dc05a64
BLAKE2b-256 checksum
How to use checksums
83364b5fee2579d53df5cc4543531251e247927ed0f7f73dec3c6929246076ec
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.13.1

Security for automated-data-analysis 1.1.1

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

Release history Release notifications | RSS feed

This release

1.1.1 This release

2 release files No provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page