exploratory-data-analysis

Name: exploratory-data-analysis
Author: K-Dense-AI

31kstars3.1kforks

How to install exploratory-data-analysis?

k-dense-ai/scientific-agent-skills/exploratory-data-analysis

$npx -y skills add K-Dense-AI/scientific-agent-skills --skill exploratory-data-analysis

Installs into the current project.

Summary

Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzing any scientific data file to understand its structure, content, quality, and characteristics. Automatically detects file type and generates d

Files · 1

View on GitHub

SKILL.md

1	# Exploratory Data Analysis
2
3	## Overview
4
5	Perform comprehensive exploratory data analysis (EDA) on scientific data files across multiple domains. This skill provides automated file type detection, format-specific analysis, data quality assessment, and generates detailed markdown reports suitable for documentation and downstream analysis planning.
6
7	Key Capabilities:
8	- Automatic detection and analysis of 200+ scientific file formats
9	- Comprehensive format-specific metadata extraction
10	- Data quality and integrity assessment
11	- Statistical summaries and distributions
12	- Visualization recommendations
13	- Downstream analysis suggestions
14	- Markdown report generation
15
16	## When to Use This Skill
17
18	Use this skill when:
19	- User provides a path to a scientific data file for analysis
20	- User asks to "explore", "analyze", or "summarize" a data file
21	- User wants to understand the structure and content of scientific data
22	- User needs a comprehensive report of a dataset before analysis
23	- User wants to assess data quality or completeness
24	- User asks what type of analysis is appropriate for a file
25
26	## Supported File Categories
27
28	The skill has comprehensive coverage of scientific file formats organized into six major categories:
29
30	### 1. Chemistry and Molecular Formats (60+ extensions)
31	Structure files, computational chemistry outputs, molecular dynamics trajectories, and chemical databases.
32
33	File types include: `.pdb`, `.cif`, `.mol`, `.mol2`, `.sdf`, `.xyz`, `.smi`, `.gro`, `.log`, `.fchk`, `.cube`, `.dcd`, `.xtc`, `.trr`, `.prmtop`, `.psf`, and more.
34
35	Reference file: `references/chemistry_molecular_formats.md`
36
37	### 2. Bioinformatics and Genomics Formats (50+ extensions)
38	Sequence data, alignments, annotations, variants, and expression data.
39
40	File types include: `.fasta`, `.fastq`, `.sam`, `.bam`, `.vcf`, `.bed`, `.gff`, `.gtf`, `.bigwig`, `.h5ad`, `.loom`, `.counts`, `.mtx`, and more.
41
42	Reference file: `references/bioinformatics_genomics_formats.md`
43
44	### 3. Microscopy and Imaging Formats (45+ extensions)
45	Microscopy images, medical imaging, whole slide imaging, and electron microscopy.
46
47	File types include: `.tif`, `.nd2`, `.lif`, `.czi`, `.ims`, `.dcm`, `.nii`, `.mrc`, `.dm3`, `.vsi`, `.svs`, `.ome.tiff`, and more.
48
49	Reference file: `references/microscopy_imaging_formats.md`
50
51	### 4. Spectroscopy and Analytical Chemistry Formats (35+ extensions)
52	NMR, mass spectrometry, IR/Raman, UV-Vis, X-ray, chromatography, and other analytical techniques.
53
54	File types include: `.fid`, `.mzML`, `.mzXML`, `.raw`, `.mgf`, `.spc`, `.jdx`, `.xy`, `.cif` (crystallography), `.wdf`, and more.
55
56	Reference file: `references/spectroscopy_analytical_formats.md`
57
58	### 5. Proteomics and Metabolomics Formats (30+ extensions)
59	Mass spec proteomics, metabolomics, lipidomics, and multi-omics data.
60
61	File types include: `.mzML`, `.pepXML`, `.protXML`, `.mzid`, `.mzTab`, `.sky`, `.mgf`, `.msp`, `.h5ad`, and more.
62
63	Reference file: `references/proteomics_metabolomics_formats.md`
64
65	### 6. General Scientific Data Formats (30+ extensions)
66	Arrays, tables, hierarchical data, compressed archives, and common scientific formats.
67
68	File types include: `.npy`, `.npz`, `.csv`, `.xlsx`, `.json`, `.hdf5`, `.zarr`, `.parquet`, `.mat`, `.fits`, `.nc`, `.xml`, and more.
69
70	Reference file: `references/general_scientific_formats.md`
71
72	## Workflow
73
74	### Step 1: File Type Detection
75
76	When a user provides a file path, first identify the file type:
77
78	1. Extract the file extension
79	2. Look up the extension in the appropriate reference file
80	3. Identify the file category and format description
81	4. Load format-specific information
82
83	Example:
84	```
85	User: "Analyze data.fastq"
86	→ Extension: .fastq
87	→ Category: bioinformatics_genomics
88	→ Format: FASTQ Format (sequence data with quality scores)
89	→ Reference: references/bioinformatics_genomics_formats.md
90	```
91
92	### Step 2: Load Format-Specific Information
93
94	Based on the file type, read the corresponding reference file to understand:
95	- Typical Data: What kind of data this format contains
96	- Use Cases: Common applications for this format
97	- Python Libraries: How to read the file in Python
98	- EDA Approach: What analyses are appropriate for this data type
99
100	Search the reference file for the specific extension (e.g., search for "### .fastq" in `bioinformatics_genomics_formats.md

People who liked this also viewed

6 picks

Type

exploratory-data-analysis

31kstars3.1kforks

View on GitHub

How to install exploratory-data-analysis?

k-dense-ai/scientific-agent-skills/exploratory-data-analysis

$npx -y skills add K-Dense-AI/scientific-agent-skills --skill exploratory-data-analysis

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# Exploratory Data Analysis
2
3	## Overview
4
5	Perform comprehensive exploratory data analysis (EDA) on scientific data files across multiple domains. This skill provides automated file type detection, format-specific analysis, data quality assessment, and generates detailed markdown reports suitable for documentation and downstream analysis planning.
6
7	Key Capabilities:
8	- Automatic detection and analysis of 200+ scientific file formats
9	- Comprehensive format-specific metadata extraction
10	- Data quality and integrity assessment
11	- Statistical summaries and distributions
12	- Visualization recommendations
13	- Downstream analysis suggestions
14	- Markdown report generation
15
16	## When to Use This Skill
17
18	Use this skill when:
19	- User provides a path to a scientific data file for analysis
20	- User asks to "explore", "analyze", or "summarize" a data file
21	- User wants to understand the structure and content of scientific data
22	- User needs a comprehensive report of a dataset before analysis
23	- User wants to assess data quality or completeness
24	- User asks what type of analysis is appropriate for a file
25
26	## Supported File Categories
27
28	The skill has comprehensive coverage of scientific file formats organized into six major categories:
29
30	### 1. Chemistry and Molecular Formats (60+ extensions)
31	Structure files, computational chemistry outputs, molecular dynamics trajectories, and chemical databases.
32
33	File types include: `.pdb`, `.cif`, `.mol`, `.mol2`, `.sdf`, `.xyz`, `.smi`, `.gro`, `.log`, `.fchk`, `.cube`, `.dcd`, `.xtc`, `.trr`, `.prmtop`, `.psf`, and more.
34
35	Reference file: `references/chemistry_molecular_formats.md`
36
37	### 2. Bioinformatics and Genomics Formats (50+ extensions)
38	Sequence data, alignments, annotations, variants, and expression data.
39
40	File types include: `.fasta`, `.fastq`, `.sam`, `.bam`, `.vcf`, `.bed`, `.gff`, `.gtf`, `.bigwig`, `.h5ad`, `.loom`, `.counts`, `.mtx`, and more.
41
42	Reference file: `references/bioinformatics_genomics_formats.md`
43
44	### 3. Microscopy and Imaging Formats (45+ extensions)
45	Microscopy images, medical imaging, whole slide imaging, and electron microscopy.
46
47	File types include: `.tif`, `.nd2`, `.lif`, `.czi`, `.ims`, `.dcm`, `.nii`, `.mrc`, `.dm3`, `.vsi`, `.svs`, `.ome.tiff`, and more.
48
49	Reference file: `references/microscopy_imaging_formats.md`
50
51	### 4. Spectroscopy and Analytical Chemistry Formats (35+ extensions)
52	NMR, mass spectrometry, IR/Raman, UV-Vis, X-ray, chromatography, and other analytical techniques.
53
54	File types include: `.fid`, `.mzML`, `.mzXML`, `.raw`, `.mgf`, `.spc`, `.jdx`, `.xy`, `.cif` (crystallography), `.wdf`, and more.
55
56	Reference file: `references/spectroscopy_analytical_formats.md`
57
58	### 5. Proteomics and Metabolomics Formats (30+ extensions)
59	Mass spec proteomics, metabolomics, lipidomics, and multi-omics data.
60
61	File types include: `.mzML`, `.pepXML`, `.protXML`, `.mzid`, `.mzTab`, `.sky`, `.mgf`, `.msp`, `.h5ad`, and more.
62
63	Reference file: `references/proteomics_metabolomics_formats.md`
64
65	### 6. General Scientific Data Formats (30+ extensions)
66	Arrays, tables, hierarchical data, compressed archives, and common scientific formats.
67
68	File types include: `.npy`, `.npz`, `.csv`, `.xlsx`, `.json`, `.hdf5`, `.zarr`, `.parquet`, `.mat`, `.fits`, `.nc`, `.xml`, and more.
69
70	Reference file: `references/general_scientific_formats.md`
71
72	## Workflow
73
74	### Step 1: File Type Detection
75
76	When a user provides a file path, first identify the file type:
77
78	1. Extract the file extension
79	2. Look up the extension in the appropriate reference file
80	3. Identify the file category and format description
81	4. Load format-specific information
82
83	Example:
84	```
85	User: "Analyze data.fastq"
86	→ Extension: .fastq
87	→ Category: bioinformatics_genomics
88	→ Format: FASTQ Format (sequence data with quality scores)
89	→ Reference: references/bioinformatics_genomics_formats.md
90	```
91
92	### Step 2: Load Format-Specific Information
93
94	Based on the file type, read the corresponding reference file to understand:
95	- Typical Data: What kind of data this format contains
96	- Use Cases: Common applications for this format
97	- Python Libraries: How to read the file in Python
98	- EDA Approach: What analyses are appropriate for this data type
99
100	Search the reference file for the specific extension (e.g., search for "### .fastq" in `bioinformatics_genomics_formats.md

People who liked this also viewed

6 picks

Type