Skill Demand Index
Python (pandas, NumPy) — Demand & Depth Analysis
Based on 2 scored job postings out of 4,033 total. Depth levels reflect actual proficiency tiers, not just keyword presence.
0%
Demand Rate
L3
Median Depth
0%
Gap Rate
2
Jobs Analyzed
Proficient
Most employers want Python (pandas, NumPy) at hands-on daily use, not textbook knowledge.
Overview
What is Python (pandas, NumPy)?
Market context for Python (pandas, NumPy) in the current job market
Python (pandas, NumPy) is required in 0% of scored job postings on ShouldApply, making it a growing skill in the current job market. Employers looking for Python (pandas, NumPy) typically want candidates who can demonstrate real proficiency, not just surface awareness.
What the data shows for Python (pandas, NumPy):
- •Required in 0% of all scored postings — demand is growing as more employers add it to requirements
- •Employers typically expect L3 depth — hands-on proficiency, not surface awareness
- •Most demand comes from Data Science / ML roles — 50% of all Python (pandas, NumPy) jobs
What L3 means in practice:
L3 (Proficient) means daily professional use. You should be able to work independently with Python (pandas, NumPy) without needing supervision or constant guidance.
This means employers aren't looking for someone who has used Python (pandas, NumPy) once or twice. They want evidence of professional application — shipped work, measurable outcomes, and the ability to operate independently.
Common skill gaps:
The gap rate of 0% means most candidates have adequate Python (pandas, NumPy) proficiency. To stand out, aim for L4-L5 depth with concrete evidence.
Which roles need Python (pandas, NumPy) most:
Data Science / ML positions drive 50% of demand. Data Analysis also frequently list Python (pandas, NumPy) as a requirement. Skills commonly paired with Python (pandas, NumPy) include SQL (advanced query design and optimization) and ML frameworks (scikit-learn, TensorFlow or PyTorch).
Depth Level Distribution
Proficiency Distribution
How candidates match Python (pandas, NumPy) requirements across 2 scored evaluations
Average depth: L3.0·Median depth: L3.0
Salary Correlation
Pay Impact
How Python (pandas, NumPy) affects compensation based on postings with disclosed salary data
Without Python (pandas, NumPy)
$140K
Median $131K
1093 jobs
Skill Demand Insight
“Python (pandas, NumPy) appears in 0% of all scored jobs.”
From 2 scored job postings
Skill Pairings
Commonly Paired Skills
Other skills that frequently appear alongside Python (pandas, NumPy)
50%
co-occurrence
50%
co-occurrence
50%
co-occurrence
50%
co-occurrence
50%
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50%
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co-occurrence
Role Breakdown
Top Role Categories
Job categories most likely to require Python (pandas, NumPy)
Gap Analysis
Gap Rate Explained
How often Python (pandas, NumPy) is identified as a skill gap (L0–L1) in scored applications
Very low gap rate — candidates generally have this skill
When Python (pandas, NumPy) appears in a job's requirements, 0% of scored applicants received an L0 or L1 (missing or minimal).
Frequently Asked Questions
Is Python (pandas, NumPy) in demand in 2026?
Yes. Python (pandas, NumPy) appears in 0% of scored job postings on ShouldApply, making it a growing skill in the current market. Based on 2 analyzed jobs, demand is steady across multiple role types.
What level of Python (pandas, NumPy) do most jobs require?
The median required depth is L3. Most roles expect intermediate competency — independent work without supervision.
Does knowing Python (pandas, NumPy) increase salary?
Salary data for Python (pandas, NumPy) is still accumulating.
What other skills pair with Python (pandas, NumPy)?
The most common pairings are SQL (advanced query design and optimization), ML frameworks (scikit-learn, TensorFlow or PyTorch), 5+ years data science, Spark / PySpark, Deploying, monitoring, and maintaining models. Strengthening these alongside Python (pandas, NumPy) improves your fit across more positions.
What roles need Python (pandas, NumPy) the most?
Top roles: Data Science / ML, Data Analysis. Data Science / ML positions have the highest demand at 50% of all Python (pandas, NumPy) jobs.
How do I improve my Python (pandas, NumPy) level?
L1→L2: online courses and personal projects. L2→L3: daily professional use and shipped work. L3→L4: mentoring others and optimizing processes. L4→L5: architecture decisions, open source contributions, or published work.
See how you stack up against Python (pandas, NumPy) job requirements
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Analyze my Python (pandas, NumPy) gaps →See how your depth compares to what employers actually require
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