# Python Scicomp Pattern1 Load Process Eng Data

> Sub-skill of python-scientific-computing: Pattern 1: Load and Process Engineering Data (+2).

- Skill: `vamseeachanta/python-scicomp-pattern1-load-process-eng-data` (Agent Skill)
- Install (CLI): `npx skillmds@latest add vamseeachanta/python-scicomp-pattern1-load-process-eng-data`
- Raw SKILL.md: https://api.skillmd.com/api/skills/vamseeachanta/python-scicomp-pattern1-load-process-eng-data/raw
- Safety review: PASS (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: vamseeachanta (https://skillmd.com/u/vamseeachanta)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/vamseeachanta/python-scicomp-pattern1-load-process-eng-data

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# Pattern 1: Load and Process Engineering Data (+2)

## Pattern 1: Load and Process Engineering Data


```python
import numpy as np

# Load CSV data
data = np.loadtxt('../data/measurements.csv', delimiter=',', skiprows=1)

# Extract columns
time = data[:, 0]
temperature = data[:, 1]
pressure = data[:, 2]

*See sub-skills for full details.*

## Pattern 2: Solve System of Equations


```python
from scipy.optimize import fsolve

def system(vars):
    x, y, z = vars
    eq1 = x + y + z - 6
    eq2 = 2*x - y + z - 1
    eq3 = x + 2*y - z - 3
    return [eq1, eq2, eq3]

solution = fsolve(system, [1, 1, 1])
```

## Pattern 3: Curve Fitting


```python
from scipy.optimize import curve_fit

def model(x, a, b, c):
    return a * np.exp(-b * x) + c

# Fit data
params, covariance = curve_fit(model, x_data, y_data)
a_fit, b_fit, c_fit = params
```