Python Data Tools
Python / Data Analysis
Exploratory Python work focused on data analysis, automation, transformation, and visualization.
tools/normalise.py
1import pandas as pd
2from pathlib import Path
3
4df = pd.read_excel(src)
5df = df.dropna(subset=[…])
6
7def normalise(frame):
8 frame.columns = […]
9 return frame
10
11summary = df.groupby(…)
12summary.to_csv(out)
output
- Overview
- Exploratory Python work focused on learning data manipulation, analysis, simple automation and visualization.
- Problem
- Some data preparation steps were repetitive and better suited to a script than a spreadsheet.
- System architecture
- Source file → pandas transformation → validation → output extract and chart.
- Workflow
- Load → clean → reshape → check → export.
- Tools
- Python / Data Analysis
- Role
- Self-directed learning work, written and iterated independently.
- Impact
- Shown as technical development rather than production software engineering.
- Implementation notes
- All interfaces shown are representative reconstructions using fictitious sample data. No internal names, documents or confidential metrics are published.