02 — Exploratory Data Analysis
Data quality checks, descriptive statistics, time-series visualization, and rolling SMA trend analysis of chiller plant operations.
chiller-plant eda time-series rolling-average
Pythonpandasmatplotlib
Key Findings
- ● Zero missing values across all 23 columns
- ● 24-hour and 240-hour SMAs reveal drift in kW/ton efficiency over the dataset period
- ● CW flow vs kW/ton spline analysis highlights flow-efficiency coupling
Initial exploration of the chiller plant dataset: data quality validation, summary statistics, dual-axis time-series of plant kW vs cooling tons, and rolling simple moving average analysis to detect efficiency trends.