Temperature vs. Humidity

Contents

Temperature vs. Humidity#

Goal

Scatter plot of indoor temperature against relative humidity with comfort zone boundaries. This helps evaluate whether indoor conditions fall within acceptable thermal comfort ranges.

Data Basis

The dataset flatTempHum.csv contains hourly indoor temperature and humidity measurements for multiple flats (columns: time, FlatA_Hum, FlatA_Temp, FlatB_Hum, FlatB_Temp, …; separator ;). We use FlatA_Temp and FlatA_Hum and build a 3-column DataFrame [timestamp, temperature, humidity].

Data Preparation#

import pandas as pd

url = "https://raw.githubusercontent.com/retomarek/edap/main/edap/sampleData/flatTempHum.csv"
raw = pd.read_csv(url, sep=";")

# Parse timestamp
raw["time"] = pd.to_datetime(raw["time"])

# Select [timestamp, temperature, humidity] — 3-column DataFrame
df = raw[["time", "FlatA_Temp", "FlatA_Hum"]].copy()
df.columns = ["timestamp", "temperature", "humidity"]
df = df.dropna()

df.head()

	timestamp	temperature	humidity
0	2018-10-03 00:00:00	24.43	53.0
1	2018-10-03 01:00:00	24.40	53.0
2	2018-10-03 02:00:00	24.40	53.0
3	2018-10-03 03:00:00	24.40	53.0
4	2018-10-03 04:00:00	24.40	53.3

Visualization#

from pyedautils.plots import plot_comfort_temp_humidity

fig = plot_comfort_temp_humidity(df, title="Indoor Comfort — Temperature vs. Humidity")
fig.show()