Boxplot

Boxplot#

Compare distributions across multiple groups using interactive boxplots.

Goal

Compare temperature distributions across four flats using interactive Plotly boxplots. Boxplots reveal the median, quartiles, and outliers of each distribution at a glance.

Data Basis

Dataset: flatTempHum.csv — Hourly indoor temperature and humidity measurements from four residential flats (A–D).
Columns used: FlatA_Temp, FlatB_Temp, FlatC_Temp, FlatD_Temp
Time range: October 2018 – September 2020

Data Preparation#

import pandas as pd

url = "https://raw.githubusercontent.com/retomarek/edap/main/edap/sampleData/flatTempHum.csv"
df = pd.read_csv(url, sep=";")
df["time"] = pd.to_datetime(df["time"])
df = df.set_index("time", drop=True)
df.head()

	FlatA_Hum	FlatA_Temp	FlatB_Hum	FlatB_Temp	FlatC_Hum	FlatC_Temp	FlatD_Hum	FlatD_Temp
time
2018-10-03 00:00:00	53.0	24.43	38.8	22.40	44.0	24.5	49.0	24.43
2018-10-03 01:00:00	53.0	24.40	38.8	22.40	44.0	24.5	49.0	24.40
2018-10-03 02:00:00	53.0	24.40	39.3	22.40	44.7	24.5	48.3	24.38
2018-10-03 03:00:00	53.0	24.40	40.3	22.40	45.0	24.5	48.0	24.33
2018-10-03 04:00:00	53.3	24.40	41.0	22.37	45.2	24.5	47.7	24.30

# Select temperature columns and melt to long format
temp_cols = ["FlatA_Temp", "FlatB_Temp", "FlatC_Temp", "FlatD_Temp"]
df_long = df[temp_cols].melt(var_name="flat", value_name="value")

# Clean up flat names for display
df_long["flat"] = df_long["flat"].str.replace("_Temp", "")
df_long.head()

	flat	value
0	FlatA	24.43
1	FlatA	24.40
2	FlatA	24.40
3	FlatA	24.40
4	FlatA	24.40

Visualization#

import plotly.express as px

fig = px.box(
    df_long,
    x="flat",
    y="value",
    title="Temperature Distribution by Flat",
    labels={"value": "Temperature [°C]", "flat": "Flat"},
)
fig.show()

Boxplot by Time Group#

Use plot_boxplot() from pyedautils to group values by a time unit (month, hour, weekday, quarter). This reveals seasonal or daily patterns in the data.

from pyedautils.plots import plot_boxplot

fig = plot_boxplot(
    df,
    column="FlatA_Temp",
    groupby="month",
    title="FlatA Temperature by Month",
    ylab="Temperature [°C]",
)
fig.show()