Visualize a dataset#

Visualize a dataset

The package includes basic tools to visualize BDF data as line plots. This notebook demonstrates the core functionality, including:

  • default plotting of a minimal dataset

  • custom plotting of defined quantities

  • adding a secondary axis to the plot

  • converting units in the plot

import bdf

# Read the raw source data and display the header
df = bdf.read("https://zenodo.org/records/17289383/files/SINTEF__NaCR32140-MP10-04__2025-08-25__GITT_0p05C_25degC__BioLogic.mpt")

# The package plots Voltage / V versus Test Time / s by default, if no other information is provided
bdf.plot(df)

image1

# The user can also make custom plots from the dataframe
bdf.plot(
    df,
    xdata="Test Time / s",
    ydata="Ambient Temperature / degC"
)

image2

# The yydata option can be added to introduce a secondary axis
bdf.plot(
    df,
    xdata="Test Time / s",
    ydata="Voltage / V",
    yydata="Current / A"
)

image3

# Unit conversions can also be done directly in the plot function without additional steps
bdf.plot(
    df,
    xdata="Test Time / s", xunit="h",
    ydata="Voltage / V",
    yydata="Current / A", yyunit="mA"
)

image4

Interactive exploration#

Use bdf.explore() for interactive plotting. Choose a backend:

  • backend="bokeh" (requires pip install batterydf[hvplot])

  • backend="plotly" (included in the base install)

bdf.explore(
    df,
    xdata="Test Time / s", xunit="h",
    ydata="Voltage / V",
    yydata="Current / A", yyunit="mA",
    backend="bokeh",
    kind="scatter",
)

bdf.explore(
    df,
    xdata="Test Time / s", xunit="h",
    ydata="Voltage / V",
    yydata="Current / A", yyunit="mA",
    backend="plotly",
    kind="scatter",
)