📈 Seaborn Line Plot

Last Updated: 07 Nov 2025

A line plot is used to show a trend or change over continuous values.

Hinglish Tip 🗣: Time-series ya continuous data ka trend dekhna ho toh line plot perfect hai.

Basic Syntax

sns.lineplot(data=df, x='col1', y='col2')
plt.show()

📘 Example Dataset

We will use the inbuilt fmri dataset.It is a time-series dataset, which contains fMRI data(Functional Magnetic Resonance Imaging).

df = sns.load_dataset('fmri')
df.head()

📈 Basic Line Plot

sns.lineplot(data=df, x='timepoint', y='signal')
plt.show()

Important Parameters

Below are the parameters you must know.

  • data The dataset you want to plot (usually a pandas DataFrame).Example: data=df
  • x & y Columns to plot on X-axis and Y-axis.Example: x='timepoint', y='signal'
  • hue Separate lines for each category.
sns.lineplot(data=df, x='timepoint', y='signal', hue='region')
plt.show()
  • style Different line styles (dashed/solid) per category.
sns.lineplot(data=df, x='timepoint', y='signal', hue='region', style='event')
plt.show()
  • size Change line thickness.
sns.lineplot(data=df, x='timepoint', y='signal', size='event')
plt.show()
  • palette Customize colors.
sns.lineplot(data=df, x='timepoint', y='signal', hue='region', palette='coolwarm')
plt.show()
  • markers Show data points on line.
sns.lineplot(data=df, x='timepoint', y='signal', markers=True)
plt.show()
  • dashes Customize dash pattern.
sns.lineplot(data=df, x='timepoint', y='signal', dashes=False)
plt.show()
  • legend Show/hide legend.
sns.lineplot(data=df, x='timepoint', y='signal', hue='region', legend=False)
plt.show()

⭐ Full Example

sns.lineplot(
    data=df,
    x='timepoint',
    y='signal',
    hue='event',
    style='region',
    markers=True,
    dashes=False,
    size='region',
    palette='viridis'
)
plt.show()

Quick Practice

  1. Load any dataset containing time-series data.
  2. Plot a line graph with hue.
  3. Add markers.
  4. Try changing dash styles.
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