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Some of the common functions of seaborn library with their descriptions is given below:

Function Name Description

sns.lineplot() Creates a line plot to show trends over time or sequence.

sns.barplot() Creates a bar chart showing average values with optional error bars.

sns.countplot() Shows the count of categories (like number of students in each class).

sns.histplot() Creates a histogram showing distribution of a numeric variable.

sns.boxplot() Creates a box plot to show the distribution and outliers in the data.

sns.scatterplot() Creates a scatter plot to show the relationship between two numeric variables.

sns.heatmap() Displays data in a color-coded matrix, often used for correlation.

sns.set_style("style") Sets the background style ("darkgrid", "whitegrid", "dark", etc.).

sns.set_palette("palette") Changes the color theme ("pastel", "muted", "bright", etc.).

sns.kdeplot() Plots a smooth curve (KDE) for a distribution, often used with histplot().

VIDEO SESSION 21 st Centu-
ry Skills #Digital Literacy
Scan the QR code or visit the following link to watch the video:
Python Tutorials - Making a Simple Plot using pyplot module | matplotlib

https://www.youtube.com/watch?v=flwF6aJtmJs&list=PLzgPDYo_3xulakyk7r5h_djrWq1gjD6hm&index=2
After watching the video, answer the following question:
Create the plot explained in the video.

Visualizations are often the simplest way to convey facts! Psychologically, our brain experiences
BRAINY less stress when viewing graphical representations compared to examining the same data in a
FACT
numerical list format.

Let us understand how to create various charts in Excel as well as using Python programming.

Types of Graphs

Graphs are visual representations of data. They help us understand trends, patterns, and comparisons quickly. Different
types of graphs are used depending on the nature of the data and the purpose of analysis.

Line Graph

A line graph is a strong tool for representing continuous data on a numbered axis. It enables us to visually represent
trends and changes in data points across time.

Line graphs are appropriate for data that can take any value within a defined range. The line may slope upwards,
suggesting an increase, or downwards, indicating a decrease, reflecting changes in the data over time.

156 Touchpad Artificial Intelligence - XI