Python Coding challenge - Day 797| What is the output of the following Python Code?

 

Code Explanation:

Importing the Altair Library

import altair as alt

What it does:

Imports the Altair library and gives it the short alias alt.

Why:

Altair is a declarative data visualization library for Python — you describe what you want to visualize (not how to draw it). It integrates very well with Pandas dataframes and Vega-Lite under the hood.

Importing the Pandas Library

import pandas as pd

What it does:

Imports the Pandas library with the alias pd.

Why:

Pandas provides powerful data structures like DataFrame — ideal for storing and manipulating tabular data (rows and columns).

Creating a Pandas DataFrame

df = pd.DataFrame({'x':[1,2,3], 'y':[4,5,6]})

What it does:

Creates a small DataFrame with two columns:

'x' = [1, 2, 3]

'y' = [4, 5, 6]

So the DataFrame looks like this:

   x  y

0  1  4

1  2  5

2  3  6

Why:

This serves as the data source for the chart.

Each row will represent one bar in the bar chart.

Creating an Altair Chart Object

chart = alt.Chart(df).mark_bar().encode(x='x', y='y')

What it does:

alt.Chart(df) creates a Chart object using the DataFrame df as the data source.

.mark_bar() specifies that you want a bar chart (as opposed to points, lines, etc.).

.encode(x='x', y='y') tells Altair how to map data columns to visual elements:

The column 'x' goes on the x-axis.

The column 'y' goes on the y-axis.

Why:

This single line fully defines the bar chart’s structure — Altair takes care of rendering the visualization using Vega-Lite automatically.

Printing the Column Names

print(list(df.columns))

What it does:

df.columns gives an Index object containing the column names (Index(['x', 'y'], dtype='object')).

Wrapping it in list() converts it to a normal Python list.

print() outputs that list to the console.

Output:

['x', 'y']

500 Days Python Coding Challenges with Explanation