Different DataFrame attributes in Polars

Polars is a fast and efficient data manipulation library written in Rust. It’s designed to provide high-performance operations on large datasets and handles them more quickly than pandas. It’s particularly suitable when working with tabular data.

Importing the library

First, let’s import the polars library:

import polars as pl

Importing polars library

Creating a DataFrame

Let’s consider the example of a student’s score report. We create a DataFrame for the student’s scores in the following courses: calculus, data structures, and operating system.

import polars as pl
df = pl.DataFrame(
  {
    "Students": ["Joseph", "Danial", "Ema"],
    "Calculus": [98, 85, 92],
    "Data structures": [91, 87, 89],
    "Operating system": [96, 88, 91],
  }
)
print(df)

Attributes of the `polars` DataFrame library

Now, let’s look at some of the most common DataFrame attributes of the polars library, which are:

height
width
shape
dtypes
columns

The `height` attribute

The height attribute is used to get the count of rows in the DataFrame.

import polars as pl
df = pl.DataFrame(
  {
    "Students": ["Joseph", "Danial", "Ema"],
    "Calculus": [98, 85, 92],
    "Data structures": [91, 87, 89],
    "Operating system": [96, 88, 91],
  }
)
print(df.height)

The `width` attribute

The width attribute is used to get the count of columns in the DataFrame.

import polars as pl
df = pl.DataFrame(
  {
    "Students": ["Joseph", "Danial", "Ema"],
    "Calculus": [98, 85, 92],
    "Data structures": [91, 87, 89],
    "Operating system": [96, 88, 91],
  }
)
print(df.width)

The `shape` attribute

The shape attribute is used to get the shape of the DataFrame. It returns a tuple of rows and columns that represents the dimensions of the DataFrame.

import polars as pl
df = pl.DataFrame(
  {
    "Students": ["Joseph", "Danial", "Ema"],
    "Calculus": [98, 85, 92],
    "Data structures": [91, 87, 89],
    "Operating system": [96, 88, 91],
  }
)
print(df.shape)

The `dtypes` attribute

The dtypes attribute is used to get the datatypes of the columns of the DataFrame.

import polars as pl
df = pl.DataFrame(
  {
    "Students": ["Joseph", "Danial", "Ema"],
    "Calculus": [98, 85, 92],
    "Data structures": [91, 87, 89],
    "Operating system": [96, 88, 91],
  }
)
print(df.dtypes)

Note: We can also get the shape of the DataFrame and datatypes of the columns by printing the DataFrame.

The `columns` attribute

The columns attribute is used to get the headers of the columns of the DataFrame.

import polars as pl
df = pl.DataFrame(
  {
    "Students": ["Joseph", "Danial", "Ema"],
    "Calculus": [98, 85, 92],
    "Data structures": [91, 87, 89],
    "Operating system": [96, 88, 91],
  }
)
print(df.columns)