Section 1.1: Popular Python Packages for Datasets

When starting with data science, several widely-used Python packages can assist in dataset acquisition:

1. Seaborn/Scikit-Learn/Statsmodels

   These three packages are commonly employed in data science and come equipped with built-in datasets. Let's explore them one by one.

Seaborn

Seaborn is primarily a visualization library, but it also includes foundational datasets for experimentation. You can easily list available datasets and fetch them as follows:

import seaborn as sns

sns.get_dataset_names()

From Seaborn, you have access to 19 datasets. To load the Titanic dataset, for instance, use:

titanic = sns.load_dataset('titanic')

titanic.head()

Scikit-Learn

Scikit-Learn offers a variety of APIs for both toy and real-world datasets. Each dataset can be loaded using its specific API. To load the Iris dataset, you would write:

from sklearn.datasets import load_iris

data = load_iris()

data.target[[10, 25, 50]]

data.keys()

The datasets are organized in a dictionary, allowing you to manipulate them as needed.

Statsmodels

Statsmodels is designed for statistical modeling but also provides various datasets. To access a specific dataset, you can run:

import statsmodels as sm

data = sm.datasets.longley.load_pandas()

data.data

For more detailed information on these datasets, refer to the respective documentation.

Section 1.2: Additional Python Packages for Dataset Acquisition

2. Pydataset

   Pydataset is another valuable package that offers numerous open-source datasets, many of which are familiar from introductory data science courses, like Titanic and Iris. To install it, run:

pip install pydataset

After installation, you can acquire a list of datasets:

from pydataset import data

data()

This package boasts a collection of 757 datasets, a wealth of options for your projects. You can also retrieve detailed information about specific datasets:

data('BJsales', show_doc=True)

Here's how to load a dataset for use:

bjsales = data('BJsales')

bjsales.head()

3. NLTK

   The Natural Language Toolkit (NLTK) is tailored for natural language processing and provides various text-related datasets. For instance, to download the ABC corpus, use:

import nltk

nltk.download('abc')

After downloading, you can access the words as follows:

abc.words()

4. Datasets by HuggingFace

   The Datasets package by HuggingFace allows quick access to a wide range of datasets, particularly for NLP, computer vision, and audio tasks. To install, run:

pip install datasets

To load a dataset, first, decide which one you need, then use:

from datasets import load_dataset_builder

dataset_builder = load_dataset_builder('imdb')

This enables you to view features and splits of the dataset.

5. Opendatasets

   Opendatasets is an excellent tool for downloading datasets from online platforms like Kaggle. To begin, sign up on Kaggle and obtain your API key. Install the package using:

pip install opendatasets

To download a dataset, input the dataset link as shown below:

import opendatasets as od