Data Analysis with Python

Load and Explore a Dataset

Download a CSV dataset and use Pandas to load it. Display the first 10 rows and summarize its statistics.

Expected output: Printed first 10 rows and summary statistics of the dataset.

Hint: Use pd.read_csv(), head(), and describe() methods.

Create a Histogram

Using the dataset loaded, create a histogram of a numerical column to visualize its distribution.

Expected output: A histogram plot showing the frequency distribution of the selected column.

Hint: Use matplotlib.pyplot.hist() and plt.show().

A DataFrame is a two-dimensional labeled data structure in Pandas that can hold data of different types in columns, similar to a spreadsheet or SQL table.

Data cleaning is important because it removes errors, inconsistencies, and missing values that can distort analysis results and lead to incorrect insights.

Data analysis is the process of inspecting, cleaning, and modeling data to discover useful information.