Pandas Tutorial

Pandas is a powerful Python library for data analysis and manipulation. In this tutorial, we will cover the basics of Pandas and how to use it effectively.

Getting Started

Before we dive into the details, let's ensure you have Pandas installed. You can install it using pip:

pip install pandas

Introduction to Pandas

Pandas provides high-performance, easy-to-use data structures and data analysis tools. Its main data structure is the DataFrame, which is a 2-dimensional labeled data structure with columns of potentially different types.

DataFrame

A DataFrame is similar to a table in a relational database or an Excel spreadsheet. It is made up of rows and columns, where each cell contains a value.

Creating a DataFrame

You can create a DataFrame from various sources, such as a CSV file, a SQL database, or even a Python dictionary.

import pandas as pd

data = {'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35]}
df = pd.DataFrame(data)

Selecting Data

You can select data from a DataFrame using various methods, such as .loc[] and .iloc[].

Using `.loc[]`

.loc[] is label-based indexing, which means you use the index labels to select data.

print(df.loc['Alice', 'Age'])

Using `.iloc[]`

.iloc[] is integer-location based indexing, which means you use the integer positions of the data.

print(df.iloc[0, 1])