15 Advanced Python Pandas Code Snippets

Python’s Pandas library is a powerful tool for data manipulation and analysis. It’s widely used in data science for its simplicity and ability to handle large datasets. In this article, we’ll explore 15 advanced Pandas code snippets that can help you streamline your data analysis tasks. Each snippet includes code examples and results to illustrate their practical applications.

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1. Setting Options for Better Display

Before diving into the advanced snippets, let’s set some options to enhance the display of DataFrames.

import pandas as pd
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', 20)
pd.set_option('display.float_format', '{:.2f}'.format)

These settings ensure that all columns are displayed, the maximum number of rows shown is 20, and floating-point numbers are formatted to two decimal places.

2. Loading a Dataset

We’ll use the Titanic dataset for our examples. Load it using Seaborn’s load_dataset function.

import seaborn as sns

# Load Titanic dataset
titanic = sns.load_dataset('titanic')
print(titanic.head())

Result:

survived  pclass     sex   age  sibsp  parch     fare embarked  class    who  …