Pandas

Welcome to Realcare Tech Mark's Online Pandas Course, where you will dive into the world of data manipulation and analysis with one of the most powerful data manipulation libraries in Python—Pandas. Whether you're a data scientist, analyst, or enthusiast, this course is tailored to enhance your skills in handling, cleaning, and analyzing data efficiently using Pandas.

Curriculum

9 Sections
27 Lessons
0 Quizzes
0m Duration

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Introduction to Pandas

3 Lessons0 Quizzes

Overview of Pandas and its Applications
Installation and Setup
Introduction to Series and DataFrame

Data Loading in Pandas

3 Lessons0 Quizzes

Reading Data from Different Sources
Importing CSV, Excel, and SQL Data
Handling Data Formats and Options

Exploratory Data Analysis with Pandas

3 Lessons0 Quizzes

Descriptive Statistics
Data Distribution Analysis
Correlation and Covariance

Indexing and Selection in Pandas

3 Lessons0 Quizzes

Indexing Techniques in Pandas
Selection and Slicing
Conditional Indexing

Data Cleaning in Pandas

3 Lessons0 Quizzes

Handling Missing Values
Removing Duplicates
Outlier Detection and Treatment

Data Transformation in Pandas

3 Lessons0 Quizzes

Merging and Concatenating DataFrames
Pivoting and Melting DataFrames
Grouping and Aggregation

Time Series Analysis with Pandas

3 Lessons0 Quizzes

Working with Date-Time Indexing
Resampling and Shifting Time Series Data
Analyzing Time Series Patterns

Visualization with Pandas

3 Lessons0 Quizzes

Creating Basic Plots with Pandas
Customizing Plots for Data Communication
Visualizing Time Series Data

Advanced Pandas Features

3 Lessons0 Quizzes

Hierarchical Indexing
Multi-Indexing in Pandas
Working with Large Datasets

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Last Updated: March 15, 2024

This course includes

Learn key data structures
Understanding Series
Explore DataFrame
Introduction to Pandas: Explore the fundamentals of Pandas, understanding its role in data manipulation, and its key data structures, Series and DataFrame.
Data Loading: Learn to import data from various sources, including CSV files, Excel spreadsheets, SQL databases, and more.
Exploratory Data Analysis (EDA): Master the art of exploring and summarizing data using Pandas, gaining insights into key statistical measures and data distributions.
Indexing and Selection: Understand how to effectively index and select data within Pandas DataFrames for manipulation and analysis.
Data Cleaning Techniques: Dive into the essential skills of cleaning and preprocessing data, handling missing values, duplicates, and outliers.
Data Transformation: Explore techniques for transforming and reshaping data, including merging, pivoting, and grouping operations.
Time Series Analysis: Gain practical skills in handling and analyzing time series data using Pandas, with a focus on date-time indexing and time-based operations.
Visualization with Pandas: Learn how to create informative visualizations directly within Pandas, enabling effective data communication.