Akshaykumarcp/pandas

Pandas for data science

Table of content

1. What is pandas ❓
2. Why use Pandas ❓
3. Pandas Operations 👨‍💻
4. Pandas MindMap 🧠
5. Connect with me 😃

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1. what is pandas ❓

• Popular python library for analyzing and transforming structured data
• Open library that integrates with matplotlib
• Pandas has a flexible data structure called as dataframe which is similar to spreadsheet
• Pandas can read & write many types of data formats, such as CSV or excel files.
• Official github repo of pandas can be found here
• Quick links: Pandas homepage, Pandas IO, Sort data, Pandas group by, Pandas indexing, Pandas Viz

2. Why use Pandas ❓

• Dataframe: Easy to use & efficient object for data manipulation
• Handle inconsistent data: Find and fix missing data
• Select & query dataframes: Select rows, columns or filter rows based on a query
• Aggregation and plotting: Group rows and generate high quality plots with a few lines of code

3. Pandas Operations 👨‍💻

• 3.1 Basic-usage
• 3.2 Indexing
• 3.3 Drop NA by column and row
• 3.4 Fill NA by default value
• 3.5 Dataframe creation
• 3.6 Concatenate dataframes
• 3.7 Merge dataframes
• 3.8 Group by
• 3.9 Join and apply
• 3.10 Export dataframe

4. Pandas MindMap 🧠

5. Connect with me 😃