pandas练习手册_20201119

Essential Pandas for Machine Learning

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Agenda

1. Introduction to Pandas
2. Understanding Series & DataFrames
3. Loading CSV,JSON
4. Connecting databases
5. Descriptive Statistics
6. Accessing subsets of data - Rows, Columns, Filters
7. Handling Missing Data
8. Dropping rows & columns
9. Handling Duplicates
10. Function Application - map, apply, groupby, rolling, str
11. Merge, Join & Concatenate
12. Pivot-tables
13. Normalizing JSON

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1. Introduction to Pandas

• High Performance, Easy-to-use open source library for Data Analysis
• Creates tabular format of data from different sources like csv, json, database.
• Have utilities for descriptive statistics, aggregation, handling missing data
• Database utilities like merge, join a