Python - data analysis (Pandas)

• Course participants will learn to use the Pandas library and other supporting libraries that are needed to work with data, analyze and visualize it.

• Data Scientist, data analysts, especially in the Big Data environment, is the primary auditor for this intensive course.
• Software developers who are familiar with Python at least at intermediate and advanced levels and aim to create data-intensive allocations using the SPARK Big Data (Cloud) engine.
• Data architects

• Basic knowledge of Python at the PYTHON_INTRO level

• Professional explanation with practical samples and examples.

• Powerpoint handouts and module printouts.

Introduction to IPython

• Tools for online work with data (Jupyter Notebook and Jupyter Lab)
• Export output to PDF and other formats

Overview of data structures in Python

• Sheet, tuple, etc.

Pandas module

• Objects for working with tay (Series, DataFrame)

NumPy module

• Work with multidimensional data structures

Import data from different sources

• CSV
• HTML
• JSON
• SQL

Work with data

• Transformation
• Filling in missing values
• Mapping
• Replacement

Advanced work with data

• Concat merge join
• Pivoting, stacking, unstacking
• Melting

Aggregation and grouping of data

• Split apply combine
• Transformation
• Filtering

Time lines

• Representation of date, time, and time intervals
• Timestamp, Timedelta, DateTimeIndex, and more

Visualization

• IPython graphing
• Loading data into charts from Pandas objects
• Work with charts of different types
• Data aggregation into graphs

Previous courses

Python I - introduction to programming [PYTHON_INTRO]

Next courses

Python - Data Analysis II (Advanced Data Processing) [PYTHON_DATAN2]

Python - data analysis III (BigData Spark Analysis) [PYTHON_DATAN3]

Related courses

Python III - development of database applications [PYTHON_DB]

Python - web development [PYTHON_WEB]

Python II - advanced techniques [PYTHON_ADV]

Python - BigData and Hadoop [PYTHON_BIGDATA]