Python Data Analytics Course

Description

Python Data Analytics with Python using

Most attendees are in-work Data Professional. Private individuals are very welcome.
Our Style: Hands-on, Practical
Location: Online, Instructor-led
Download: anaconda.com
Duration: 1 consecutive day, 11am-5pm
Dates Times: You may let us know which dates your would prefer, or attend as scheduled

Session 1: Database:

SQLite3:
Linking with SQL Database.
Create, Amend and Drop Tables.
Insert, Update and delete records.
Select queries.
Traverse and display query results.
Using parameters in queries.
Get metadata about tables and columns.

Session 2: Data Structures

Data Structures:
Tuples.
Sets.
Dictionary. Nested Dictionary.
Json Files.

Session 3: Python Numpy

Numpy:
The Python NumPy Module:
Working with arrays, create data using arrays.
Array manipulation.
String functions on arrays.
Math, arithmetic and statistical functions.

Session 4: Python Pandas Dataframes and data importing

Python Dataframes
Data Series. Date/ Time Functionality. Time series.
Creating Dataframes, Indexing.
Dict to Dataframe, Dataframe to Dict.
Csv to Dataframe, Dataframe to csv.
Excel to Dataframe, Dataframe to Excel.

Session 5: Data Cleaning and preparation

Data Cleaning and preparation
Finding, replacing and filtering missing data.
Remove Duplicates.
Replacing values.
Renaming Axis Indexes.

Session 6: Pandas Data Wrangling

Data Wrangling:
Indexing, Re-indexing,
Reorder,
Sorting, Stastitics,
Transforming data using
Dataframe Joins, Merging, Concatenation, Overlap, Append, zip.

Week 6: Pandas Data Analysis

Data Analysis:
Sorting.
Analysing and finding data using filter, slicing and dataframe queries.
Finding data by Iteration.
Find statistics: Functions, Aggregate functions.
Unique values.
String objects, Regex.