Python Data Analysis & Visualization

Duration : 2 Days

About the course: This course teaches a good foundation on how to combine a variety of disciplines,  including computer science, statistics, and domain expertise to extract insights and knowledge from data. With this Data Science knowledge, the participants can apply the key data analysis concepts and how to use data to help make informed business decisions.

Reference

Module 1: Basic Programming 

• Jupyter as development IDE
• Programming in Python
• Python programming syntax and construct

Module 2: Data frames & Datasets

• Inspecting Data Frames: head(), tail(), etc.
• Datatype and info()

Module 3: Data Frame Methods and Computations

• Min, Max, Sum and Count
• Mean, Median, & Mode
• Describe With Numeric Value
• Describe With Objects (Text) Values

Module 4: Series and Columns

• Selecting A Single Column
• A Closer Look At Series
• Important Series Methods
• unique & nunique
• nlargest & nsmallest
• Selecting Multiple Columns
• The powerful value_counts() method
• Using plot() to visualize
• Adding / Removing Columns

Module 5: Organizing Data and Working With Dates/Times

• Indexing / Creating a MultiIndex
• Sorting
• Filtering DataFrames
• Condition Operators –  AND  / OR 

• Dates and DataFrame
• Date Math & TimeDeltas

Module 6: Python for Data Analysis with NumPy

• Numpy and usage in Data Analysis
• Numpy Arrays
• Numpy Array indexing
• Numpy Operations

Module 7: Python for Data Analysis – Panda

• Panda and usage in Data Analysis
• DataFrames
• Analyse Missing Data
• Merging, Joining and Concatenating raw data
• Operations
• Data Input and Output

Module 8: Data Visualization with Matplotlib 

• Importing data into Matplotlib
• Matplotlib in Visualizing data
• Additional tool for Visualization – Seaborn
• Plotting graphs 
• Enhance the look of Visuals
• Apply, Map & Applymap

Module 9: Working With Text

• The String Datatype Vs. Object Datatype
• Indexing String Series With []
• Text related function

Module 10: Combining Series & DataFrames

• Concatenating Series
• Concatenating Series By Index
• Inner vs. Outer Joins
• Concatenating DataFrames By Index

Module 11: Intro to Seaborn

• Seaborn Scatterplots
• Seaborn Lineplots
• Seaborn Histograms
• Seaboard Categorical Plots

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