Data Analysis with Python, Pandas and NumPy
Learn data analysis techniques using numpy, pandas, matplotlib, and seaborn. Gain theoretical and practical understanding of data analysis and visualization. Perfect for Python developers and data analysts looking to derive business insights from data.
What you’ll learn
- Student will learn data analysis techniques using numpy, pandas, matplotlib and seaborn.
- This course provides theoretical and practical understanding of the key concept of data analysis and data visualization
- The course provides excellent learning tool for creating strategies and correct business decision from the data at hand.
- Student will learn NumPy and Pandas introduction, Data ingestion, Data Preparation, Data Wrangling and Data Aggregation.
- Student will learn Data Visualization techniques using matplotlib, seaborn & pandas object.
Data Analysis with Python is for everyone who would like to create meaningful insight out of the data with the power of Numpy, Pandas, Matplotlib & Seaborn. The course has the right recipe to equip student with the right set of skill to ingest, clean, merge, manipulate, transform and finally visualize the data to create the meaning out of the data at hand.
The goal of this course is many fold :
– To provide theoretical and practical understanding of data analysis with Python package like NumPy and Pandas.
– To provide the knowledge of visualization tool ( matplotlib and seaborn ) so that one will be able to visualize and make correct decision based on the data.
– And finally practice with real life data to feel confident of the topic and be able to ready to work on data analysis project or interview.
The whole project is divided into following module :
– NumPy introduction
– Pandas introduction (Series and dataframe objects )
– Data ingestion & Storage ( CSV, Excel, SQLite, JSON, HTML, Pickle and HDF5 storage etc. )
– Data Preparation ( Identify missing data, Handle missing data, handling duplicate data, Data transformation, Manipulating Row & Columns, Bucket Analysis, Outlier detection, Sampling, Creating dummy variable etc. )
– Data Wrangling ( Data Aggregation, Merging, Joins – Inner, Outer, Left & Right join, Join, Concatenate, Pivot, Melt etc. )
– Data Aggregation (Split, Apply & Combine, GroupBy clause, Binning data, Pivot table and Cross tabulations etc. )
– Visualization ( MatplotLib, Pandas Object visualization, Seaborn )
– Project – Practice data analysis with real life datasets.
Who this course is for:
- Python developers who aim to learn data ingestion, data analysis and data visualization
- Data analyst who would like to derive business insight out the data.
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