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Data Analysis with Python libraries – NumPy, Pandas, MatplotLib and Seaborn 150+ MCQ Question 2 Projects
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Data Analysis with Python, Pandas and NumPy
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.
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