Description
The following topics are covered:
- What is Data Science
- How to get (real) stock data , how to plot data in Jupyter
- SQL and MySQL interaction using Pandas
- read csv file and do various operations. Stocks data is considered as example
- write csv file and associated operations
- Handling missing data,
- Data filtering / Wrangling using Pandas
- Group by support in Pandas
- Concat support in Pandas
- Merge of Dataframes
- Pivot Table support in Pandas
- Stack / Unstack support in Pandas
- Reshape with Pandas
- Cross Tab with Pandas
- excel support
- Time series Support for calendar ( Business Days, Holidays)
- Time series Support for resampling, indexing time series dataHands-on / Practical with various datasets like: stock /share data, weather data etc
Who this course is for:
- Beginner Python developers, Data Science students, Students who have some exposure to data analytics
- This course is meant typically for those who want to learn Data Science and who have some exposure to python programming, like freshers..
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