pandas Essential Training (2017)
What I Learned:
In Pandas Essential Training (2017), I learned how to use Python’s pandas library to efficiently manipulate, clean, and analyze data. Key skills I gained include:
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Importing data from various sources like CSV and Excel files.
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Exploring datasets with functions such as
.head(),.info(), and.describe(). -
Cleaning data by handling missing values, renaming columns, and filtering rows.
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Performing operations like grouping, aggregating, merging, and pivoting datasets.
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Creating basic visualizations using pandas’ integration with libraries like Matplotlib.
How It Relates to My Major (MIS):
As a Management Information Systems (MIS) major, understanding data is crucial because businesses rely on accurate analysis for decision-making. Learning pandas helps me:
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Analyze business data efficiently: I can clean and transform raw data to uncover trends.
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Support data-driven decision making: With pandas, I can provide insights that help managers make strategic choices.
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Integrate with other systems: Pandas works well with databases, spreadsheets, and other tools used in business intelligence.
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Prepare for analytics roles: Skills in data manipulation and analysis are directly applicable to roles like business analyst, data analyst, or UX/UI researcher.