Python - Manipulating & Analyzing Data in Pandas DataFrames
Python 3
| Intermediate
- 10 Videos | 44m 10s
- Includes Assessment
- Earns a Badge
Explore advanced data manipulation and analysis with Pandas DataFrames, a Python library that shares similarities with relational databases. To take this course, prior basic experience is needed with Pandas DataFrames, data loading, and Jupyter Notebook data manipulation. You will learn to iterate data in your DataFrame. See how to export data to Excel files, JSON (JavaScript Object Notation) files, and CSV (comma separated values) files. Sort the contents of a DataFrame and manage missing data. Group data with a multi-index. Merge disparate data into a single DataFrame through join and concatenate operations. Finally, you will determine when and where to integrate data with structured queries, similar to SQL.
WHAT YOU WILL LEARN
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learn how to iterate over a DataFrame's rows and columnsexport the contents of a DataFrame into files of various formatsdescribe and apply the different techniques involved in handling datasets where some information is missingdescribe and apply the different techniques involved in handling datasets where some information is missingimplement a hierarchical index and access the DataFrame's contents based on that index
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combine two similar DataFrames using the concat operationapply a join operation on two related but dissimilar DataFrames using the merge functionload data into a Pandas DataFrame from a table in a relational databaseuse Pandas for advanced tabular data manipulation
IN THIS COURSE
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1.Course Overview2m 8sUP NEXT
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2.Iterating Over the Contents of a DataFrame3m 24s
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3.Exporting a DataFrame3m 27s
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4.Sorting4m 46s
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5.Handling Missing Data5m 36s
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6.Grouping with a Multi-Index5m 17s
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7.Merging DataFrames3m 24s
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8.Applying Join Operations on DataFrames5m 13s
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9.Pandas and Relational Databases6m 34s
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10.Exercise: Pandas for Advanced Data Manipulation4m 20s
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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