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Python for Data Science

Data I/O Using Python

2 Modules
1 Hour


Data import and export are processes that involve transferring data between different systems or formats. Data import is the process of bringing data into a data analysis tool or platform from an external source, such as a database, file, or web service. Data export, on the other hand, involves transferring data from the analysis tool to another destination, such as a file, database, or web service. Data import and export play a critical role in data wrangling because they enable data analysts to access and integrate data from various sources and prepare it for analysis. By importing data into a data analysis tool, analysts can combine data from different sources, perform transformations, and clean the data to remove inconsistencies, errors, and missing values.

In this course, you will:

  • Understand the importance of data import and export in data analysis
  • Recall the different file types that can be used to import and export data
  • Apply data import and export techniques to different file types
  • Assess the appropriateness of various data import and export techniques for specific data analysis tasks

Course Contents

1. Importing Data

  • What is importing data?
  • Why is it important?
  • Importing data from Excel
  • Importing data from CSV
  • Importing data from JSON
  • Importing data from XML
  • Importing data from HTML
  • Knowledge check

2. Exporting Data

  • What is exporting data?
  • Why is it important?
  • Exporting data to JSON
  • Exporting data to XML
  • Exporting data to HTML
  • Exporting data to Excel
  • Exporting data to LaTex
  • Knowledge check