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File Processing with Python
Rating: 4.5 out of 5(175 ratings)
26,068 students

File Processing with Python

Work with CSV, Excel and JSON
Created byFrank Anemaet
Last updated 7/2021
English

What you'll learn

  • How to use Python to access data stored in a variety of common formats.
  • How to read and write comma-separated value (CSV) files using both the Python Standard Library and pandas.
  • How to read and write JavaScript Object Notation (JSON) files using the Python Standard Library.
  • How to process JSON data received from an API.

Course content

1 section • 10 lectures • 39m total length

  • Introduction0:10
  • Read CSV5:26
  • Write CSV7:03

    Learn to write csv files in python with the csv module, define headers and data as lists or dictionaries, and use writer or dictionary writer to produce rows.

  • Read CSV with Pandas5:10

    Install and import pandas to read csv files into a data frame, then access rows by index or convert to Python lists with dataframe.values; compare pandas and csfi approaches.

  • Write CSV with Pandas3:26

    Learn to write csv files with pandas by converting data to dictionaries, creating a data frame, and exporting to csv for office programs.

  • Read CSV as dictionary4:46

    Learn to read csv data into Python dictionaries using dict reader and compare it with reading as lists, and customize delimiters for semicolon or other characters.

  • Read Excel2:56
  • Write Excel2:36

    Learn how to write excel files from pendas by installing excel w.t. and open by excel modules, creating a data frame, and using the to excel function to export data.

  • Read and write JSON4:00

    Learn to read and write json in Python by converting data frames to json, and load json across languages as an interchangeable format.

  • Read JSON from URI3:33

    Load json data from a web uri using Python's requests module, receive json responses from APIs, and convert them to Python dictionaries for easy access.

Requirements

  • Basic Python knowledge

Description

Python is a widely used, general-purpose, high-level programming language. Its design philosophy emphasizes code readability, and its syntax allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java. The language provides constructs intended to enable clear programs on both a small and large scale.

This course makes it very easy to read popular file formats with Python. They include comma separated value (csv) files, excel files (xls, xlsx) and json data. If you want to take your Python skills to the next level, you should know how to work with various file formats.

It uses a step-by-step approach to teach these concepts. The course includes source code so you can try it on your own. It uses both the Python standard library as well as the Pandas module. As with many things in programming, there is more than one way to do it.

If you have just learned the basics of Python or OOP, this course is for you. You most likely will work with Excel and other file formats at some point. Especially because these formats are popular not only in office environment but also in web-apps and other type of applications.

Who this course is for:

  • Python developers who want to learn how to access data from a range of file types.

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