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Coursera Project Network

C++ Data Structures in the STL

Coursera Project Network via Coursera

Overview

In this project you will read weather data from a file and populate a C++ Vector with the file data. The data is then uniquified in a Set data structure and stored in a Map for accessing data by year.

C++'s standard template library or STL contains data structures or containers that are built for efficiency. They are used to store and retrieve data in various formats. A list such as a Vector can be used in place of an array to contain data where the size cannot be determined ahead of time. A List is like a Vector, except elements can be more quickly added and deleted from it, since no shifting needs to occur. A Map is used to quickly look up a value based on a key rather than a numerical index, for example, to look up a phone number based on a key containing a person's name. A Set may be used to remove duplicates from a list, simply by assigning the data to it.

Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Syllabus

  • C++ Data Structures in the STL
    • In this project you will read weather data from a file and populate a C++ Vector with the file data. The data is then uniquified in a Set data structure and stored in a Map for accessing data by year. C++'s standard template library or STL contains data structures or containers that are built for efficiency. They are used to store and retrieve data in various formats. A list such as a Vector can be used in place of an array to contain data where the size cannot be determined ahead of time. A List is like a Vector, except elements can be more quickly added and deleted from it, since no shifting needs to occur. A Map is used to quickly look up a value based on a key rather than a numerical index, for example, to look up a phone number based on a key containing a person's name. A Set may be used to remove duplicates from a list, simply by assigning the data to it.

Taught by

David Dalsveen

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4.5 rating at Coursera based on 33 ratings

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