Midterm Flashcards

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1
Q

python language

A
  • Simple
  • Intuitive and Open Source
  • Scripting Language Interpreted
  • Multi-platform
  • Multi-paradigm
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2
Q
A
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3
Q

interpreted language

A
  • no cross-compiling
  • computational costs
  • multi platform
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4
Q

module

A
  • A module is a collection of functions that can be imported in other programs
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5
Q

Strongly typed language

A

the language has strong constraints on the data type

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6
Q

Dynamically typed language

A

the type can be changed

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7
Q

Python interpreter

A
  • An interpreted language at runt-time
  • Code -> python code syntax checker translator -> (input ->) python execution environment (python virtual machine PVM) -> output
  • Will work independently from the platform
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8
Q

random function

A
  • Generate pseudo-random numbers
  • The seed allows the identification of a sequence (every time the function is called it returns the next random value)
  • Two execution with the same seed will return the same sequence
  • It is possible to generate real numbers, random.random() or integer numbers, random.randint(from,to) - (from,to) define the range)
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9
Q

for loop example print 1 to 9

A
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10
Q

information systems

A
  • Collection, Storage, and processing of data
  • Include a computer system for task automation
  • A database management system (DBMS) is a software to support data management.
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11
Q

data modeling

A
  • The process of creating a data model for an information system
  • Necessary to confer to data a structure useful in the context of a specific business process
  • It can have several abstraction layers
  • conceptual (drawing) -> logic (deatils of tables) -> physical (mySQL)
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12
Q

Entity-Relationship model

A
  • The Entity-Relationship model is an abstract model to represent the structure of data for a business process
  • Typically used of relational databases
  • Can represent concepts and relations among them
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13
Q

entities

A

object categories with shared properties

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14
Q

1.

relationships

A

connections among entities.

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15
Q

many-to-many relationship

A
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16
Q

one-to-many relationship

A
17
Q

one-to-one relationship

A
18
Q

attributes

A
  • An entity always has a primary key (black bullet)
  • Surrogate Key
  • Composed Key
  • Foreign Key
19
Q

Logic data Model

A

A logic data model allows the translation of a conceptual models into data structures

20
Q

SQL

A
  • The Structure Query Language is the most used language for querying relational databases
  • Three sub-languages:
    – DDL (Data Definition Language)
    – DML (Data Manipulation Language)
    – DCL (Data Control Language)
21
Q

Query Language: DDL

A
  • Define metadata of structures and objects in a data base
  • Useful in the design phase
  • Create and manipulate a schema
22
Q

MySQL

A
  • An open-source DBMS An open-source DBMS
  • Community Edition is open-source
  • Community Edition is open-source Community Edition in the Ubuntu Repository Community Edition in the Ubuntu Repository
23
Q

MySQL -Workbench

A
  • The Workbench handles connection towards running MySQL Instances
  • Once a connection is activated, it allows the management of the database
  • Once a connection is activated, it allows the management of the database.
24
Q

MySQL -Schema

A
  • A schema is a collection of tables
  • In MySQL schema and database are synonyms
25
Q

Indexing

A
  • An additional data structure designed to get fastest query response times
  • Different type of indexing: BTREE, HASH
26
Q

Binary tree

A

A self-balancing tree data structure (generalization of binary search tree)

In a B-tree of order n: Every node has at most n children. Every internal node except the root has at least n/2 children. Every non-leaf node has at least 2 children. All leaves appear on the same level and carry no information. A non-leaf node with k children contains k−1 keys.

27
Q

Strcutured data

A
  • prefiend schema
28
Q

Unstructured data

A
  • Unstructured data have no referring schema and cannot be queried easily
  • Examples: Text Files, Media data, Emails
29
Q

Semi-structured data

A
  • Semi-structured data impose some form of structure Less constraints
  • Tags can be used to define a partial structure– XML– JSON– CSV
30
Q

Pandas objects

A

Three main data structures:
* Series
* DataFrame
* Index

31
Q

Pandas Series

A
  • Indexes can be customized
  • Element are, then, accessible as in NumPy arrays
  • Can be used as a dictionary mapping typed key to typed values
  • Typing allows for high performance
32
Q

Pandas dataframe

A
  • A DataFrame can be seen as an enhanced twodimensional array
  • Both row indexes and column names are flexible
  • A sequence of Series sharing the same indexes
  • Can be created from loops, arrays
  • Columns of a DataFrame can be accessed in different ways: As Individual Series, As a multi-dimensional array
33
Q

Access rows in indexed data

A
  • Using custom indexes (the one defined by the data structure) –> loc
  • Using native indexes (the implicit ones from underying arrays) –> iloc
  • can also be used defining ranges [from:to]
34
Q
A