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Data science > Lesson 1 , 2 and 3 > Flashcards

Lesson 1 , 2 and 3 Flashcards

1
Q

Two basic categorizations of data is?

A

Organized and Unorganized

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2
Q

Which are the three basic areas of DS?

A

Maths , Computer Programming and Domain Knowledge

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3
Q

Full form of EDA is?

A

Exploratory Data Analysis

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4
Q

Big data is too large to be processed by ?

A

a single machine

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5
Q

Model is a _____ between two elements.

A

relationship

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6
Q

Text , video and audio are types of _____ data.

A

Unorganized

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7
Q

Data in the form of rows and columns is _____ data

A

Organized

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8
Q

Columns depict ____________ of the data.

A

Features/ Characteristics

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9
Q

Skikitlearns ___________ helps convert unstructured to structured.

A

CountVectorizer

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10
Q

Average tweet length is _____

A

30

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11
Q

Qualitative data can be described using numbers and mathematical operations can be performed on it. True or false ?

A

False. It is for quantitative

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12
Q

Average monthly customers. Qualitative or Quantitative?

A

Quantitative

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13
Q

Country of coffee origin? Quali or quanti

A

Quali

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14
Q

Zip code? Quali or Quanti

A

Quali

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15
Q

Quantitative can be further divided into ________ and __________ type.

A

Continuous and Discrete

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16
Q

The four levels of data are ____________?

A

Nominal, Ordinal, interval, ratio

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17
Q

Nominal level is qualitative or quantitative?

A

Qualitative

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18
Q

Measure of center for nominal level is ?

A

Mode

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19
Q

___________ is most common ordinal level scale

A

Likert

20
Q

At ordinal level ______ is the usual measure of center

A

Median

21
Q

________ denotes a long comment (more than a single line)

A

”’

22
Q

The measure that describes how spread out our data is ________

A

Standard deviation

23
Q

Does ratio data level allow multiplication & division?

A

Yes

24
Q

Data at the ratio level is usually ______.
1. non-negative
2. Positive

A

Non-negative

25
Q

Three questions that you should ask before starting the analysis are?

A
  • Is the data organized or unorganized?
  • Is each column quantitative or qualitative?
  • At what level of data is each column?
26
Q

The first step to performing data science is :

A

Asking an interesting question

27
Q

Last step while performing data analysis is:

A
  1. Communicating and visualizing the results
28
Q

How many steps are there while performing data analysis?

A

5

29
Q

State any 3 basic questions you should think of while exploring the data.

A

Organized or not?
What does each row represent?
What does each column represent?
Are there any missing data points?
Do we need to perform any transformations?

30
Q

dataset.shape gives us?

A

number of rows and columns in the dataset

31
Q

date is which type of data ?

A

Ordinal

32
Q

Stars is which type of data?

A

ordinal

33
Q

Which command can be used to check if there are any missing values?

A

df.isnull().sum()

34
Q

The name dataframe is borrowed from which language?

A

R

35
Q

Each column in df is considered to be a _________ object?

A

Series

36
Q

Which 4 stats come up when nominal variables are described?

A

Count, unique, freq , top

37
Q

In the titanic dataset, what type of data is age?

A

Ratio

38
Q

Survived (Yes/No) is which type of data?

A

Nominal

39
Q

When dealing with missing values , which two options do we have?

A

Drop the rows which have missing values , try to fill them in

40
Q

What drawback does dropping rows with empty values have

A

Risk of losing valuable data

41
Q

An object having both magnitude and direction is a ________.

A

Vector

42
Q

A matrix having same number of rows and columns is called a _______ matrix?

A

Square

43
Q

Sigma symbol is an universal symbol for _________

A

Addition

44
Q

When dot product is performed , the answer is a ______________? Scalar / vector

A

Scalar

45
Q

x axis denotes the ______ variable , while y axis denotes the ______ variable.

A

independent , dependent

Data science (3 decks)

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