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

20
Q

At ordinal level ______ is the usual measure of center

21
Q

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

22
Q

The measure that describes how spread out our data is ________

A

Standard deviation

23
Q

Does ratio data level allow multiplication & division?

24
Q

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

A

Non-negative

25
Three questions that you should ask before starting the analysis are?
* Is the data organized or unorganized? * Is each column quantitative or qualitative? * At what level of data is each column?
26
The first step to performing data science is :
Asking an interesting question
27
Last step while performing data analysis is:
5. Communicating and visualizing the results
28
How many steps are there while performing data analysis?
5
29
State any 3 basic questions you should think of while exploring the data.
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
dataset.shape gives us?
number of rows and columns in the dataset
31
date is which type of data ?
Ordinal
32
Stars is which type of data?
ordinal
33
Which command can be used to check if there are any missing values?
df.isnull().sum()
34
The name dataframe is borrowed from which language?
R
35
Each column in df is considered to be a _________ object?
Series
36
Which 4 stats come up when nominal variables are described?
Count, unique, freq , top
37
In the titanic dataset, what type of data is age?
Ratio
38
Survived (Yes/No) is which type of data?
Nominal
39
When dealing with missing values , which two options do we have?
Drop the rows which have missing values , try to fill them in
40
What drawback does dropping rows with empty values have
Risk of losing valuable data
41
An object having both magnitude and direction is a ________.
Vector
42
A matrix having same number of rows and columns is called a _______ matrix?
Square
43
Sigma symbol is an universal symbol for _________
Addition
44
When dot product is performed , the answer is a ______________? Scalar / vector
Scalar
45
x axis denotes the ______ variable , while y axis denotes the ______ variable.
independent , dependent