COS10022 – INTRODUCTION TO DATA SCIENCE
Dr Pei-Wei Tsai (Lecturer, Unit Convenor)
ptsai@swin.edu.au, EN508d
What Data Can Do for You?
The base for recommendation
applications
Driving peoples’ behaviours
without being noticed
2
Impact Example
Facebook & Cambridge Analytica
Scandal
Behavioural Psychology + Big Data
can change human behaviour
3
Main Character
Strategic Communication
Laboratories (SCL) Group
• Was a private British behavioural
research and strategic
communication company.
• SCL’s subsidiaries: Cambridge
Analytica and Crow Business Solutions
MENA are involved in the FacebookCambridge Analytica data scandal.
4
Elections that SCL Involved
1994 –
South
Africa
2009 –
Trinidad
& Tobago
1998 –
Indonesia
1997 –
Thailand
2004 –
Ukraine
2010 – St.
Kitts &
Nevis
2010 –
India
2012 Italy
2011 Colombia
2013 –
Kenya
2013 –
Malaysia
2015 –
Argentina
2013 –
Antigua
…
5
Prediction
Accuracy Analysis
◦ By simply utilise the comments, forward,
and the click on the like button can reveal a
high accuracy prediction results on some
dichotomous/dichotomized attributes.
6
ESTABLISHING
THE
SUBSIDIARY
Since this is a good business, SCL creates a
subsidiary called “Cambridge Analytica.”
Let’s call it CA for simplification.
7
Goal of CA
CA is a profit-driven company. The goal is specific
and thus the operation can be clearly defined.
What CA does include:
• Aggregating Data.
• Analysing Data.
• Changing Crowd Behaviours.
8
DATA
AGGREGATION
Existing
literature
has
shown
the way.
Facebook
API is
also
ready.
Find the
author to
do the
job.
Find the
colleague of
the author in
the same
university –
Aleksandr
Kogan.
App “This is
your Digital
Life” is up.
9
Security Breach
“This is your digital life” is an upgraded version of the original questionnaire created by the
original authors.
• It has 120 questions, which is not that attractive. But, they offer money (around $2 - $4) for the participant who
completed the questionnaire.
When retrieving the data of the users who completed the questionnaire, they found a security
breach of Facebook resulting that they can also gather data of the users’ friends.
• This means that any of your friend on Facebook filled in the questionnaire, which is totally not related to you, results in
all your data is collected without your permission.
Finding this “exciting” fact, Kogen speeded up the issuing of the questionnaire. In a few
months, he has issued 270,000 questionnaires. As the return, he collected 50,000,000 users’
data. (some reports says 70,000,000 or 80,000,000)
CA confessed that they had collected the data of all people in US who is eligible to vote.
10
Data Analysis
The big data source is
collected. Now CA can move
into the data analysis phase.
With building models to find
relations between attributes,
it is easy to conclude what is
the personality of a user.
11
12
Example Analysis
Outcome
If a user who liked he “Hello Kitty”
brand tended to be high on Openness
and low on “Conscientiousness,”
“Agreeableness,” and “Emotional
Stability.”
They were also more likely to have
Democratic political views and to be of
African-American origin,
predominantly Christian, and slightly
below average age.
13
CSL Proposed
OCEAN
Analysis
◦ OCEAN is a scoring
system with 5
attributes.
Openness
Neuroticism
Conscientiousness
◦ The result can be
used to conclude the
characteristic of a
user.
Agreeableness
Extroversion
14
CROWD
BEHAVIOUR
CHANGING
◦ Since the data
aggregation and
analysis are nailed,
CA start to involve in
the US election and
joined the team of
Trump.
◦ The last work is what
CA most capable of:
affect the election
result by changing
crowd behaviours.
15
How PSYOP Affects
the Election Result?
◦ In 2009-2010, CSL involved in the election in Trinidad
and Tobago.
◦ The population in this country can be roughly divided
into two races (Let’s call them A and B).
◦ Team A is more tradition and the family education is
more strict while team B is a bit loose on family
education.
◦ CSL is involved as the consultant in team A.
◦ After a series of analysis, they decide to focus on the
youth people.
◦ The corresponding strategy is proposing an activity
called “Do So.”
16
2016 US ELECTION
17
Involved?
Cambridge
Analytica
US
Election
Brexit
18
COS10022 – INTRODUCTION TO DATA SCIENCE
Dr Pei-Wei Tsai (Lecturer, Unit Convenor)
ptsai@swin.edu.au, EN508d
LOGISTIC REGRESSION
3
𝑃𝐶
𝑃𝐴
𝑃𝐵
𝑃𝐴 + 𝑃𝐵 + 𝑃𝐶 = 1
𝑃𝐶 = 1 − 𝑃𝐴 − 𝑃𝐵
4
𝑃𝐶
𝑃𝐴
𝑃𝐵
𝑃𝐶 = 1 − 𝑃𝐴 − 𝑃𝐵
5
LOGISTIC
REGRESSION
EXAMPLE
6
LINEAR REGRESSION PRACTICE
Problem 1
Consider the following set of points:
{(-2, -1), (1, 1), (3, 2)}
Find the least square regression line for the given
data points.
Plot the given points and the regression line in the
same rectangular system of axes.
8
https://www.analyzemath.com/statistics/linear_regression.html
Solution for Problem 1
◦ Organising the data in a table:
𝒙
𝒚
𝒙∙𝒚
𝒙𝟐
−2
−1
2
4
1
1
1
1
3
2
6
9
෍𝑥 = 2
෍𝑦 = 2
෍ 𝑥𝑦 = 9
෍ 𝑥 2 = 14
9
Solution for Problem 1
◦ Calculate the coefficients for the regression line: 𝑦 = 𝑎 ∙ 𝑥 + 𝑏
𝑛 σ 𝑥𝑦 − σ 𝑥 σ 𝑦
3×9−2×2
23
𝑎=
=
=
≈ 0.61
𝑛 σ 𝑥2 − σ 𝑥 2
3 × 14 − 22
38
σ𝑦 − 𝑎 ∙ σ𝑥
2 − 0.61 × 2
0.78
𝑏=
=
=
= 0.26
𝑛
3
3
10
Problem 2
Consider the following set of points:
{(-1, 0), (0, 2), (1, 4), (2, 5)}
Find the least square regression line for the given
data points.
Plot the given points and the regression line in the
same rectangular system of axes.
11
Solution for Problem 2
◦ Organising the data in a table:
𝒙
𝒚
𝒙∙𝒚
𝒙𝟐
−1
0
0
1
0
2
0
0
1
4
4
1
2
5
10
4
෍𝑥 = 2
෍ 𝑦 = 11
෍ 𝑥𝑦 = 14
෍ 𝑥2 = 6
12
Solution for Problem 2
◦ Calculate the coefficients for the regression line: 𝑦 = 𝑎 ∙ 𝑥 + 𝑏
𝑛 σ 𝑥𝑦 − σ 𝑥 σ 𝑦
4 × 14 − 2 × 11
17
𝑎=
=
=
= 1.7
𝑛 σ 𝑥2 − σ 𝑥 2
4 × 6 − 22
10
σ𝑦 − 𝑎 ∙ σ𝑥
11 − 1.7 × 2
7.6
𝑏=
=
=
= 1.9
𝑛
4
4
13
Question
◦ If you have the regression formula for input
𝑥 to predict 𝑦, can you use it in the other way
around?
14
ANSWER
TO THE
QUESTION
Nope. You can’t reverse the input
and output directly except
recalculate a new regression line.
15
COS10022 – INTRODUCTION TO DATA SCIENCE
Dr Pei-Wei Tsai (Lecturer, Unit Convenor)
ptsai@swin.edu.au, EN508d
UNIT SURVEY IS DUE ON 28/03
2
K-MEANS AND DBSCAN
DATASET
4
Parameters
𝒌-means
DBSCAN
𝒌=𝟑
𝛆=𝟐
𝐦𝐢𝐧𝐏𝐭𝐬 = 𝟑
5
INPUT
DATASET
6
Centroids
K-MEANS RESULT
7
DBSCAN
RESULT
8
Comparison between
k-means and DBSCAN
k-means
DBSCAN
k-means has centroids for every cluster.
DBSCAN has no centroids.
k-means has no outliers even if the data
point is far away from others.
DBSCAN produces outliers under certain
criteria.
k-means has no limitation on how many
data points can be in a single cluster.
DBSCAN has the lower limit for forming a
cluster.
9
Online Resources
Visualising k-means clustering
• https://www.naftaliharris.com/blog/visualizingk-means-clustering/
Visualising DBSCAN clustering
• https://www.naftaliharris.com/blog/visualizingdbscan-clustering/
10
COS10022 – INTRODUCTION TO DATA SCIENCE
Dr Pei-Wei Tsai (Lecturer, Unit Convenor)
ptsai@swin.edu.au, EN508d
BAYES’ THEOREM
Bayes’ Theorem
◦ If you know the probability of A happens conditional on B happens, the probabilities of A happens, and B
happens, independently, you can derive the probability of B happens conditional on A happens.
𝑃 𝐵 𝐴 : Conditional
Probability of B given A
Bayes’ Theorem 𝑃 𝐴 𝐵 =
𝑃 𝐴 : Probability of event A
𝑃 𝐵𝐴 𝑃 𝐴
𝑃 𝐵
𝑃 𝐴 𝐵 : Conditional
Probability of A given B
𝑃 𝐵 : Probability of event B
𝑃 𝐵𝐴 =
𝑃 𝐴𝐵 𝑃 𝐵
𝑃 𝐴
3
Why Using Bayes’ Theorem?
Cost of Data Collection.
Timeless.
4
Exercise 1
◦ If we want to find out a patient’s probability of having liver disease if he or she is an
alcoholic.
◦ A could mean the event “patient has liver disease.”
◦ Past data tells you that 10% of patients entering your clinic have liver disease. → 𝑷 𝑨 = 𝟎. 𝟏
◦ B could mean the litmus test that “patient is an alcoholic.”
◦ Past data tells you that 5% of patients are alcoholics. → 𝑷 𝑩 = 𝟎. 𝟎𝟓
◦ You might also know that among those patients diagnosed with liver disease, 7% are
alcoholics.
◦ The probability that a patient is alcoholic given that he/she has liver disease is 7%.
→ 𝑷 𝑩ȁ𝑨 = 𝟎. 𝟎𝟕
◦ Bayes’ Theorem tells you that 𝑷 𝑨ȁ𝑩 =
𝟎.𝟎𝟕×𝟎.𝟏
𝟎.𝟎𝟓
= 𝟎. 𝟏𝟒
◦ Thus, if the patient is an alcoholic, the chance of the patient having liver disease is 14%.
5
MODEL EVALUATION
Supervised Models: Metrics and Methods
Popular metrics for evaluating the performance of supervised models:
1. Accuracy
2. True Positive Rate (TPR) – also called Sensitivity or Recall.
3. True Negative Rate (TNR) – also called Specificity or Selectivity.
4. False Positive Rate (FPR) – also called Fall-out.
5. False Negative Rate (FNR) – also called Missing rate.
6. Precision:
𝐓𝐫𝐮𝐞 𝐩𝐨𝐬𝐢𝐭𝐢𝐯𝐞
𝐏𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐯𝐞 𝐂𝐨𝐧𝐝𝐢𝐭𝐢𝐨𝐧 𝐏𝐨𝐬𝐢𝐭𝐢𝐯𝐞
7. Area Under the Curve (AUC) – also called the plasma concentrationtime profile.
These metrics can be calculated by utilising a confusion matrix.
7
https://en.wikipedia.org/wiki/Sensitivity_and_specificity
Supervised Models: Metrics and Methods
True Positives
(TP):
the number of positive instances that a classifier
correctly classifies as positive.
False Positives
(FP):
the number of instances that a classifier identified as
positive but in reality, are negative.
True Negatives
(TN):
the number of negative instances that a classifier
correctly identifies as negative.
False Negatives
(FN):
the number of instances classified as negative but in
reality, are positive.
TP and TN are correct predictions. A good classifier should have large TP and TN,
and small (ideally, zero) numbers of FP and FN.
8
Supervised Models: Metrics and Methods
Example 1. A confusion matrix of Naïve Bayes classifier for 100
customers in predicting whether they would subscribe to the term
deposit.
Predicted Class
Subscribed
Actual
Class
Total
Not Subscribed
Total
Subscribed
3 (correct prediction)
8 (wrong prediction)
11
Not Subscribed
2 (wrong prediction)
87 (correct prediction)
89
5
95
100
9
QUESTION
Which type of error is more
important?
10
COVID-19 CRP Test
◦ Even in different stage, the important index is also different.
Contain and
Control Phase
Missing rate (Type II error) is more
important.
FNR should be as low as possible.
Herd Immunity
(Community
Immunity) Phase
FPR (Type I error) is more important.
Low FPR reduces the waste of resources.
11
COS10022 – INTRODUCTION TO DATA SCIENCE
Dr Pei-Wei Tsai (Lecturer, Unit Convenor)
ptsai@swin.edu.au, EN508d
DECISION MAKING
PRACTICAL PROBLEM
– USING DECISION TREE
Background
◦ Alpha cookware Ltd. is a company producing multiple cookware.
◦ The managers are now considering the addition of a new cookware to the company’s existing production
line.
◦ To test this concept, they will perform a 1-month trial.
◦ Three alternative courses of action are available for them:
a)
b)
c)
Work overtime to meet the demand of the new cookware. The overtime expenses are estimated at AUD 20,000 per
month.
Install a new equipment for which fixed expenses per month are expected at AUD 80,000.
Rent a machine at the rate of AUD 35,000 per month.
◦ Variable cost associated with the above three alternatives are AUD 9, 7, and 8 per cookware,
respectively.
◦ The price per unit of the cookware, which is independent of the manufacturing alternative, is fixed at AUD
15.
3
Background (2)
Expected Demand
60000
50000
◦ The expected demand for the new cookware is as
given below:
40000
30000
a)
10,000 pieces with a probability of 0.5.
b)
20, 000 pieces with a probability of 0.3.
c)
50,000 pieces with a probability of 0.2.
◦ Which alternative should the company adopt to
manufacture the cookware?
20000
10000
0
0
0.1
0.2
0.3
0.4
0.5
0.6
Probability
4
APPLY DECISION TREE
AS THE SOLVER
Demand
Concept
Profit
10,000
Node 2
20,000
50,000
10,000
Node 1
New
Equipment
Node 3
20,000
50,000
10,000
Node 4
20,000
50,000
6
Profit = 𝐵 − 𝐶 × 𝐷 − 𝐴
= 15 − 9 × 10,000 − 20,000
= 40,000
Calculation
Alternative
Fixed Cost
(A)
Selling
Price (B)
Production
Cost (C)
Monthly Demand (D)
10,000
20,000
50,000
Overtime
20,000
15
9
40,000
100,000
280,000
New Eq.
80,000
15
7
0
80,000
320,000
Rent
35,000
15
8
35,000
105,000
315,000
Profit = 𝐵 − 𝐶 × 𝐷 − 𝐴
Profit = 𝐵 − 𝐶 × 𝐷 − 𝐴
= 15 − 8 × 20,000 − 35,000
= 105,000
7
Demand
Concept
Node 2
10,000
(0.5)
40,000
20,000
(0.3)
100,000
50,000
(0.2)
10,000
(0.5)
Node 1
New
Equipment
Node 3
20,000
(0.3)
50,000
(0.2)
10,000
(0.5)
Node 4
Profit
280,000
0
80,000
𝐸𝑁𝑜𝑑𝑒 2 = 0.5 × 40,000
+0.3 × 100,000
+0.2 × 280,000
= 106,000
𝐸𝑁𝑜𝑑𝑒 3 = 0.5 × 0
+0.3 × 800,000
+0.2 × 320,000
= 88,000
320,000
35,000
20,000
(0.3)
105,000
50,000
(0.2)
315,000
Probability
𝐸 = ෍ 𝑃𝑟𝑜𝑏 × 𝑃𝑟𝑜𝑓𝑖𝑡
𝐸𝑁𝑜𝑑𝑒 4 = 0.5 × 35,000
+0.3 × 105,000
+0.2 × 315,000
= 112,000
8
DECISION TREE
FOR CLASSIFICATION
Why there is a negative
operator in the entropy
calculation?
Entropy:
Η 𝑝 = − σ𝑛𝑖=1 𝑝𝑖 log 2 𝑝𝑖
for 𝑝 ∈ ℚ𝑛
where Η (Greek capital letter eta) defines the entropy, 𝑝𝑖
indicates the probability mass function, and 𝑛 is the number
of output states.
10
COS10022 – INTRODUCTION TO DATA SCIENCE
Dr Pei-Wei Tsai (Lecturer, Unit Convenor)
ptsai@swin.edu.au, EN508d
ASSOCIATION RULE
APPLICATIONS
ASSOCIATION
RULE
EXAMPLE
https://www.researchgate.net/figure/Association-Rules-Network-with-z-BAGEL_fig5_220183340/download
3
This Photo by Unknown Author is licensed under CC BY
APPLICATION 1
Market basket analysis.
4
Application
2
◦ Medical diagnosis
◦ Assisting
physicians to cure
patients.
5
APPLICATION 3
Determining the protein
sequences
6
CASE 4
Census data processing
7
CASE 5
Customer Relationship
Management (CRM) of credit
card business
8
CASE 6
Recommendation Systems
9
ASSOCIATION RULE
MINING EXAMPLE IN
TITANIC DATASET
ANOTHER
CODE-FREE
SOLUTION FOR
ASSOCIATION
RULES
https://youtu.be/aslTl6i-hpQ
11
COS10022 – INTRODUCTION TO DATA SCIENCE
Dr Pei-Wei Tsai (Lecturer, Unit Convenor)
ptsai@swin.edu.au, EN508d
DATA SCIENCE LIFE CYCLE
Data Analytics Lifecycle
Do I have enough
information to draft
an analytic plan?
1
Discovery
6
2
Operationalise
5
Data Prep
3
Communicate
Results
Is the model robust
enough? Have we
failed enough?
4
Model Building
Model
Planning
Do I have
enough
“good” data
to start
building the
model?
Do I have a good idea about
the type of model to try? Can
I refine the analytic plan?
3
https://mkhernandez.wordpress.com/2018/12/01/data-analytics-lifecycle/
Phase 1: Discovery
What is the problem that needs to be solved?
What form should the solution take?
What results would constitute “success”?
What relevant data is available to be used for testing and what data sources would be available for real-time
deployment?
Do you have a robust data acquisition process?
If you do not have enough available data to train your model, would data extraction tools and open source
databases prove useful in acquiring new data?
4
Phase 2: Data Preparation
You data must be preprocessed and conditioned before testing your
hypotheses.
Your data can be conditioned, surveyed, and visualised to pinpoint and
potentially remove anomalies, leaving you with relevant and clean data.
Data cleaning and refining tools can be built into your central database,
which would ensure that issues such as record duplication are corrected
automatically before they can adversely affect your own data preparation.
5
Phase 3: Model Planning
Choose the methodology best suite to your requirements.
Exploratory data analytics (EDA) in the form of visualisation tools
and statistical formulas help you unlock your data, identifying main
characteristics of your data, manipulate your sources to reveal the
correct information, and test your hypotheses and proposed
techniques.
6
Phase 4: Model Building
Determine the training data sets you will use to test your proposed
model.
Build a baseline model that has proved successful in similar
situations and then tailor it to suit the specifics of your problem.
Better start with a simpler model and add complexities with each
revision.
7
Phase 5: Communicate Results
The test results of your project can now be communicated to those
involved (the stakeholders).
If your process needs to be refined to improve the quality of your
result, you can begin again at phase 1 with a more specific problem
to solve.
With each refinement, your model gets closer to being ready for
deployment in a real-time environment.
8
Phase 6: Operationalise
Run your chosen model and deploy it.
Starting from the trial and then moving into the full scale test. This
will reveal any unforeseen constraints that will need to be accounted
for before your model can be fully put to use.
Deliver the final reports on your model performance findings.
9
ONLINE TEST 2
Online Test 2
Hosted in week 9 lab sessions.
Open-book test.
Tools can be used for calculation, if any.
20 questions to answer in 60 minutes.
Covering from week 5 to week 8 contents.
11
COS10022 – INTRODUCTION TO DATA SCIENCE
Dr Pei-Wei Tsai (Lecturer, Unit Convenor)
ptsai@swin.edu.au, EN508d
DATA PREPARATION
Data Analytics Lifecycle
Do I have enough
information to draft
an analytic plan?
1
Discovery
6
2
Operationalise
5
Data Prep
3
Communicate
Results
Is the model robust
enough? Have we
failed enough?
4
Model Building
Model
Planning
Do I have
enough
“good” data
to start
building the
model?
Do I have a good idea about
the type of model to try? Can
I refine the analytic plan?
3
https://mkhernandez.wordpress.com/2018/12/01/data-analytics-lifecycle/
Phase 2: Data Preparation
You data must be preprocessed and conditioned before testing your
hypotheses.
Your data can be conditioned, surveyed, and visualised to pinpoint and
potentially remove anomalies, leaving you with relevant and clean data.
Data cleaning and refining tools can be built into your central database,
which would ensure that issues such as record duplication are corrected
automatically before they can adversely affect your own data preparation.
4
Missing Value vs Incorrect Value
S/N Temperature
Missing
Value
Incorrect
Value
211
22.5
212
24.3
213
23.2
214
0.0
215
21.7
216
22:4
217
23.3
5
Missing Value vs Incorrect Value
S/N Temperature
211
22.5
212
24.3
213
23.2
214
0.0
215
21.7
216
22:4
217
23.3
S/N Temperature
Sol 1:
22.5
Fix with reasonable treatment. 211
212
24.3
Sol 2:
Remove the tuple.
S/N Temperature
213
23.2
211
22.5
214
0.0
212
24.3
215
21.7
213
23.2
216
22.4
214
0.0
217
23.3
215
21.7
217
23.3
6
Missing Value vs Incorrect Value
S/N Temperature
211
22.5
212
24.3
213
23.2
214
0.0
215
21.7
216
22.4
217
23.3
Sol 1:
Patch with the mean.
22.5 + 24.3 + 23.2
ൗ6
+21.7 + 22.4 + 23.3
= 22.9
22.5 + 24.3 + 23.2
ൗ5
+21.7 + 23.3
= 23
Sol 2:
Remove the tuple.
S/N Temperature
211
22.5
212
24.3
213
23.2
214
23
215
21.7
216
22.4
217
23.3
S/N Temperature
211
22.5
212
24.3
213
23.2
215
21.7
216
22.4
217
23.3
7
Noisy Data
◦ Too many details may
not be a good thing to
your analysis.
8
Data Integration Example
9
ASSIGNMENT 2
Description
Update
11
ONLINE TEST 2
Online Test 2
Hosted in week 9 lab sessions.
Open-book test.
Tools can be used for calculation, if any.
20 questions to answer in 60 minutes.
Covering from week 5 to week 8 contents.
13
COS10022 – INTRODUCTION TO DATA SCIENCE
Dr Pei-Wei Tsai (Lecturer, Unit Convenor)
ptsai@swin.edu.au, EN508d
ASSIGNMENT 2 EXAMPLE
Input Data
Airline ID
Name
Alias
IATA
ICAO
-2 President Airlines
null
TO
PSD
25 Aviation Management Corporation
\N
Callsign
Country
Active
Cambodia
N
AAM
AM CORP
United States (USA)
N
324 All Nippon Airways
ANA All Nippon Airways
NH
ANA
ALL NIPPON
Japan
Y
576 Air-Asia
Air-Asia
AK
AXM
ASIAN EXPRESS
Malaysia
Y
641 Rossiya-Russian Airlines
Pulkovo Aviation Enterprise
FV
SDM
PULKOVO
Russia[[
Y
1437 mib
bmi British Midland
BD
BMA
MIDLAND
UNited Kingdom
Y
1531 Brussels Airlines
SN Brussels Airlines
SN
DAT
BEE-LINE
Belgium
Y
1879 Contact Air
Contactair
C3
KIS
CONTACTAIR
Germany
Y
8J
JFU
ARGAN
Morocco
Y
XW
SXR
SKYSTORM
Russia
Y
Y0
\N
United States
N
??
***
Namibia
N
BQ
BQB
Uruguay
Y
2D
\N
Belgium
N
КТК
Russia
Y
PKV
Russia
Y
3027 Jet4You
5584 Sky Express
SkyExpress
5640 Yellow Air Taxi
13389 South West Africa Territory Force
SWATF
13732 Buquebus LÃneas Aéreas
16616 Alaniya Airlines
Е
ланиѕ
18860 Катѕ
кавиа
18863 Пѕ
ковавиа
Пѕ
ков Е
виа
3
Output Data
C_Airline ID
C_Name
C_Alias
C_IATA
C_ICAO C_Callsign
C_Country
C_Active
null
TO
PSD
Unknown
Cambodia
N
Unknown
Unknown AAM
AM CORP
United States (USA)
N
324All Nippon Airways
ANA All Nippon Airways
NH
ANA
ALL NIPPON
Japan
Y
576Air-Asia
Air-Asia
AK
AXM
ASIAN EXPRESS
Malaysia
Y
641Rossiya-Russian Airlines
Pulkovo Aviation Enterprise
FV
SDM
PULKOVO
Russia[[
Y
1437mib
bmi British Midland
BD
BMA
MIDLAND
UNited Kingdom
Y
1531Brussels Airlines
SN Brussels Airlines
SN
DAT
BEE-LINE
Belgium
Y
1879Contact Air
Contactair
C3
KIS
CONTACTAIR
Germany
Y
3027Jet4You
Unknown
8J
JFU
ARGAN
Morocco
Y
5584Sky Express
SkyExpress
XW
SXR
SKYSTORM
Russia
Y
Unknown
BQ
BQB
Unknown
Uruguay
Y
0President Airlines
25Aviation Management Corporation
13732Buquebus LÃneas Aéreas
4
Key Concept
Unless you are in charge of the whole data science
project, otherwise, the requirements should come from
other engineers that work on the cleaned dataset.
Communicate with the team to clear doubts.
5
Instruction 1
Airline ID
Name
Alias
IATA
ICAO
-2 President Airlines
null
TO
PSD
25 Aviation Management Corporation
\N
Callsign
Country
Active
Cambodia
N
AAM
AM CORP
United States (USA)
N
324All Nippon Airways
ANA All Nippon Airways
NH
ANA
ALL NIPPON
Japan
Y
576Air-Asia
Air-Asia
AK
AXM
ASIAN EXPRESS
Malaysia
Y
641Rossiya-Russian Airlines
Pulkovo Aviation Enterprise
FV
SDM
PULKOVO
Russia[[
Y
1437 mib
bmi British Midland
BD
BMA
MIDLAND
UNited Kingdom
Y
1531 Brussels Airlines
SN Brussels Airlines
SN
DAT
BEE-LINE
Belgium
Y
1879 Contact Air
Contactair
C3
KIS
CONTACTAIR
Germany
Y
8J
JFU
ARGAN
Morocco
Y
XW
SXR
SKYSTORM
Russia
Y
Y0
\N
United States
N
??
***
Namibia
N
BQ
BQB
Uruguay
Y
2D
\N
Belgium
N
КТК
Russia
Y
PKV
Russia
Y
3027 Jet4You
5584 Sky Express
SkyExpress
5640 Yellow Air Taxi
13389 South West Africa Territory Force
SWATF
13732 Buquebus LÃneas Aéreas
16616 Alaniya Airlines
Е
ланиѕ
18860 Катѕ
кавиа
18863 Пѕ
ковавиа
Пѕ
ков Е
виа
6
Instruction 1
Airline ID Name
-2 President Airlines
25 Aviation Management Corporation
324 All Nippon Airways
576 Air-Asia
641 Rossiya-Russian Airlines
1437 mib
1531 Brussels Airlines
1879 Contact Air
3027 Jet4You
5584 Sky Express
5640 Yellow Air Taxi
13389 South West Africa Territory Force
13732 Buquebus LÃneas Aéreas
16616 Alaniya Airlines
18860 Катѕ
кавиа
18863 Пѕ
ковавиа
Alias
null
\N
ANA All Nippon Airways
Air-Asia
Pulkovo Aviation Enterprise
bmi British Midland
SN Brussels Airlines
Contactair
SkyExpress
SWATF
Е
ланиѕ
Пѕ
ков Е
виа
IATA ICAO
TO PSD
AAM
NH ANA
AK AXM
FV SDM
BD BMA
SN DAT
C3 KIS
8J
JFU
XW SXR
Y0 \N
??
***
BQ BQB
2D \N
КТК
PKV
Callsign
Country
Cambodia
AM CORP
United States (USA)
ALL NIPPON
Japan
ASIAN EXPRESS Malaysia
PULKOVO
Russia[[
MIDLAND
UNited Kingdom
BEE-LINE
Belgium
CONTACTAIR
Germany
ARGAN
Morocco
SKYSTORM
Russia
United States
Namibia
Uruguay
Belgium
Russia
Russia
Active C_Airline ID
N
0
N
25
Y
324
Y
576
Y
641
Y
1437
Y
1531
Y
1879
Y
3027
Y
5584
N
5640
N
13389
Y
13732
N
16616
Y
18860
Y
18863
7
Instruction 2
Airline ID Name
-2 President Airlines
25 Aviation Management Corporation
324 All Nippon Airways
576 Air-Asia
641 Rossiya-Russian Airlines
1437 mib
1531 Brussels Airlines
1879 Contact Air
3027 Jet4You
5584 Sky Express
5640 Yellow Air Taxi
13389 South West Africa Territory Force
13732 Buquebus LÃneas Aéreas
16616 Alaniya Airlines
18860 Катѕ
кавиа
18863 Пѕ
ковавиа
Alias
null
\N
ANA All Nippon Airways
Air-Asia
Pulkovo Aviation Enterprise
bmi British Midland
SN Brussels Airlines
Contactair
SkyExpress
SWATF
Е
ланиѕ
Пѕ
ков Е
виа
IATA ICAO
TO PSD
AAM
NH ANA
AK AXM
FV SDM
BD BMA
SN DAT
C3 KIS
8J
JFU
XW SXR
Y0 \N
??
***
BQ BQB
2D \N
КТК
PKV
Callsign
Country
Cambodia
AM CORP
United States (USA)
ALL NIPPON
Japan
ASIAN EXPRESS Malaysia
PULKOVO
Russia[[
MIDLAND
UNited Kingdom
BEE-LINE
Belgium
CONTACTAIR
Germany
ARGAN
Morocco
SKYSTORM
Russia
United States
Namibia
Uruguay
Belgium
Russia
Russia
Active C_Airline ID
N
0
N
25
Y
324
Y
576
Y
641
Y
1437
Y
1531
Y
1879
Y
3027
Y
5584
N
5640
N
13389
Y
13732
N
16616
Y
18860
Y
18863
8
Instruction 2
Airline
ID
Name
-2 President Airlines
Aviation Management
25 Corporation
324 All Nippon Airways
Alias
null
576 Air-Asia
Air-Asia
Pulkovo Aviation
Enterprise
bmi British Midland
SN Brussels Airlines
Contactair
641 Rossiya-Russian Airlines
1437 mib
1531 Brussels Airlines
1879 Contact Air
3027 Jet4You
5584 Sky Express
5640 Yellow Air Taxi
South West Africa Territory
13389 Force
13732 Buquebus LÃneas Aéreas
16616 Alaniya Airlines
18860 КатÑ?кавиа
18863 ПÑ?ковавиа
IAT
A
ICAO
TO PSD
AK
AXM
Country
Cambodia
United States
AM CORP
(USA)
ALL NIPPON Japan
ASIAN
EXPRESS
Malaysia
FV
BD
SN
C3
8J
XW
Y0
SDM
BMA
DAT
KIS
JFU
SXR
\N
PULKOVO
Russia[[
MIDLAND
UNited Kingdom
BEE-LINE
Belgium
CONTACTAIR Germany
ARGAN
Morocco
SKYSTORM Russia
United States
\N
AAM
ANA All Nippon Airways NH ANA
SkyExpress
SWATF
Ð?ланиÑ?
ПÑ?ков Ð?виа
?? ***
BQ BQB
2D \N
КТÐ
š
PKV
Callsign
Activ C_Airline
e
ID
C_Name
N
0 President Airlines
Aviation Management
N
25 Corporation
Y
324 All Nippon Airways
Y
Y
Y
Y
Y
Y
Y
N
576 Air-Asia
Namibia
Uruguay
Belgium
N
Y
N
641 Rossiya-Russian Airlines
1437 mib
1531 Brussels Airlines
1879 Contact Air
3027 Jet4You
5584 Sky Express
5640 Yellow Air Taxi
South West Africa Territory
13389 Force
13732 Buquebus LÃneas Aéreas
16616 Alaniya Airlines
Russia
Russia
Y
Y
18860 00000_pending_remove
18863 00000_pending_remove
9
Instruction 3
Airline
ID
Name
-2 President Airlines
Aviation Management
25 Corporation
324 All Nippon Airways
Alias
null
576 Air-Asia
Air-Asia
Pulkovo Aviation
Enterprise
bmi British Midland
SN Brussels Airlines
Contactair
641 Rossiya-Russian Airlines
1437 mib
1531 Brussels Airlines
1879 Contact Air
3027 Jet4You
5584 Sky Express
5640 Yellow Air Taxi
South West Africa Territory
13389 Force
13732 Buquebus LÃneas Aéreas
16616 Alaniya Airlines
18860 КатÑ?кавиа
18863 ПÑ?ковавиа
IAT
A
ICAO
TO PSD
AK
AXM
Country
Cambodia
United States
AM CORP
(USA)
ALL NIPPON Japan
ASIAN
EXPRESS
Malaysia
FV
BD
SN
C3
8J
XW
Y0
SDM
BMA
DAT
KIS
JFU
SXR
\N
PULKOVO
Russia[[
MIDLAND
UNited Kingdom
BEE-LINE
Belgium
CONTACTAIR Germany
ARGAN
Morocco
SKYSTORM Russia
United States
\N
AAM
ANA All Nippon Airways NH ANA
SkyExpress
SWATF
Ð?ланиÑ?
ПÑ?ков Ð?виа
?? ***
BQ BQB
2D \N
КТÐ
š
PKV
Callsign
Activ C_Airline
e
ID
C_Name
N
0 President Airlines
Aviation Management
N
25 Corporation
Y
324 All Nippon Airways
Y
Y
Y
Y
Y
Y
Y
N
576 Air-Asia
Namibia
Uruguay
Belgium
N
Y
N
641 Rossiya-Russian Airlines
1437 mib
1531 Brussels Airlines
1879 Contact Air
3027 Jet4You
5584 Sky Express
5640 Yellow Air Taxi
South West Africa Territory
13389 Force
13732 Buquebus LÃneas Aéreas
16616 Alaniya Airlines
Russia
Russia
Y
Y
18860 00000_pending_remove
18863 00000_pending_remove
10
Instruction 3
Airline
ID
IAT
A
ICAO Callsign
TO PSD
Name
-2 President Airlines
Aviation Management
25 Corporation
324 All Nippon Airways
Alias
null
576 Air-Asia
Air-Asia
Pulkovo Aviation
Enterprise
bmi British Midland
SN Brussels Airlines
AK AXM
Contactair
C3
8J
XW
Y0
641 Rossiya-Russian Airlines
1437 mib
1531 Brussels Airlines
1879 Contact Air
3027 Jet4You
5584 Sky Express
5640 Yellow Air Taxi
South West Africa Territory
13389 Force
13732 Buquebus LÃneas Aéreas
16616 Alaniya Airlines
18860 КатÑ?кавиа
18863 ПÑ?ковавиа
\N
AAM
ANA All Nippon Airways NH ANA
SkyExpress
SWATF
FV SDM
BD BMA
SN DAT
KIS
JFU
SXR
\N
?? ***
BQ BQB
Ð?ланиÑ?
2D \N
КТÐ
š
ПÑ?ков Ð?виа
PKV
Country
Cambodia
United States
AM CORP
(USA)
ALL NIPPON Japan
ASIAN
EXPRESS
Malaysia
PULKOVO
MIDLAND
BEE-LINE
CONTACTAI
R
ARGAN
SKYSTORM
Activ C_Airline
e
ID
C_Name
N
0 President Airlines
Aviation Management
N
25 Corporation
Y
324 All Nippon Airways
Y
Russia[[
Y
UNited Kingdom Y
Belgium
Y
Germany
Morocco
Russia
United States
Y
Y
Y
N
Namibia
Uruguay
Belgium
Russia
Russia
576 Air-Asia
641 Rossiya-Russian Airlines
1437 mib
1531 Brussels Airlines
C_Alias
null
Unknown
ANA All Nippon Airways
Air-Asia
Pulkovo Aviation
Enterprise
bmi British Midland
SN Brussels Airlines
Contactair
Unknown
SkyExpress
Unknown
N
Y
N
1879 Contact Air
3027 Jet4You
5584 Sky Express
5640 Yellow Air Taxi
South West Africa Territory
13389 Force
13732 Buquebus LÃneas Aéreas
16616 Alaniya Airlines
Y
Y
18860 00000_pending_remove
18863 00000_pending_remove
Unknown
00000_pending_remove
SWATF
Unknown
00000_pending_remove
11
Instruction 4
Airline
ID
IAT
A
ICAO Callsign
TO PSD
Name
-2 President Airlines
Aviation Management
25 Corporation
324 All Nippon Airways
Alias
null
576 Air-Asia
Air-Asia
Pulkovo Aviation
Enterprise
bmi British Midland
SN Brussels Airlines
AK AXM
Contactair
C3
8J
XW
Y0
641 Rossiya-Russian Airlines
1437 mib
1531 Brussels Airlines
1879 Contact Air
3027 Jet4You
5584 Sky Express
5640 Yellow Air Taxi
South West Africa Territory
13389 Force
13732 Buquebus LÃneas Aéreas
16616 Alaniya Airlines
18860 КатÑ?кавиа
18863 ПÑ?ковавиа
\N
AAM
ANA All Nippon Airways NH ANA
SkyExpress
SWATF
FV SDM
BD BMA
SN DAT
KIS
JFU
SXR
\N
?? ***
BQ BQB
Ð?ланиÑ?
2D \N
КТÐ
š
ПÑ?ков Ð?виа
PKV
Country
Cambodia
United States
AM CORP
(USA)
ALL NIPPON Japan
ASIAN
EXPRESS
Malaysia
PULKOVO
MIDLAND
BEE-LINE
CONTACTAI
R
ARGAN
SKYSTORM
Activ C_Airline
e
ID
C_Name
N
0 President Airlines
Aviation Management
N
25 Corporation
Y
324 All Nippon Airways
Y
Russia[[
Y
UNited Kingdom Y
Belgium
Y
Germany
Morocco
Russia
United States
Y
Y
Y
N
Namibia
Uruguay
Belgium
Russia
Russia
576 Air-Asia
641 Rossiya-Russian Airlines
1437 mib
1531 Brussels Airlines
C_Alias
null
Unknown
ANA All Nippon Airways
Air-Asia
Pulkovo Aviation
Enterprise
bmi British Midland
SN Brussels Airlines
Contactair
Unknown
SkyExpress
Unknown
N
Y
N
1879 Contact Air
3027 Jet4You
5584 Sky Express
5640 Yellow Air Taxi
South West Africa Territory
13389 Force
13732 Buquebus LÃneas Aéreas
16616 Alaniya Airlines
Y
Y
18860 00000_pending_remove
18863 00000_pending_remove
Unknown
00000_pending_remove
SWATF
Unknown
00000_pending_remove
12
Instruction 4
Airline
ID
IAT
A
ICAO
TO PSD
Name
-2 President Airlines
Aviation Management
25 Corporation
324 All Nippon Airways
Alias
null
576 Air-Asia
Air-Asia
Pulkovo Aviation
Enterprise
bmi British Midland
SN Brussels Airlines
AK AXM
Contactair
C3
8J
XW
Y0
641 Rossiya-Russian Airlines
1437 mib
1531 Brussels Airlines
1879 Contact Air
3027 Jet4You
5584 Sky Express
5640 Yellow Air Taxi
South West Africa Territory
13389 Force
13732 Buquebus LÃneas Aéreas
16616 Alaniya Airlines
18860 КатÑ?кавиа
18863 ПÑ?ковавиа
\N
AAM
ANA All Nippon Airways NH ANA
SkyExpress
SWATF
FV SDM
BD BMA
SN DAT
KIS
JFU
SXR
\N
?? ***
BQ BQB
Ð?ланиÑ?
2D \N
КТÐ
š
ПÑ?ков Ð?виа
PKV
Callsign
Country
Cambodia
United States
AM CORP
(USA)
ALL NIPPON Japan
ASIAN
EXPRESS
Malaysia
PULKOVO
MIDLAND
BEE-LINE
CONTACTAI
R
ARGAN
SKYSTORM
Activ C_Airline
e
ID
C_Name
N
0 President Airlines
Aviation Management
N
25 Corporation
Y
324 All Nippon Airways
Y
Russia[[
Y
UNited Kingdom Y
Belgium
Y
Germany
Morocco
Russia
United States
Y
Y
Y
N
Namibia
Uruguay
Belgium
Russia
Russia
576 Air-Asia
641 Rossiya-Russian Airlines
1437 mib
1531 Brussels Airlines
C_Alias
null
C_IATA
TO
Unknown
Unknown
ANA All Nippon Airways NH
Air-Asia
Pulkovo Aviation
Enterprise
bmi British Midland
SN Brussels Airlines
AK
FV
BD
SN
Contactair
Unknown
SkyExpress
Unknown
N
Y
N
1879 Contact Air
3027 Jet4You
5584 Sky Express
5640 Yellow Air Taxi
South West Africa Territory
13389 Force
13732 Buquebus LÃneas Aéreas
16616 Alaniya Airlines
C3
8J
XW
Y0
00000_pending_rem
SWATF
ove
Unknown
BQ
00000_pending_remove 2D
Y
Y
18860 00000_pending_remove
18863 00000_pending_remove
Unknown
Unknown
00000_pending_remove Unknown
13
Instruction 5
Airline
ID
IAT
A
ICAO
TO PSD
Name
-2 President Airlines
Aviation Management
25 Corporation
324 All Nippon Airways
Alias
null
576 Air-Asia
Air-Asia
Pulkovo Aviation
Enterprise
bmi British Midland
SN Brussels Airlines
AK AXM
Contactair
C3
8J
XW
Y0
641 Rossiya-Russian Airlines
1437 mib
1531 Brussels Airlines
1879 Contact Air
3027 Jet4You
5584 Sky Express
5640 Yellow Air Taxi
South West Africa Territory
13389 Force
13732 Buquebus LÃneas Aéreas
16616 Alaniya Airlines
18860 КатÑ?кавиа
18863 ПÑ?ковавиа
\N
AAM
ANA All Nippon Airways NH ANA
SkyExpress
SWATF
FV SDM
BD BMA
SN DAT
KIS
JFU
SXR
\N
?? ***
BQ BQB
Ð?ланиÑ?
2D \N
КТÐ
š
ПÑ?ков Ð?виа
PKV
Callsign
Country
Cambodia
United States
AM CORP
(USA)
ALL NIPPON Japan
ASIAN
EXPRESS
Malaysia
PULKOVO
MIDLAND
BEE-LINE
CONTACTAI
R
ARGAN
SKYSTORM
Activ C_Airline
e
ID
C_Name
N
0 President Airlines
Aviation Management
N
25 Corporation
Y
324 All Nippon Airways
Y
Russia[[
Y
UNited Kingdom Y
Belgium
Y
Germany
Morocco
Russia
United States
Y
Y
Y
N
Namibia
Uruguay
Belgium
Russia
Russia
576 Air-Asia
641 Rossiya-Russian Airlines
1437 mib
1531 Brussels Airlines
C_Alias
null
C_IATA
TO
Unknown
Unknown
ANA All Nippon Airways NH
Air-Asia
Pulkovo Aviation
Enterprise
bmi British Midland
SN Brussels Airlines
AK
FV
BD
SN
Contactair
Unknown
SkyExpress
Unknown
N
Y
N
1879 Contact Air
3027 Jet4You
5584 Sky Express
5640 Yellow Air Taxi
South West Africa Territory
13389 Force
13732 Buquebus LÃneas Aéreas
16616 Alaniya Airlines
C3
8J
XW
Y0
00000_pending_rem
SWATF
ove
Unknown
BQ
00000_pending_remove 2D
Y
Y
18860 00000_pending_remove
18863 00000_pending_remove
Unknown
Unknown
00000_pending_remove Unknown
14
Instruction 5
Airline
ID
Name
-2 President Airlines
Aviation Management
25 Corporation
324 All Nippon Airways
Alias
null
576 Air-Asia
Air-Asia
Pulkovo Aviation
Enterprise
bmi British Midland
SN Brussels Airlines
Contactair
641 Rossiya-Russian Airlines
1437 mib
1531 Brussels Airlines
1879 Contact Air
3027 Jet4You
5584 Sky Express
5640 Yellow Air Taxi
South West Africa Territory
13389 Force
13732 Buquebus LÃneas Aéreas
IAT
A
ICAO
TO PSD
AK
AXM
Country
Cambodia
United States
AM CORP
(USA)
ALL NIPPON Japan
ASIAN
EXPRESS
Malaysia
FV
BD
SN
C3
8J
XW
SDM
BMA
DAT
KIS
JFU
SXR
PULKOVO
MIDLAND
BEE-LINE
CONTACTAIR
ARGAN
SKYSTORM
Y0
\N
\N
AAM
ANA All Nippon Airways NH ANA
SkyExpress
Callsign
Activ C_Airline
e
ID
C_Name
N
0 President Airlines
Aviation Management
N
25 Corporation
Y
324 All Nippon Airways
Y
Russia[[
UNited Kingdom
Belgium
Germany
Morocco
Russia
Y
Y
Y
Y
Y
Y
United States
N
576 Air-Asia
641 Rossiya-Russian Airlines
1437 mib
1531 Brussels Airlines
1879 Contact Air
3027 Jet4You
5584 Sky Express
C_Alias
null
C_ICAO
PSD
Unknown
Unknown
ANA All Nippon Airways NH
AAM
ANA
Air-Asia
Pulkovo Aviation
Enterprise
bmi British Midland
SN Brussels Airlines
Contactair
Unknown
SkyExpress
AXM
SWATF
?? ***
BQ BQB
Namibia
Uruguay
N
Y
5640 Yellow Air Taxi
South West Africa Territory
13389 Force
13732 Buquebus LÃneas Aéreas
16616 Alaniya Airlines
Ð?ланиÑ?
2D
Belgium
N
16616 Alaniya Airlines
00000_pending_remove
18860 КатÑ?кавиа
18863 ПÑ?ковавиа
ПÑ?ков Ð?виа
Russia
Russia
Y
Y
18860 00000_pending_remove
18863 00000_pending_remove
Unknown
00000_pending_remove
\N
КТÐ
š
PKV
C_IATA
TO
Unknown
SWATF
Unknown
AK
FV
BD
SN
C3
8J
XW
SDM
BMA
DAT
KIS
JFU
SXR
00000_pending_remo
Y0
ve
00000_pending_remo 00000_pending_remo
ve
ve
BQ
BQB
00000_pending_remo
2D
ve
00000_pending_remo
Unknown
ve
Unknown
PKV
15
Instruction 6
Airline
ID
Name
-2 President Airlines
Aviation Management
25 Corporation
324 All Nippon Airways
Alias
null
576 Air-Asia
Air-Asia
Pulkovo Aviation
Enterprise
bmi British Midland
SN Brussels Airlines
Contactair
641 Rossiya-Russian Airlines
1437 mib
1531 Brussels Airlines
1879 Contact Air
3027 Jet4You
5584 Sky Express
5640 Yellow Air Taxi
South West Africa Territory
13389 Force
13732 Buquebus LÃneas Aéreas
IAT
A
ICAO
TO PSD
AK
AXM
Country
Cambodia
United States
AM CORP
(USA)
ALL NIPPON Japan
ASIAN
EXPRESS
Malaysia
FV
BD
SN
C3
8J
XW
SDM
BMA
DAT
KIS
JFU
SXR
PULKOVO
MIDLAND
BEE-LINE
CONTACTAIR
ARGAN
SKYSTORM
Y0
\N
\N
AAM
ANA All Nippon Airways NH ANA
SkyExpress
Callsign
Activ C_Airline
e
ID
C_Name
N
0 President Airlines
Aviation Management
N
25 Corporation
Y
324 All Nippon Airways
Y
Russia[[
UNited Kingdom
Belgium
Germany
Morocco
Russia
Y
Y
Y
Y
Y
Y
United States
N
576 Air-Asia
641 Rossiya-Russian Airlines
1437 mib
1531 Brussels Airlines
1879 Contact Air
3027 Jet4You
5584 Sky Express
C_Alias
null
C_ICAO
PSD
Unknown
Unknown
ANA All Nippon Airways NH
AAM
ANA
Air-Asia
Pulkovo Aviation
Enterprise
bmi British Midland
SN Brussels Airlines
Contactair
Unknown
SkyExpress
AXM
SWATF
?? ***
BQ BQB
Namibia
Uruguay
N
Y
5640 Yellow Air Taxi
South West Africa Territory
13389 Force
13732 Buquebus LÃneas Aéreas
16616 Alaniya Airlines
Ð?ланиÑ?
2D
Belgium
N
16616 Alaniya Airlines
00000_pending_remove
18860 КатÑ?кавиа
18863 ПÑ?ковавиа
ПÑ?ков Ð?виа
Russia
Russia
Y
Y
18860 00000_pending_remove
18863 00000_pending_remove
Unknown
00000_pending_remove
\N
КТÐ
š
PKV
C_IATA
TO
Unknown
SWATF
Unknown
AK
FV
BD
SN
C3
8J
XW
SDM
BMA
DAT
KIS
JFU
SXR
00000_pending_remo
Y0
ve
00000_pending_remo 00000_pending_remo
ve
ve
BQ
BQB
00000_pending_remo
2D
ve
00000_pending_remo
Unknown
ve
Unknown
PKV
16
Instruction 6
Airline ID Name
-2 President Airlines
Aviation Management
25 Corporation
324 All Nippon Airways
Country
Cambodia
United States
(USA)
Japan
C_Airline
Active ID
C_Name
N
0 President Airlines
Aviation Management
N
25 Corporation
Y
324 All Nippon Airways
Malaysia
Y
Russia[[
UNited Kingdom
Belgium
Germany
Morocco
Russia
Y
Y
Y
Y
Y
Y
\N
United States
N
??
BQ
***
BQB
Namibia
Uruguay
2D
\N
КТÐ
š
PKV
Alias
null
IATA ICAO
TO PSD
\N
ANA All Nippon Airways
NH
AAM
ANA
AK
AXM
AM CORP
ALL NIPPON
ASIAN
EXPRESS
FV
BD
SN
C3
8J
XW
SDM
BMA
DAT
KIS
JFU
SXR
PULKOVO
MIDLAND
BEE-LINE
CONTACTAIR
ARGAN
SKYSTORM
Y0
SWATF
16616 Alaniya Airlines
Ð?ланиÑ?
18860 КатÑ?кавиа
18863 ПÑ?ковавиа
ПÑ?ков Ð?виа
576 Air-Asia
641 Rossiya-Russian Airlines
1437 mib
1531 Brussels Airlines
1879 Contact Air
3027 Jet4You
5584 Sky Express
5640 Yellow Air Taxi
South West Africa Territory
13389 Force
13732 Buquebus LÃneas Aéreas
Air-Asia
Pulkovo Aviation
Enterprise
bmi British Midland
SN Brussels Airlines
Contactair
SkyExpress
Callsign
576 Air-Asia
641 Rossiya-Russian Airlines
1437 mib
1531 Brussels Airlines
1879 Contact Air
3027 Jet4You
5584 Sky Express
C_Alias
null
C_IATA
TO
C_ICAO
PSD
C_Callsign
Unknown
Unknown
ANA All Nippon Airways
Unknown
NH
AAM
ANA
Air-Asia
Pulkovo Aviation
Enterprise
bmi British Midland
SN Brussels Airlines
Contactair
Unknown
SkyExpress
AK
AXM
AM CORP
ALL NIPPON
ASIAN
EXPRESS
Unknown
N
Y
5640 Yellow Air Taxi
South West Africa Territory
13389 Force
13732 Buquebus LÃneas Aéreas
Belgium
N
16616 Alaniya Airlines
00000_pending_remove
Russia
Russia
Y
Y
18860 00000_pending_remove
18863 00000_pending_remove
Unknown
00000_pending_remove
SWATF
Unknown
FV
BD
SN
C3
8J
XW
SDM
PULKOVO
BMA
MIDLAND
DAT
BEE-LINE
KIS
CONTACTAIR
JFU
ARGAN
SXR
SKYSTORM
00000_pending_remov
Y0
e
Unknown
00000_pending_remov 00000_pending_remov
e
e
Unknown
BQ
BQB
Unknown
00000_pending_remov
2D
e
Unknown
00000_pending_remov
Unknown
e
Unknown
Unknown
PKV
Unknown
17
Instruction 7
Airline ID
Name
President
-2 Airlines
Alias
IATA
ICAO
null
TO
PSD
Aviation
Management
25 Corporation \N
ANA All
All Nippon
Nippon
324 Airways
Airways
576 Air-Asia
RossiyaRussian
641 Airlines
Air-Asia
Pulkovo
Aviation
Enterprise
Callsign
Country
Active
Cambodia
N
United States
(USA)
N
C_Airline ID
C_Name
0 President Airlines
25 Aviation Management Corporation
C_Alias
C_IATA
C_ICAO
C_Callsign
C_Country
null
TO
PSD
Unknown
Cambodia
Unknown
Unknown
AAM
AM CORP
United States (USA)
AAM
AM CORP
NH
ANA
Japan
Y
324 All Nippon Airways
ANA All Nippon Airways
NH
ANA
ALL NIPPON
Japan
AK
AXM
ALL NIPPON
ASIAN
EXPRESS
Malaysia
Y
576 Air-Asia
Air-Asia
AK
AXM
ASIAN EXPRESS
Malaysia
FV
SDM
PULKOVO
Russia[[
Y
641 Rossiya-Russian Airlines
Pulkovo Aviation Enterprise
FV
SDM
PULKOVO
Russia[[
1437 mib
bmi British
Midland
BD
BMA
MIDLAND
UNited
Kingdom
Y
1437 mib
bmi British Midland
BD
BMA
MIDLAND
UNited Kingdom
Brussels
1531 Airlines
SN Brussels
Airlines
SN
DAT
BEE-LINE
Belgium
Y
1531 Brussels Airlines
SN Brussels Airlines
SN
DAT
BEE-LINE
Belgium
1879 Contact Air
3027 Jet4You
Contactair
C3
8J
KIS
JFU
CONTACTAIR Germany
ARGAN
Morocco
Y
Y
1879 Contact Air
3027 Jet4You
Contactair
Unknown
C3
8J
KIS
JFU
CONTACTAIR
ARGAN
Germany
Morocco
5584 Sky Express
SkyExpress
XW
SXR
SKYSTORM
Y
5584 Sky Express
SkyExpress
XW
SXR
SKYSTORM
Russia
Y0
\N
United States N
5640 Yellow Air Taxi
Unknown
Y0
00000_pending_remove
Unknown
United States
??
5640 Yellow Air Taxi
South West
Africa
Territory
13389 Force
SWATF
Russia
***
Namibia
N
13389 South West Africa Territory Force
SWATF
00000_pending_remove
00000_pending_remove
Unknown
Namibia
13732 Buquebus LÃneas Aéreas BQ
Alaniya
Ð?лани
16616 Airlines
Ñ?
2D
BQB
Uruguay
Y
13732 Buquebus LÃneas Aéreas
Unknown
BQ
BQB
Unknown
Uruguay
\N
Belgium
N
16616 Alaniya Airlines
00000_pending_remove
2D
00000_pending_remove
Unknown
Belgium
18860 КатÑ?кавиа
КТК
Russia
Y
18860 00000_pending_remove
Unknown
Unknown
00000_pending_remove
Unknown
Russia
ПÑ?ков
18863 авиа
ПÑ?ков Ð?виа
PKV
Russia
Y
18863 00000_pending_remove
00000_pending_remove
Unknown
PKV
Unknown
Russia
No invalid content in the country column.
18
Instruction 8
Airline ID
Name
President
-2 Airlines
Alias
IATA
ICAO
null
TO
PSD
Aviation
Management
25 Corporation \N
ANA All
All Nippon
Nippon
324 Airways
Airways
576 Air-Asia
RossiyaRussian
641 Airlines
Air-Asia
Pulkovo
Aviation
Enterprise
Callsign
Country
Active
Cambodia
N
United States
(USA)
N
C_Airline ID
C_Name
0 President Airlines
25 Aviation Management Corporation
C_Alias
C_IATA
C_ICAO
C_Callsign
C_Country
null
TO
PSD
Unknown
Cambodia
Unknown
Unknown
AAM
AM CORP
United States (USA)
AAM
AM CORP
NH
ANA
Japan
Y
324 All Nippon Airways
ANA All Nippon Airways
NH
ANA
ALL NIPPON
Japan
AK
AXM
ALL NIPPON
ASIAN
EXPRESS
Malaysia
Y
576 Air-Asia
Air-Asia
AK
AXM
ASIAN EXPRESS
Malaysia
FV
SDM
PULKOVO
Russia[[
Y
641 Rossiya-Russian Airlines
Pulkovo Aviation Enterprise
FV
SDM
PULKOVO
Russia[[
1437 mib
bmi British
Midland
BD
BMA
MIDLAND
UNited
Kingdom
Y
1437 mib
bmi British Midland
BD
BMA
MIDLAND
UNited Kingdom
Brussels
1531 Airlines
SN Brussels
Airlines
SN
DAT
BEE-LINE
Belgium
Y
1531 Brussels Airlines
SN Brussels Airlines
SN
DAT
BEE-LINE
Belgium
1879 Contact Air
3027 Jet4You
Contactair
C3
8J
KIS
JFU
CONTACTAIR Germany
ARGAN
Morocco
Y
Y
1879 Contact Air
3027 Jet4You
Contactair
Unknown
C3
8J
KIS
JFU
CONTACTAIR
ARGAN
Germany
Morocco
5584 Sky Express
SkyExpress
XW
SXR
SKYSTORM
Y
5584 Sky Express
SkyExpress
XW
SXR
SKYSTORM
Russia
Y0
\N
United States N
5640 Yellow Air Taxi
Unknown
Y0
00000_pending_remove
Unknown
United States
??
5640 Yellow Air Taxi
South West
Africa
Territory
13389 Force
SWATF
Russia
***
Namibia
N
13389 South West Africa Territory Force
SWATF
00000_pending_remove
00000_pending_remove
Unknown
Namibia
13732 Buquebus LÃneas Aéreas BQ
Alaniya
Ð?лани
16616 Airlines
Ñ?
2D
BQB
Uruguay
Y
13732 Buquebus LÃneas Aéreas
Unknown
BQ
BQB
Unknown
Uruguay
\N
Belgium
N
16616 Alaniya Airlines
00000_pending_remove
2D
00000_pending_remove
Unknown
Belgium
18860 КатÑ?кавиа
КТК
Russia
Y
18860 00000_pending_remove
Unknown
Unknown
00000_pending_remove
Unknown
Russia
ПÑ?ков
18863 авиа
ПÑ?ков Ð?виа
PKV
Russia
Y
18863 00000_pending_remove
00000_pending_remove
Unknown
PKV
Unknown
Russia
No invalid content in the Active column.
19
Instruction 9
Airline ID
Name
President
-2 Airlines
Alias
IATA
ICAO
null
TO
PSD
Aviation
Management
25 Corporation \N
ANA All
All Nippon
Nippon
324 Airways
Airways
576 Air-Asia
RossiyaRussian
641 Airlines
Air-Asia
Pulkovo
Aviation
Enterprise
Callsign
Country
Active
Cambodia
N
United States
(USA)
N
C_Airline ID
C_Name
0 President Airlines
25 Aviation Management Corporation
C_Alias
C_IATA
C_ICAO
C_Callsign
C_Country
null
TO
PSD
Unknown
Cambodia
Unknown
Unknown
AAM
AM CORP
United States (USA)
AAM
AM CORP
NH
ANA
Japan
Y
324 All Nippon Airways
ANA All Nippon Airways
NH
ANA
ALL NIPPON
Japan
AK
AXM
ALL NIPPON
ASIAN
EXPRESS
Malaysia
Y
576 Air-Asia
Air-Asia
AK
AXM
ASIAN EXPRESS
Malaysia
FV
SDM
PULKOVO
Russia[[
Y
641 Rossiya-Russian Airlines
Pulkovo Aviation Enterprise
FV
SDM
PULKOVO
Russia[[
1437 mib
bmi British
Midland
BD
BMA
MIDLAND
UNited
Kingdom
Y
1437 mib
bmi British Midland
BD
BMA
MIDLAND
UNited Kingdom
Brussels
1531 Airlines
SN Brussels
Airlines
SN
DAT
BEE-LINE
Belgium
Y
1531 Brussels Airlines
SN Brussels Airlines
SN
DAT
BEE-LINE
Belgium
1879 Contact Air
3027 Jet4You
Contactair
C3
8J
KIS
JFU
CONTACTAIR Germany
ARGAN
Morocco
Y
Y
1879 Contact Air
3027 Jet4You
Contactair
Unknown
C3
8J
KIS
JFU
CONTACTAIR
ARGAN
Germany
Morocco
5584 Sky Express
SkyExpress
XW
SXR
SKYSTORM
Y
5584 Sky Express
SkyExpress
XW
SXR
SKYSTORM
Russia
Y0
\N
United States N
5640 Yellow Air Taxi
Unknown
Y0
00000_pending_remove
Unknown
United States
??
5640 Yellow Air Taxi
South West
Africa
Territory
13389 Force
SWATF
Russia
***
Namibia
N
13389 South West Africa Territory Force
SWATF
00000_pending_remove
00000_pending_remove
Unknown
Namibia
13732 Buquebus LÃneas Aéreas BQ
Alaniya
Ð?лани
16616 Airlines
Ñ?
2D
BQB
Uruguay
Y
13732 Buquebus LÃneas Aéreas
Unknown
BQ
BQB
Unknown
Uruguay
\N
Belgium
N
16616 Alaniya Airlines
00000_pending_remove
2D
00000_pending_remove
Unknown
Belgium
18860 КатÑ?кавиа
КТК
Russia
Y
18860 00000_pending_remove
Unknown
Unknown
00000_pending_remove
Unknown
Russia
ПÑ?ков
18863 авиа
ПÑ?ков Ð?виа
PKV
Russia
Y
18863 00000_pending_remove
00000_pending_remove
Unknown
PKV
Unknown
Russia
20
Output Data
C_Airline ID
C_Name
C_Alias
C_IATA
C_ICAO C_Callsign
C_Country
C_Active
null
TO
PSD
Unknown
Cambodia
N
Unknown
Unknown AAM
AM CORP
United States (USA)
N
324All Nippon Airways
ANA All Nippon Airways
NH
ANA
ALL NIPPON
Japan
Y
576Air-Asia
Air-Asia
AK
AXM
ASIAN EXPRESS
Malaysia
Y
641Rossiya-Russian Airlines
Pulkovo Aviation Enterprise
FV
SDM
PULKOVO
Russia[[
Y
1437mib
bmi British Midland
BD
BMA
MIDLAND
UNited Kingdom
Y
1531Brussels Airlines
SN Brussels Airlines
SN
DAT
BEE-LINE
Belgium
Y
1879Contact Air
Contactair
C3
KIS
CONTACTAIR
Germany
Y
3027Jet4You
Unknown
8J
JFU
ARGAN
Morocco
Y
5584Sky Express
SkyExpress
XW
SXR
SKYSTORM
Russia
Y
Unknown
BQ
BQB
Unknown
Uruguay
Y
0President Airlines
25Aviation Management Corporation
13732Buquebus LÃneas Aéreas
21