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    Home / Data Portal / STATSSA / ZAF-STATSSA-QLFS-2019-Q1-V1 / variable [F2]
StatsSA

Quarterly Labour Force Survey 2019, Quarter 1

South Africa, 2019
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Reference ID
zaf-statssa-qlfs-2019-q1-v1
Producer(s)
Statistics South Africa
Collections
Statistics South Africa
Metadata
DDI/XML JSON
Created on
Jun 24, 2019
Last modified
Sep 10, 2020
Page views
35699
Downloads
3908
  • Study Description
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  • qlfs-2019-q1-worker-v1

Study field (Q18FIELD)

Data file: qlfs-2019-q1-worker-v1

Overview

Valid: 965
Invalid: 9034
Type: Discrete
Decimal: 0
loc_start_pos: 27
loc_end_pos: 28
Width: 2
Range: 1 - 38
Format: Numeric

Questions and instructions

Categories
Value Category Cases
1 Agriculture or Renewable natural resources 15
1.6%
2 Architecture or environmental design 11
1.1%
3 Arts; Visual or Performing 19
2%
4 Business; commerce and management studies 113
11.7%
5 Communication 5
0.5%
6 Computer science 16
1.7%
7 Education; training or development 165
17.1%
8 Engineering or engineering technology 39
4%
9 Health care or health sciences 101
10.5%
10 Home economics 3
0.3%
11 Industrial arts; traders or technology 2
0.2%
12 Languages; linguistic or literature 11
1.1%
13 Law 31
3.2%
14 Libraries or museums 2
0.2%
15 Life sciences or physical sciences 10
1%
16 Mathematical sciences 3
0.3%
17 Military sciences 1
0.1%
18 Philosophy; religion or theology 7
0.7%
19 Physical education or leisure 4
0.4%
20 Psychology 8
0.8%
21 Public administration or social services 18
1.9%
22 Social sciences or social studies 12
1.2%
23 Other 74
7.7%
24 Management 37
3.8%
25 Marketing 20
2.1%
26 Information technology and computer science 24
2.5%
27 Finance; economics and accounting 45
4.7%
28 Office administration 30
3.1%
29 Electrical infrastructure construction 11
1.1%
30 Civil engineering and building construction 21
2.2%
31 Engineering 16
1.7%
32 Primary agriculture 1
0.1%
33 Hospitality 15
1.6%
34 Tourism 13
1.3%
35 Safety in society 6
0.6%
36 Mechatronics 3
0.3%
37 Education and development 5
0.5%
38 Other 48
5%
Sysmiss 9034
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
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