Overview

Dataset statistics

Number of variables24
Number of observations427
Missing cells2535
Missing cells (%)24.7%
Duplicate rows6
Duplicate rows (%)1.4%
Total size in memory81.4 KiB
Average record size in memory195.3 B

Variable types

Categorical10
Text11
Unsupported3

Dataset

Description2021년 12월말 기준 강원도 양양군의 산업 소분류 및 읍면동별(양양읍, 서면, 손양면, 현북면, 현남면, 강현면 사업체 수, 종사자 수입니다.
Author강원특별자치도 양양군
URLhttps://www.data.go.kr/data/15116982/fileData.do

Alerts

Dataset has 6 (1.4%) duplicate rowsDuplicates
2. 산업소분류 및 읍면동별 사업체수, 종사자수 is highly imbalanced (77.4%)Imbalance
Unnamed: 1 is highly imbalanced (81.5%)Imbalance
2. Number of Establishments and Workers by Industrial Groups & Provinces is highly imbalanced (82.7%)Imbalance
Unnamed: 23 is highly imbalanced (81.5%)Imbalance
Unnamed: 2 has 324 (75.9%) missing valuesMissing
Unnamed: 3 has 105 (24.6%) missing valuesMissing
Unnamed: 4 has 105 (24.6%) missing valuesMissing
Unnamed: 5 has 427 (100.0%) missing valuesMissing
Unnamed: 6 has 81 (19.0%) missing valuesMissing
Unnamed: 7 has 93 (21.8%) missing valuesMissing
Unnamed: 8 has 81 (19.0%) missing valuesMissing
Unnamed: 9 has 93 (21.8%) missing valuesMissing
Unnamed: 11 has 427 (100.0%) missing valuesMissing
Unnamed: 13 has 93 (21.8%) missing valuesMissing
Unnamed: 15 has 93 (21.8%) missing valuesMissing
Unnamed: 19 has 93 (21.8%) missing valuesMissing
Unnamed: 21 has 93 (21.8%) missing valuesMissing
Unnamed: 22 has 427 (100.0%) missing valuesMissing
Unnamed: 5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 22 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 11:03:41.509568
Analysis finished2024-03-14 11:03:42.445919
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct23
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
373 
산업분류 Industrial Classification
 
12
2. 산업소분류 및 읍면동별 사업체수, 종사자수
 
11
C
 
6
F
 
2
Other values (18)
 
23

Length

Max length30
Median length4
Mean length5.0819672
Min length1

Unique

Unique13 ?
Unique (%)3.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row산업분류 Industrial Classification

Common Values

ValueCountFrequency (%)
<NA> 373
87.4%
산업분류 Industrial Classification 12
 
2.8%
2. 산업소분류 및 읍면동별 사업체수, 종사자수 11
 
2.6%
C 6
 
1.4%
F 2
 
0.5%
Q 2
 
0.5%
N 2
 
0.5%
L 2
 
0.5%
J 2
 
0.5%
H 2
 
0.5%
Other values (13) 13
 
3.0%

Length

2024-03-14T20:03:42.654881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 373
73.7%
industrial 12
 
2.4%
classification 12
 
2.4%
산업분류 12
 
2.4%
2 11
 
2.2%
산업소분류 11
 
2.2%
11
 
2.2%
읍면동별 11
 
2.2%
사업체수 11
 
2.2%
종사자수 11
 
2.2%
Other values (20) 31
 
6.1%

Unnamed: 1
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
415 
(2021 기준년도, 강원도 양양군)
 
12

Length

Max length20
Median length4
Mean length4.4496487
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row(2021 기준년도, 강원도 양양군)
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 415
97.2%
(2021 기준년도, 강원도 양양군) 12
 
2.8%

Length

2024-03-14T20:03:43.068971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:03:43.413256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 415
89.6%
2021 12
 
2.6%
기준년도 12
 
2.6%
강원도 12
 
2.6%
양양군 12
 
2.6%

Unnamed: 2
Text

MISSING 

Distinct75
Distinct (%)72.8%
Missing324
Missing (%)75.9%
Memory size3.5 KiB
2024-03-14T20:03:44.144120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters206
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)63.1%

Sample

1st row**
2nd row**
3rd row01
4th row02
5th row03
ValueCountFrequency (%)
20
 
19.4%
86 2
 
1.9%
34 2
 
1.9%
42 2
 
1.9%
68 2
 
1.9%
49 2
 
1.9%
28 2
 
1.9%
10 2
 
1.9%
59 2
 
1.9%
75 2
 
1.9%
Other values (65) 65
63.1%
2024-03-14T20:03:45.296278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 40
19.4%
1 20
9.7%
2 20
9.7%
6 20
9.7%
5 19
9.2%
3 17
8.3%
4 16
 
7.8%
0 15
 
7.3%
7 14
 
6.8%
8 13
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 166
80.6%
Other Punctuation 40
 
19.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20
12.0%
2 20
12.0%
6 20
12.0%
5 19
11.4%
3 17
10.2%
4 16
9.6%
0 15
9.0%
7 14
8.4%
8 13
7.8%
9 12
7.2%
Other Punctuation
ValueCountFrequency (%)
* 40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 206
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 40
19.4%
1 20
9.7%
2 20
9.7%
6 20
9.7%
5 19
9.2%
3 17
8.3%
4 16
 
7.8%
0 15
 
7.3%
7 14
 
6.8%
8 13
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 206
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 40
19.4%
1 20
9.7%
2 20
9.7%
6 20
9.7%
5 19
9.2%
3 17
8.3%
4 16
 
7.8%
0 15
 
7.3%
7 14
 
6.8%
8 13
 
6.3%

Unnamed: 3
Text

MISSING 

Distinct229
Distinct (%)71.1%
Missing105
Missing (%)24.6%
Memory size3.5 KiB
2024-03-14T20:03:46.787181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.7080745
Min length2

Characters and Unicode

Total characters872
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique228 ?
Unique (%)70.8%

Sample

1st row**
2nd row**
3rd row**
4th row011
5th row012
ValueCountFrequency (%)
94
29.2%
764 1
 
0.3%
425 1
 
0.3%
426 1
 
0.3%
512 1
 
0.3%
521 1
 
0.3%
529 1
 
0.3%
551 1
 
0.3%
559 1
 
0.3%
561 1
 
0.3%
Other values (219) 219
68.0%
2024-03-14T20:03:48.659751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 188
21.6%
1 125
14.3%
2 114
13.1%
3 78
8.9%
4 73
 
8.4%
5 58
 
6.7%
6 58
 
6.7%
7 50
 
5.7%
0 49
 
5.6%
9 42
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 684
78.4%
Other Punctuation 188
 
21.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 125
18.3%
2 114
16.7%
3 78
11.4%
4 73
10.7%
5 58
8.5%
6 58
8.5%
7 50
 
7.3%
0 49
 
7.2%
9 42
 
6.1%
8 37
 
5.4%
Other Punctuation
ValueCountFrequency (%)
* 188
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 872
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 188
21.6%
1 125
14.3%
2 114
13.1%
3 78
8.9%
4 73
 
8.4%
5 58
 
6.7%
6 58
 
6.7%
7 50
 
5.7%
0 49
 
5.6%
9 42
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 872
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 188
21.6%
1 125
14.3%
2 114
13.1%
3 78
8.9%
4 73
 
8.4%
5 58
 
6.7%
6 58
 
6.7%
7 50
 
5.7%
0 49
 
5.6%
9 42
 
4.8%

Unnamed: 4
Text

MISSING 

Distinct322
Distinct (%)100.0%
Missing105
Missing (%)24.6%
Memory size3.5 KiB
2024-03-14T20:03:49.807391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length30
Mean length19.397516
Min length7

Characters and Unicode

Total characters6246
Distinct characters288
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique322 ?
Unique (%)100.0%

Sample

1st rowTT 전체산업
2nd rowA.농업, 임업 및 어업(01~03)
3rd row 01.농업
4th row 011.작물 재배업
5th row 012.축산업
ValueCountFrequency (%)
166
 
14.4%
제조업 98
 
8.5%
서비스업 42
 
3.6%
기타 12
 
1.0%
운송업 12
 
1.0%
소매업 9
 
0.8%
광업 8
 
0.7%
도매업 7
 
0.6%
제외 7
 
0.6%
기계 7
 
0.6%
Other values (630) 783
68.0%
2024-03-14T20:03:51.432820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1890
30.3%
324
 
5.2%
. 321
 
5.1%
166
 
2.7%
157
 
2.5%
1 151
 
2.4%
2 134
 
2.1%
121
 
1.9%
106
 
1.7%
3 101
 
1.6%
Other values (278) 2775
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2977
47.7%
Space Separator 1890
30.3%
Decimal Number 903
 
14.5%
Other Punctuation 402
 
6.4%
Uppercase Letter 21
 
0.3%
Close Punctuation 19
 
0.3%
Open Punctuation 19
 
0.3%
Math Symbol 15
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
324
 
10.9%
166
 
5.6%
157
 
5.3%
121
 
4.1%
106
 
3.6%
83
 
2.8%
69
 
2.3%
66
 
2.2%
54
 
1.8%
41
 
1.4%
Other values (240) 1790
60.1%
Uppercase Letter
ValueCountFrequency (%)
T 2
 
9.5%
N 1
 
4.8%
C 1
 
4.8%
M 1
 
4.8%
L 1
 
4.8%
O 1
 
4.8%
R 1
 
4.8%
A 1
 
4.8%
S 1
 
4.8%
Q 1
 
4.8%
Other values (10) 10
47.6%
Decimal Number
ValueCountFrequency (%)
1 151
16.7%
2 134
14.8%
3 101
11.2%
4 96
10.6%
6 86
9.5%
5 84
9.3%
0 70
7.8%
7 69
7.6%
9 58
 
6.4%
8 54
 
6.0%
Other Punctuation
ValueCountFrequency (%)
. 321
79.9%
, 69
 
17.2%
; 8
 
2.0%
? 4
 
1.0%
Space Separator
ValueCountFrequency (%)
1890
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Math Symbol
ValueCountFrequency (%)
~ 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3248
52.0%
Hangul 2977
47.7%
Latin 21
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
324
 
10.9%
166
 
5.6%
157
 
5.3%
121
 
4.1%
106
 
3.6%
83
 
2.8%
69
 
2.3%
66
 
2.2%
54
 
1.8%
41
 
1.4%
Other values (240) 1790
60.1%
Latin
ValueCountFrequency (%)
T 2
 
9.5%
N 1
 
4.8%
C 1
 
4.8%
M 1
 
4.8%
L 1
 
4.8%
O 1
 
4.8%
R 1
 
4.8%
A 1
 
4.8%
S 1
 
4.8%
Q 1
 
4.8%
Other values (10) 10
47.6%
Common
ValueCountFrequency (%)
1890
58.2%
. 321
 
9.9%
1 151
 
4.6%
2 134
 
4.1%
3 101
 
3.1%
4 96
 
3.0%
6 86
 
2.6%
5 84
 
2.6%
0 70
 
2.2%
, 69
 
2.1%
Other values (8) 246
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3269
52.3%
Hangul 2971
47.6%
Compat Jamo 6
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1890
57.8%
. 321
 
9.8%
1 151
 
4.6%
2 134
 
4.1%
3 101
 
3.1%
4 96
 
2.9%
6 86
 
2.6%
5 84
 
2.6%
0 70
 
2.1%
, 69
 
2.1%
Other values (28) 267
 
8.2%
Hangul
ValueCountFrequency (%)
324
 
10.9%
166
 
5.6%
157
 
5.3%
121
 
4.1%
106
 
3.6%
83
 
2.8%
69
 
2.3%
66
 
2.2%
54
 
1.8%
41
 
1.4%
Other values (239) 1784
60.0%
Compat Jamo
ValueCountFrequency (%)
6
100.0%

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing427
Missing (%)100.0%
Memory size3.9 KiB

Unnamed: 6
Text

MISSING 

Distinct89
Distinct (%)25.7%
Missing81
Missing (%)19.0%
Memory size3.5 KiB
2024-03-14T20:03:52.215859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length1
Mean length1.8930636
Min length1

Characters and Unicode

Total characters655
Distinct characters24
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)14.7%

Sample

1st row양양군
2nd row사업체수 Estab.
3rd row4,989
4th row46
5th row34
ValueCountFrequency (%)
0 90
25.1%
1 19
 
5.3%
3 18
 
5.0%
2 17
 
4.7%
6 15
 
4.2%
사업체수 12
 
3.4%
estab 12
 
3.4%
5 12
 
3.4%
양양군 12
 
3.4%
4 8
 
2.2%
Other values (80) 143
39.9%
2024-03-14T20:03:53.178604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 108
16.5%
1 93
14.2%
3 49
 
7.5%
2 47
 
7.2%
6 39
 
6.0%
5 35
 
5.3%
7 33
 
5.0%
4 30
 
4.6%
8 29
 
4.4%
24
 
3.7%
Other values (14) 168
25.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 485
74.0%
Other Letter 84
 
12.8%
Lowercase Letter 48
 
7.3%
Other Punctuation 14
 
2.1%
Control 12
 
1.8%
Uppercase Letter 12
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 108
22.3%
1 93
19.2%
3 49
10.1%
2 47
9.7%
6 39
 
8.0%
5 35
 
7.2%
7 33
 
6.8%
4 30
 
6.2%
8 29
 
6.0%
9 22
 
4.5%
Other Letter
ValueCountFrequency (%)
24
28.6%
12
14.3%
12
14.3%
12
14.3%
12
14.3%
12
14.3%
Lowercase Letter
ValueCountFrequency (%)
t 12
25.0%
b 12
25.0%
a 12
25.0%
s 12
25.0%
Other Punctuation
ValueCountFrequency (%)
. 12
85.7%
, 2
 
14.3%
Control
ValueCountFrequency (%)
12
100.0%
Uppercase Letter
ValueCountFrequency (%)
E 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 511
78.0%
Hangul 84
 
12.8%
Latin 60
 
9.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 108
21.1%
1 93
18.2%
3 49
9.6%
2 47
9.2%
6 39
 
7.6%
5 35
 
6.8%
7 33
 
6.5%
4 30
 
5.9%
8 29
 
5.7%
9 22
 
4.3%
Other values (3) 26
 
5.1%
Hangul
ValueCountFrequency (%)
24
28.6%
12
14.3%
12
14.3%
12
14.3%
12
14.3%
12
14.3%
Latin
ValueCountFrequency (%)
t 12
20.0%
b 12
20.0%
a 12
20.0%
s 12
20.0%
E 12
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 571
87.2%
Hangul 84
 
12.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 108
18.9%
1 93
16.3%
3 49
8.6%
2 47
8.2%
6 39
 
6.8%
5 35
 
6.1%
7 33
 
5.8%
4 30
 
5.3%
8 29
 
5.1%
9 22
 
3.9%
Other values (8) 86
15.1%
Hangul
ValueCountFrequency (%)
24
28.6%
12
14.3%
12
14.3%
12
14.3%
12
14.3%
12
14.3%

Unnamed: 7
Text

MISSING 

Distinct133
Distinct (%)39.8%
Missing93
Missing (%)21.8%
Memory size3.5 KiB
2024-03-14T20:03:54.241375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length6
Mean length2.2724551
Min length1

Characters and Unicode

Total characters759
Distinct characters22
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique86 ?
Unique (%)25.7%

Sample

1st row종사자수 Workers
2nd row16,351
3rd row142
4th row86
5th row62
ValueCountFrequency (%)
0 90
26.0%
workers 12
 
3.5%
종사자수 12
 
3.5%
3 11
 
3.2%
1 9
 
2.6%
9 8
 
2.3%
5 8
 
2.3%
12 5
 
1.4%
8 5
 
1.4%
24 4
 
1.2%
Other values (124) 182
52.6%
2024-03-14T20:03:55.890334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 122
16.1%
1 101
13.3%
2 81
10.7%
3 57
 
7.5%
9 48
 
6.3%
4 46
 
6.1%
6 43
 
5.7%
5 42
 
5.5%
8 32
 
4.2%
7 27
 
3.6%
Other values (12) 160
21.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 599
78.9%
Lowercase Letter 72
 
9.5%
Other Letter 48
 
6.3%
Other Punctuation 16
 
2.1%
Uppercase Letter 12
 
1.6%
Control 12
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 122
20.4%
1 101
16.9%
2 81
13.5%
3 57
9.5%
9 48
 
8.0%
4 46
 
7.7%
6 43
 
7.2%
5 42
 
7.0%
8 32
 
5.3%
7 27
 
4.5%
Lowercase Letter
ValueCountFrequency (%)
r 24
33.3%
e 12
16.7%
k 12
16.7%
o 12
16.7%
s 12
16.7%
Other Letter
ValueCountFrequency (%)
12
25.0%
12
25.0%
12
25.0%
12
25.0%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%
Uppercase Letter
ValueCountFrequency (%)
W 12
100.0%
Control
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 627
82.6%
Latin 84
 
11.1%
Hangul 48
 
6.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 122
19.5%
1 101
16.1%
2 81
12.9%
3 57
9.1%
9 48
 
7.7%
4 46
 
7.3%
6 43
 
6.9%
5 42
 
6.7%
8 32
 
5.1%
7 27
 
4.3%
Other values (2) 28
 
4.5%
Latin
ValueCountFrequency (%)
r 24
28.6%
e 12
14.3%
k 12
14.3%
o 12
14.3%
W 12
14.3%
s 12
14.3%
Hangul
ValueCountFrequency (%)
12
25.0%
12
25.0%
12
25.0%
12
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 711
93.7%
Hangul 48
 
6.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 122
17.2%
1 101
14.2%
2 81
11.4%
3 57
8.0%
9 48
 
6.8%
4 46
 
6.5%
6 43
 
6.0%
5 42
 
5.9%
8 32
 
4.5%
7 27
 
3.8%
Other values (8) 112
15.8%
Hangul
ValueCountFrequency (%)
12
25.0%
12
25.0%
12
25.0%
12
25.0%

Unnamed: 8
Text

MISSING 

Distinct65
Distinct (%)18.8%
Missing81
Missing (%)19.0%
Memory size3.5 KiB
2024-03-14T20:03:56.519406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length1
Mean length1.7138728
Min length1

Characters and Unicode

Total characters593
Distinct characters24
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)9.8%

Sample

1st row양양읍
2nd row사업체수 Estab.
3rd row2,044
4th row12
5th row8
ValueCountFrequency (%)
0 123
34.4%
1 31
 
8.7%
4 20
 
5.6%
3 13
 
3.6%
2 13
 
3.6%
사업체수 12
 
3.4%
estab 12
 
3.4%
양양읍 12
 
3.4%
5 10
 
2.8%
9 8
 
2.2%
Other values (56) 104
29.1%
2024-03-14T20:03:57.530273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 136
22.9%
1 78
13.2%
4 44
 
7.4%
3 36
 
6.1%
2 33
 
5.6%
5 32
 
5.4%
24
 
4.0%
8 20
 
3.4%
9 18
 
3.0%
6 15
 
2.5%
Other values (14) 157
26.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 424
71.5%
Other Letter 84
 
14.2%
Lowercase Letter 48
 
8.1%
Other Punctuation 13
 
2.2%
Uppercase Letter 12
 
2.0%
Control 12
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 136
32.1%
1 78
18.4%
4 44
 
10.4%
3 36
 
8.5%
2 33
 
7.8%
5 32
 
7.5%
8 20
 
4.7%
9 18
 
4.2%
6 15
 
3.5%
7 12
 
2.8%
Other Letter
ValueCountFrequency (%)
24
28.6%
12
14.3%
12
14.3%
12
14.3%
12
14.3%
12
14.3%
Lowercase Letter
ValueCountFrequency (%)
b 12
25.0%
t 12
25.0%
a 12
25.0%
s 12
25.0%
Other Punctuation
ValueCountFrequency (%)
. 12
92.3%
, 1
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
E 12
100.0%
Control
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 449
75.7%
Hangul 84
 
14.2%
Latin 60
 
10.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 136
30.3%
1 78
17.4%
4 44
 
9.8%
3 36
 
8.0%
2 33
 
7.3%
5 32
 
7.1%
8 20
 
4.5%
9 18
 
4.0%
6 15
 
3.3%
7 12
 
2.7%
Other values (3) 25
 
5.6%
Hangul
ValueCountFrequency (%)
24
28.6%
12
14.3%
12
14.3%
12
14.3%
12
14.3%
12
14.3%
Latin
ValueCountFrequency (%)
b 12
20.0%
t 12
20.0%
a 12
20.0%
s 12
20.0%
E 12
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 509
85.8%
Hangul 84
 
14.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 136
26.7%
1 78
15.3%
4 44
 
8.6%
3 36
 
7.1%
2 33
 
6.5%
5 32
 
6.3%
8 20
 
3.9%
9 18
 
3.5%
6 15
 
2.9%
b 12
 
2.4%
Other values (8) 85
16.7%
Hangul
ValueCountFrequency (%)
24
28.6%
12
14.3%
12
14.3%
12
14.3%
12
14.3%
12
14.3%

Unnamed: 9
Text

MISSING 

Distinct103
Distinct (%)30.8%
Missing93
Missing (%)21.8%
Memory size3.5 KiB
2024-03-14T20:03:58.404249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length1
Mean length2.011976
Min length1

Characters and Unicode

Total characters672
Distinct characters22
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)17.7%

Sample

1st row종사자수 Workers
2nd row7,836
3rd row38
4th row27
5th row21
ValueCountFrequency (%)
0 123
35.5%
workers 12
 
3.5%
종사자수 12
 
3.5%
2 10
 
2.9%
1 8
 
2.3%
9 7
 
2.0%
6 7
 
2.0%
3 6
 
1.7%
47 6
 
1.7%
4 5
 
1.4%
Other values (94) 150
43.4%
2024-03-14T20:03:59.432772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 141
21.0%
1 76
11.3%
2 54
 
8.0%
3 49
 
7.3%
7 39
 
5.8%
4 38
 
5.7%
6 36
 
5.4%
8 35
 
5.2%
5 28
 
4.2%
9 27
 
4.0%
Other values (12) 149
22.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 523
77.8%
Lowercase Letter 72
 
10.7%
Other Letter 48
 
7.1%
Uppercase Letter 12
 
1.8%
Control 12
 
1.8%
Other Punctuation 5
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 141
27.0%
1 76
14.5%
2 54
 
10.3%
3 49
 
9.4%
7 39
 
7.5%
4 38
 
7.3%
6 36
 
6.9%
8 35
 
6.7%
5 28
 
5.4%
9 27
 
5.2%
Lowercase Letter
ValueCountFrequency (%)
r 24
33.3%
s 12
16.7%
e 12
16.7%
k 12
16.7%
o 12
16.7%
Other Letter
ValueCountFrequency (%)
12
25.0%
12
25.0%
12
25.0%
12
25.0%
Uppercase Letter
ValueCountFrequency (%)
W 12
100.0%
Control
ValueCountFrequency (%)
12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 540
80.4%
Latin 84
 
12.5%
Hangul 48
 
7.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 141
26.1%
1 76
14.1%
2 54
 
10.0%
3 49
 
9.1%
7 39
 
7.2%
4 38
 
7.0%
6 36
 
6.7%
8 35
 
6.5%
5 28
 
5.2%
9 27
 
5.0%
Other values (2) 17
 
3.1%
Latin
ValueCountFrequency (%)
r 24
28.6%
s 12
14.3%
e 12
14.3%
k 12
14.3%
o 12
14.3%
W 12
14.3%
Hangul
ValueCountFrequency (%)
12
25.0%
12
25.0%
12
25.0%
12
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 624
92.9%
Hangul 48
 
7.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 141
22.6%
1 76
12.2%
2 54
 
8.7%
3 49
 
7.9%
7 39
 
6.2%
4 38
 
6.1%
6 36
 
5.8%
8 35
 
5.6%
5 28
 
4.5%
9 27
 
4.3%
Other values (8) 101
16.2%
Hangul
ValueCountFrequency (%)
12
25.0%
12
25.0%
12
25.0%
12
25.0%

Unnamed: 10
Categorical

Distinct31
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
0
200 
<NA>
81 
1
36 
2
 
18
사업체수 Estab.
 
12
Other values (26)
80 

Length

Max length11
Median length1
Mean length1.941452
Min length1

Unique

Unique16 ?
Unique (%)3.7%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row서면

Common Values

ValueCountFrequency (%)
0 200
46.8%
<NA> 81
19.0%
1 36
 
8.4%
2 18
 
4.2%
사업체수 Estab. 12
 
2.8%
서면 12
 
2.8%
3 12
 
2.8%
5 11
 
2.6%
4 9
 
2.1%
7 5
 
1.2%
Other values (21) 31
 
7.3%

Length

2024-03-14T20:03:59.660738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 200
45.6%
na 81
18.5%
1 36
 
8.2%
2 18
 
4.1%
사업체수 12
 
2.7%
estab 12
 
2.7%
서면 12
 
2.7%
3 12
 
2.7%
5 11
 
2.5%
4 9
 
2.1%
Other values (22) 36
 
8.2%

Unnamed: 11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing427
Missing (%)100.0%
Memory size3.9 KiB
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
416 
2. Number of Establishments and Workers by Industrial Groups & Provinces
 
11

Length

Max length72
Median length4
Mean length5.7517564
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 416
97.4%
2. Number of Establishments and Workers by Industrial Groups & Provinces 11
 
2.6%

Length

2024-03-14T20:03:59.909314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:04:00.170251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 416
77.5%
2 11
 
2.0%
number 11
 
2.0%
of 11
 
2.0%
establishments 11
 
2.0%
and 11
 
2.0%
workers 11
 
2.0%
by 11
 
2.0%
industrial 11
 
2.0%
groups 11
 
2.0%
Other values (2) 22
 
4.1%

Unnamed: 13
Text

MISSING 

Distinct58
Distinct (%)17.4%
Missing93
Missing (%)21.8%
Memory size3.5 KiB
2024-03-14T20:04:00.704101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length1
Mean length1.6437126
Min length1

Characters and Unicode

Total characters549
Distinct characters22
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)9.6%

Sample

1st row종사자수 Workers
2nd row1,736
3rd row6
4th row6
5th row6
ValueCountFrequency (%)
0 200
57.8%
2 14
 
4.0%
종사자수 12
 
3.5%
workers 12
 
3.5%
3 10
 
2.9%
1 10
 
2.9%
4 7
 
2.0%
6 6
 
1.7%
5 4
 
1.2%
89 3
 
0.9%
Other values (49) 68
 
19.7%
2024-03-14T20:04:01.692798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 208
37.9%
1 43
 
7.8%
2 35
 
6.4%
3 26
 
4.7%
r 24
 
4.4%
6 20
 
3.6%
4 19
 
3.5%
5 18
 
3.3%
7 14
 
2.6%
8 12
 
2.2%
Other values (12) 130
23.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 404
73.6%
Lowercase Letter 72
 
13.1%
Other Letter 48
 
8.7%
Uppercase Letter 12
 
2.2%
Control 12
 
2.2%
Other Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 208
51.5%
1 43
 
10.6%
2 35
 
8.7%
3 26
 
6.4%
6 20
 
5.0%
4 19
 
4.7%
5 18
 
4.5%
7 14
 
3.5%
8 12
 
3.0%
9 9
 
2.2%
Lowercase Letter
ValueCountFrequency (%)
r 24
33.3%
s 12
16.7%
e 12
16.7%
k 12
16.7%
o 12
16.7%
Other Letter
ValueCountFrequency (%)
12
25.0%
12
25.0%
12
25.0%
12
25.0%
Uppercase Letter
ValueCountFrequency (%)
W 12
100.0%
Control
ValueCountFrequency (%)
12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 417
76.0%
Latin 84
 
15.3%
Hangul 48
 
8.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 208
49.9%
1 43
 
10.3%
2 35
 
8.4%
3 26
 
6.2%
6 20
 
4.8%
4 19
 
4.6%
5 18
 
4.3%
7 14
 
3.4%
8 12
 
2.9%
12
 
2.9%
Other values (2) 10
 
2.4%
Latin
ValueCountFrequency (%)
r 24
28.6%
s 12
14.3%
e 12
14.3%
k 12
14.3%
o 12
14.3%
W 12
14.3%
Hangul
ValueCountFrequency (%)
12
25.0%
12
25.0%
12
25.0%
12
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 501
91.3%
Hangul 48
 
8.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 208
41.5%
1 43
 
8.6%
2 35
 
7.0%
3 26
 
5.2%
r 24
 
4.8%
6 20
 
4.0%
4 19
 
3.8%
5 18
 
3.6%
7 14
 
2.8%
8 12
 
2.4%
Other values (8) 82
 
16.4%
Hangul
ValueCountFrequency (%)
12
25.0%
12
25.0%
12
25.0%
12
25.0%

Unnamed: 14
Categorical

Distinct32
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
0
185 
<NA>
81 
1
38 
2
 
18
3
 
16
Other values (27)
89 

Length

Max length11
Median length1
Mean length1.9789227
Min length1

Unique

Unique14 ?
Unique (%)3.3%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row손양면

Common Values

ValueCountFrequency (%)
0 185
43.3%
<NA> 81
19.0%
1 38
 
8.9%
2 18
 
4.2%
3 16
 
3.7%
4 13
 
3.0%
사업체수 Estab. 12
 
2.8%
손양면 12
 
2.8%
7 10
 
2.3%
10 5
 
1.2%
Other values (22) 37
 
8.7%

Length

2024-03-14T20:04:01.916831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 185
42.1%
na 81
18.5%
1 38
 
8.7%
2 18
 
4.1%
3 16
 
3.6%
4 13
 
3.0%
사업체수 12
 
2.7%
estab 12
 
2.7%
손양면 12
 
2.7%
7 10
 
2.3%
Other values (23) 42
 
9.6%

Unnamed: 15
Text

MISSING 

Distinct54
Distinct (%)16.2%
Missing93
Missing (%)21.8%
Memory size3.5 KiB
2024-03-14T20:04:02.351792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length1
Mean length1.6646707
Min length1

Characters and Unicode

Total characters556
Distinct characters22
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)9.3%

Sample

1st row종사자수 Workers
2nd row1,607
3rd row17
4th row17
5th row10
ValueCountFrequency (%)
0 185
53.5%
1 15
 
4.3%
종사자수 12
 
3.5%
workers 12
 
3.5%
3 12
 
3.5%
4 10
 
2.9%
5 9
 
2.6%
2 9
 
2.6%
23 6
 
1.7%
8 5
 
1.4%
Other values (45) 71
 
20.5%
2024-03-14T20:04:03.102956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 197
35.4%
1 53
 
9.5%
2 33
 
5.9%
3 32
 
5.8%
4 26
 
4.7%
r 24
 
4.3%
5 23
 
4.1%
8 16
 
2.9%
6 13
 
2.3%
7 13
 
2.3%
Other values (12) 126
22.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 411
73.9%
Lowercase Letter 72
 
12.9%
Other Letter 48
 
8.6%
Uppercase Letter 12
 
2.2%
Control 12
 
2.2%
Other Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 197
47.9%
1 53
 
12.9%
2 33
 
8.0%
3 32
 
7.8%
4 26
 
6.3%
5 23
 
5.6%
8 16
 
3.9%
6 13
 
3.2%
7 13
 
3.2%
9 5
 
1.2%
Lowercase Letter
ValueCountFrequency (%)
r 24
33.3%
s 12
16.7%
e 12
16.7%
k 12
16.7%
o 12
16.7%
Other Letter
ValueCountFrequency (%)
12
25.0%
12
25.0%
12
25.0%
12
25.0%
Uppercase Letter
ValueCountFrequency (%)
W 12
100.0%
Control
ValueCountFrequency (%)
12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 424
76.3%
Latin 84
 
15.1%
Hangul 48
 
8.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 197
46.5%
1 53
 
12.5%
2 33
 
7.8%
3 32
 
7.5%
4 26
 
6.1%
5 23
 
5.4%
8 16
 
3.8%
6 13
 
3.1%
7 13
 
3.1%
12
 
2.8%
Other values (2) 6
 
1.4%
Latin
ValueCountFrequency (%)
r 24
28.6%
s 12
14.3%
e 12
14.3%
k 12
14.3%
o 12
14.3%
W 12
14.3%
Hangul
ValueCountFrequency (%)
12
25.0%
12
25.0%
12
25.0%
12
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 508
91.4%
Hangul 48
 
8.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 197
38.8%
1 53
 
10.4%
2 33
 
6.5%
3 32
 
6.3%
4 26
 
5.1%
r 24
 
4.7%
5 23
 
4.5%
8 16
 
3.1%
6 13
 
2.6%
7 13
 
2.6%
Other values (8) 78
 
15.4%
Hangul
ValueCountFrequency (%)
12
25.0%
12
25.0%
12
25.0%
12
25.0%

Unnamed: 16
Categorical

Distinct33
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
0
197 
<NA>
81 
1
47 
2
 
16
3
 
14
Other values (28)
72 

Length

Max length11
Median length1
Mean length1.971897
Min length1

Unique

Unique17 ?
Unique (%)4.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row현북면

Common Values

ValueCountFrequency (%)
0 197
46.1%
<NA> 81
19.0%
1 47
 
11.0%
2 16
 
3.7%
3 14
 
3.3%
사업체수 Estab. 12
 
2.8%
현북면 12
 
2.8%
7 8
 
1.9%
4 7
 
1.6%
9 3
 
0.7%
Other values (23) 30
 
7.0%

Length

2024-03-14T20:04:03.326828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 197
44.9%
na 81
18.5%
1 47
 
10.7%
2 16
 
3.6%
3 14
 
3.2%
사업체수 12
 
2.7%
estab 12
 
2.7%
현북면 12
 
2.7%
7 8
 
1.8%
4 7
 
1.6%
Other values (24) 33
 
7.5%

Unnamed: 17
Categorical

Distinct41
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
0
197 
<NA>
93 
1
21 
2
 
18
5
 
15
Other values (36)
83 

Length

Max length12
Median length1
Mean length2.0936768
Min length1

Unique

Unique22 ?
Unique (%)5.2%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
0 197
46.1%
<NA> 93
21.8%
1 21
 
4.9%
2 18
 
4.2%
5 15
 
3.5%
3 12
 
2.8%
종사자수 Workers 12
 
2.8%
4 5
 
1.2%
8 5
 
1.2%
15 4
 
0.9%
Other values (31) 45
 
10.5%

Length

2024-03-14T20:04:03.537781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 197
44.9%
na 93
21.2%
1 21
 
4.8%
2 18
 
4.1%
5 15
 
3.4%
3 12
 
2.7%
종사자수 12
 
2.7%
workers 12
 
2.7%
8 5
 
1.1%
4 5
 
1.1%
Other values (32) 49
 
11.2%

Unnamed: 18
Categorical

Distinct35
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
0
172 
<NA>
81 
1
47 
3
20 
2
 
15
Other values (30)
92 

Length

Max length11
Median length1
Mean length2.0140515
Min length1

Unique

Unique14 ?
Unique (%)3.3%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row현남면

Common Values

ValueCountFrequency (%)
0 172
40.3%
<NA> 81
19.0%
1 47
 
11.0%
3 20
 
4.7%
2 15
 
3.5%
사업체수 Estab. 12
 
2.8%
현남면 12
 
2.8%
4 12
 
2.8%
5 7
 
1.6%
6 5
 
1.2%
Other values (25) 44
 
10.3%

Length

2024-03-14T20:04:03.750879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 172
39.2%
na 81
18.5%
1 47
 
10.7%
3 20
 
4.6%
2 15
 
3.4%
사업체수 12
 
2.7%
estab 12
 
2.7%
현남면 12
 
2.7%
4 12
 
2.7%
5 7
 
1.6%
Other values (26) 49
 
11.2%

Unnamed: 19
Text

MISSING 

Distinct55
Distinct (%)16.5%
Missing93
Missing (%)21.8%
Memory size3.5 KiB
2024-03-14T20:04:04.263016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length1
Mean length1.6796407
Min length1

Characters and Unicode

Total characters561
Distinct characters22
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)7.8%

Sample

1st row종사자수 Workers
2nd row1,698
3rd row33
4th row19
5th row14
ValueCountFrequency (%)
0 172
49.7%
1 25
 
7.2%
종사자수 12
 
3.5%
workers 12
 
3.5%
3 9
 
2.6%
2 9
 
2.6%
5 7
 
2.0%
35 6
 
1.7%
6 6
 
1.7%
21 5
 
1.4%
Other values (46) 83
24.0%
2024-03-14T20:04:04.941539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 175
31.2%
1 70
 
12.5%
2 40
 
7.1%
3 36
 
6.4%
r 24
 
4.3%
4 20
 
3.6%
5 19
 
3.4%
9 17
 
3.0%
6 16
 
2.9%
7 14
 
2.5%
Other values (12) 130
23.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 416
74.2%
Lowercase Letter 72
 
12.8%
Other Letter 48
 
8.6%
Uppercase Letter 12
 
2.1%
Control 12
 
2.1%
Other Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 175
42.1%
1 70
 
16.8%
2 40
 
9.6%
3 36
 
8.7%
4 20
 
4.8%
5 19
 
4.6%
9 17
 
4.1%
6 16
 
3.8%
7 14
 
3.4%
8 9
 
2.2%
Lowercase Letter
ValueCountFrequency (%)
r 24
33.3%
s 12
16.7%
e 12
16.7%
k 12
16.7%
o 12
16.7%
Other Letter
ValueCountFrequency (%)
12
25.0%
12
25.0%
12
25.0%
12
25.0%
Uppercase Letter
ValueCountFrequency (%)
W 12
100.0%
Control
ValueCountFrequency (%)
12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 429
76.5%
Latin 84
 
15.0%
Hangul 48
 
8.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 175
40.8%
1 70
 
16.3%
2 40
 
9.3%
3 36
 
8.4%
4 20
 
4.7%
5 19
 
4.4%
9 17
 
4.0%
6 16
 
3.7%
7 14
 
3.3%
12
 
2.8%
Other values (2) 10
 
2.3%
Latin
ValueCountFrequency (%)
r 24
28.6%
s 12
14.3%
e 12
14.3%
k 12
14.3%
o 12
14.3%
W 12
14.3%
Hangul
ValueCountFrequency (%)
12
25.0%
12
25.0%
12
25.0%
12
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 513
91.4%
Hangul 48
 
8.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 175
34.1%
1 70
 
13.6%
2 40
 
7.8%
3 36
 
7.0%
r 24
 
4.7%
4 20
 
3.9%
5 19
 
3.7%
9 17
 
3.3%
6 16
 
3.1%
7 14
 
2.7%
Other values (8) 82
16.0%
Hangul
ValueCountFrequency (%)
12
25.0%
12
25.0%
12
25.0%
12
25.0%

Unnamed: 20
Categorical

Distinct44
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
0
146 
<NA>
81 
1
47 
2
32 
4
 
13
Other values (39)
108 

Length

Max length11
Median length1
Mean length2.0257611
Min length1

Unique

Unique22 ?
Unique (%)5.2%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row강현면

Common Values

ValueCountFrequency (%)
0 146
34.2%
<NA> 81
19.0%
1 47
 
11.0%
2 32
 
7.5%
4 13
 
3.0%
사업체수 Estab. 12
 
2.8%
강현면 12
 
2.8%
3 11
 
2.6%
5 10
 
2.3%
7 8
 
1.9%
Other values (34) 55
 
12.9%

Length

2024-03-14T20:04:05.240469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 146
33.3%
na 81
18.5%
1 47
 
10.7%
2 32
 
7.3%
4 13
 
3.0%
사업체수 12
 
2.7%
estab 12
 
2.7%
강현면 12
 
2.7%
3 11
 
2.5%
5 10
 
2.3%
Other values (35) 63
14.4%

Unnamed: 21
Text

MISSING 

Distinct68
Distinct (%)20.4%
Missing93
Missing (%)21.8%
Memory size3.5 KiB
2024-03-14T20:04:05.739691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length1
Mean length1.7185629
Min length1

Characters and Unicode

Total characters574
Distinct characters22
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)12.0%

Sample

1st row종사자수 Workers
2nd row2,559
3rd row41
4th row12
5th row7
ValueCountFrequency (%)
0 146
42.2%
1 28
 
8.1%
2 15
 
4.3%
종사자수 12
 
3.5%
workers 12
 
3.5%
3 10
 
2.9%
4 9
 
2.6%
5 9
 
2.6%
10 8
 
2.3%
6 6
 
1.7%
Other values (59) 91
26.3%
2024-03-14T20:04:06.482791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 156
27.2%
1 71
12.4%
2 45
 
7.8%
3 39
 
6.8%
5 26
 
4.5%
4 25
 
4.4%
r 24
 
4.2%
6 20
 
3.5%
7 19
 
3.3%
9 17
 
3.0%
Other values (12) 132
23.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 429
74.7%
Lowercase Letter 72
 
12.5%
Other Letter 48
 
8.4%
Uppercase Letter 12
 
2.1%
Control 12
 
2.1%
Other Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 156
36.4%
1 71
16.6%
2 45
 
10.5%
3 39
 
9.1%
5 26
 
6.1%
4 25
 
5.8%
6 20
 
4.7%
7 19
 
4.4%
9 17
 
4.0%
8 11
 
2.6%
Lowercase Letter
ValueCountFrequency (%)
r 24
33.3%
e 12
16.7%
s 12
16.7%
k 12
16.7%
o 12
16.7%
Other Letter
ValueCountFrequency (%)
12
25.0%
12
25.0%
12
25.0%
12
25.0%
Uppercase Letter
ValueCountFrequency (%)
W 12
100.0%
Control
ValueCountFrequency (%)
12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 442
77.0%
Latin 84
 
14.6%
Hangul 48
 
8.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 156
35.3%
1 71
16.1%
2 45
 
10.2%
3 39
 
8.8%
5 26
 
5.9%
4 25
 
5.7%
6 20
 
4.5%
7 19
 
4.3%
9 17
 
3.8%
12
 
2.7%
Other values (2) 12
 
2.7%
Latin
ValueCountFrequency (%)
r 24
28.6%
e 12
14.3%
s 12
14.3%
k 12
14.3%
o 12
14.3%
W 12
14.3%
Hangul
ValueCountFrequency (%)
12
25.0%
12
25.0%
12
25.0%
12
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 526
91.6%
Hangul 48
 
8.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 156
29.7%
1 71
13.5%
2 45
 
8.6%
3 39
 
7.4%
5 26
 
4.9%
4 25
 
4.8%
r 24
 
4.6%
6 20
 
3.8%
7 19
 
3.6%
9 17
 
3.2%
Other values (8) 84
16.0%
Hangul
ValueCountFrequency (%)
12
25.0%
12
25.0%
12
25.0%
12
25.0%

Unnamed: 22
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing427
Missing (%)100.0%
Memory size3.9 KiB

Unnamed: 23
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
415 
(단위 : 개, 명)
 
12

Length

Max length11
Median length4
Mean length4.1967213
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row(단위 : 개, 명)
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 415
97.2%
(단위 : 개, 명) 12
 
2.8%

Length

2024-03-14T20:04:06.913266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:04:07.251257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 415
89.6%
단위 12
 
2.6%
12
 
2.6%
12
 
2.6%
12
 
2.6%

Sample

2. 산업소분류 및 읍면동별 사업체수, 종사자수Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 112. Number of Establishments and Workers by Industrial Groups & ProvincesUnnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23
0<NA>(2021 기준년도, 강원도 양양군)<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>(단위 : 개, 명)
2<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
4산업분류 Industrial Classification<NA><NA><NA><NA><NA>양양군<NA>양양읍<NA>서면<NA><NA><NA>손양면<NA>현북면<NA>현남면<NA>강현면<NA><NA><NA>
5<NA><NA><NA><NA><NA><NA>사업체수 Estab.종사자수 Workers사업체수 Estab.종사자수 Workers사업체수 Estab.<NA><NA>종사자수 Workers사업체수 Estab.종사자수 Workers사업체수 Estab.종사자수 Workers사업체수 Estab.종사자수 Workers사업체수 Estab.종사자수 Workers<NA><NA>
6**<NA>****TT 전체산업<NA>4,98916,3512,0447,836431<NA><NA>1,7364091,6074289157041,6989732,559<NA><NA>
7A<NA>****A.농업, 임업 및 어업(01~03)<NA>4614212383<NA><NA>6717579331041<NA><NA>
8<NA><NA>01**01.농업<NA>34868273<NA><NA>671745519712<NA><NA>
9<NA><NA><NA>011011.작물 재배업<NA>26626213<NA><NA>65103441457<NA><NA>
2. 산업소분류 및 읍면동별 사업체수, 종사자수Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 112. Number of Establishments and Workers by Industrial Groups & ProvincesUnnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23
417<NA><NA><NA>941941.산업 및 전문가 단체<NA>1214790<NA><NA>022110022<NA><NA>
418<NA><NA><NA>942942.노동조합<NA>22110<NA><NA>000000011<NA><NA>
419<NA><NA><NA>949949.기타 협회 및 단체<NA>1582986911319<NA><NA>301636182118291869<NA><NA>
420<NA><NA>95**95.개인 및 소비용품 수리업<NA>6311045852<NA><NA>3332322914<NA><NA>
421<NA><NA><NA>951951.컴퓨터 및 통신장비 수리업<NA>33110<NA><NA>011001100<NA><NA>
422<NA><NA><NA>952952.자동차 및 모터사이클 수리업<NA>397829661<NA><NA>211110078<NA><NA>
423<NA><NA><NA>953953.개인 및 가정용품 수리업<NA>212915181<NA><NA>111121126<NA><NA>
424<NA><NA>96**96.기타 개인 서비스업<NA>126237861532<NA><NA>210363311171426<NA><NA>
425<NA><NA><NA>961961.미용, 욕탕 및 유사 서비스업<NA>779356631<NA><NA>1353358913<NA><NA>
426<NA><NA><NA>969969.그 외 기타 개인 서비스업<NA>4914430901<NA><NA>17310069513<NA><NA>

Duplicate rows

Most frequently occurring

2. 산업소분류 및 읍면동별 사업체수, 종사자수Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 102. Number of Establishments and Workers by Industrial Groups & ProvincesUnnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 23# duplicates
5<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>46
1산업분류 Industrial Classification<NA><NA><NA><NA>양양군<NA>양양읍<NA>서면<NA><NA>손양면<NA>현북면<NA>현남면<NA>강현면<NA><NA>12
2<NA>(2021 기준년도, 강원도 양양군)<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>12
3<NA><NA><NA><NA><NA>사업체수 Estab.종사자수 Workers사업체수 Estab.종사자수 Workers사업체수 Estab.<NA>종사자수 Workers사업체수 Estab.종사자수 Workers사업체수 Estab.종사자수 Workers사업체수 Estab.종사자수 Workers사업체수 Estab.종사자수 Workers<NA>12
4<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>(단위 : 개, 명)12
02. 산업소분류 및 읍면동별 사업체수, 종사자수<NA><NA><NA><NA><NA><NA><NA><NA><NA>2. Number of Establishments and Workers by Industrial Groups & Provinces<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>11