Overview

Dataset statistics

Number of variables6
Number of observations2680
Missing cells830
Missing cells (%)5.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory125.8 KiB
Average record size in memory48.0 B

Variable types

Numeric1
Categorical1
Text4

Dataset

Description인허가번호,민원구분,노동조합단체명,사업장명,소속단체명,노동조합주소
Author동작구
URLhttps://data.seoul.go.kr/dataList/OA-10631/S/1/datasetView.do

Alerts

인허가번호 is highly overall correlated with 민원구분High correlation
민원구분 is highly overall correlated with 인허가번호High correlation
소속단체명 has 631 (23.5%) missing valuesMissing
노동조합주소 has 193 (7.2%) missing valuesMissing

Reproduction

Analysis started2024-05-11 06:23:02.633092
Analysis finished2024-05-11 06:23:44.024790
Duration41.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

인허가번호
Real number (ℝ)

HIGH CORRELATION 

Distinct772
Distinct (%)28.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.845321 × 1018
Minimum2.011611 × 1017
Maximum2.023611 × 1019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.7 KiB
2024-05-11T15:23:44.187808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.011611 × 1017
5-th percentile1.999301 × 1018
Q12.007317 × 1018
median2.010313 × 1018
Q32.017318 × 1018
95-th percentile2.024321 × 1018
Maximum2.023611 × 1019
Range2.0034949 × 1019
Interquartile range (IQR)1.0001009 × 1016

Descriptive statistics

Standard deviation3.8070604 × 1018
Coefficient of variation (CV)1.3380074
Kurtosis16.681356
Mean2.845321 × 1018
Median Absolute Deviation (MAD)3.9900009 × 1015
Skewness4.3193179
Sum7.6254603 × 1021
Variance1.4493709 × 1037
MonotonicityNot monotonic
2024-05-11T15:23:44.592669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.0083220000261e+18 219
 
8.2%
2.0093180120261e+18 63
 
2.4%
2.0073210000261e+18 47
 
1.8%
2.0073170107261e+18 43
 
1.6%
2.0073000126261e+18 41
 
1.5%
2.0073160117261e+18 34
 
1.3%
2.0083010000261e+18 33
 
1.2%
2.0073090103261e+18 29
 
1.1%
2.0073010000261e+18 28
 
1.0%
2.0073020095261e+18 23
 
0.9%
Other values (762) 2120
79.1%
ValueCountFrequency (%)
2.01161100002e+17 1
< 0.1%
2.01261100002e+17 1
< 0.1%
2.01361100002e+17 1
< 0.1%
2.01461100002e+17 1
< 0.1%
2.01561100002e+17 1
< 0.1%
1.9613070118261e+18 1
< 0.1%
1.9633010100261005e+18 1
< 0.1%
1.9633200099261e+18 1
< 0.1%
1.9653070118261e+18 1
< 0.1%
1.9663070118261e+18 1
< 0.1%
ValueCountFrequency (%)
2.02361100001019e+19 2
 
0.1%
2.02261100001019e+19 8
0.3%
2.02161100001019e+19 5
0.2%
2.02061100001019e+19 9
0.3%
2.01961100001019e+19 10
0.4%
2.01861100001019e+19 6
0.2%
2.01761100001019e+19 11
0.4%
2.01661100001019e+19 6
0.2%
2.01561100001019e+19 8
0.3%
2.01461100001019e+19 7
0.3%

민원구분
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.1 KiB
노동조합해산신고
1297 
노동조합설립신고
1005 
노동조합변경신고
372 
노동조합신고
 
6

Length

Max length8
Median length8
Mean length7.9955224
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row노동조합변경신고
2nd row노동조합변경신고
3rd row노동조합변경신고
4th row노동조합설립신고
5th row노동조합설립신고

Common Values

ValueCountFrequency (%)
노동조합해산신고 1297
48.4%
노동조합설립신고 1005
37.5%
노동조합변경신고 372
 
13.9%
노동조합신고 6
 
0.2%

Length

2024-05-11T15:23:44.935595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:45.185388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노동조합해산신고 1297
48.4%
노동조합설립신고 1005
37.5%
노동조합변경신고 372
 
13.9%
노동조합신고 6
 
0.2%
Distinct2535
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Memory size21.1 KiB
2024-05-11T15:23:45.535741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length30
Mean length11.784701
Min length2

Characters and Unicode

Total characters31583
Distinct characters619
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2401 ?
Unique (%)89.6%

Sample

1st row삼성이앤에이 노동조합 &U
2nd row안정호
3rd row도원에프앤지㈜노동조합
4th row의료연대노동조합
5th row클래시스생산본부노동조합
ValueCountFrequency (%)
노동조합 993
 
22.6%
영업 186
 
4.2%
해산 56
 
1.3%
주식회사 17
 
0.4%
지부 12
 
0.3%
민주노동조합 11
 
0.3%
서울특별시 10
 
0.2%
서울지점 9
 
0.2%
공무직 9
 
0.2%
서울시버스노동조합 8
 
0.2%
Other values (2717) 3084
70.2%
2024-05-11T15:23:46.292563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2222
 
7.0%
2150
 
6.8%
2120
 
6.7%
2101
 
6.7%
1716
 
5.4%
821
 
2.6%
) 772
 
2.4%
( 761
 
2.4%
453
 
1.4%
432
 
1.4%
Other values (609) 18035
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27361
86.6%
Space Separator 1716
 
5.4%
Close Punctuation 1014
 
3.2%
Open Punctuation 1003
 
3.2%
Uppercase Letter 395
 
1.3%
Decimal Number 41
 
0.1%
Lowercase Letter 30
 
0.1%
Other Punctuation 13
 
< 0.1%
Dash Punctuation 8
 
< 0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2222
 
8.1%
2150
 
7.9%
2120
 
7.7%
2101
 
7.7%
821
 
3.0%
453
 
1.7%
432
 
1.6%
429
 
1.6%
410
 
1.5%
406
 
1.5%
Other values (551) 15817
57.8%
Uppercase Letter
ValueCountFrequency (%)
S 57
14.4%
K 50
12.7%
B 35
8.9%
C 33
 
8.4%
T 31
 
7.8%
G 25
 
6.3%
M 24
 
6.1%
N 22
 
5.6%
I 21
 
5.3%
A 14
 
3.5%
Other values (14) 83
21.0%
Lowercase Letter
ValueCountFrequency (%)
s 4
13.3%
c 3
10.0%
i 3
10.0%
h 3
10.0%
e 3
10.0%
k 2
 
6.7%
r 2
 
6.7%
p 2
 
6.7%
b 2
 
6.7%
z 1
 
3.3%
Other values (5) 5
16.7%
Decimal Number
ValueCountFrequency (%)
1 14
34.1%
2 7
17.1%
3 6
14.6%
9 5
 
12.2%
6 4
 
9.8%
4 3
 
7.3%
0 1
 
2.4%
5 1
 
2.4%
Other Punctuation
ValueCountFrequency (%)
. 4
30.8%
& 4
30.8%
, 4
30.8%
? 1
 
7.7%
Close Punctuation
ValueCountFrequency (%)
) 772
76.1%
] 242
 
23.9%
Open Punctuation
ValueCountFrequency (%)
( 761
75.9%
[ 242
 
24.1%
Space Separator
ValueCountFrequency (%)
1716
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27362
86.6%
Common 3795
 
12.0%
Latin 425
 
1.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2222
 
8.1%
2150
 
7.9%
2120
 
7.7%
2101
 
7.7%
821
 
3.0%
453
 
1.7%
432
 
1.6%
429
 
1.6%
410
 
1.5%
406
 
1.5%
Other values (551) 15818
57.8%
Latin
ValueCountFrequency (%)
S 57
13.4%
K 50
11.8%
B 35
 
8.2%
C 33
 
7.8%
T 31
 
7.3%
G 25
 
5.9%
M 24
 
5.6%
N 22
 
5.2%
I 21
 
4.9%
A 14
 
3.3%
Other values (29) 113
26.6%
Common
ValueCountFrequency (%)
1716
45.2%
) 772
20.3%
( 761
20.1%
] 242
 
6.4%
[ 242
 
6.4%
1 14
 
0.4%
- 8
 
0.2%
2 7
 
0.2%
3 6
 
0.2%
9 5
 
0.1%
Other values (8) 22
 
0.6%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27360
86.6%
ASCII 4220
 
13.4%
None 2
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2222
 
8.1%
2150
 
7.9%
2120
 
7.7%
2101
 
7.7%
821
 
3.0%
453
 
1.7%
432
 
1.6%
429
 
1.6%
410
 
1.5%
406
 
1.5%
Other values (550) 15816
57.8%
ASCII
ValueCountFrequency (%)
1716
40.7%
) 772
18.3%
( 761
18.0%
] 242
 
5.7%
[ 242
 
5.7%
S 57
 
1.4%
K 50
 
1.2%
B 35
 
0.8%
C 33
 
0.8%
T 31
 
0.7%
Other values (47) 281
 
6.7%
None
ValueCountFrequency (%)
2
100.0%
CJK
ValueCountFrequency (%)
1
100.0%
Distinct2303
Distinct (%)86.1%
Missing6
Missing (%)0.2%
Memory size21.1 KiB
2024-05-11T15:23:46.746140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length81
Median length40
Mean length7.5205684
Min length1

Characters and Unicode

Total characters20110
Distinct characters614
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2024 ?
Unique (%)75.7%

Sample

1st row삼성이앤에이
2nd row한국종합기술
3rd row도원에프앤지
4th row(주)우림맨테크
5th row문정공장
ValueCountFrequency (%)
주식회사 30
 
1.0%
17
 
0.6%
선진상운(주 8
 
0.3%
sh공사 6
 
0.2%
노동조합 6
 
0.2%
서울대학교 6
 
0.2%
재단법인 6
 
0.2%
서울지점 5
 
0.2%
5
 
0.2%
남양상운 5
 
0.2%
Other values (2401) 2792
96.7%
2024-05-11T15:23:47.549105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1095
 
5.4%
) 1043
 
5.2%
( 1026
 
5.1%
433
 
2.2%
393
 
2.0%
368
 
1.8%
344
 
1.7%
284
 
1.4%
283
 
1.4%
282
 
1.4%
Other values (604) 14559
72.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17317
86.1%
Close Punctuation 1043
 
5.2%
Open Punctuation 1026
 
5.1%
Uppercase Letter 352
 
1.8%
Space Separator 213
 
1.1%
Other Punctuation 58
 
0.3%
Decimal Number 50
 
0.2%
Lowercase Letter 27
 
0.1%
Dash Punctuation 20
 
0.1%
Other Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1095
 
6.3%
433
 
2.5%
393
 
2.3%
368
 
2.1%
344
 
2.0%
284
 
1.6%
283
 
1.6%
282
 
1.6%
273
 
1.6%
266
 
1.5%
Other values (547) 13296
76.8%
Uppercase Letter
ValueCountFrequency (%)
S 59
16.8%
K 46
13.1%
B 31
8.8%
T 30
8.5%
C 24
 
6.8%
G 24
 
6.8%
I 21
 
6.0%
N 16
 
4.5%
M 16
 
4.5%
H 14
 
4.0%
Other values (14) 71
20.2%
Lowercase Letter
ValueCountFrequency (%)
h 4
14.8%
k 4
14.8%
e 3
11.1%
s 3
11.1%
b 2
7.4%
t 2
7.4%
i 2
7.4%
c 2
7.4%
y 1
 
3.7%
p 1
 
3.7%
Other values (3) 3
11.1%
Decimal Number
ValueCountFrequency (%)
1 15
30.0%
2 9
18.0%
3 7
14.0%
6 5
 
10.0%
4 4
 
8.0%
9 3
 
6.0%
5 3
 
6.0%
8 2
 
4.0%
0 1
 
2.0%
7 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 46
79.3%
. 5
 
8.6%
& 4
 
6.9%
/ 2
 
3.4%
1
 
1.7%
Close Punctuation
ValueCountFrequency (%)
) 1043
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1026
100.0%
Space Separator
ValueCountFrequency (%)
213
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Other Symbol
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17321
86.1%
Common 2410
 
12.0%
Latin 379
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1095
 
6.3%
433
 
2.5%
393
 
2.3%
368
 
2.1%
344
 
2.0%
284
 
1.6%
283
 
1.6%
282
 
1.6%
273
 
1.6%
266
 
1.5%
Other values (548) 13300
76.8%
Latin
ValueCountFrequency (%)
S 59
15.6%
K 46
12.1%
B 31
 
8.2%
T 30
 
7.9%
C 24
 
6.3%
G 24
 
6.3%
I 21
 
5.5%
N 16
 
4.2%
M 16
 
4.2%
H 14
 
3.7%
Other values (27) 98
25.9%
Common
ValueCountFrequency (%)
) 1043
43.3%
( 1026
42.6%
213
 
8.8%
, 46
 
1.9%
- 20
 
0.8%
1 15
 
0.6%
2 9
 
0.4%
3 7
 
0.3%
. 5
 
0.2%
6 5
 
0.2%
Other values (9) 21
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17317
86.1%
ASCII 2788
 
13.9%
None 5
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1095
 
6.3%
433
 
2.5%
393
 
2.3%
368
 
2.1%
344
 
2.0%
284
 
1.6%
283
 
1.6%
282
 
1.6%
273
 
1.6%
266
 
1.5%
Other values (547) 13296
76.8%
ASCII
ValueCountFrequency (%)
) 1043
37.4%
( 1026
36.8%
213
 
7.6%
S 59
 
2.1%
K 46
 
1.6%
, 46
 
1.6%
B 31
 
1.1%
T 30
 
1.1%
C 24
 
0.9%
G 24
 
0.9%
Other values (45) 246
 
8.8%
None
ValueCountFrequency (%)
4
80.0%
1
 
20.0%

소속단체명
Text

MISSING 

Distinct366
Distinct (%)17.9%
Missing631
Missing (%)23.5%
Memory size21.1 KiB
2024-05-11T15:23:47.967134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length26
Mean length6.7213275
Min length1

Characters and Unicode

Total characters13772
Distinct characters205
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique227 ?
Unique (%)11.1%

Sample

1st row전국건설산업노동조합연맹
2nd row상급단체미가입
3rd row없음
4th row에이치피엘(주)
5th row상급단체 미가입
ValueCountFrequency (%)
없음 404
 
17.7%
미가입 272
 
11.9%
전국택시노동조합연맹 123
 
5.4%
상급단체미가입 117
 
5.1%
전국연합노동조합연맹 72
 
3.2%
한국노총 71
 
3.1%
상급단체 59
 
2.6%
택시노련 52
 
2.3%
민주노총 45
 
2.0%
전국자동차노동조합연맹 36
 
1.6%
Other values (348) 1032
45.2%
2024-05-11T15:23:48.659611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1208
 
8.8%
755
 
5.5%
745
 
5.4%
744
 
5.4%
693
 
5.0%
653
 
4.7%
642
 
4.7%
633
 
4.6%
445
 
3.2%
444
 
3.2%
Other values (195) 6810
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13351
96.9%
Space Separator 234
 
1.7%
Close Punctuation 83
 
0.6%
Open Punctuation 42
 
0.3%
Uppercase Letter 37
 
0.3%
Other Punctuation 20
 
0.1%
Dash Punctuation 4
 
< 0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1208
 
9.0%
755
 
5.7%
745
 
5.6%
744
 
5.6%
693
 
5.2%
653
 
4.9%
642
 
4.8%
633
 
4.7%
445
 
3.3%
444
 
3.3%
Other values (175) 6389
47.9%
Uppercase Letter
ValueCountFrequency (%)
I 13
35.1%
T 13
35.1%
S 2
 
5.4%
K 2
 
5.4%
B 1
 
2.7%
G 1
 
2.7%
N 1
 
2.7%
E 1
 
2.7%
C 1
 
2.7%
P 1
 
2.7%
Other Punctuation
ValueCountFrequency (%)
. 7
35.0%
, 6
30.0%
? 5
25.0%
/ 2
 
10.0%
Space Separator
ValueCountFrequency (%)
234
100.0%
Close Punctuation
ValueCountFrequency (%)
) 83
100.0%
Open Punctuation
ValueCountFrequency (%)
( 42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Decimal Number
ValueCountFrequency (%)
0 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13349
96.9%
Common 384
 
2.8%
Latin 37
 
0.3%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1208
 
9.0%
755
 
5.7%
745
 
5.6%
744
 
5.6%
693
 
5.2%
653
 
4.9%
642
 
4.8%
633
 
4.7%
445
 
3.3%
444
 
3.3%
Other values (173) 6387
47.8%
Latin
ValueCountFrequency (%)
I 13
35.1%
T 13
35.1%
S 2
 
5.4%
K 2
 
5.4%
B 1
 
2.7%
G 1
 
2.7%
N 1
 
2.7%
E 1
 
2.7%
C 1
 
2.7%
P 1
 
2.7%
Common
ValueCountFrequency (%)
234
60.9%
) 83
 
21.6%
( 42
 
10.9%
. 7
 
1.8%
, 6
 
1.6%
? 5
 
1.3%
- 4
 
1.0%
/ 2
 
0.5%
0 1
 
0.3%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13347
96.9%
ASCII 421
 
3.1%
Compat Jamo 2
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1208
 
9.1%
755
 
5.7%
745
 
5.6%
744
 
5.6%
693
 
5.2%
653
 
4.9%
642
 
4.8%
633
 
4.7%
445
 
3.3%
444
 
3.3%
Other values (172) 6385
47.8%
ASCII
ValueCountFrequency (%)
234
55.6%
) 83
 
19.7%
( 42
 
10.0%
I 13
 
3.1%
T 13
 
3.1%
. 7
 
1.7%
, 6
 
1.4%
? 5
 
1.2%
- 4
 
1.0%
/ 2
 
0.5%
Other values (10) 12
 
2.9%
Compat Jamo
ValueCountFrequency (%)
2
100.0%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%

노동조합주소
Text

MISSING 

Distinct2185
Distinct (%)87.9%
Missing193
Missing (%)7.2%
Memory size21.1 KiB
2024-05-11T15:23:49.335746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length46
Mean length28.026136
Min length16

Characters and Unicode

Total characters69701
Distinct characters508
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1970 ?
Unique (%)79.2%

Sample

1st row서울특별시 강동구 강일동 679번지 2호 MIDC빌딩
2nd row서울특별시 송파구 풍납동 388번지 1호 서울아산병원
3rd row서울특별시 송파구 문정동 645번지 에이치비지니스파크
4th row서울특별시 송파구 방이동 88번지 15호 한국체육대학교
5th row서울특별시 송파구 마천동 194번지 1호 덕왕기업
ValueCountFrequency (%)
서울특별시 2483
 
18.7%
강남구 416
 
3.1%
1호 292
 
2.2%
중구 254
 
1.9%
영등포구 215
 
1.6%
마포구 158
 
1.2%
2호 150
 
1.1%
서초구 138
 
1.0%
강서구 132
 
1.0%
송파구 129
 
1.0%
Other values (2475) 8927
67.2%
2024-05-11T15:23:50.341828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17046
24.5%
3023
 
4.3%
2664
 
3.8%
2622
 
3.8%
2571
 
3.7%
2550
 
3.7%
2543
 
3.6%
2494
 
3.6%
2486
 
3.6%
2423
 
3.5%
Other values (498) 29279
42.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 41510
59.6%
Space Separator 17046
24.5%
Decimal Number 10437
 
15.0%
Uppercase Letter 322
 
0.5%
Dash Punctuation 178
 
0.3%
Open Punctuation 57
 
0.1%
Close Punctuation 57
 
0.1%
Lowercase Letter 51
 
0.1%
Other Punctuation 34
 
< 0.1%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3023
 
7.3%
2664
 
6.4%
2622
 
6.3%
2571
 
6.2%
2550
 
6.1%
2543
 
6.1%
2494
 
6.0%
2486
 
6.0%
2423
 
5.8%
1711
 
4.1%
Other values (438) 16423
39.6%
Uppercase Letter
ValueCountFrequency (%)
S 36
11.2%
T 33
10.2%
K 32
9.9%
B 31
 
9.6%
C 24
 
7.5%
I 20
 
6.2%
M 20
 
6.2%
D 19
 
5.9%
E 16
 
5.0%
R 12
 
3.7%
Other values (14) 79
24.5%
Lowercase Letter
ValueCountFrequency (%)
e 11
21.6%
s 8
15.7%
r 5
9.8%
t 4
 
7.8%
i 4
 
7.8%
c 4
 
7.8%
a 3
 
5.9%
o 3
 
5.9%
n 3
 
5.9%
b 2
 
3.9%
Other values (4) 4
 
7.8%
Decimal Number
ValueCountFrequency (%)
1 2231
21.4%
2 1288
12.3%
3 1150
11.0%
4 972
9.3%
5 949
9.1%
6 912
8.7%
7 807
 
7.7%
0 791
 
7.6%
8 693
 
6.6%
9 644
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 13
38.2%
. 10
29.4%
/ 9
26.5%
& 1
 
2.9%
1
 
2.9%
Letter Number
ValueCountFrequency (%)
2
66.7%
1
33.3%
Space Separator
ValueCountFrequency (%)
17046
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 178
100.0%
Open Punctuation
ValueCountFrequency (%)
( 57
100.0%
Close Punctuation
ValueCountFrequency (%)
) 57
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 41510
59.6%
Common 27815
39.9%
Latin 376
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3023
 
7.3%
2664
 
6.4%
2622
 
6.3%
2571
 
6.2%
2550
 
6.1%
2543
 
6.1%
2494
 
6.0%
2486
 
6.0%
2423
 
5.8%
1711
 
4.1%
Other values (438) 16423
39.6%
Latin
ValueCountFrequency (%)
S 36
 
9.6%
T 33
 
8.8%
K 32
 
8.5%
B 31
 
8.2%
C 24
 
6.4%
I 20
 
5.3%
M 20
 
5.3%
D 19
 
5.1%
E 16
 
4.3%
R 12
 
3.2%
Other values (30) 133
35.4%
Common
ValueCountFrequency (%)
17046
61.3%
1 2231
 
8.0%
2 1288
 
4.6%
3 1150
 
4.1%
4 972
 
3.5%
5 949
 
3.4%
6 912
 
3.3%
7 807
 
2.9%
0 791
 
2.8%
8 693
 
2.5%
Other values (10) 976
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 41510
59.6%
ASCII 28187
40.4%
Number Forms 3
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17046
60.5%
1 2231
 
7.9%
2 1288
 
4.6%
3 1150
 
4.1%
4 972
 
3.4%
5 949
 
3.4%
6 912
 
3.2%
7 807
 
2.9%
0 791
 
2.8%
8 693
 
2.5%
Other values (47) 1348
 
4.8%
Hangul
ValueCountFrequency (%)
3023
 
7.3%
2664
 
6.4%
2622
 
6.3%
2571
 
6.2%
2550
 
6.1%
2543
 
6.1%
2494
 
6.0%
2486
 
6.0%
2423
 
5.8%
1711
 
4.1%
Other values (438) 16423
39.6%
Number Forms
ValueCountFrequency (%)
2
66.7%
1
33.3%
None
ValueCountFrequency (%)
1
100.0%

Interactions

2024-05-11T15:23:06.408927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T15:23:50.546901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가번호민원구분
인허가번호1.0000.182
민원구분0.1821.000
2024-05-11T15:23:50.709148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가번호민원구분
인허가번호1.0001.000
민원구분1.0001.000

Missing values

2024-05-11T15:23:43.222009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T15:23:43.541131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-05-11T15:23:43.856978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

인허가번호민원구분노동조합단체명사업장명소속단체명노동조합주소
02024324029026100003노동조합변경신고삼성이앤에이 노동조합 &U삼성이앤에이<NA><NA>
12024324029026100002노동조합변경신고안정호한국종합기술전국건설산업노동조합연맹<NA>
22024324029026100001노동조합변경신고도원에프앤지㈜노동조합도원에프앤지<NA>서울특별시 강동구 강일동 679번지 2호 MIDC빌딩
32024323029126100005노동조합설립신고의료연대노동조합(주)우림맨테크<NA>서울특별시 송파구 풍납동 388번지 1호 서울아산병원
42024323029126100004노동조합설립신고클래시스생산본부노동조합문정공장<NA>서울특별시 송파구 문정동 645번지 에이치비지니스파크
52024323029126100002노동조합설립신고교권수호 한국체육대학교 교수 노동조합한국체육대학교<NA>서울특별시 송파구 방이동 88번지 15호 한국체육대학교
62024323029126100001노동조합설립신고덕왕기업㈜ 노동조합덕왕기업㈜<NA>서울특별시 송파구 마천동 194번지 1호 덕왕기업
72024322025026100002노동조합설립신고유니티테크놀로지코리아(유) 노동조합유니티테크놀로지<NA>서울특별시 강남구 역삼동 648번지 9호 21층
82024322025026100001노동조합설립신고태화태화용역<NA>서울특별시 강남구 일원동 639번지 1호 동아빌딩-B01
92024321019526100002노동조합설립신고(주)성광환경기업노동조합(주)성광환경<NA>서울특별시 서초구 원지동 23번지 서초구청소종합시설
인허가번호민원구분노동조합단체명사업장명소속단체명노동조합주소
26701969307011826100001노동조합해산신고대진여객(주) 노동조합대진여객(주)전국자동차노동조합연맹서울특별시 성북구 정릉동 820번지 18호
26711968303010326100002노동조합해산신고서울버스노동조합 태진운수지부서울버스노동조합<NA>서울특별시 성동구 성수동2가 649번지 1호
26721967301010026101201노동조합변경신고뱅크오브아메리카서울지점뱅크오브아메리카서울지점전국민주금융노동조합서울특별시 중구 태평로1가 84번지 파이낸스빌딩
26731967301010026101025노동조합설립신고서울클럽사단법인 서울클럽<NA>서울특별시 중구 장충동2가 208번지 서울클럽
26741966307011826100001노동조합해산신고대진여객 노동조합대진여객전국자동차노동조합서울특별시 성북구 정릉동 818번지
26751965307011826100001노동조합해산신고도원교통 노동조합도원교통(주)전자노련 서울버스서울특별시 성북구 정릉동 893번지 1호
26761963320009926100001노동조합설립신고한남여객지부(주)한남운수전국자동차노동조합연맹서울특별시 관악구 신림동 241번지 42호
26771963301010026100308노동조합해산신고국립중앙의료원 노동조합국립중앙의료원전국보건의료노동조합서울특별시 중구 을지로6가 18번지 79호
267819626110000101900001노동조합변경신고서울특별시청노동조합서울특별시청한국노총서울특별시 성동구 마장동 527번지
26791961307011826100001노동조합해산신고상진운수 노동조합상진운수주식회사서울시버스노동조합서울특별시 성북구 석관동 124번지 9호