Overview

Dataset statistics

Number of variables8
Number of observations92
Missing cells17
Missing cells (%)2.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.1 KiB
Average record size in memory67.4 B

Variable types

Numeric2
Text5
Categorical1

Dataset

Description근로복지공단 공단본부와 지사 현황입니다. (기관명,주소,관할구역,우편번호,대표전화번호,전자팩스번호,이용시간 등)
URLhttps://www.data.go.kr/data/15049970/fileData.do

Alerts

이용시간 has constant value ""Constant
관할구역 has 17 (18.5%) missing valuesMissing
연번 has unique valuesUnique
기관(지사)명 has unique valuesUnique
대표 전화번호 has unique valuesUnique
대표 전자팩스 has unique valuesUnique

Reproduction

Analysis started2023-12-11 23:02:03.822794
Analysis finished2023-12-11 23:02:05.022221
Duration1.2 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct92
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.5
Minimum1
Maximum92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size960.0 B
2023-12-12T08:02:05.138031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.55
Q123.75
median46.5
Q369.25
95-th percentile87.45
Maximum92
Range91
Interquartile range (IQR)45.5

Descriptive statistics

Standard deviation26.70206
Coefficient of variation (CV)0.57423785
Kurtosis-1.2
Mean46.5
Median Absolute Deviation (MAD)23
Skewness0
Sum4278
Variance713
MonotonicityStrictly increasing
2023-12-12T08:02:05.308127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.1%
60 1
 
1.1%
69 1
 
1.1%
68 1
 
1.1%
67 1
 
1.1%
66 1
 
1.1%
65 1
 
1.1%
64 1
 
1.1%
63 1
 
1.1%
62 1
 
1.1%
Other values (82) 82
89.1%
ValueCountFrequency (%)
1 1
1.1%
2 1
1.1%
3 1
1.1%
4 1
1.1%
5 1
1.1%
6 1
1.1%
7 1
1.1%
8 1
1.1%
9 1
1.1%
10 1
1.1%
ValueCountFrequency (%)
92 1
1.1%
91 1
1.1%
90 1
1.1%
89 1
1.1%
88 1
1.1%
87 1
1.1%
86 1
1.1%
85 1
1.1%
84 1
1.1%
83 1
1.1%

기관(지사)명
Text

UNIQUE 

Distinct92
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size868.0 B
2023-12-12T08:02:05.650291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length4
Mean length5.8804348
Min length4

Characters and Unicode

Total characters541
Distinct characters95
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique92 ?
Unique (%)100.0%

Sample

1st row공단본부
2nd row산업재해보상보험심사위원회
3rd row서울지역본부
4th row서울강남지사
5th row서울동부지사
ValueCountFrequency (%)
공단본부 1
 
1.1%
여수지사 1
 
1.1%
보령지사 1
 
1.1%
충주지사 1
 
1.1%
천안지사 1
 
1.1%
청주지사 1
 
1.1%
대전동부지사 1
 
1.1%
대전지역본부 1
 
1.1%
광주업무상질병판정위원회 1
 
1.1%
순천지사 1
 
1.1%
Other values (82) 82
89.1%
2023-12-12T08:02:06.150414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 64
 
11.8%
사 61
 
11.3%
부 30
 
5.5%
원 26
 
4.8%
병 18
 
3.3%
서 17
 
3.1%
산 16
 
3.0%
울 13
 
2.4%
대 11
 
2.0%
주 10
 
1.8%
Other values (85) 275
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 541
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 64
 
11.8%
사 61
 
11.3%
부 30
 
5.5%
원 26
 
4.8%
병 18
 
3.3%
서 17
 
3.1%
산 16
 
3.0%
울 13
 
2.4%
대 11
 
2.0%
주 10
 
1.8%
Other values (85) 275
50.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 541
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 64
 
11.8%
사 61
 
11.3%
부 30
 
5.5%
원 26
 
4.8%
병 18
 
3.3%
서 17
 
3.1%
산 16
 
3.0%
울 13
 
2.4%
대 11
 
2.0%
주 10
 
1.8%
Other values (85) 275
50.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 541
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 64
 
11.8%
사 61
 
11.3%
부 30
 
5.5%
원 26
 
4.8%
병 18
 
3.3%
서 17
 
3.1%
산 16
 
3.0%
울 13
 
2.4%
대 11
 
2.0%
주 10
 
1.8%
Other values (85) 275
50.8%

주소
Text

Distinct91
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size868.0 B
2023-12-12T08:02:06.492076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length35
Mean length26.108696
Min length16

Characters and Unicode

Total characters2402
Distinct characters224
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)97.8%

Sample

1st row울산 중구 종가로 340(교동)
2nd row서울 영등포구 버드나루로2길 8, 5층(영등포동2가)
3rd row서울 중구 퇴계로 173, 19층(충무로3가)
4th row서울 강남구 테헤란로 418 8-10층(대치동)
5th row서울 송파구 송파대로 558, 14-15층(신천동, 월드타워빌딩)
ValueCountFrequency (%)
서울 14
 
2.9%
경기 13
 
2.7%
강원 8
 
1.6%
경남 7
 
1.4%
인천 7
 
1.4%
부산 6
 
1.2%
부평구 6
 
1.2%
중앙대로 6
 
1.2%
대전 5
 
1.0%
경북 5
 
1.0%
Other values (339) 412
84.3%
2023-12-12T08:02:07.005536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
397
 
16.5%
, 100
 
4.2%
로 90
 
3.7%
동 89
 
3.7%
1 85
 
3.5%
( 81
 
3.4%
) 81
 
3.4%
구 75
 
3.1%
층 74
 
3.1%
3 58
 
2.4%
Other values (214) 1272
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1290
53.7%
Decimal Number 421
 
17.5%
Space Separator 397
 
16.5%
Other Punctuation 101
 
4.2%
Open Punctuation 81
 
3.4%
Close Punctuation 81
 
3.4%
Math Symbol 14
 
0.6%
Dash Punctuation 12
 
0.5%
Uppercase Letter 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 90
 
7.0%
동 89
 
6.9%
구 75
 
5.8%
층 74
 
5.7%
시 45
 
3.5%
대 40
 
3.1%
산 38
 
2.9%
경 32
 
2.5%
남 27
 
2.1%
서 25
 
1.9%
Other values (192) 755
58.5%
Decimal Number
ValueCountFrequency (%)
1 85
20.2%
3 58
13.8%
2 52
12.4%
4 42
10.0%
8 41
9.7%
7 36
8.6%
6 35
8.3%
5 33
 
7.8%
0 21
 
5.0%
9 18
 
4.3%
Math Symbol
ValueCountFrequency (%)
∼ 8
57.1%
~ 5
35.7%
～ 1
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
K 2
40.0%
T 2
40.0%
G 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 100
99.0%
& 1
 
1.0%
Space Separator
ValueCountFrequency (%)
397
100.0%
Open Punctuation
ValueCountFrequency (%)
( 81
100.0%
Close Punctuation
ValueCountFrequency (%)
) 81
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1290
53.7%
Common 1107
46.1%
Latin 5
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 90
 
7.0%
동 89
 
6.9%
구 75
 
5.8%
층 74
 
5.7%
시 45
 
3.5%
대 40
 
3.1%
산 38
 
2.9%
경 32
 
2.5%
남 27
 
2.1%
서 25
 
1.9%
Other values (192) 755
58.5%
Common
ValueCountFrequency (%)
397
35.9%
, 100
 
9.0%
1 85
 
7.7%
( 81
 
7.3%
) 81
 
7.3%
3 58
 
5.2%
2 52
 
4.7%
4 42
 
3.8%
8 41
 
3.7%
7 36
 
3.3%
Other values (9) 134
 
12.1%
Latin
ValueCountFrequency (%)
K 2
40.0%
T 2
40.0%
G 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1290
53.7%
ASCII 1103
45.9%
Math Operators 8
 
0.3%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
397
36.0%
, 100
 
9.1%
1 85
 
7.7%
( 81
 
7.3%
) 81
 
7.3%
3 58
 
5.3%
2 52
 
4.7%
4 42
 
3.8%
8 41
 
3.7%
7 36
 
3.3%
Other values (10) 130
 
11.8%
Hangul
ValueCountFrequency (%)
로 90
 
7.0%
동 89
 
6.9%
구 75
 
5.8%
층 74
 
5.7%
시 45
 
3.5%
대 40
 
3.1%
산 38
 
2.9%
경 32
 
2.5%
남 27
 
2.1%
서 25
 
1.9%
Other values (192) 755
58.5%
Math Operators
ValueCountFrequency (%)
∼ 8
100.0%
None
ValueCountFrequency (%)
～ 1
100.0%

관할구역
Text

MISSING 

Distinct75
Distinct (%)100.0%
Missing17
Missing (%)18.5%
Memory size868.0 B
2023-12-12T08:02:07.203206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length36
Mean length22.413333
Min length5

Characters and Unicode

Total characters1681
Distinct characters162
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)100.0%

Sample

1st row서울특별시 중구,종로구,동대문구
2nd row서울특별시 강남구
3rd row서울특별시 송파구,광진구,강동구
4th row서울특별시 마포구,서대문구,용산구,은평구
5th row서울특별시 영등포구,강서구,양천구
ValueCountFrequency (%)
경기도 14
 
6.9%
서울특별시 9
 
4.5%
경상북도 8
 
4.0%
강원도 6
 
3.0%
경상남도 6
 
3.0%
전라남도 5
 
2.5%
소재하는 5
 
2.5%
부산광역시 5
 
2.5%
전라북도 4
 
2.0%
대전광역시 4
 
2.0%
Other values (115) 136
67.3%
2023-12-12T08:02:07.583725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 214
 
12.7%
128
 
7.6%
시 128
 
7.6%
군 87
 
5.2%
구 79
 
4.7%
도 72
 
4.3%
광 37
 
2.2%
남 37
 
2.2%
경 35
 
2.1%
서 33
 
2.0%
Other values (152) 831
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1331
79.2%
Other Punctuation 214
 
12.7%
Space Separator 128
 
7.6%
Close Punctuation 4
 
0.2%
Open Punctuation 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 128
 
9.6%
군 87
 
6.5%
구 79
 
5.9%
도 72
 
5.4%
광 37
 
2.8%
남 37
 
2.8%
경 35
 
2.6%
서 33
 
2.5%
천 32
 
2.4%
주 32
 
2.4%
Other values (148) 759
57.0%
Other Punctuation
ValueCountFrequency (%)
, 214
100.0%
Space Separator
ValueCountFrequency (%)
128
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1331
79.2%
Common 350
 
20.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 128
 
9.6%
군 87
 
6.5%
구 79
 
5.9%
도 72
 
5.4%
광 37
 
2.8%
남 37
 
2.8%
경 35
 
2.6%
서 33
 
2.5%
천 32
 
2.4%
주 32
 
2.4%
Other values (148) 759
57.0%
Common
ValueCountFrequency (%)
, 214
61.1%
128
36.6%
) 4
 
1.1%
( 4
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1331
79.2%
ASCII 350
 
20.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 214
61.1%
128
36.6%
) 4
 
1.1%
( 4
 
1.1%
Hangul
ValueCountFrequency (%)
시 128
 
9.6%
군 87
 
6.5%
구 79
 
5.9%
도 72
 
5.4%
광 37
 
2.8%
남 37
 
2.8%
경 35
 
2.6%
서 33
 
2.5%
천 32
 
2.4%
주 32
 
2.4%
Other values (148) 759
57.0%

우편번호
Real number (ℝ)

Distinct81
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31236.391
Minimum2098
Maximum63225
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size960.0 B
2023-12-12T08:02:07.752471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2098
5-th percentile4679.4
Q116117.75
median29825
Q346722
95-th percentile60594.15
Maximum63225
Range61127
Interquartile range (IQR)30604.25

Descriptive statistics

Standard deviation17955.238
Coefficient of variation (CV)0.57481792
Kurtosis-1.1735745
Mean31236.391
Median Absolute Deviation (MAD)15019
Skewness0.1012869
Sum2873748
Variance3.2239055 × 108
MonotonicityNot monotonic
2023-12-12T08:02:07.885987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21417 5
 
5.4%
7254 4
 
4.3%
35209 3
 
3.3%
61687 2
 
2.2%
48731 2
 
2.2%
58730 1
 
1.1%
34675 1
 
1.1%
57934 1
 
1.1%
62363 1
 
1.1%
63225 1
 
1.1%
Other values (71) 71
77.2%
ValueCountFrequency (%)
2098 1
1.1%
3143 1
1.1%
4108 1
1.1%
4548 1
1.1%
4554 1
1.1%
4782 1
1.1%
5510 1
1.1%
6193 1
1.1%
6720 1
1.1%
7071 1
1.1%
ValueCountFrequency (%)
63225 1
1.1%
62363 1
1.1%
61925 1
1.1%
61687 2
2.2%
59700 1
1.1%
58730 1
1.1%
57947 1
1.1%
57934 1
1.1%
55014 1
1.1%
54552 1
1.1%

대표 전화번호
Text

UNIQUE 

Distinct92
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size868.0 B
2023-12-12T08:02:08.173483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.978261
Min length11

Characters and Unicode

Total characters1102
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

Unique92 ?
Unique (%)100.0%

Sample

1st row052-704-7040
2nd row02-2109-3611
3rd row02-2230-9789
4th row02-3459-7182
5th row02-3433-1370
ValueCountFrequency (%)
052-704-7040 1
 
1.1%
061-680-0150 1
 
1.1%
041-939-2256 1
 
1.1%
043-840-0342 1
 
1.1%
041-629-5171 1
 
1.1%
043-229-5090 1
 
1.1%
042-722-4111 1
 
1.1%
042-870-9201 1
 
1.1%
062-975-0500 1
 
1.1%
061-805-0220 1
 
1.1%
Other values (82) 82
89.1%
2023-12-12T08:02:08.564976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 221
20.1%
- 184
16.7%
1 128
11.6%
2 102
9.3%
5 99
9.0%
3 93
8.4%
4 79
 
7.2%
6 61
 
5.5%
7 57
 
5.2%
8 40
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 918
83.3%
Dash Punctuation 184
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 221
24.1%
1 128
13.9%
2 102
11.1%
5 99
10.8%
3 93
10.1%
4 79
 
8.6%
6 61
 
6.6%
7 57
 
6.2%
8 40
 
4.4%
9 38
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 184
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1102
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 221
20.1%
- 184
16.7%
1 128
11.6%
2 102
9.3%
5 99
9.0%
3 93
8.4%
4 79
 
7.2%
6 61
 
5.5%
7 57
 
5.2%
8 40
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1102
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 221
20.1%
- 184
16.7%
1 128
11.6%
2 102
9.3%
5 99
9.0%
3 93
8.4%
4 79
 
7.2%
6 61
 
5.5%
7 57
 
5.2%
8 40
 
3.6%

대표 전자팩스
Text

UNIQUE 

Distinct92
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size868.0 B
2023-12-12T08:02:08.876076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length13
Mean length12.869565
Min length12

Characters and Unicode

Total characters1184
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

Unique92 ?
Unique (%)100.0%

Sample

1st row0505-073-1210
2nd row0505-175-7777
3rd row0505-282-1201
4th row0505-084-1103
5th row0505-847-1100
ValueCountFrequency (%)
0505-073-1210 1
 
1.1%
0505-731-1100 1
 
1.1%
0505-765-1100 1
 
1.1%
0505-847-1101 1
 
1.1%
0505-838-1101 1
 
1.1%
0505-845-1101 1
 
1.1%
0505-720-5898 1
 
1.1%
0505-235-1101 1
 
1.1%
0505-282-8116 1
 
1.1%
0505-838-4100 1
 
1.1%
Other values (82) 82
89.1%
2023-12-12T08:02:09.345178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 311
26.3%
1 201
17.0%
5 200
16.9%
- 184
15.5%
3 65
 
5.5%
2 56
 
4.7%
8 49
 
4.1%
7 39
 
3.3%
4 33
 
2.8%
9 29
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
84.5%
Dash Punctuation 184
 
15.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 311
31.1%
1 201
20.1%
5 200
20.0%
3 65
 
6.5%
2 56
 
5.6%
8 49
 
4.9%
7 39
 
3.9%
4 33
 
3.3%
9 29
 
2.9%
6 17
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 184
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1184
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 311
26.3%
1 201
17.0%
5 200
16.9%
- 184
15.5%
3 65
 
5.5%
2 56
 
4.7%
8 49
 
4.1%
7 39
 
3.3%
4 33
 
2.8%
9 29
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1184
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 311
26.3%
1 201
17.0%
5 200
16.9%
- 184
15.5%
3 65
 
5.5%
2 56
 
4.7%
8 49
 
4.1%
7 39
 
3.3%
4 33
 
2.8%
9 29
 
2.4%

이용시간
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size868.0 B
평일 09:00~18:00
92 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row평일 09:00~18:00
2nd row평일 09:00~18:00
3rd row평일 09:00~18:00
4th row평일 09:00~18:00
5th row평일 09:00~18:00

Common Values

ValueCountFrequency (%)
평일 09:00~18:00 92
100.0%

Length

2023-12-12T08:02:09.513606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:02:09.608912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
평일 92
50.0%
09:00~18:00 92
50.0%

Interactions

2023-12-12T08:02:04.628710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:04.465488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:04.718687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:04.533973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:02:09.674674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번기관(지사)명주소관할구역우편번호대표 전화번호대표 전자팩스
연번1.0001.0000.9501.0000.9011.0001.000
기관(지사)명1.0001.0001.0001.0001.0001.0001.000
주소0.9501.0001.0001.0001.0001.0001.000
관할구역1.0001.0001.0001.0001.0001.0001.000
우편번호0.9011.0001.0001.0001.0001.0001.000
대표 전화번호1.0001.0001.0001.0001.0001.0001.000
대표 전자팩스1.0001.0001.0001.0001.0001.0001.000
2023-12-12T08:02:10.068761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번우편번호
연번1.0000.224
우편번호0.2241.000

Missing values

2023-12-12T08:02:04.836303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:02:04.958825image/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.

Sample

연번기관(지사)명주소관할구역우편번호대표 전화번호대표 전자팩스이용시간
01공단본부울산 중구 종가로 340(교동)<NA>44428052-704-70400505-073-1210평일 09:00~18:00
12산업재해보상보험심사위원회서울 영등포구 버드나루로2길 8, 5층(영등포동2가)<NA>725402-2109-36110505-175-7777평일 09:00~18:00
23서울지역본부서울 중구 퇴계로 173, 19층(충무로3가)서울특별시 중구,종로구,동대문구455402-2230-97890505-282-1201평일 09:00~18:00
34서울강남지사서울 강남구 테헤란로 418 8-10층(대치동)서울특별시 강남구619302-3459-71820505-084-1103평일 09:00~18:00
45서울동부지사서울 송파구 송파대로 558, 14-15층(신천동, 월드타워빌딩)서울특별시 송파구,광진구,강동구551002-3433-13700505-847-1100평일 09:00~18:00
56서울서부지사서울 마포구 백범로 23, 8-11층(신수동)서울특별시 마포구,서대문구,용산구,은평구410802-2077-01500505-381-1101평일 09:00~18:00
67서울남부지사서울 영등포구 버드나루로2길 8, 3층(영등포동2가)서울특별시 영등포구,강서구,양천구725402-2165-31000505-332-1101평일 09:00~18:00
78서울북부지사서울 중랑구 망우로 307, 6층(상봉1동,리베로빌딩)서울특별시 중랑구,성북구,도봉구,강북구,노원구209802-944-82220505-377-1101평일 09:00~18:00
89서울관악지사서울 동작구 보라매로5길 23, 6-7층(신대방봉, 삼성보라매옴니타워)서울특별시 관악구,구로구,금천구,동작구707102-2109-23200505-329-1101평일 09:00~18:00
910서울서초지사서울 서초구 효령로 304, 16층(서초동, 국제전자센터)서울특별시 서초구672002-6250-72120505-560-1100평일 09:00~18:00
연번기관(지사)명주소관할구역우편번호대표 전화번호대표 전자팩스이용시간
8283대전병원대전광역시 대덕구 계족로 637 (법동285-3)<NA>34384042-670-5114042-631-8250평일 09:00~18:00
8384태백병원강원 태백시 보드미길 8(장성동)<NA>26052033-580-3114033-581-8547평일 09:00~18:00
8485동해병원강원 동해시 하평로 11(평릉동)<NA>25738033-530-3100033-532-3136평일 09:00~18:00
8586정선병원강원 정선군 정선읍 봉양1길 145<NA>26129033-560-7100033-562-8110평일 09:00~18:00
8687경기요양병원경기 화성시 우정읍 쌍봉로 465-4<NA>18558031-351-3083031-351-3086평일 09:00~18:00
8788인재개발원충북 진천군 광혜원면 구암길 64-13<NA>27803043-539-55070505-099-1206평일 09:00~18:00
8889직업환경연구원인천 부평구 무네미로 478, 본관 2층(구산동)<NA>21417032-540-4961032-540-4998평일 09:00~18:00
8990근로복지연구원서울 영등포구 버드나루로2길 8, 3층(영등포동2가)<NA>725402-2670-04670505-139-0430평일 09:00~18:00
9091재활공학연구소인천 부평구 경인로10번길 26, (구산동)<NA>21417032-509-5300032-512-9794평일 09:00~18:00
9192고객센터광주 남구 봉선로 1, 2층(봉선동)<NA>61687062-975-05510505-545-1200평일 09:00~18:00