Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory130.0 B

Variable types

Numeric2
Categorical1
Text8
Boolean2
DateTime2

Dataset

Description공공기관이 등록하여 공공데이터포털에서 개방중인 목록 정보(목록명, 목록타입(파일, API), 표준데이터 여부, 국가중점여부, 등록기관, 기관 분류, 분류체계, 등록일, 마지막 수정일) 를 제공합니다.
Author공공데이터활용지원센터
URLhttps://www.data.go.kr/data/15062804/fileData.do

Alerts

표준데이터여부 is highly overall correlated with 목록유형High correlation
목록유형 is highly overall correlated with 표준데이터여부High correlation
목록키 is highly overall correlated with 조회수High correlation
조회수 is highly overall correlated with 목록키High correlation
목록유형 is highly imbalanced (76.8%)Imbalance
국가중점여부 is highly imbalanced (72.6%)Imbalance
표준데이터여부 is highly imbalanced (96.1%)Imbalance
조회수 is highly skewed (γ1 = 20.23009052)Skewed
목록키 has unique valuesUnique
URL has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:34:55.262092
Analysis finished2024-04-06 08:35:01.994057
Duration6.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

목록키
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14012629
Minimum2414851
Maximum15127409
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T17:35:02.169275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2414851
5-th percentile3074654
Q115045232
median15085084
Q315119167
95-th percentile15125466
Maximum15127409
Range12712558
Interquartile range (IQR)73934.75

Descriptive statistics

Standard deviation3426729.7
Coefficient of variation (CV)0.24454581
Kurtosis6.3110468
Mean14012629
Median Absolute Deviation (MAD)35181
Skewness-2.8824567
Sum1.4012629 × 1011
Variance1.1742477 × 1013
MonotonicityNot monotonic
2024-04-06T17:35:02.452886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3068269 1
 
< 0.1%
15120152 1
 
< 0.1%
15046050 1
 
< 0.1%
15052757 1
 
< 0.1%
15068943 1
 
< 0.1%
15045905 1
 
< 0.1%
15124385 1
 
< 0.1%
15100225 1
 
< 0.1%
15044010 1
 
< 0.1%
15118468 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
2414851 1
< 0.1%
2805258 1
< 0.1%
3033244 1
< 0.1%
3033249 1
< 0.1%
3033255 1
< 0.1%
3033273 1
< 0.1%
3033292 1
< 0.1%
3033301 1
< 0.1%
3033302 1
< 0.1%
3033333 1
< 0.1%
ValueCountFrequency (%)
15127409 1
< 0.1%
15127401 1
< 0.1%
15127399 1
< 0.1%
15127398 1
< 0.1%
15127395 1
< 0.1%
15127394 1
< 0.1%
15127386 1
< 0.1%
15127384 1
< 0.1%
15127381 1
< 0.1%
15127376 1
< 0.1%

목록유형
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
FILE
9354 
API
 
604
STD
 
42

Length

Max length4
Median length4
Mean length3.9354
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFILE
2nd rowFILE
3rd rowFILE
4th rowFILE
5th rowFILE

Common Values

ValueCountFrequency (%)
FILE 9354
93.5%
API 604
 
6.0%
STD 42
 
0.4%

Length

2024-04-06T17:35:02.716549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:35:02.909585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
file 9354
93.5%
api 604
 
6.0%
std 42
 
0.4%

목록명
Text

Distinct9997
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-06T17:35:03.247496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length52
Mean length21.1134
Min length6

Characters and Unicode

Total characters211134
Distinct characters768
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9994 ?
Unique (%)99.9%

Sample

1st row병무청_승선근무예비역 인원배정 명부
2nd row경상북도 포항시_코로나 일일확진자 수
3rd row해양경찰청_수상안전종합관리_첨부파일관리
4th row인천광역시 서구_소아과의원
5th row충청남도_여성새로일하기센터 현황
ValueCountFrequency (%)
현황 2680
 
9.5%
정보 679
 
2.4%
경기도 485
 
1.7%
및 459
 
1.6%
인천광역시 408
 
1.4%
부산광역시 299
 
1.1%
서울특별시 243
 
0.9%
전라남도 240
 
0.8%
경상남도 212
 
0.7%
전북특별자치도 185
 
0.7%
Other values (14156) 22431
79.2%
2024-04-06T17:35:03.947091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18343
 
8.7%
_ 12013
 
5.7%
시 5709
 
2.7%
현 4820
 
2.3%
황 4793
 
2.3%
도 4728
 
2.2%
정 3565
 
1.7%
보 3530
 
1.7%
국 3482
 
1.6%
공 3352
 
1.6%
Other values (758) 146799
69.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 175748
83.2%
Space Separator 18343
 
8.7%
Connector Punctuation 12013
 
5.7%
Uppercase Letter 1822
 
0.9%
Close Punctuation 1026
 
0.5%
Open Punctuation 1025
 
0.5%
Decimal Number 786
 
0.4%
Lowercase Letter 267
 
0.1%
Other Punctuation 71
 
< 0.1%
Other Symbol 19
 
< 0.1%
Other values (2) 14
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 5709
 
3.2%
현 4820
 
2.7%
황 4793
 
2.7%
도 4728
 
2.7%
정 3565
 
2.0%
보 3530
 
2.0%
국 3482
 
2.0%
공 3352
 
1.9%
기 3233
 
1.8%
광 3058
 
1.7%
Other values (686) 135478
77.1%
Uppercase Letter
ValueCountFrequency (%)
S 198
 
10.9%
I 172
 
9.4%
D 132
 
7.2%
P 127
 
7.0%
C 122
 
6.7%
A 113
 
6.2%
T 110
 
6.0%
O 95
 
5.2%
R 83
 
4.6%
B 70
 
3.8%
Other values (15) 600
32.9%
Lowercase Letter
ValueCountFrequency (%)
e 40
15.0%
n 28
10.5%
a 26
9.7%
c 22
 
8.2%
i 21
 
7.9%
o 17
 
6.4%
t 14
 
5.2%
s 12
 
4.5%
u 12
 
4.5%
l 11
 
4.1%
Other values (14) 64
24.0%
Decimal Number
ValueCountFrequency (%)
1 247
31.4%
2 108
13.7%
0 95
 
12.1%
3 86
 
10.9%
9 73
 
9.3%
5 59
 
7.5%
4 47
 
6.0%
8 36
 
4.6%
7 19
 
2.4%
6 16
 
2.0%
Other Punctuation
ValueCountFrequency (%)
· 31
43.7%
/ 22
31.0%
, 7
 
9.9%
. 7
 
9.9%
? 3
 
4.2%
& 1
 
1.4%
Space Separator
ValueCountFrequency (%)
18343
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 12013
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1026
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1025
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 19
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 175764
83.2%
Common 33277
 
15.8%
Latin 2090
 
1.0%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 5709
 
3.2%
현 4820
 
2.7%
황 4793
 
2.7%
도 4728
 
2.7%
정 3565
 
2.0%
보 3530
 
2.0%
국 3482
 
2.0%
공 3352
 
1.9%
기 3233
 
1.8%
광 3058
 
1.7%
Other values (684) 135494
77.1%
Latin
ValueCountFrequency (%)
S 198
 
9.5%
I 172
 
8.2%
D 132
 
6.3%
P 127
 
6.1%
C 122
 
5.8%
A 113
 
5.4%
T 110
 
5.3%
O 95
 
4.5%
R 83
 
4.0%
B 70
 
3.3%
Other values (40) 868
41.5%
Common
ValueCountFrequency (%)
18343
55.1%
_ 12013
36.1%
) 1026
 
3.1%
( 1025
 
3.1%
1 247
 
0.7%
2 108
 
0.3%
0 95
 
0.3%
3 86
 
0.3%
9 73
 
0.2%
5 59
 
0.2%
Other values (11) 202
 
0.6%
Han
ValueCountFrequency (%)
圖 1
33.3%
次 1
33.3%
班 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 175745
83.2%
ASCII 35335
 
16.7%
None 50
 
< 0.1%
CJK 3
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18343
51.9%
_ 12013
34.0%
) 1026
 
2.9%
( 1025
 
2.9%
1 247
 
0.7%
S 198
 
0.6%
I 172
 
0.5%
D 132
 
0.4%
P 127
 
0.4%
C 122
 
0.3%
Other values (59) 1930
 
5.5%
Hangul
ValueCountFrequency (%)
시 5709
 
3.2%
현 4820
 
2.7%
황 4793
 
2.7%
도 4728
 
2.7%
정 3565
 
2.0%
보 3530
 
2.0%
국 3482
 
2.0%
공 3352
 
1.9%
기 3233
 
1.8%
광 3058
 
1.7%
Other values (683) 135475
77.1%
None
ValueCountFrequency (%)
· 31
62.0%
㈜ 19
38.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%
CJK
ValueCountFrequency (%)
圖 1
33.3%
次 1
33.3%
班 1
33.3%

목록설명
Text

Distinct9834
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-06T17:35:04.613055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1024
Median length594
Mean length96.6837
Min length9

Characters and Unicode

Total characters966837
Distinct characters1172
Distinct categories19 ?
Distinct scripts5 ?
Distinct blocks15 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9799 ?
Unique (%)98.0%

Sample

1st row승선근무예비역은 전시사변 또는 비상시 국민경제에 긴요한 물자와 군수물자를 수송하기 위한 업무 또는 이와 관련된 업무의 지원을 위하여 소집되어 승선근무하는 병역대체복무제도입니다.<br/>2024년 승선근무예비역에 대하여 해운업체, 수산업체별 인원배정한 명부입니다.
2nd row공공데이터 제공 신청에 따른 2020년 포항시 코로나 일일확진자 수(남구, 북구, 총 누적)에 대한 데이터를 제공합니다
3rd row메타관리시스템 기반 공공데이터 개방계획 수립 및 이행을 위한 수상구조사 시스템의 수상안전종합관리 첨부파일관리 데이터로 파일 ID, 파일생성일, 사용여부 등의 항목을 제공합니다.
4th row인천광역시 서구 소아과의원의 현황에 대한 데이터입니다. 이 데이터는 의원명, 소재지, 전화번호 등에 대한 정보를 제공합니다.
5th row여성새로일하기센터를 명칭, 지정일, 소재지, 전화번호, 종사자 수, 시설규모, 법인명으로 나열하여 개방하고자 합니다.
ValueCountFrequency (%)
대한 3599
 
2.0%
제공합니다 3051
 
1.7%
및 2446
 
1.4%
정보를 1997
 
1.1%
데이터로 1979
 
1.1%
1976
 
1.1%
등의 1681
 
0.9%
있습니다 1518
 
0.9%
등 1512
 
0.8%
수 1024
 
0.6%
Other values (48986) 157186
88.3%
2024-04-06T17:35:05.509077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
170889
 
17.7%
, 36837
 
3.8%
이 12315
 
1.3%
. 12298
 
1.3%
공 12122
 
1.3%
다 11324
 
1.2%
시 11262
 
1.2%
정 11073
 
1.1%
니 10553
 
1.1%
기 9752
 
1.0%
Other values (1162) 668412
69.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 649076
67.1%
Space Separator 170893
 
17.7%
Other Punctuation 61726
 
6.4%
Lowercase Letter 24628
 
2.5%
Decimal Number 19163
 
2.0%
Math Symbol 13782
 
1.4%
Uppercase Letter 8492
 
0.9%
Close Punctuation 7706
 
0.8%
Open Punctuation 7636
 
0.8%
Dash Punctuation 1819
 
0.2%
Other values (9) 1916
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 12315
 
1.9%
공 12122
 
1.9%
다 11324
 
1.7%
시 11262
 
1.7%
정 11073
 
1.7%
니 10553
 
1.6%
기 9752
 
1.5%
에 9681
 
1.5%
의 9536
 
1.5%
보 9528
 
1.5%
Other values (1012) 541930
83.5%
Lowercase Letter
ValueCountFrequency (%)
r 7175
29.1%
b 6615
26.9%
t 1021
 
4.1%
o 971
 
3.9%
e 967
 
3.9%
s 945
 
3.8%
a 792
 
3.2%
n 666
 
2.7%
i 665
 
2.7%
p 593
 
2.4%
Other values (18) 4218
17.1%
Uppercase Letter
ValueCountFrequency (%)
S 933
 
11.0%
I 899
 
10.6%
P 602
 
7.1%
D 563
 
6.6%
A 521
 
6.1%
T 513
 
6.0%
C 472
 
5.6%
R 402
 
4.7%
O 362
 
4.3%
M 344
 
4.1%
Other values (16) 2881
33.9%
Other Symbol
ValueCountFrequency (%)
㎡ 72
31.3%
○ 63
27.4%
㎥ 31
13.5%
㎎ 23
 
10.0%
□ 9
 
3.9%
㎢ 6
 
2.6%
● 5
 
2.2%
℃ 4
 
1.7%
☎ 3
 
1.3%
㎍ 3
 
1.3%
Other values (9) 11
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 36837
59.7%
. 12298
 
19.9%
/ 8043
 
13.0%
: 2017
 
3.3%
· 749
 
1.2%
" 548
 
0.9%
* 388
 
0.6%
※ 250
 
0.4%
' 242
 
0.4%
? 134
 
0.2%
Other values (8) 220
 
0.4%
Math Symbol
ValueCountFrequency (%)
> 6578
47.7%
< 6393
46.4%
~ 519
 
3.8%
= 128
 
0.9%
⊙ 77
 
0.6%
+ 62
 
0.4%
→ 18
 
0.1%
× 2
 
< 0.1%
∑ 2
 
< 0.1%
～ 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
Other Number
ValueCountFrequency (%)
① 13
22.8%
② 12
21.1%
③ 11
19.3%
④ 5
 
8.8%
₂ 4
 
7.0%
⑤ 3
 
5.3%
⑥ 3
 
5.3%
₃ 2
 
3.5%
⑦ 1
 
1.8%
⑨ 1
 
1.8%
Other values (2) 2
 
3.5%
Decimal Number
ValueCountFrequency (%)
2 5343
27.9%
0 4227
22.1%
1 3414
17.8%
3 1664
 
8.7%
4 911
 
4.8%
5 826
 
4.3%
9 767
 
4.0%
6 726
 
3.8%
8 663
 
3.5%
7 622
 
3.2%
Close Punctuation
ValueCountFrequency (%)
) 7479
97.1%
] 158
 
2.1%
」 66
 
0.9%
} 2
 
< 0.1%
』 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 7410
97.0%
[ 159
 
2.1%
「 64
 
0.8%
{ 2
 
< 0.1%
『 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
170889
> 99.9%
　 4
 
< 0.1%
Control
ValueCountFrequency (%)
432
53.7%
372
46.3%
Final Punctuation
ValueCountFrequency (%)
’ 56
84.8%
” 10
 
15.2%
Initial Punctuation
ValueCountFrequency (%)
‘ 45
81.8%
“ 10
 
18.2%
Letter Number
ValueCountFrequency (%)
Ⅰ 9
81.8%
Ⅱ 2
 
18.2%
Modifier Symbol
ValueCountFrequency (%)
` 2
66.7%
^ 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1819
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 686
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 649034
67.1%
Common 284639
29.4%
Latin 33119
 
3.4%
Han 43
 
< 0.1%
Greek 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 12315
 
1.9%
공 12122
 
1.9%
다 11324
 
1.7%
시 11262
 
1.7%
정 11073
 
1.7%
니 10553
 
1.6%
기 9752
 
1.5%
에 9681
 
1.5%
의 9536
 
1.5%
보 9528
 
1.5%
Other values (982) 541888
83.5%
Common
ValueCountFrequency (%)
170889
60.0%
, 36837
 
12.9%
. 12298
 
4.3%
/ 8043
 
2.8%
) 7479
 
2.6%
( 7410
 
2.6%
> 6578
 
2.3%
< 6393
 
2.2%
2 5343
 
1.9%
0 4227
 
1.5%
Other values (84) 19142
 
6.7%
Latin
ValueCountFrequency (%)
r 7175
21.7%
b 6615
20.0%
t 1021
 
3.1%
o 971
 
2.9%
e 967
 
2.9%
s 945
 
2.9%
S 933
 
2.8%
I 899
 
2.7%
a 792
 
2.4%
n 666
 
2.0%
Other values (44) 12135
36.6%
Han
ValueCountFrequency (%)
班 3
 
7.0%
次 3
 
7.0%
圖 3
 
7.0%
系 2
 
4.7%
內 2
 
4.7%
科 2
 
4.7%
學 2
 
4.7%
非 2
 
4.7%
馬 2
 
4.7%
垂 1
 
2.3%
Other values (21) 21
48.8%
Greek
ValueCountFrequency (%)
μ 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 648860
67.1%
ASCII 316088
32.7%
None 901
 
0.1%
Punctuation 373
 
< 0.1%
Compat Jamo 173
 
< 0.1%
CJK Compat 144
 
< 0.1%
Math Operators 80
 
< 0.1%
Geometric Shapes 77
 
< 0.1%
Enclosed Alphanum 51
 
< 0.1%
CJK 42
 
< 0.1%
Other values (5) 48
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
170889
54.1%
, 36837
 
11.7%
. 12298
 
3.9%
/ 8043
 
2.5%
) 7479
 
2.4%
( 7410
 
2.3%
r 7175
 
2.3%
b 6615
 
2.1%
> 6578
 
2.1%
< 6393
 
2.0%
Other values (84) 46371
 
14.7%
Hangul
ValueCountFrequency (%)
이 12315
 
1.9%
공 12122
 
1.9%
다 11324
 
1.7%
시 11262
 
1.7%
정 11073
 
1.7%
니 10553
 
1.6%
기 9752
 
1.5%
에 9681
 
1.5%
의 9536
 
1.5%
보 9528
 
1.5%
Other values (973) 541714
83.5%
None
ValueCountFrequency (%)
· 749
83.1%
」 66
 
7.3%
「 64
 
7.1%
₂ 4
 
0.4%
　 4
 
0.4%
． 2
 
0.2%
μ 2
 
0.2%
₃ 2
 
0.2%
× 2
 
0.2%
』 1
 
0.1%
Other values (5) 5
 
0.6%
Punctuation
ValueCountFrequency (%)
※ 250
67.0%
’ 56
 
15.0%
‘ 45
 
12.1%
“ 10
 
2.7%
” 10
 
2.7%
… 2
 
0.5%
Math Operators
ValueCountFrequency (%)
⊙ 77
96.2%
∑ 2
 
2.5%
∼ 1
 
1.2%
Compat Jamo
ValueCountFrequency (%)
ㅇ 77
44.5%
ㆍ 52
30.1%
ㅁ 37
21.4%
ㅡ 3
 
1.7%
ㅣ 1
 
0.6%
ㅋ 1
 
0.6%
ㅗ 1
 
0.6%
ㄹ 1
 
0.6%
CJK Compat
ValueCountFrequency (%)
㎡ 72
50.0%
㎥ 31
21.5%
㎎ 23
 
16.0%
㎢ 6
 
4.2%
㎍ 3
 
2.1%
㎘ 2
 
1.4%
㎝ 2
 
1.4%
㎜ 1
 
0.7%
㎧ 1
 
0.7%
㎏ 1
 
0.7%
Other values (2) 2
 
1.4%
Geometric Shapes
ValueCountFrequency (%)
○ 63
81.8%
□ 9
 
11.7%
● 5
 
6.5%
Arrows
ValueCountFrequency (%)
→ 18
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
① 13
25.5%
② 12
23.5%
③ 11
21.6%
④ 5
 
9.8%
⑤ 3
 
5.9%
⑥ 3
 
5.9%
⑦ 1
 
2.0%
⑨ 1
 
2.0%
⑧ 1
 
2.0%
⑩ 1
 
2.0%
Letterlike Symbols
ValueCountFrequency (%)
ℓ 10
71.4%
℃ 4
 
28.6%
Number Forms
ValueCountFrequency (%)
Ⅰ 9
81.8%
Ⅱ 2
 
18.2%
Misc Symbols
ValueCountFrequency (%)
☎ 3
75.0%
★ 1
 
25.0%
CJK
ValueCountFrequency (%)
班 3
 
7.1%
次 3
 
7.1%
圖 3
 
7.1%
系 2
 
4.8%
內 2
 
4.8%
科 2
 
4.8%
學 2
 
4.8%
非 2
 
4.8%
馬 2
 
4.8%
垂 1
 
2.4%
Other values (20) 20
47.6%
CJK Compat Ideographs
ValueCountFrequency (%)
律 1
100.0%

조회수
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct3795
Distinct (%)38.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2098.8186
Minimum2
Maximum227546
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T17:35:05.798658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile58
Q1232.75
median1706.5
Q32616
95-th percentile4820
Maximum227546
Range227544
Interquartile range (IQR)2383.25

Descriptive statistics

Standard deviation5307.1581
Coefficient of variation (CV)2.5286407
Kurtosis627.39759
Mean2098.8186
Median Absolute Deviation (MAD)1235
Skewness20.230091
Sum20988186
Variance28165927
MonotonicityNot monotonic
2024-04-06T17:35:06.062687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
72 27
 
0.3%
74 27
 
0.3%
76 26
 
0.3%
65 26
 
0.3%
82 26
 
0.3%
92 25
 
0.2%
77 24
 
0.2%
83 24
 
0.2%
84 24
 
0.2%
45 24
 
0.2%
Other values (3785) 9747
97.5%
ValueCountFrequency (%)
2 1
 
< 0.1%
5 1
 
< 0.1%
6 4
< 0.1%
7 1
 
< 0.1%
8 5
0.1%
9 2
 
< 0.1%
10 6
0.1%
11 2
 
< 0.1%
12 3
< 0.1%
13 3
< 0.1%
ValueCountFrequency (%)
227546 1
< 0.1%
197396 1
< 0.1%
129362 1
< 0.1%
116657 1
< 0.1%
97162 1
< 0.1%
94676 1
< 0.1%
88132 1
< 0.1%
84617 1
< 0.1%
84543 1
< 0.1%
72928 1
< 0.1%

분류체계
Text

Distinct74
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-06T17:35:06.495962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length12.6692
Min length7

Characters and Unicode

Total characters126692
Distinct characters139
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row국방 - 병무행정
2nd row보건 - 보건의료
3rd row공공질서및안전 - 해경
4th row보건 - 보건의료
5th row사회복지 - 보육·가족및여성
ValueCountFrequency (%)
10000
33.3%
일반공공행정 1724
 
5.7%
일반행정 1107
 
3.7%
산업·통상·중소기업 1075
 
3.6%
교통및물류 949
 
3.2%
문화체육관광 867
 
2.9%
사회복지 866
 
2.9%
환경 853
 
2.8%
보건 785
 
2.6%
지역개발 738
 
2.5%
Other values (81) 11036
36.8%
2024-04-06T17:35:07.242675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20000
 
15.8%
- 10000
 
7.9%
· 4707
 
3.7%
공 4694
 
3.7%
일 4284
 
3.4%
반 4210
 
3.3%
업 3930
 
3.1%
정 3639
 
2.9%
지 3288
 
2.6%
행 3012
 
2.4%
Other values (129) 64928
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 91985
72.6%
Space Separator 20000
 
15.8%
Dash Punctuation 10000
 
7.9%
Other Punctuation 4707
 
3.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 4694
 
5.1%
일 4284
 
4.7%
반 4210
 
4.6%
업 3930
 
4.3%
정 3639
 
4.0%
지 3288
 
3.6%
행 3012
 
3.3%
및 2779
 
3.0%
기 2389
 
2.6%
통 2373
 
2.6%
Other values (126) 57387
62.4%
Space Separator
ValueCountFrequency (%)
20000
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10000
100.0%
Other Punctuation
ValueCountFrequency (%)
· 4707
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 91985
72.6%
Common 34707
 
27.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 4694
 
5.1%
일 4284
 
4.7%
반 4210
 
4.6%
업 3930
 
4.3%
정 3639
 
4.0%
지 3288
 
3.6%
행 3012
 
3.3%
및 2779
 
3.0%
기 2389
 
2.6%
통 2373
 
2.6%
Other values (126) 57387
62.4%
Common
ValueCountFrequency (%)
20000
57.6%
- 10000
28.8%
· 4707
 
13.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 91985
72.6%
ASCII 30000
 
23.7%
None 4707
 
3.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20000
66.7%
- 10000
33.3%
None
ValueCountFrequency (%)
· 4707
100.0%
Hangul
ValueCountFrequency (%)
공 4694
 
5.1%
일 4284
 
4.7%
반 4210
 
4.6%
업 3930
 
4.3%
정 3639
 
4.0%
지 3288
 
3.6%
행 3012
 
3.3%
및 2779
 
3.0%
기 2389
 
2.6%
통 2373
 
2.6%
Other values (126) 57387
62.4%

기관코드
Text

Distinct676
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-06T17:35:07.934918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters70000
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique99 ?
Unique (%)1.0%

Sample

1st row1300000
2nd row5020000
3rd row1532000
4th row3560000
5th row6440000
ValueCountFrequency (%)
6540000 234
 
2.3%
b554334 219
 
2.2%
6290000 166
 
1.7%
1741000 164
 
1.6%
6280000 156
 
1.6%
3560000 131
 
1.3%
1613000 130
 
1.3%
6500000 119
 
1.2%
b190016 106
 
1.1%
6410000 102
 
1.0%
Other values (666) 8473
84.7%
2024-04-06T17:35:08.933127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 28275
40.4%
5 8788
 
12.6%
1 5605
 
8.0%
3 5592
 
8.0%
4 5052
 
7.2%
6 3840
 
5.5%
2 3238
 
4.6%
B 3108
 
4.4%
9 2260
 
3.2%
8 2016
 
2.9%
Other values (3) 2226
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66595
95.1%
Uppercase Letter 3405
 
4.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 28275
42.5%
5 8788
 
13.2%
1 5605
 
8.4%
3 5592
 
8.4%
4 5052
 
7.6%
6 3840
 
5.8%
2 3238
 
4.9%
9 2260
 
3.4%
8 2016
 
3.0%
7 1929
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
B 3108
91.3%
A 294
 
8.6%
C 3
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 66595
95.1%
Latin 3405
 
4.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 28275
42.5%
5 8788
 
13.2%
1 5605
 
8.4%
3 5592
 
8.4%
4 5052
 
7.6%
6 3840
 
5.8%
2 3238
 
4.9%
9 2260
 
3.4%
8 2016
 
3.0%
7 1929
 
2.9%
Latin
ValueCountFrequency (%)
B 3108
91.3%
A 294
 
8.6%
C 3
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 28275
40.4%
5 8788
 
12.6%
1 5605
 
8.0%
3 5592
 
8.0%
4 5052
 
7.2%
6 3840
 
5.5%
2 3238
 
4.6%
B 3108
 
4.4%
9 2260
 
3.2%
8 2016
 
2.9%
Other values (3) 2226
 
3.2%

기관명
Text

Distinct676
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-06T17:35:09.490382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length7.5426
Min length3

Characters and Unicode

Total characters75426
Distinct characters279
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

Unique99 ?
Unique (%)1.0%

Sample

1st row병무청
2nd row경상북도 포항시
3rd row해양경찰청
4th row인천광역시 서구
5th row충청남도
ValueCountFrequency (%)
경기도 679
 
4.8%
인천광역시 585
 
4.2%
전북특별자치도 543
 
3.9%
부산광역시 536
 
3.8%
전라남도 365
 
2.6%
서울특별시 348
 
2.5%
경상남도 316
 
2.2%
서구 314
 
2.2%
충청남도 268
 
1.9%
광주광역시 249
 
1.8%
Other values (645) 9843
70.1%
2024-04-06T17:35:10.294801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 4075
 
5.4%
4046
 
5.4%
도 3431
 
4.5%
광 2742
 
3.6%
국 2701
 
3.6%
역 2142
 
2.8%
구 2072
 
2.7%
공 2059
 
2.7%
부 1932
 
2.6%
전 1862
 
2.5%
Other values (269) 48364
64.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 70827
93.9%
Space Separator 4046
 
5.4%
Close Punctuation 245
 
0.3%
Open Punctuation 245
 
0.3%
Uppercase Letter 36
 
< 0.1%
Other Symbol 19
 
< 0.1%
Decimal Number 6
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 4075
 
5.8%
도 3431
 
4.8%
광 2742
 
3.9%
국 2701
 
3.8%
역 2142
 
3.0%
구 2072
 
2.9%
공 2059
 
2.9%
부 1932
 
2.7%
전 1862
 
2.6%
경 1733
 
2.4%
Other values (259) 46078
65.1%
Uppercase Letter
ValueCountFrequency (%)
N 12
33.3%
D 12
33.3%
K 12
33.3%
Decimal Number
ValueCountFrequency (%)
2 4
66.7%
8 2
33.3%
Space Separator
ValueCountFrequency (%)
4046
100.0%
Close Punctuation
ValueCountFrequency (%)
) 245
100.0%
Open Punctuation
ValueCountFrequency (%)
( 245
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 19
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 70846
93.9%
Common 4544
 
6.0%
Latin 36
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 4075
 
5.8%
도 3431
 
4.8%
광 2742
 
3.9%
국 2701
 
3.8%
역 2142
 
3.0%
구 2072
 
2.9%
공 2059
 
2.9%
부 1932
 
2.7%
전 1862
 
2.6%
경 1733
 
2.4%
Other values (260) 46097
65.1%
Common
ValueCountFrequency (%)
4046
89.0%
) 245
 
5.4%
( 245
 
5.4%
2 4
 
0.1%
8 2
 
< 0.1%
. 2
 
< 0.1%
Latin
ValueCountFrequency (%)
N 12
33.3%
D 12
33.3%
K 12
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 70827
93.9%
ASCII 4580
 
6.1%
None 19
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 4075
 
5.8%
도 3431
 
4.8%
광 2742
 
3.9%
국 2701
 
3.8%
역 2142
 
3.0%
구 2072
 
2.9%
공 2059
 
2.9%
부 1932
 
2.7%
전 1862
 
2.6%
경 1733
 
2.4%
Other values (259) 46078
65.1%
ASCII
ValueCountFrequency (%)
4046
88.3%
) 245
 
5.3%
( 245
 
5.3%
N 12
 
0.3%
D 12
 
0.3%
K 12
 
0.3%
2 4
 
0.1%
8 2
 
< 0.1%
. 2
 
< 0.1%
None
ValueCountFrequency (%)
㈜ 19
100.0%

국가중점여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
9528 
True
 
472
ValueCountFrequency (%)
False 9528
95.3%
True 472
 
4.7%
2024-04-06T17:35:10.496965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

표준데이터여부
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
9958 
True
 
42
ValueCountFrequency (%)
False 9958
99.6%
True 42
 
0.4%
2024-04-06T17:35:10.667033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

목록 등록일
Date

Distinct1738
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2011-12-03 00:00:00
Maximum2024-03-28 00:00:00
2024-04-06T17:35:10.878219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:35:11.181293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

목록 수정일
Date

Distinct215
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-08-11 00:00:00
Maximum2024-03-29 00:00:00
2024-04-06T17:35:11.470402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:35:11.777923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

URL
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-06T17:35:12.282263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length48
Mean length47.8504
Min length46

Characters and Unicode

Total characters478504
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10000 ?
Unique (%)100.0%

Sample

1st rowhttps://www.data.go.kr/data/3068269/fileData.do
2nd rowhttps://www.data.go.kr/data/15121131/fileData.do
3rd rowhttps://www.data.go.kr/data/15118343/fileData.do
4th rowhttps://www.data.go.kr/data/15086609/fileData.do
5th rowhttps://www.data.go.kr/data/15095087/fileData.do
ValueCountFrequency (%)
https://www.data.go.kr/data/3068269/filedata.do 1
 
< 0.1%
https://www.data.go.kr/data/15100225/filedata.do 1
 
< 0.1%
https://www.data.go.kr/data/15119812/filedata.do 1
 
< 0.1%
https://www.data.go.kr/data/15106012/filedata.do 1
 
< 0.1%
https://www.data.go.kr/data/15046050/filedata.do 1
 
< 0.1%
https://www.data.go.kr/data/15052757/filedata.do 1
 
< 0.1%
https://www.data.go.kr/data/15068943/filedata.do 1
 
< 0.1%
https://www.data.go.kr/data/15045905/filedata.do 1
 
< 0.1%
https://www.data.go.kr/data/15124385/filedata.do 1
 
< 0.1%
https://www.data.go.kr/data/15120152/filedata.do 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-04-06T17:35:13.171169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 59396
 
12.4%
/ 50000
 
10.4%
t 49396
 
10.3%
. 40000
 
8.4%
d 30084
 
6.3%
w 30000
 
6.3%
o 20604
 
4.3%
1 18201
 
3.8%
5 13904
 
2.9%
p 11208
 
2.3%
Other values (20) 155711
32.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 290042
60.6%
Other Punctuation 100000
 
20.9%
Decimal Number 79108
 
16.5%
Uppercase Letter 9354
 
2.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 59396
20.5%
t 49396
17.0%
d 30084
10.4%
w 30000
10.3%
o 20604
 
7.1%
p 11208
 
3.9%
r 10042
 
3.5%
s 10042
 
3.5%
h 10000
 
3.4%
k 10000
 
3.4%
Other values (6) 49270
17.0%
Decimal Number
ValueCountFrequency (%)
1 18201
23.0%
5 13904
17.6%
0 11148
14.1%
2 6347
 
8.0%
3 5607
 
7.1%
4 5110
 
6.5%
9 4798
 
6.1%
6 4760
 
6.0%
8 4740
 
6.0%
7 4493
 
5.7%
Other Punctuation
ValueCountFrequency (%)
/ 50000
50.0%
. 40000
40.0%
: 10000
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
D 9354
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 299396
62.6%
Common 179108
37.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 59396
19.8%
t 49396
16.5%
d 30084
10.0%
w 30000
10.0%
o 20604
 
6.9%
p 11208
 
3.7%
r 10042
 
3.4%
s 10042
 
3.4%
h 10000
 
3.3%
k 10000
 
3.3%
Other values (7) 58624
19.6%
Common
ValueCountFrequency (%)
/ 50000
27.9%
. 40000
22.3%
1 18201
 
10.2%
5 13904
 
7.8%
0 11148
 
6.2%
: 10000
 
5.6%
2 6347
 
3.5%
3 5607
 
3.1%
4 5110
 
2.9%
9 4798
 
2.7%
Other values (3) 13993
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 478504
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 59396
 
12.4%
/ 50000
 
10.4%
t 49396
 
10.3%
. 40000
 
8.4%
d 30084
 
6.3%
w 30000
 
6.3%
o 20604
 
4.3%
1 18201
 
3.8%
5 13904
 
2.9%
p 11208
 
2.3%
Other values (20) 155711
32.5%

다운로드_활용건수
Text

Distinct2056
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-06T17:35:14.073086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.8322
Min length1

Characters and Unicode

Total characters28322
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

Unique699 ?
Unique (%)7.0%

Sample

1st row2270
2nd row37
3rd row20
4th row493
5th row325
ValueCountFrequency (%)
24 92
 
0.9%
2 91
 
0.9%
23 83
 
0.8%
0 81
 
0.8%
25 77
 
0.8%
1 76
 
0.8%
22 71
 
0.7%
3 71
 
0.7%
21 67
 
0.7%
26 58
 
0.6%
Other values (2046) 9233
92.3%
2024-04-06T17:35:15.025693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4587
16.2%
2 3716
13.1%
3 2869
10.1%
5 2692
9.5%
6 2690
9.5%
4 2608
9.2%
7 2541
9.0%
8 2286
8.1%
0 2226
7.9%
9 2089
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28304
99.9%
Dash Punctuation 18
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4587
16.2%
2 3716
13.1%
3 2869
10.1%
5 2692
9.5%
6 2690
9.5%
4 2608
9.2%
7 2541
9.0%
8 2286
8.1%
0 2226
7.9%
9 2089
7.4%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 28322
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4587
16.2%
2 3716
13.1%
3 2869
10.1%
5 2692
9.5%
6 2690
9.5%
4 2608
9.2%
7 2541
9.0%
8 2286
8.1%
0 2226
7.9%
9 2089
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28322
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4587
16.2%
2 3716
13.1%
3 2869
10.1%
5 2692
9.5%
6 2690
9.5%
4 2608
9.2%
7 2541
9.0%
8 2286
8.1%
0 2226
7.9%
9 2089
7.4%

키워드
Text

Distinct9699
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-06T17:35:15.910151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length42
Mean length13.6636
Min length6

Characters and Unicode

Total characters136636
Distinct characters791
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9557 ?
Unique (%)95.6%

Sample

1st row승선근무예비역,인원배정,명부
2nd row보건,감염,통계
3rd row수상구조사,국가자격,첨부파일관리
4th row병원,의원,소아과
5th row여성,일자리센터,구직
ValueCountFrequency (%)
국회,입법,의안 66
 
0.5%
및 59
 
0.5%
현황 56
 
0.5%
정보 54
 
0.4%
부동산거래 45
 
0.4%
가맹본부,본부,브랜드 34
 
0.3%
수 18
 
0.1%
위치 12
 
0.1%
거래규모별 11
 
0.1%
건축물거래 11
 
0.1%
Other values (11064) 11887
97.0%
2024-04-06T17:35:16.608493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 20009
 
14.6%
지 2695
 
2.0%
기 2351
 
1.7%
2255
 
1.7%
업 2004
 
1.5%
사 1992
 
1.5%
정 1981
 
1.4%
시 1921
 
1.4%
보 1900
 
1.4%
도 1878
 
1.4%
Other values (781) 97650
71.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 112152
82.1%
Other Punctuation 20098
 
14.7%
Space Separator 2255
 
1.7%
Uppercase Letter 1301
 
1.0%
Decimal Number 634
 
0.5%
Lowercase Letter 139
 
0.1%
Open Punctuation 19
 
< 0.1%
Close Punctuation 19
 
< 0.1%
Connector Punctuation 7
 
< 0.1%
Dash Punctuation 6
 
< 0.1%
Other values (2) 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 2695
 
2.4%
기 2351
 
2.1%
업 2004
 
1.8%
사 1992
 
1.8%
정 1981
 
1.8%
시 1921
 
1.7%
보 1900
 
1.7%
도 1878
 
1.7%
수 1854
 
1.7%
공 1683
 
1.5%
Other values (709) 91893
81.9%
Uppercase Letter
ValueCountFrequency (%)
C 135
 
10.4%
I 132
 
10.1%
S 126
 
9.7%
D 117
 
9.0%
A 96
 
7.4%
T 90
 
6.9%
O 71
 
5.5%
P 70
 
5.4%
V 49
 
3.8%
E 46
 
3.5%
Other values (15) 369
28.4%
Lowercase Letter
ValueCountFrequency (%)
n 13
 
9.4%
o 12
 
8.6%
s 11
 
7.9%
i 10
 
7.2%
e 10
 
7.2%
p 9
 
6.5%
c 9
 
6.5%
d 9
 
6.5%
g 8
 
5.8%
a 8
 
5.8%
Other values (12) 40
28.8%
Decimal Number
ValueCountFrequency (%)
1 223
35.2%
2 84
 
13.2%
3 83
 
13.1%
9 72
 
11.4%
0 58
 
9.1%
5 44
 
6.9%
4 29
 
4.6%
6 18
 
2.8%
7 13
 
2.1%
8 10
 
1.6%
Other Punctuation
ValueCountFrequency (%)
, 20009
99.6%
@ 40
 
0.2%
/ 29
 
0.1%
· 10
 
< 0.1%
. 8
 
< 0.1%
! 1
 
< 0.1%
& 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
| 4
80.0%
~ 1
 
20.0%
Space Separator
ValueCountFrequency (%)
2255
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 112152
82.1%
Common 23044
 
16.9%
Latin 1440
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 2695
 
2.4%
기 2351
 
2.1%
업 2004
 
1.8%
사 1992
 
1.8%
정 1981
 
1.8%
시 1921
 
1.7%
보 1900
 
1.7%
도 1878
 
1.7%
수 1854
 
1.7%
공 1683
 
1.5%
Other values (709) 91893
81.9%
Latin
ValueCountFrequency (%)
C 135
 
9.4%
I 132
 
9.2%
S 126
 
8.8%
D 117
 
8.1%
A 96
 
6.7%
T 90
 
6.2%
O 71
 
4.9%
P 70
 
4.9%
V 49
 
3.4%
E 46
 
3.2%
Other values (37) 508
35.3%
Common
ValueCountFrequency (%)
, 20009
86.8%
2255
 
9.8%
1 223
 
1.0%
2 84
 
0.4%
3 83
 
0.4%
9 72
 
0.3%
0 58
 
0.3%
5 44
 
0.2%
@ 40
 
0.2%
/ 29
 
0.1%
Other values (15) 147
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 112152
82.1%
ASCII 24474
 
17.9%
None 10
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 20009
81.8%
2255
 
9.2%
1 223
 
0.9%
C 135
 
0.6%
I 132
 
0.5%
S 126
 
0.5%
D 117
 
0.5%
A 96
 
0.4%
T 90
 
0.4%
2 84
 
0.3%
Other values (61) 1207
 
4.9%
Hangul
ValueCountFrequency (%)
지 2695
 
2.4%
기 2351
 
2.1%
업 2004
 
1.8%
사 1992
 
1.8%
정 1981
 
1.8%
시 1921
 
1.7%
보 1900
 
1.7%
도 1878
 
1.7%
수 1854
 
1.7%
공 1683
 
1.5%
Other values (709) 91893
81.9%
None
ValueCountFrequency (%)
· 10
100.0%

Interactions

2024-04-06T17:35:00.826291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:35:00.376063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:35:01.105122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:35:00.603148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:35:16.778917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
목록키목록유형조회수분류체계국가중점여부표준데이터여부
목록키1.0000.0310.0000.1940.0880.023
목록유형0.0311.0000.4710.4580.1581.000
조회수0.0000.4711.0000.0000.0940.624
분류체계0.1940.4580.0001.0000.5560.080
국가중점여부0.0880.1580.0940.5561.0000.006
표준데이터여부0.0231.0000.6240.0800.0061.000
2024-04-06T17:35:17.005274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
표준데이터여부국가중점여부목록유형
표준데이터여부1.0000.0041.000
국가중점여부0.0041.0000.260
목록유형1.0000.2601.000
2024-04-06T17:35:17.182796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
목록키조회수목록유형국가중점여부표준데이터여부
목록키1.000-0.8470.0510.0560.014
조회수-0.8471.0000.3400.0710.473
목록유형0.0510.3401.0000.2601.000
국가중점여부0.0560.0710.2601.0000.004
표준데이터여부0.0140.4731.0000.0041.000

Missing values

2024-04-06T17:35:01.375053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:35:01.767707image/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

목록키목록유형목록명목록설명조회수분류체계기관코드기관명국가중점여부표준데이터여부목록 등록일목록 수정일URL다운로드_활용건수키워드
69223068269FILE병무청_승선근무예비역 인원배정 명부승선근무예비역은 전시사변 또는 비상시 국민경제에 긴요한 물자와 군수물자를 수송하기 위한 업무 또는 이와 관련된 업무의 지원을 위하여 소집되어 승선근무하는 병역대체복무제도입니다.<br/>2024년 승선근무예비역에 대하여 해운업체, 수산업체별 인원배정한 명부입니다.3483국방 - 병무행정1300000병무청NN2018-10-112024-01-19https://www.data.go.kr/data/3068269/fileData.do2270승선근무예비역,인원배정,명부
2147315121131FILE경상북도 포항시_코로나 일일확진자 수공공데이터 제공 신청에 따른 2020년 포항시 코로나 일일확진자 수(남구, 북구, 총 누적)에 대한 데이터를 제공합니다146보건 - 보건의료5020000경상북도 포항시NN2023-08-292023-08-31https://www.data.go.kr/data/15121131/fileData.do37보건,감염,통계
2103815118343FILE해양경찰청_수상안전종합관리_첨부파일관리메타관리시스템 기반 공공데이터 개방계획 수립 및 이행을 위한 수상구조사 시스템의 수상안전종합관리 첨부파일관리 데이터로 파일 ID, 파일생성일, 사용여부 등의 항목을 제공합니다.146공공질서및안전 - 해경1532000해양경찰청NN2023-08-102023-09-04https://www.data.go.kr/data/15118343/fileData.do20수상구조사,국가자격,첨부파일관리
2410215086609FILE인천광역시 서구_소아과의원인천광역시 서구 소아과의원의 현황에 대한 데이터입니다. 이 데이터는 의원명, 소재지, 전화번호 등에 대한 정보를 제공합니다.1039보건 - 보건의료3560000인천광역시 서구NN2021-08-262023-08-24https://www.data.go.kr/data/15086609/fileData.do493병원,의원,소아과
684815095087FILE충청남도_여성새로일하기센터 현황여성새로일하기센터를 명칭, 지정일, 소재지, 전화번호, 종사자 수, 시설규모, 법인명으로 나열하여 개방하고자 합니다.965사회복지 - 보육·가족및여성6440000충청남도NN2021-11-242024-01-21https://www.data.go.kr/data/15095087/fileData.do325여성,일자리센터,구직
579415055535FILE전북특별자치도_국립공원내 도유재산(토지) 현황국립공원내 도유재산(토지) 현황(재산분류,재산의소재,면적, 위치, 특수지, 본번, 부번, 공시지가, 재산가격, 총 사용허가면적 등) 제공2080일반공공행정 - 국정운영6540000전북특별자치도NN2019-09-252024-01-29https://www.data.go.kr/data/15055535/fileData.do780국공유재산,국가재산,재산
1257215041068FILE국가철도공단_우이신설_환승정보우이신설에서 운영하는 역사들의 환승정보 데이터로 철도운영기관명, 선명, 역명, 환승철도운영기관, 환승선명, 환승이후역명, 환승기점역명, 차량순서, 차량출입문번호의 데이터가 있습니다.2730교통및물류 - 철도B554334국가철도공단YN2019-11-222023-11-09https://www.data.go.kr/data/15041068/fileData.do1026도시광역철도,환승정보,우이신설지하철
89093036703FILE경기도 안양시_사업체기초통계전국적으로 실시한 기준 사업체조사를 실시하여 안양시에 해당하는 부문을 발췌하여 수록한 (사업체조사에 관한 종자사수, 조직형테, 사업체구분별) 간행물 데이터정보입니다.3011일반공공행정 - 일반행정3830000경기도 안양시NN2014-04-012023-12-22https://www.data.go.kr/data/3036703/fileData.do2954사업체,조사,행정
1578115038511FILE제주특별자치도교육청_학교현황제주특별자치도 소재 유.초.중.고.특수학교 소재지, 개교일자, 우편번호, 주소, 전화번호, 홈페이지주소 안내3195교육 - 교육일반9290000제주특별자치도교육청NN2019-09-052023-10-04https://www.data.go.kr/data/15038511/fileData.do1805학교주소,개교일자,학교홈페이지
2634515070169FILE교육부 국립국제교육원_기관홈페이지_메뉴별_뷰카운트국립국제교육원 기관대표 홈페이지에서 이용 가능한 주요 메뉴들의 메뉴명,접근단계, 방문자수를 집계한 현황 자료로 인기가 많은 순으로 정렬한 것임1758교육 - 교육일반1342090교육부 국립국제교육원NN2020-10-192023-08-17https://www.data.go.kr/data/15070169/fileData.do637대표홈페이지,주요메뉴,이용현황
목록키목록유형목록명목록설명조회수분류체계기관코드기관명국가중점여부표준데이터여부목록 등록일목록 수정일URL다운로드_활용건수키워드
1119515099038FILE대외경제정책연구원_각국의 대세계 RCA 6단위UN Comtrade의 주요 40여개 국가의 무역통계를 사용하여 해당년도 HS 기준(6단위)으로 현시비교우위(RCA)지수를 산출한 DB702산업·통상·중소기업 - 통상B090003대외경제정책연구원NN2022-02-172023-11-24https://www.data.go.kr/data/15099038/fileData.do2511무역통계,RCA 6단위,현시비교우위
239215113165FILE대전광역시 서구_지역아동센터 운영지원현황대전광역시 서구 지역아동센터 운영지원현황(순번, 지원구분명, 예산액, 예산액단위, 대상명, 지원기준, 시기, 재원비율, 데이터기준일자) 입니다.177사회복지 - 사회복지일반3660000대전광역시 서구NN2023-04-042024-03-08https://www.data.go.kr/data/15113165/fileData.do47아동복지,아동보호,아동교육
2547215118986FILE한국환경공단_순환골재 폐기물 데이터순환골재 규격별, 업체별, 연도별 생산, 판매 실적에 대한 데이터를 제공합니다. (세부 업체명은 블라인드 처리되었습니다)146환경 - 폐기물B552584한국환경공단NN2023-08-172023-08-21https://www.data.go.kr/data/15118986/fileData.do111순환골재,폐기물,재활용
2072515121037FILE부산교통공사_부산진역 측선 특수촬영본(VR 스캐닝)부산교통공사와 부산영상위원회가 촬영장소 비대면 답사 지원을 위해 협업하여 제작한 부산진역 측선 특수촬영본입니다. <br/>해당 촬영본은 VR스캐너를 통해 부산진역 측선을 360도 스캐닝하였으며, 링크 접속 시 3D로 촬영본을 보실 수 있습니다.126교통및물류 - 철도B551542부산교통공사NN2023-08-292023-09-05https://www.data.go.kr/data/15121037/fileData.do29도시철도,VR,촬영
1811815123305FILE경기도_도로대장 전산화 시스템_생태통로경기도_도로대장 전산화 시스템_생태통로 테이블의 정보입니다.<br/><br/>생태통로 위치, 유형, 규모 등에 대한 정보를 제공합니다.183교통및물류 - 도로6410000경기도NN2023-09-182023-09-18https://www.data.go.kr/data/15123305/fileData.do7야생동물,고속도로,동물안전
2638215042200FILE한국동서발전(주)_중소기업제품 구매 현황한국동서발전의 중소기업 제품 구매 현황 정보입니다. 중소기업 제품 구매 현황은 년도, 분기, 구분, 종류, 구매액의 항목으로 구성됩니다.2122산업·통상·중소기업 - 산업·중소기업일반B552070한국동서발전(주)NN2019-12-272023-08-17https://www.data.go.kr/data/15042200/fileData.do753중소기업,중소기업제품,구매현황
2482815083349FILE한국서부발전(주)_발전소배출수질한국서부발전 발전소 배출 수질 정보입니다. 제공데이터는 연도,사업소,방류량(톤),pH,COD기준(㎎/ℓ),COD평균(㎎/ℓ),SS기준(㎎/ℓ),SS평균(㎎/ℓ),광유 기준(㎎/ℓ),광유 평균(㎎/ℓ),T-N기준(㎎/ℓ),T-N평균(㎎/ℓ),T-P기준(㎎/ℓ),T-P평균(㎎/ℓ)입니다.<br/>- pH : 수소이온농도<br/>- COD: 화학적산소요구량<br/>- SS: 부유물질량<br/>- T-N : 총질소<br/>- T-P : 총인3221산업·통상·중소기업 - 에너지및자원개발B552522한국서부발전(주)NN2016-08-032023-08-23https://www.data.go.kr/data/15083349/fileData.do543배출,수질,환경
1317615041487FILE국가철도공단_경의중앙선_역위치경의중앙선에서 운영하는 도시광역철도역들의 역위치에 관한 파일데이터로 철도운영기관명, 선명, 역명, 경도, 위도 의 항목이 있습니다.3423교통및물류 - 철도B554334국가철도공단YN2019-12-022023-11-03https://www.data.go.kr/data/15041487/fileData.do1259도시광역철도,역위치,수도권 지하철
192915053529FILE대구광역시교육청 대구광역시군위교육지원청_학원현황대구광역시교육청 대구광역시군위교육지원청 학원 현황에 대한 데이터로 학원명, 학원 주소. 학원 전화번호 등에 대한 정보를 포함합니다.2791교육 - 유아및초·중등교육8862000대구광역시교육청 대구광역시군위교육지원청NN2019-06-172024-03-14https://www.data.go.kr/data/15053529/fileData.do665교육,초중등,학원
319215090113FILE여수광양항만공사_광양항 지역별 차량출입대수 정보광양항 컨테이너부두 구역 월간 지역별 출입차량수 데이터입니다. 데이터는 자동차번호판 지역, 대수, 순위로 구성되어 있습니다.<br/>데이터는 매월 갱신됩니다.<br/>1583교통및물류 - 해운·항만B552782여수광양항만공사NN2021-09-272024-02-29https://www.data.go.kr/data/15090113/fileData.do2317광양항,월별,출입차량수