Overview

Dataset statistics

Number of variables11
Number of observations10000
Missing cells1
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory976.6 KiB
Average record size in memory100.0 B

Variable types

Numeric4
Text4
Categorical3

Dataset

Description경상남도기록원 소장 비공개 기록물 중 생산 후 30년이 지난 기록물에 대해 공개재분류를 실시하고 그에 따라 공개전환된 기록물 목록을 게시합니다.
URLhttps://www.data.go.kr/data/15084202/fileData.do

Alerts

재분류공개구분 has constant value ""Constant
순번 is highly overall correlated with 생산기관High correlation
시작쪽 is highly overall correlated with 끝쪽High correlation
끝쪽 is highly overall correlated with 시작쪽High correlation
생산기관 is highly overall correlated with 순번High correlation
공개구분 is highly imbalanced (96.6%)Imbalance
생산년도 is highly skewed (γ1 = 37.44340665)Skewed
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 04:06:22.741438
Analysis finished2023-12-12 04:06:27.254569
Duration4.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24357.34
Minimum5
Maximum48894
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:06:27.353573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile2248.95
Q111898
median24271.5
Q336752.75
95-th percentile46564.3
Maximum48894
Range48889
Interquartile range (IQR)24854.75

Descriptive statistics

Standard deviation14259.368
Coefficient of variation (CV)0.58542386
Kurtosis-1.2193738
Mean24357.34
Median Absolute Deviation (MAD)12428.5
Skewness0.006473199
Sum2.435734 × 108
Variance2.0332957 × 108
MonotonicityNot monotonic
2023-12-12T13:06:27.546921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7326 1
 
< 0.1%
11895 1
 
< 0.1%
8559 1
 
< 0.1%
10883 1
 
< 0.1%
46653 1
 
< 0.1%
15424 1
 
< 0.1%
11975 1
 
< 0.1%
43433 1
 
< 0.1%
242 1
 
< 0.1%
17691 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
5 1
< 0.1%
6 1
< 0.1%
20 1
< 0.1%
22 1
< 0.1%
23 1
< 0.1%
28 1
< 0.1%
29 1
< 0.1%
31 1
< 0.1%
32 1
< 0.1%
33 1
< 0.1%
ValueCountFrequency (%)
48894 1
< 0.1%
48892 1
< 0.1%
48890 1
< 0.1%
48887 1
< 0.1%
48885 1
< 0.1%
48883 1
< 0.1%
48871 1
< 0.1%
48870 1
< 0.1%
48867 1
< 0.1%
48864 1
< 0.1%

관리번호
Text

Distinct4504
Distinct (%)45.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T13:06:27.877085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length13
Mean length11.7268
Min length9

Characters and Unicode

Total characters117268
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2921 ?
Unique (%)29.2%

Sample

1st rowGA0019205-003
2nd rowGA0019241-002
3rd rowGA0019192-002
4th rowGA0019419-002
5th rowGA0019248-002
ValueCountFrequency (%)
gf0001128 36
 
0.4%
ga0013173-002 29
 
0.3%
ga0005250 26
 
0.3%
ga0019396 26
 
0.3%
ga0019434-001 26
 
0.3%
ga0019440-004 26
 
0.3%
ga0019451-003 26
 
0.3%
gf0000734 25
 
0.2%
ga0019451-002 24
 
0.2%
ga0019468-001 24
 
0.2%
Other values (4494) 9732
97.3%
2023-12-12T13:06:28.461591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 40346
34.4%
1 11096
 
9.5%
G 10000
 
8.5%
A 9640
 
8.2%
2 7593
 
6.5%
- 6817
 
5.8%
9 6346
 
5.4%
3 6035
 
5.1%
4 5436
 
4.6%
5 4123
 
3.5%
Other values (5) 9836
 
8.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 90451
77.1%
Uppercase Letter 20000
 
17.1%
Dash Punctuation 6817
 
5.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 40346
44.6%
1 11096
 
12.3%
2 7593
 
8.4%
9 6346
 
7.0%
3 6035
 
6.7%
4 5436
 
6.0%
5 4123
 
4.6%
8 3946
 
4.4%
7 2889
 
3.2%
6 2641
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
G 10000
50.0%
A 9640
48.2%
F 325
 
1.6%
B 35
 
0.2%
Dash Punctuation
ValueCountFrequency (%)
- 6817
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 97268
82.9%
Latin 20000
 
17.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 40346
41.5%
1 11096
 
11.4%
2 7593
 
7.8%
- 6817
 
7.0%
9 6346
 
6.5%
3 6035
 
6.2%
4 5436
 
5.6%
5 4123
 
4.2%
8 3946
 
4.1%
7 2889
 
3.0%
Latin
ValueCountFrequency (%)
G 10000
50.0%
A 9640
48.2%
F 325
 
1.6%
B 35
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 117268
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 40346
34.4%
1 11096
 
9.5%
G 10000
 
8.5%
A 9640
 
8.2%
2 7593
 
6.5%
- 6817
 
5.8%
9 6346
 
5.4%
3 6035
 
5.1%
4 5436
 
4.6%
5 4123
 
3.5%
Other values (5) 9836
 
8.4%

기록물철명
Text

Distinct4032
Distinct (%)40.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T13:06:28.748369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length93
Median length49
Mean length15.9127
Min length2

Characters and Unicode

Total characters159127
Distinct characters470
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2647 ?
Unique (%)26.5%

Sample

1st row규칙 공포 원본-사천군(4-3)
2nd row조례 공포-사천군(2-2)
3rd row조례관계철-사천군(4-2)
4th row인사발령철(2-2)
5th row조례제정-사천군(2-2)
ValueCountFrequency (%)
상환대장(2-2 222
 
1.2%
상환대장(2-1 213
 
1.2%
진입로 211
 
1.2%
포장공사 200
 
1.1%
제 189
 
1.0%
설계서 179
 
1.0%
공포 146
 
0.8%
상환대장(3-3 130
 
0.7%
조례 128
 
0.7%
상환대장(3-1 127
 
0.7%
Other values (4772) 16314
90.3%
2023-12-12T13:06:29.221725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 8953
 
5.6%
) 8909
 
5.6%
8183
 
5.1%
- 7870
 
4.9%
2 5801
 
3.6%
1 5770
 
3.6%
계 3812
 
2.4%
사 3674
 
2.3%
3 3641
 
2.3%
장 3525
 
2.2%
Other values (460) 98989
62.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 96764
60.8%
Decimal Number 27029
 
17.0%
Open Punctuation 8953
 
5.6%
Close Punctuation 8909
 
5.6%
Space Separator 8183
 
5.1%
Dash Punctuation 7870
 
4.9%
Other Punctuation 1088
 
0.7%
Math Symbol 229
 
0.1%
Uppercase Letter 81
 
0.1%
Other Symbol 9
 
< 0.1%
Other values (3) 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 3812
 
3.9%
사 3674
 
3.8%
장 3525
 
3.6%
지 3293
 
3.4%
공 3032
 
3.1%
대 2922
 
3.0%
상 2801
 
2.9%
환 2456
 
2.5%
관 2195
 
2.3%
설 1963
 
2.0%
Other values (419) 67091
69.3%
Uppercase Letter
ValueCountFrequency (%)
I 15
18.5%
B 11
13.6%
G 7
8.6%
D 6
 
7.4%
C 6
 
7.4%
R 6
 
7.4%
S 5
 
6.2%
N 5
 
6.2%
A 5
 
6.2%
T 5
 
6.2%
Other values (4) 10
12.3%
Decimal Number
ValueCountFrequency (%)
2 5801
21.5%
1 5770
21.3%
3 3641
13.5%
9 3009
11.1%
4 2679
9.9%
5 1839
 
6.8%
0 1580
 
5.8%
7 1024
 
3.8%
6 893
 
3.3%
8 793
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 461
42.4%
. 323
29.7%
* 277
25.5%
/ 14
 
1.3%
: 13
 
1.2%
Math Symbol
ValueCountFrequency (%)
~ 217
94.8%
> 6
 
2.6%
< 6
 
2.6%
Lowercase Letter
ValueCountFrequency (%)
o 5
83.3%
w 1
 
16.7%
Open Punctuation
ValueCountFrequency (%)
( 8953
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8909
100.0%
Space Separator
ValueCountFrequency (%)
8183
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7870
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 9
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 4
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 96773
60.8%
Common 62263
39.1%
Latin 91
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 3812
 
3.9%
사 3674
 
3.8%
장 3525
 
3.6%
지 3293
 
3.4%
공 3032
 
3.1%
대 2922
 
3.0%
상 2801
 
2.9%
환 2456
 
2.5%
관 2195
 
2.3%
설 1963
 
2.0%
Other values (420) 67100
69.3%
Common
ValueCountFrequency (%)
( 8953
14.4%
) 8909
14.3%
8183
13.1%
- 7870
12.6%
2 5801
9.3%
1 5770
9.3%
3 3641
5.8%
9 3009
 
4.8%
4 2679
 
4.3%
5 1839
 
3.0%
Other values (13) 5609
9.0%
Latin
ValueCountFrequency (%)
I 15
16.5%
B 11
12.1%
G 7
 
7.7%
D 6
 
6.6%
C 6
 
6.6%
R 6
 
6.6%
S 5
 
5.5%
N 5
 
5.5%
o 5
 
5.5%
A 5
 
5.5%
Other values (7) 20
22.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 96764
60.8%
ASCII 62350
39.2%
None 9
 
< 0.1%
Number Forms 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 8953
14.4%
) 8909
14.3%
8183
13.1%
- 7870
12.6%
2 5801
9.3%
1 5770
9.3%
3 3641
5.8%
9 3009
 
4.8%
4 2679
 
4.3%
5 1839
 
2.9%
Other values (29) 5696
9.1%
Hangul
ValueCountFrequency (%)
계 3812
 
3.9%
사 3674
 
3.8%
장 3525
 
3.6%
지 3293
 
3.4%
공 3032
 
3.1%
대 2922
 
3.0%
상 2801
 
2.9%
환 2456
 
2.5%
관 2195
 
2.3%
설 1963
 
2.0%
Other values (419) 67091
69.3%
None
ValueCountFrequency (%)
㈜ 9
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 4
100.0%

생산기관
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경상남도 사천시
3545 
경상남도 합천군
2218 
경상남도 함안군
1006 
경상남도
621 
경상남도 양산시
561 
Other values (11)
2049 

Length

Max length8
Median length8
Mean length7.7516
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경상남도 사천시
2nd row경상남도 사천시
3rd row경상남도 사천시
4th row경상남도 사천시
5th row경상남도 사천시

Common Values

ValueCountFrequency (%)
경상남도 사천시 3545
35.4%
경상남도 합천군 2218
22.2%
경상남도 함안군 1006
 
10.1%
경상남도 621
 
6.2%
경상남도 양산시 561
 
5.6%
경상남도 하동군 555
 
5.5%
경상남도 거제시 503
 
5.0%
경상남도 창원시 429
 
4.3%
경상남도 김해시 176
 
1.8%
경상남도 의령군 153
 
1.5%
Other values (6) 233
 
2.3%

Length

2023-12-12T13:06:29.412846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경상남도 10000
51.6%
사천시 3545
 
18.3%
합천군 2218
 
11.4%
함안군 1006
 
5.2%
양산시 561
 
2.9%
하동군 555
 
2.9%
거제시 503
 
2.6%
창원시 429
 
2.2%
김해시 176
 
0.9%
의령군 153
 
0.8%
Other values (6) 233
 
1.2%

부서명
Text

Distinct151
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T13:06:29.740521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length13.6708
Min length4

Characters and Unicode

Total characters136708
Distinct characters140
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)0.1%

Sample

1st row경상남도 사천시 기획담당관
2nd row경상남도 사천시 기획담당관
3rd row경상남도 사천시 기획담당관
4th row경상남도 삼천포시
5th row경상남도 사천시 기획담당관
ValueCountFrequency (%)
경상남도 9990
32.5%
합천군 2218
 
7.2%
사천시 1899
 
6.2%
건설과 1475
 
4.8%
도시개발과 1411
 
4.6%
사천군 1320
 
4.3%
함안군 1006
 
3.3%
지역개발국 874
 
2.8%
총무국 575
 
1.9%
하동군 555
 
1.8%
Other values (140) 9392
30.6%
2023-12-12T13:06:30.333468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20715
15.2%
도 13361
 
9.8%
경 10317
 
7.5%
상 10259
 
7.5%
남 10056
 
7.4%
시 7177
 
5.2%
과 5813
 
4.3%
천 5777
 
4.2%
군 5768
 
4.2%
사 3796
 
2.8%
Other values (130) 43669
31.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 115993
84.8%
Space Separator 20715
 
15.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 13361
 
11.5%
경 10317
 
8.9%
상 10259
 
8.8%
남 10056
 
8.7%
시 7177
 
6.2%
과 5813
 
5.0%
천 5777
 
5.0%
군 5768
 
5.0%
사 3796
 
3.3%
국 3013
 
2.6%
Other values (129) 40656
35.1%
Space Separator
ValueCountFrequency (%)
20715
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 115993
84.8%
Common 20715
 
15.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 13361
 
11.5%
경 10317
 
8.9%
상 10259
 
8.8%
남 10056
 
8.7%
시 7177
 
6.2%
과 5813
 
5.0%
천 5777
 
5.0%
군 5768
 
5.0%
사 3796
 
3.3%
국 3013
 
2.6%
Other values (129) 40656
35.1%
Common
ValueCountFrequency (%)
20715
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 115993
84.8%
ASCII 20715
 
15.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20715
100.0%
Hangul
ValueCountFrequency (%)
도 13361
 
11.5%
경 10317
 
8.9%
상 10259
 
8.8%
남 10056
 
8.7%
시 7177
 
6.2%
과 5813
 
5.0%
천 5777
 
5.0%
군 5768
 
5.0%
사 3796
 
3.3%
국 3013
 
2.6%
Other values (129) 40656
35.1%

생산년도
Real number (ℝ)

SKEWED 

Distinct66
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1981.2721
Minimum1936
Maximum9999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:06:30.501667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1936
5-th percentile1950
Q11961
median1976
Q31989
95-th percentile2002
Maximum9999
Range8063
Interquartile range (IQR)28

Descriptive statistics

Standard deviation212.81425
Coefficient of variation (CV)0.10741294
Kurtosis1408.2509
Mean1981.2721
Median Absolute Deviation (MAD)14
Skewness37.443407
Sum19812721
Variance45289.906
MonotonicityNot monotonic
2023-12-12T13:06:31.067978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1950 822
 
8.2%
1960 611
 
6.1%
1981 365
 
3.6%
1959 360
 
3.6%
1979 346
 
3.5%
1978 323
 
3.2%
1975 301
 
3.0%
1977 299
 
3.0%
1976 278
 
2.8%
1972 265
 
2.6%
Other values (56) 6030
60.3%
ValueCountFrequency (%)
1936 3
 
< 0.1%
1942 1
 
< 0.1%
1945 25
 
0.2%
1948 5
 
0.1%
1949 8
 
0.1%
1950 822
8.2%
1951 22
 
0.2%
1952 15
 
0.1%
1953 21
 
0.2%
1954 116
 
1.2%
ValueCountFrequency (%)
9999 7
 
0.1%
2009 1
 
< 0.1%
2008 12
 
0.1%
2007 27
 
0.3%
2006 58
 
0.6%
2005 60
 
0.6%
2004 104
1.0%
2003 218
2.2%
2002 168
1.7%
2001 172
1.7%

건명
Text

Distinct7387
Distinct (%)73.9%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-12T13:06:31.442371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length112
Median length71
Mean length17.985399
Min length2

Characters and Unicode

Total characters179836
Distinct characters588
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6730 ?
Unique (%)67.3%

Sample

1st row사천군 읍면 직제 규칙중 개정 규칙 공포
2nd row사천군 장학금 지급조례중 개정조례 승인 신청 보완
3rd row출장복명서(군,수입증지인쇄감시)
4th row해임
5th row시군수도 급수조례 개정조례 준칙 보완지시
ValueCountFrequency (%)
시행 357
 
1.5%
및 247
 
1.0%
통보 222
 
0.9%
설계서 171
 
0.7%
따른 166
 
0.7%
대한 166
 
0.7%
포장공사 164
 
0.7%
진입로 157
 
0.6%
의뢰 154
 
0.6%
사천군 148
 
0.6%
Other values (9440) 22309
92.0%
2023-12-12T13:06:31.983402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14280
 
7.9%
( 5941
 
3.3%
) 5927
 
3.3%
사 5079
 
2.8%
* 4980
 
2.8%
지 4190
 
2.3%
공 3970
 
2.2%
장 3723
 
2.1%
대 3449
 
1.9%
상 3282
 
1.8%
Other values (578) 125015
69.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 138512
77.0%
Space Separator 14280
 
7.9%
Other Punctuation 7210
 
4.0%
Open Punctuation 5944
 
3.3%
Close Punctuation 5930
 
3.3%
Decimal Number 5310
 
3.0%
Dash Punctuation 2494
 
1.4%
Uppercase Letter 74
 
< 0.1%
Math Symbol 64
 
< 0.1%
Other Symbol 10
 
< 0.1%
Other values (2) 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 5079
 
3.7%
지 4190
 
3.0%
공 3970
 
2.9%
장 3723
 
2.7%
대 3449
 
2.5%
상 3282
 
2.4%
시 2878
 
2.1%
정 2635
 
1.9%
환 2628
 
1.9%
조 2331
 
1.7%
Other values (529) 104347
75.3%
Uppercase Letter
ValueCountFrequency (%)
P 10
13.5%
C 8
10.8%
I 8
10.8%
T 6
8.1%
A 6
8.1%
B 5
 
6.8%
R 5
 
6.8%
F 5
 
6.8%
N 5
 
6.8%
D 3
 
4.1%
Other values (9) 13
17.6%
Decimal Number
ValueCountFrequency (%)
2 940
17.7%
1 909
17.1%
9 658
12.4%
7 578
10.9%
4 475
8.9%
3 436
8.2%
5 372
 
7.0%
0 366
 
6.9%
8 361
 
6.8%
6 215
 
4.0%
Other Punctuation
ValueCountFrequency (%)
* 4980
69.1%
/ 1677
 
23.3%
, 269
 
3.7%
. 209
 
2.9%
" 37
 
0.5%
: 36
 
0.5%
' 2
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 5941
99.9%
「 2
 
< 0.1%
[ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 5927
99.9%
」 2
 
< 0.1%
] 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
o 5
83.3%
w 1
 
16.7%
Space Separator
ValueCountFrequency (%)
14280
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2494
100.0%
Math Symbol
ValueCountFrequency (%)
~ 64
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 10
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 138522
77.0%
Common 41234
 
22.9%
Latin 80
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 5079
 
3.7%
지 4190
 
3.0%
공 3970
 
2.9%
장 3723
 
2.7%
대 3449
 
2.5%
상 3282
 
2.4%
시 2878
 
2.1%
정 2635
 
1.9%
환 2628
 
1.9%
조 2331
 
1.7%
Other values (530) 104357
75.3%
Common
ValueCountFrequency (%)
14280
34.6%
( 5941
14.4%
) 5927
14.4%
* 4980
 
12.1%
- 2494
 
6.0%
/ 1677
 
4.1%
2 940
 
2.3%
1 909
 
2.2%
9 658
 
1.6%
7 578
 
1.4%
Other values (17) 2850
 
6.9%
Latin
ValueCountFrequency (%)
P 10
12.5%
C 8
10.0%
I 8
10.0%
T 6
 
7.5%
A 6
 
7.5%
o 5
 
6.2%
B 5
 
6.2%
R 5
 
6.2%
F 5
 
6.2%
N 5
 
6.2%
Other values (11) 17
21.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 138508
77.0%
ASCII 41310
 
23.0%
None 14
 
< 0.1%
Compat Jamo 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14280
34.6%
( 5941
14.4%
) 5927
14.3%
* 4980
 
12.1%
- 2494
 
6.0%
/ 1677
 
4.1%
2 940
 
2.3%
1 909
 
2.2%
9 658
 
1.6%
7 578
 
1.4%
Other values (36) 2926
 
7.1%
Hangul
ValueCountFrequency (%)
사 5079
 
3.7%
지 4190
 
3.0%
공 3970
 
2.9%
장 3723
 
2.7%
대 3449
 
2.5%
상 3282
 
2.4%
시 2878
 
2.1%
정 2635
 
1.9%
환 2628
 
1.9%
조 2331
 
1.7%
Other values (527) 104343
75.3%
None
ValueCountFrequency (%)
㈜ 10
71.4%
「 2
 
14.3%
」 2
 
14.3%
Compat Jamo
ValueCountFrequency (%)
ㆍ 3
75.0%
ㅂ 1
 
25.0%

시작쪽
Real number (ℝ)

HIGH CORRELATION 

Distinct668
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean120.3383
Minimum1
Maximum4427
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:06:32.185955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q122
median77
Q3162
95-th percentile409
Maximum4427
Range4426
Interquartile range (IQR)140

Descriptive statistics

Standard deviation147.00091
Coefficient of variation (CV)1.2215638
Kurtosis79.185575
Mean120.3383
Median Absolute Deviation (MAD)63
Skewness4.4642489
Sum1203383
Variance21609.268
MonotonicityNot monotonic
2023-12-12T13:06:32.374961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1419
 
14.2%
3 85
 
0.9%
37 78
 
0.8%
17 69
 
0.7%
11 69
 
0.7%
4 67
 
0.7%
29 64
 
0.6%
23 61
 
0.6%
13 61
 
0.6%
21 61
 
0.6%
Other values (658) 7966
79.7%
ValueCountFrequency (%)
1 1419
14.2%
2 37
 
0.4%
3 85
 
0.9%
4 67
 
0.7%
5 60
 
0.6%
6 54
 
0.5%
7 51
 
0.5%
8 45
 
0.4%
9 49
 
0.5%
10 36
 
0.4%
ValueCountFrequency (%)
4427 1
< 0.1%
1333 1
< 0.1%
1204 1
< 0.1%
1200 1
< 0.1%
1188 1
< 0.1%
1172 1
< 0.1%
1118 1
< 0.1%
1100 1
< 0.1%
1090 1
< 0.1%
1037 1
< 0.1%

끝쪽
Real number (ℝ)

HIGH CORRELATION 

Distinct718
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean139.8037
Minimum1
Maximum4658
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:06:32.545205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q140
median92
Q3184
95-th percentile433
Maximum4658
Range4657
Interquartile range (IQR)144

Descriptive statistics

Standard deviation155.47037
Coefficient of variation (CV)1.1120619
Kurtosis78.090129
Mean139.8037
Median Absolute Deviation (MAD)62
Skewness4.5434176
Sum1398037
Variance24171.037
MonotonicityNot monotonic
2023-12-12T13:06:32.728648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 170
 
1.7%
4 104
 
1.0%
22 81
 
0.8%
38 79
 
0.8%
20 78
 
0.8%
28 77
 
0.8%
6 76
 
0.8%
18 76
 
0.8%
24 72
 
0.7%
10 72
 
0.7%
Other values (708) 9115
91.1%
ValueCountFrequency (%)
1 46
 
0.5%
2 170
1.7%
3 58
 
0.6%
4 104
1.0%
5 56
 
0.6%
6 76
0.8%
7 57
 
0.6%
8 55
 
0.5%
9 50
 
0.5%
10 72
0.7%
ValueCountFrequency (%)
4658 1
< 0.1%
1377 1
< 0.1%
1337 1
< 0.1%
1336 1
< 0.1%
1332 1
< 0.1%
1262 1
< 0.1%
1251 1
< 0.1%
1213 1
< 0.1%
1198 1
< 0.1%
1171 1
< 0.1%

공개구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
비공개
9964 
부분공개
 
36

Length

Max length4
Median length3
Mean length3.0036
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
비공개 9964
99.6%
부분공개 36
 
0.4%

Length

2023-12-12T13:06:32.922052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:06:33.062396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
비공개 9964
99.6%
부분공개 36
 
0.4%

재분류공개구분
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
공개
10000 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공개 10000
100.0%

Length

2023-12-12T13:06:33.204243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:06:33.317113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공개 10000
100.0%

Interactions

2023-12-12T13:06:26.346611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:06:24.731999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:06:25.204123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:06:25.748985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:06:26.468579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:06:24.850773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:06:25.346895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:06:25.875477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:06:26.611758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:06:25.006016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:06:25.489500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:06:26.041056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:06:26.733419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:06:25.110104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:06:25.627291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:06:26.208375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:06:33.395808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번생산기관생산년도시작쪽끝쪽공개구분
순번1.0000.8750.0990.2460.1730.152
생산기관0.8751.0000.4620.1450.1990.135
생산년도0.0990.4621.0000.0000.0000.000
시작쪽0.2460.1450.0001.0000.8730.000
끝쪽0.1730.1990.0000.8731.0000.032
공개구분0.1520.1350.0000.0000.0321.000
2023-12-12T13:06:33.520358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
생산기관공개구분
생산기관1.0000.106
공개구분0.1061.000
2023-12-12T13:06:33.625384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번생산년도시작쪽끝쪽생산기관공개구분
순번1.0000.461-0.144-0.0170.5930.117
생산년도0.4611.000-0.157-0.0260.3640.000
시작쪽-0.144-0.1571.0000.8740.0740.000
끝쪽-0.017-0.0260.8741.0000.0950.021
생산기관0.5930.3640.0740.0951.0000.106
공개구분0.1170.0000.0000.0210.1061.000

Missing values

2023-12-12T13:06:26.925989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:06:27.158600image/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

순번관리번호기록물철명생산기관부서명생산년도건명시작쪽끝쪽공개구분재분류공개구분
73257326GA0019205-003규칙 공포 원본-사천군(4-3)경상남도 사천시경상남도 사천시 기획담당관1974사천군 읍면 직제 규칙중 개정 규칙 공포294296비공개공개
82278228GA0019241-002조례 공포-사천군(2-2)경상남도 사천시경상남도 사천시 기획담당관1979사천군 장학금 지급조례중 개정조례 승인 신청 보완134135비공개공개
71197120GA0019192-002조례관계철-사천군(4-2)경상남도 사천시경상남도 사천시 기획담당관1972출장복명서(군,수입증지인쇄감시)122123비공개공개
1165111652GA0019419-002인사발령철(2-2)경상남도 사천시경상남도 삼천포시1971해임158160비공개공개
84248425GA0019248-002조례제정-사천군(2-2)경상남도 사천시경상남도 사천시 기획담당관1979시군수도 급수조례 개정조례 준칙 보완지시111112비공개공개
4255842559GA0042388어곡지방산업단지실시계획(변경)승인신청서경상남도 양산시경상남도 양산시 도시개발사업단 도시개발과2006어곡일반지방산업단지실시계획변경협의회신1125비공개공개
1644416445GA0019445-001상환대장(4-1)경상남도 사천시경상남도 사천군1960상환대장(서포면)-(황**)9192비공개공개
3778237783GA0013279계성천폐천부지양여경상남도 창녕군경상남도 창녕군 건설과1983하천공작물설치공사준공정산금액조정/하천공작물설치공사준공정산금액조정보고84110비공개공개
1830518306GA0019453-004상환대장(4-4)경상남도 사천시경상남도 사천군1960상환대장(정동면)-(조**)611612비공개공개
11191120GA0017177고속버스관계경상남도경상남도 도시교통국 교통정책과1979고속버스여객자동차운송사업계획변경(영업소설치)인가신청서진달128144비공개공개
순번관리번호기록물철명생산기관부서명생산년도건명시작쪽끝쪽공개구분재분류공개구분
83918392GA0019247-003조례공포원본-삼천포시(3-3)경상남도 사천시경상남도 사천시 기획담당관1979시군수도 급수조례 개정조례 준칙 보완지시226227비공개공개
2585025851GA00051321950년분배농지상환대장(4-4)경상남도 함안군경상남도 함안군 군북면1950상환대장(허**)4344비공개공개
1725117252GA0019449-002상환대장(2-2)경상남도 사천시경상남도 사천군1960상환대장(정동면)-(박**)266267비공개공개
75197520GA0019210-005조례 공포 원본-사천군(5-5)경상남도 사천시경상남도 사천시 기획담당관1975사천군 촉탁의료인 보수 지급 조례 공포 시행447449비공개공개
1425014251GA0019434-004상환대장(4-4)경상남도 사천시경상남도 사천군1959상환대장(곤양면)-(박**)696697비공개공개
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