Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells18449
Missing cells (%)23.1%
Duplicate rows100
Duplicate rows (%)1.0%
Total size in memory732.4 KiB
Average record size in memory75.0 B

Variable types

Text3
Numeric3
Categorical2

Dataset

Description사업번호,구분코드,구분명,세부절차코드,세부절차명,일자,제목,상세내용
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-2254/S/1/datasetView.do

Alerts

Dataset has 100 (1.0%) duplicate rowsDuplicates
구분코드 is highly overall correlated with 세부절차코드 and 2 other fieldsHigh correlation
세부절차코드 is highly overall correlated with 구분코드 and 2 other fieldsHigh correlation
구분명 is highly overall correlated with 구분코드 and 2 other fieldsHigh correlation
세부절차명 is highly overall correlated with 구분코드 and 2 other fieldsHigh correlation
제목 has 8822 (88.2%) missing valuesMissing
상세내용 has 9627 (96.3%) missing valuesMissing

Reproduction

Analysis started2024-03-13 16:04:26.438469
Analysis finished2024-03-13 16:04:28.708054
Duration2.27 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업번호
Text

Distinct677
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T01:04:28.863484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length15
Mean length15
Min length15

Characters and Unicode

Total characters150000
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

Unique54 ?
Unique (%)0.5%

Sample

1st row11680-900000542
2nd row11440-100001010
3rd row11590-100001008
4th row11230-100003014
5th row11200-100002006
ValueCountFrequency (%)
11350-100002002 62
 
0.6%
11110-100003002 53
 
0.5%
11740-900000167 52
 
0.5%
11650-900000073 52
 
0.5%
11230-100003005 51
 
0.5%
11380-100001060 51
 
0.5%
11410-100007003 50
 
0.5%
11380-100001048 50
 
0.5%
11170-100004005 50
 
0.5%
11290-100016001 48
 
0.5%
Other values (667) 9481
94.8%
2024-03-14T01:04:29.166764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 66639
44.4%
1 35124
23.4%
- 10000
 
6.7%
2 6730
 
4.5%
9 5329
 
3.6%
5 5196
 
3.5%
3 5073
 
3.4%
4 5019
 
3.3%
6 4717
 
3.1%
7 3650
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 140000
93.3%
Dash Punctuation 10000
 
6.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 66639
47.6%
1 35124
25.1%
2 6730
 
4.8%
9 5329
 
3.8%
5 5196
 
3.7%
3 5073
 
3.6%
4 5019
 
3.6%
6 4717
 
3.4%
7 3650
 
2.6%
8 2523
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 150000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 66639
44.4%
1 35124
23.4%
- 10000
 
6.7%
2 6730
 
4.5%
9 5329
 
3.6%
5 5196
 
3.5%
3 5073
 
3.4%
4 5019
 
3.3%
6 4717
 
3.1%
7 3650
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 150000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 66639
44.4%
1 35124
23.4%
- 10000
 
6.7%
2 6730
 
4.5%
9 5329
 
3.6%
5 5196
 
3.5%
3 5073
 
3.4%
4 5019
 
3.3%
6 4717
 
3.1%
7 3650
 
2.4%

구분코드
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean154.361
Minimum110
Maximum230
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T01:04:29.281176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum110
5-th percentile140
Q1150
median150
Q3160
95-th percentile179
Maximum230
Range120
Interquartile range (IQR)10

Descriptive statistics

Standard deviation14.40191
Coefficient of variation (CV)0.093300188
Kurtosis6.5225676
Mean154.361
Median Absolute Deviation (MAD)6
Skewness1.8698215
Sum1543610
Variance207.41502
MonotonicityNot monotonic
2024-03-14T01:04:29.383554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
150 3070
30.7%
160 1276
12.8%
156 1168
 
11.7%
145 1122
 
11.2%
170 806
 
8.1%
140 779
 
7.8%
155 593
 
5.9%
130 402
 
4.0%
157 185
 
1.8%
210 147
 
1.5%
Other values (9) 452
 
4.5%
ValueCountFrequency (%)
110 20
 
0.2%
120 31
 
0.3%
130 402
 
4.0%
140 779
 
7.8%
145 1122
 
11.2%
150 3070
30.7%
155 593
 
5.9%
156 1168
 
11.7%
157 185
 
1.8%
160 1276
12.8%
ValueCountFrequency (%)
230 31
 
0.3%
225 2
 
< 0.1%
220 35
 
0.4%
210 147
 
1.5%
200 94
 
0.9%
190 93
 
0.9%
180 78
 
0.8%
179 68
 
0.7%
170 806
8.1%
160 1276
12.8%

구분명
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
조합설립인가
3070 
사업시행인가
1276 
설계자선정
1168 
정비사업전문관리업자선정
1122 
관리처분인가
806 
Other values (14)
2558 

Length

Max length12
Median length6
Mean length6.776
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row설계자선정
2nd row정비사업전문관리업자선정
3rd row철거업자선정
4th row조합설립인가
5th row시공자선정

Common Values

ValueCountFrequency (%)
조합설립인가 3070
30.7%
사업시행인가 1276
12.8%
설계자선정 1168
 
11.7%
정비사업전문관리업자선정 1122
 
11.2%
관리처분인가 806
 
8.1%
조합설립추진위원회승인 779
 
7.8%
시공자선정 593
 
5.9%
정비구역지정 402
 
4.0%
철거업자선정 185
 
1.8%
준공인가 147
 
1.5%
Other values (9) 452
 
4.5%

Length

2024-03-14T01:04:29.493464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
조합설립인가 3070
30.7%
사업시행인가 1276
12.8%
설계자선정 1168
 
11.7%
정비사업전문관리업자선정 1122
 
11.2%
관리처분인가 806
 
8.1%
조합설립추진위원회승인 779
 
7.8%
시공자선정 593
 
5.9%
정비구역지정 402
 
4.0%
철거업자선정 185
 
1.8%
준공인가 147
 
1.5%
Other values (9) 452
 
4.5%

세부절차코드
Real number (ℝ)

HIGH CORRELATION 

Distinct74
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean154365.94
Minimum110001
Maximum230999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T01:04:29.617326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum110001
5-th percentile140003
Q1150002
median150003
Q3160002
95-th percentile179002
Maximum230999
Range120998
Interquartile range (IQR)10000

Descriptive statistics

Standard deviation14405.052
Coefficient of variation (CV)0.09331755
Kurtosis6.525928
Mean154365.94
Median Absolute Deviation (MAD)5998
Skewness1.8712553
Sum1.5436594 × 109
Variance2.0750552 × 108
MonotonicityNot monotonic
2024-03-14T01:04:29.759259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
150003 1500
15.0%
150002 1481
14.8%
156002 669
 
6.7%
145002 581
 
5.8%
145001 530
 
5.3%
156001 494
 
4.9%
160004 443
 
4.4%
160002 428
 
4.3%
140004 397
 
4.0%
160005 374
 
3.7%
Other values (64) 3103
31.0%
ValueCountFrequency (%)
110001 6
0.1%
110002 13
0.1%
110999 1
 
< 0.1%
120001 11
0.1%
120002 3
 
< 0.1%
120003 5
 
0.1%
120004 3
 
< 0.1%
120005 9
0.1%
130001 10
0.1%
130002 6
0.1%
ValueCountFrequency (%)
230999 1
 
< 0.1%
230001 30
0.3%
225001 2
 
< 0.1%
220999 2
 
< 0.1%
220001 33
0.3%
210999 1
 
< 0.1%
210004 64
0.6%
210003 61
0.6%
210002 12
 
0.1%
210001 9
 
0.1%

세부절차명
Categorical

HIGH CORRELATION 

Distinct46
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
(변경)인가신청
2191 
(변경)인가
2097 
계약(변경)
1679 
업체선정
1367 
(변경)인가고시
667 
Other values (41)
1999 

Length

Max length24
Median length22
Mean length6.7153
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row계약(변경)
2nd row계약(변경)
3rd row계약(변경)
4th row(변경)인가신청
5th row계약(변경)

Common Values

ValueCountFrequency (%)
(변경)인가신청 2191
21.9%
(변경)인가 2097
21.0%
계약(변경) 1679
16.8%
업체선정 1367
13.7%
(변경)인가고시 667
 
6.7%
(변경)승인 397
 
4.0%
(변경)승인신청 342
 
3.4%
구역지정(변경)고시 : 서울시 288
 
2.9%
총회개최 97
 
1.0%
착공신고 80
 
0.8%
Other values (36) 795
 
8.0%

Length

2024-03-14T01:04:29.880339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
변경)인가신청 2191
19.8%
변경)인가 2097
18.9%
계약(변경 1679
15.2%
업체선정 1367
12.4%
변경)인가고시 667
 
6.0%
457
 
4.1%
변경)승인 397
 
3.6%
변경)승인신청 342
 
3.1%
서울시 320
 
2.9%
구역지정(변경)고시 288
 
2.6%
Other values (46) 1261
11.4%

일자
Real number (ℝ)

Distinct4300
Distinct (%)43.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20149840
Minimum19790921
Maximum20240223
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T01:04:30.052361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19790921
5-th percentile20051129
Q120110283
median20160225
Q320191202
95-th percentile20230316
Maximum20240223
Range449302
Interquartile range (IQR)80919.25

Descriptive statistics

Standard deviation54551.468
Coefficient of variation (CV)0.0027072904
Kurtosis-0.40577451
Mean20149840
Median Absolute Deviation (MAD)40580
Skewness-0.42926971
Sum2.014984 × 1011
Variance2.9758626 × 109
MonotonicityNot monotonic
2024-03-14T01:04:30.183660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091215 26
 
0.3%
20091211 20
 
0.2%
20091216 17
 
0.2%
20091130 17
 
0.2%
20091218 15
 
0.1%
20091214 14
 
0.1%
20091217 13
 
0.1%
20160610 11
 
0.1%
20091210 11
 
0.1%
20200918 11
 
0.1%
Other values (4290) 9845
98.5%
ValueCountFrequency (%)
19790921 1
 
< 0.1%
19811208 1
 
< 0.1%
19950518 1
 
< 0.1%
19960215 1
 
< 0.1%
19970605 1
 
< 0.1%
19970729 1
 
< 0.1%
19970806 1
 
< 0.1%
19970818 1
 
< 0.1%
19971105 2
 
< 0.1%
19980615 5
0.1%
ValueCountFrequency (%)
20240223 1
< 0.1%
20240222 1
< 0.1%
20240220 2
< 0.1%
20240219 2
< 0.1%
20240217 1
< 0.1%
20240216 2
< 0.1%
20240214 1
< 0.1%
20240207 2
< 0.1%
20240206 1
< 0.1%
20240205 2
< 0.1%

제목
Text

MISSING 

Distinct909
Distinct (%)77.2%
Missing8822
Missing (%)88.2%
Memory size156.2 KiB
2024-03-14T01:04:30.425052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length48
Mean length17.061969
Min length4

Characters and Unicode

Total characters20099
Distinct characters328
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

Unique784 ?
Unique (%)66.6%

Sample

1st row조합설립법인등기
2nd row정비구역 지정고시
3rd row고척제4주택재개발 기본계획변경, 정비구역지정 및 지형도면고시
4th row문정동136번지일대주택재건축조합설립인가신청
5th row창신1,2,3,4 도시정비형 재개발사업 정비구역 고시
ValueCountFrequency (%)
및 187
 
5.3%
고시 134
 
3.8%
지형도면 110
 
3.1%
변경 67
 
1.9%
정비구역 65
 
1.8%
신청 51
 
1.4%
지정 48
 
1.4%
위한 44
 
1.2%
승인 43
 
1.2%
결정 35
 
1.0%
Other values (1141) 2740
77.8%
2024-03-14T01:04:30.808796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2364
 
11.8%
정 958
 
4.8%
비 521
 
2.6%
지 505
 
2.5%
경 491
 
2.4%
시 483
 
2.4%
구 467
 
2.3%
고 437
 
2.2%
변 398
 
2.0%
계 384
 
1.9%
Other values (318) 13091
65.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16230
80.8%
Space Separator 2364
 
11.8%
Decimal Number 745
 
3.7%
Open Punctuation 295
 
1.5%
Close Punctuation 286
 
1.4%
Other Punctuation 89
 
0.4%
Dash Punctuation 47
 
0.2%
Connector Punctuation 18
 
0.1%
Math Symbol 16
 
0.1%
Uppercase Letter 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 958
 
5.9%
비 521
 
3.2%
지 505
 
3.1%
경 491
 
3.0%
시 483
 
3.0%
구 467
 
2.9%
고 437
 
2.7%
변 398
 
2.5%
계 384
 
2.4%
역 376
 
2.3%
Other values (287) 11210
69.1%
Decimal Number
ValueCountFrequency (%)
1 207
27.8%
2 133
17.9%
0 115
15.4%
3 100
13.4%
4 51
 
6.8%
6 43
 
5.8%
5 39
 
5.2%
8 20
 
2.7%
9 20
 
2.7%
7 17
 
2.3%
Other Punctuation
ValueCountFrequency (%)
, 40
44.9%
. 30
33.7%
? 7
 
7.9%
/ 6
 
6.7%
？ 4
 
4.5%
' 1
 
1.1%
* 1
 
1.1%
Math Symbol
ValueCountFrequency (%)
+ 12
75.0%
~ 3
 
18.8%
> 1
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
D 3
42.9%
C 2
28.6%
M 2
28.6%
Open Punctuation
ValueCountFrequency (%)
( 292
99.0%
[ 3
 
1.0%
Close Punctuation
ValueCountFrequency (%)
) 284
99.3%
] 2
 
0.7%
Space Separator
ValueCountFrequency (%)
2364
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 18
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16230
80.8%
Common 3860
 
19.2%
Latin 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 958
 
5.9%
비 521
 
3.2%
지 505
 
3.1%
경 491
 
3.0%
시 483
 
3.0%
구 467
 
2.9%
고 437
 
2.7%
변 398
 
2.5%
계 384
 
2.4%
역 376
 
2.3%
Other values (287) 11210
69.1%
Common
ValueCountFrequency (%)
2364
61.2%
( 292
 
7.6%
) 284
 
7.4%
1 207
 
5.4%
2 133
 
3.4%
0 115
 
3.0%
3 100
 
2.6%
4 51
 
1.3%
- 47
 
1.2%
6 43
 
1.1%
Other values (17) 224
 
5.8%
Latin
ValueCountFrequency (%)
D 3
33.3%
e 2
22.2%
C 2
22.2%
M 2
22.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16229
80.7%
ASCII 3865
 
19.2%
None 4
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2364
61.2%
( 292
 
7.6%
) 284
 
7.3%
1 207
 
5.4%
2 133
 
3.4%
0 115
 
3.0%
3 100
 
2.6%
4 51
 
1.3%
- 47
 
1.2%
6 43
 
1.1%
Other values (20) 229
 
5.9%
Hangul
ValueCountFrequency (%)
정 958
 
5.9%
비 521
 
3.2%
지 505
 
3.1%
경 491
 
3.0%
시 483
 
3.0%
구 467
 
2.9%
고 437
 
2.7%
변 398
 
2.5%
계 384
 
2.4%
역 376
 
2.3%
Other values (286) 11209
69.1%
None
ValueCountFrequency (%)
？ 4
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅔ 1
100.0%

상세내용
Text

MISSING 

Distinct328
Distinct (%)87.9%
Missing9627
Missing (%)96.3%
Memory size156.2 KiB
2024-03-14T01:04:31.124958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1024
Median length126
Mean length38.697051
Min length1

Characters and Unicode

Total characters14434
Distinct characters388
Distinct categories14 ?
Distinct scripts3 ?
Distinct blocks9 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique300 ?
Unique (%)80.4%

Sample

1st row문정동136번지일대주택재건축조합설립인가신청을 함
2nd row문정동 136번지 일원 재건축정비사업조합설립(변경)신청
3rd row주택과 6372(2020.8.19)로 입주자보집 승인(153세대,일반.특별공급)
4th row양재대로 1109, 1층 관리사무소 -> 오금로31가길 20, 202호 대림가락상가
5th row2012-06-27 : 흑석재정비촉진계획 변경 결정 요청
ValueCountFrequency (%)
160
 
5.7%
및 77
 
2.8%
건 58
 
2.1%
안건 33
 
1.2%
변경 33
 
1.2%
신청 22
 
0.8%
문정동 17
 
0.6%
일원 16
 
0.6%
136번지 16
 
0.6%
승인의 15
 
0.5%
Other values (1479) 2347
84.0%
2024-03-14T01:04:31.543818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2600
 
18.0%
1 453
 
3.1%
2 437
 
3.0%
0 411
 
2.8%
. 262
 
1.8%
정 233
 
1.6%
의 192
 
1.3%
사 192
 
1.3%
건 191
 
1.3%
조 191
 
1.3%
Other values (378) 9272
64.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8595
59.5%
Space Separator 2600
 
18.0%
Decimal Number 2080
 
14.4%
Other Punctuation 556
 
3.9%
Close Punctuation 197
 
1.4%
Open Punctuation 190
 
1.3%
Dash Punctuation 140
 
1.0%
Math Symbol 45
 
0.3%
Uppercase Letter 14
 
0.1%
Other Symbol 8
 
0.1%
Other values (4) 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 233
 
2.7%
의 192
 
2.2%
사 192
 
2.2%
건 191
 
2.2%
조 191
 
2.2%
시 170
 
2.0%
합 157
 
1.8%
원 152
 
1.8%
인 152
 
1.8%
업 151
 
1.8%
Other values (329) 6814
79.3%
Decimal Number
ValueCountFrequency (%)
1 453
21.8%
2 437
21.0%
0 411
19.8%
3 158
 
7.6%
6 119
 
5.7%
9 112
 
5.4%
8 102
 
4.9%
5 100
 
4.8%
4 98
 
4.7%
7 90
 
4.3%
Other Punctuation
ValueCountFrequency (%)
. 262
47.1%
, 123
22.1%
: 120
21.6%
/ 25
 
4.5%
' 12
 
2.2%
% 10
 
1.8%
？ 2
 
0.4%
* 1
 
0.2%
※ 1
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
D 4
28.6%
S 3
21.4%
N 2
14.3%
C 2
14.3%
Q 1
 
7.1%
P 1
 
7.1%
H 1
 
7.1%
Close Punctuation
ValueCountFrequency (%)
) 191
97.0%
』 3
 
1.5%
」 2
 
1.0%
] 1
 
0.5%
Open Punctuation
ValueCountFrequency (%)
( 184
96.8%
『 3
 
1.6%
「 2
 
1.1%
[ 1
 
0.5%
Math Symbol
ValueCountFrequency (%)
~ 39
86.7%
> 4
 
8.9%
→ 2
 
4.4%
Other Symbol
ValueCountFrequency (%)
○ 6
75.0%
㈜ 1
 
12.5%
㎡ 1
 
12.5%
Other Number
ValueCountFrequency (%)
② 2
40.0%
① 2
40.0%
③ 1
20.0%
Letter Number
ValueCountFrequency (%)
Ⅲ 1
50.0%
Ⅳ 1
50.0%
Space Separator
ValueCountFrequency (%)
2600
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 140
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8596
59.6%
Common 5822
40.3%
Latin 16
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 233
 
2.7%
의 192
 
2.2%
사 192
 
2.2%
건 191
 
2.2%
조 191
 
2.2%
시 170
 
2.0%
합 157
 
1.8%
원 152
 
1.8%
인 152
 
1.8%
업 151
 
1.8%
Other values (330) 6815
79.3%
Common
ValueCountFrequency (%)
2600
44.7%
1 453
 
7.8%
2 437
 
7.5%
0 411
 
7.1%
. 262
 
4.5%
) 191
 
3.3%
( 184
 
3.2%
3 158
 
2.7%
- 140
 
2.4%
, 123
 
2.1%
Other values (29) 863
 
14.8%
Latin
ValueCountFrequency (%)
D 4
25.0%
S 3
18.8%
N 2
12.5%
C 2
12.5%
Ⅲ 1
 
6.2%
Ⅳ 1
 
6.2%
Q 1
 
6.2%
P 1
 
6.2%
H 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8595
59.5%
ASCII 5809
40.2%
None 13
 
0.1%
Geometric Shapes 6
 
< 0.1%
Enclosed Alphanum 5
 
< 0.1%
Arrows 2
 
< 0.1%
Number Forms 2
 
< 0.1%
Punctuation 1
 
< 0.1%
CJK Compat 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2600
44.8%
1 453
 
7.8%
2 437
 
7.5%
0 411
 
7.1%
. 262
 
4.5%
) 191
 
3.3%
( 184
 
3.2%
3 158
 
2.7%
- 140
 
2.4%
, 123
 
2.1%
Other values (24) 850
 
14.6%
Hangul
ValueCountFrequency (%)
정 233
 
2.7%
의 192
 
2.2%
사 192
 
2.2%
건 191
 
2.2%
조 191
 
2.2%
시 170
 
2.0%
합 157
 
1.8%
원 152
 
1.8%
인 152
 
1.8%
업 151
 
1.8%
Other values (329) 6814
79.3%
Geometric Shapes
ValueCountFrequency (%)
○ 6
100.0%
None
ValueCountFrequency (%)
』 3
23.1%
『 3
23.1%
」 2
15.4%
「 2
15.4%
？ 2
15.4%
㈜ 1
 
7.7%
Arrows
ValueCountFrequency (%)
→ 2
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
② 2
40.0%
① 2
40.0%
③ 1
20.0%
Number Forms
ValueCountFrequency (%)
Ⅲ 1
50.0%
Ⅳ 1
50.0%
Punctuation
ValueCountFrequency (%)
※ 1
100.0%
CJK Compat
ValueCountFrequency (%)
㎡ 1
100.0%

Interactions

2024-03-14T01:04:28.133677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:04:27.206793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:04:27.846921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:04:28.219332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:04:27.291226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:04:27.946661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:04:28.306801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:04:27.733792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:04:28.047374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T01:04:31.634651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분코드구분명세부절차코드세부절차명일자
구분코드1.0001.0001.0000.9920.301
구분명1.0001.0001.0000.9900.392
세부절차코드1.0001.0001.0000.9940.298
세부절차명0.9920.9900.9941.0000.415
일자0.3010.3920.2980.4151.000
2024-03-14T01:04:31.719958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세부절차명구분명
세부절차명1.0000.850
구분명0.8501.000
2024-03-14T01:04:31.807116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분코드세부절차코드일자구분명세부절차명
구분코드1.0000.9860.2431.0000.924
세부절차코드0.9861.0000.2400.9990.924
일자0.2430.2401.0000.1760.171
구분명1.0000.9990.1761.0000.850
세부절차명0.9240.9240.1710.8501.000

Missing values

2024-03-14T01:04:28.441794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T01:04:28.554566image/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.
2024-03-14T01:04:28.655299image/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

사업번호구분코드구분명세부절차코드세부절차명일자제목상세내용
335911680-900000542156설계자선정156002계약(변경)20190906<NA><NA>
1270611440-100001010145정비사업전문관리업자선정145002계약(변경)20060922<NA><NA>
844311590-100001008157철거업자선정157002계약(변경)20091217<NA><NA>
2251611230-100003014150조합설립인가150002(변경)인가신청20200917<NA><NA>
2451711200-100002006155시공자선정155002계약(변경)20180314<NA><NA>
301211680-900000694150조합설립인가150004법인등기20180717조합설립법인등기<NA>
1783111320-100003000150조합설립인가150003(변경)인가20170801<NA><NA>
2435511200-100002009150조합설립인가150002(변경)인가신청20210416<NA><NA>
2430111200-100002012150조합설립인가150002(변경)인가신청20091208<NA><NA>
2507911170-900000882150조합설립인가150002(변경)인가신청20220401<NA><NA>
사업번호구분코드구분명세부절차코드세부절차명일자제목상세내용
467211650-900000608156설계자선정156002계약(변경)20170511<NA><NA>
2336911215-100002002150조합설립인가150002(변경)인가신청20221220<NA><NA>
1576611380-100001053150조합설립인가150002(변경)인가신청20141229<NA><NA>
885611560-900000008160사업시행인가160004(변경)인가고시20200102<NA><NA>
712611620-100003009156설계자선정156002계약(변경)20141001<NA><NA>
814311590-100002006150조합설립인가150002(변경)인가신청20150410<NA><NA>
1711211350-100002015140조합설립추진위원회승인140003(변경)승인신청20080912<NA><NA>
1679211380-100000035156설계자선정156002계약(변경)20050204<NA><NA>
1474711410-100003002200일반분양승인200003일반분양공고20160818<NA><NA>
972611560-100003008160사업시행인가160005(변경)인가20140128<NA><NA>

Duplicate rows

Most frequently occurring

사업번호구분코드구분명세부절차코드세부절차명일자제목상세내용# duplicates
211170-100005007156설계자선정156002계약(변경)20091211<NA><NA>3
1311200-900000044156설계자선정156001업체선정20230322<NA><NA>3
3011290-100011001150조합설립인가150002(변경)인가신청19980615<NA><NA>3
3411290-100016004150조합설립인가150003(변경)인가20131022<NA><NA>3
6811470-100001017156설계자선정156002계약(변경)20091215<NA><NA>3
8211620-100002000155시공자선정155001업체선정20091218<NA><NA>3
011110-100002009145정비사업전문관리업자선정145001업체선정20091223<NA><NA>2
111170-100004002170관리처분인가170005(변경)인가신청20080627<NA><NA>2
311200-100001001145정비사업전문관리업자선정145002계약(변경)20170531<NA><NA>2
411200-100001002140조합설립추진위원회승인140004(변경)승인20070716<NA><NA>2