Overview

Dataset statistics

Number of variables23
Number of observations2082
Missing cells5886
Missing cells (%)12.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory388.5 KiB
Average record size in memory191.1 B

Variable types

Numeric6
Text13
Categorical4

Dataset

Description건물 번호,기관 번호,주소1,소유자,조사일자,조사정보,건물용도,전체면적,구조물,준공일,이름,지상층고,지하층고,조사기관,옥탑,주소2,보고서,TMPNO,석면함유면적,재산관리부서,해체제거면적,기관명,석면함유량
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15383/S/1/datasetView.do

Alerts

조사정보 is highly imbalanced (66.3%)Imbalance
조사기관 is highly imbalanced (55.3%)Imbalance
옥탑 is highly imbalanced (59.4%)Imbalance
전체면적 has 176 (8.5%) missing valuesMissing
구조물 has 239 (11.5%) missing valuesMissing
준공일 has 256 (12.3%) missing valuesMissing
주소2 has 742 (35.6%) missing valuesMissing
보고서 has 995 (47.8%) missing valuesMissing
TMPNO has 1805 (86.7%) missing valuesMissing
해체제거면적 has 1638 (78.7%) missing valuesMissing
건물 번호 has unique valuesUnique
지상층고 has 30 (1.4%) zerosZeros
지하층고 has 1317 (63.3%) zerosZeros
석면함유량 has 1111 (53.4%) zerosZeros

Reproduction

Analysis started2024-05-18 07:27:55.639274
Analysis finished2024-05-18 07:27:58.772764
Duration3.13 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

건물 번호
Real number (ℝ)

UNIQUE 

Distinct2082
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1094.793
Minimum1
Maximum2595
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.4 KiB
2024-05-18T16:27:58.994472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile108.05
Q1534.25
median1097.5
Q31622.75
95-th percentile2070.95
Maximum2595
Range2594
Interquartile range (IQR)1088.5

Descriptive statistics

Standard deviation641.70383
Coefficient of variation (CV)0.5861417
Kurtosis-1.0184183
Mean1094.793
Median Absolute Deviation (MAD)544.5
Skewness0.081314492
Sum2279359
Variance411783.8
MonotonicityNot monotonic
2024-05-18T16:27:59.467502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2273 1
 
< 0.1%
734 1
 
< 0.1%
738 1
 
< 0.1%
739 1
 
< 0.1%
737 1
 
< 0.1%
736 1
 
< 0.1%
735 1
 
< 0.1%
744 1
 
< 0.1%
745 1
 
< 0.1%
746 1
 
< 0.1%
Other values (2072) 2072
99.5%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
2595 1
< 0.1%
2594 1
< 0.1%
2593 1
< 0.1%
2592 1
< 0.1%
2591 1
< 0.1%
2571 1
< 0.1%
2551 1
< 0.1%
2536 1
< 0.1%
2535 1
< 0.1%
2534 1
< 0.1%

기관 번호
Real number (ℝ)

Distinct599
Distinct (%)28.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean401.40682
Minimum1
Maximum767
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.4 KiB
2024-05-18T16:27:59.907675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile67.05
Q1249
median482.5
Q3531.75
95-th percentile602.95
Maximum767
Range766
Interquartile range (IQR)282.75

Descriptive statistics

Standard deviation172.61481
Coefficient of variation (CV)0.4300246
Kurtosis-0.7670605
Mean401.40682
Median Absolute Deviation (MAD)81.5
Skewness-0.57826144
Sum835729
Variance29795.872
MonotonicityNot monotonic
2024-05-18T16:28:00.349365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
563 177
 
8.5%
519 119
 
5.7%
499 95
 
4.6%
564 83
 
4.0%
502 69
 
3.3%
558 56
 
2.7%
501 51
 
2.4%
633 41
 
2.0%
246 39
 
1.9%
245 34
 
1.6%
Other values (589) 1318
63.3%
ValueCountFrequency (%)
1 1
 
< 0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 2
0.1%
9 3
0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
767 1
 
< 0.1%
766 3
0.1%
765 1
 
< 0.1%
764 1
 
< 0.1%
763 1
 
< 0.1%
762 1
 
< 0.1%
761 1
 
< 0.1%
760 1
 
< 0.1%
741 4
0.2%
740 1
 
< 0.1%
Distinct616
Distinct (%)29.6%
Missing2
Missing (%)0.1%
Memory size16.4 KiB
2024-05-18T16:28:01.140407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length23
Mean length11.782212
Min length4

Characters and Unicode

Total characters24507
Distinct characters217
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique441 ?
Unique (%)21.2%

Sample

1st row서울시 마포구 중동 38-6
2nd row강서구
3rd row서울시 마포구 중동 38-6
4th row서울시 마포구 중동 38-6
5th row서울특별시
ValueCountFrequency (%)
서울특별시 779
 
13.2%
서울시 517
 
8.7%
경기도 310
 
5.2%
강서구 217
 
3.7%
과천시 193
 
3.3%
성동구 187
 
3.2%
막계동 158
 
2.7%
마곡동 157
 
2.7%
강남구 129
 
2.2%
광진구 92
 
1.6%
Other values (691) 3174
53.7%
2024-05-18T16:28:02.171423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4461
18.2%
1797
 
7.3%
1729
 
7.1%
1646
 
6.7%
1646
 
6.7%
1323
 
5.4%
783
 
3.2%
783
 
3.2%
446
 
1.8%
1 415
 
1.7%
Other values (207) 9478
38.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17721
72.3%
Space Separator 4461
 
18.2%
Decimal Number 2012
 
8.2%
Dash Punctuation 303
 
1.2%
Open Punctuation 4
 
< 0.1%
Close Punctuation 4
 
< 0.1%
Control 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1797
 
10.1%
1729
 
9.8%
1646
 
9.3%
1646
 
9.3%
1323
 
7.5%
783
 
4.4%
783
 
4.4%
446
 
2.5%
368
 
2.1%
366
 
2.1%
Other values (191) 6834
38.6%
Decimal Number
ValueCountFrequency (%)
1 415
20.6%
2 222
11.0%
3 214
10.6%
4 194
9.6%
6 186
9.2%
0 186
9.2%
5 168
8.3%
7 161
 
8.0%
9 141
 
7.0%
8 125
 
6.2%
Space Separator
ValueCountFrequency (%)
4461
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 303
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Control
ValueCountFrequency (%)
1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17721
72.3%
Common 6786
 
27.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1797
 
10.1%
1729
 
9.8%
1646
 
9.3%
1646
 
9.3%
1323
 
7.5%
783
 
4.4%
783
 
4.4%
446
 
2.5%
368
 
2.1%
366
 
2.1%
Other values (191) 6834
38.6%
Common
ValueCountFrequency (%)
4461
65.7%
1 415
 
6.1%
- 303
 
4.5%
2 222
 
3.3%
3 214
 
3.2%
4 194
 
2.9%
6 186
 
2.7%
0 186
 
2.7%
5 168
 
2.5%
7 161
 
2.4%
Other values (6) 276
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17721
72.3%
ASCII 6786
 
27.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4461
65.7%
1 415
 
6.1%
- 303
 
4.5%
2 222
 
3.3%
3 214
 
3.2%
4 194
 
2.9%
6 186
 
2.7%
0 186
 
2.7%
5 168
 
2.5%
7 161
 
2.4%
Other values (6) 276
 
4.1%
Hangul
ValueCountFrequency (%)
1797
 
10.1%
1729
 
9.8%
1646
 
9.3%
1646
 
9.3%
1323
 
7.5%
783
 
4.4%
783
 
4.4%
446
 
2.5%
368
 
2.1%
366
 
2.1%
Other values (191) 6834
38.6%
Distinct441
Distinct (%)21.3%
Missing13
Missing (%)0.6%
Memory size16.4 KiB
2024-05-18T16:28:02.772703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length8.2266796
Min length1

Characters and Unicode

Total characters17021
Distinct characters291
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique245 ?
Unique (%)11.8%

Sample

1st row시설과
2nd row(주)서남환경
3rd row시설과
4th row시설과
5th row북부기술교육원 운영지원팀
ValueCountFrequency (%)
수처리과 166
 
5.4%
㈜서남환경 151
 
4.9%
시설팀 143
 
4.6%
총무과 143
 
4.6%
시설과 104
 
3.4%
보수과 100
 
3.2%
중랑물재생센터 90
 
2.9%
서울대공원 83
 
2.7%
난지물재생센터 83
 
2.7%
장비회계팀 77
 
2.5%
Other values (443) 1956
63.2%
2024-05-18T16:28:03.750479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1076
 
6.3%
983
 
5.8%
694
 
4.1%
674
 
4.0%
634
 
3.7%
603
 
3.5%
506
 
3.0%
460
 
2.7%
408
 
2.4%
408
 
2.4%
Other values (281) 10575
62.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15528
91.2%
Space Separator 1076
 
6.3%
Other Symbol 229
 
1.3%
Close Punctuation 69
 
0.4%
Open Punctuation 66
 
0.4%
Uppercase Letter 37
 
0.2%
Dash Punctuation 5
 
< 0.1%
Other Punctuation 5
 
< 0.1%
Decimal Number 5
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
983
 
6.3%
694
 
4.5%
674
 
4.3%
634
 
4.1%
603
 
3.9%
506
 
3.3%
460
 
3.0%
408
 
2.6%
408
 
2.6%
404
 
2.6%
Other values (259) 9754
62.8%
Uppercase Letter
ValueCountFrequency (%)
S 15
40.5%
H 6
 
16.2%
P 6
 
16.2%
A 4
 
10.8%
B 3
 
8.1%
C 1
 
2.7%
Y 1
 
2.7%
M 1
 
2.7%
Decimal Number
ValueCountFrequency (%)
1 1
20.0%
3 1
20.0%
9 1
20.0%
2 1
20.0%
5 1
20.0%
Other Punctuation
ValueCountFrequency (%)
? 3
60.0%
, 1
 
20.0%
/ 1
 
20.0%
Space Separator
ValueCountFrequency (%)
1076
100.0%
Other Symbol
ValueCountFrequency (%)
229
100.0%
Close Punctuation
ValueCountFrequency (%)
) 69
100.0%
Open Punctuation
ValueCountFrequency (%)
( 66
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15757
92.6%
Common 1227
 
7.2%
Latin 37
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
983
 
6.2%
694
 
4.4%
674
 
4.3%
634
 
4.0%
603
 
3.8%
506
 
3.2%
460
 
2.9%
408
 
2.6%
408
 
2.6%
404
 
2.6%
Other values (260) 9983
63.4%
Common
ValueCountFrequency (%)
1076
87.7%
) 69
 
5.6%
( 66
 
5.4%
- 5
 
0.4%
? 3
 
0.2%
1 1
 
0.1%
3 1
 
0.1%
_ 1
 
0.1%
9 1
 
0.1%
2 1
 
0.1%
Other values (3) 3
 
0.2%
Latin
ValueCountFrequency (%)
S 15
40.5%
H 6
 
16.2%
P 6
 
16.2%
A 4
 
10.8%
B 3
 
8.1%
C 1
 
2.7%
Y 1
 
2.7%
M 1
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15528
91.2%
ASCII 1264
 
7.4%
None 229
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1076
85.1%
) 69
 
5.5%
( 66
 
5.2%
S 15
 
1.2%
H 6
 
0.5%
P 6
 
0.5%
- 5
 
0.4%
A 4
 
0.3%
B 3
 
0.2%
? 3
 
0.2%
Other values (11) 11
 
0.9%
Hangul
ValueCountFrequency (%)
983
 
6.3%
694
 
4.5%
674
 
4.3%
634
 
4.1%
603
 
3.9%
506
 
3.3%
460
 
3.0%
408
 
2.6%
408
 
2.6%
404
 
2.6%
Other values (259) 9754
62.8%
None
ValueCountFrequency (%)
229
100.0%
Distinct375
Distinct (%)18.1%
Missing12
Missing (%)0.6%
Memory size16.4 KiB
2024-05-18T16:28:04.314034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length10
Mean length11.168116
Min length8

Characters and Unicode

Total characters23118
Distinct characters16
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)4.6%

Sample

1st row2077.07.29
2nd row2020.07.15
3rd row2020.07.15
4th row2020.07.15
5th row2020.06.26
ValueCountFrequency (%)
2012 172
 
6.7%
07 167
 
6.5%
16 167
 
6.5%
31 167
 
6.5%
2012.07.24~2012.08.07 83
 
3.2%
2012.06.19 45
 
1.7%
2012.07.09 41
 
1.6%
2012.06.07 41
 
1.6%
2012.06.22 36
 
1.4%
2012.07.03-04 32
 
1.2%
Other values (368) 1625
63.1%
2024-05-18T16:28:05.171296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5869
25.4%
. 4310
18.6%
1 4206
18.2%
2 3909
16.9%
7 1016
 
4.4%
6 703
 
3.0%
3 685
 
3.0%
9 523
 
2.3%
506
 
2.2%
8 461
 
2.0%
Other values (6) 930
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17886
77.4%
Other Punctuation 4355
 
18.8%
Space Separator 506
 
2.2%
Dash Punctuation 229
 
1.0%
Math Symbol 142
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5869
32.8%
1 4206
23.5%
2 3909
21.9%
7 1016
 
5.7%
6 703
 
3.9%
3 685
 
3.8%
9 523
 
2.9%
8 461
 
2.6%
4 264
 
1.5%
5 250
 
1.4%
Other Punctuation
ValueCountFrequency (%)
. 4310
99.0%
/ 38
 
0.9%
, 7
 
0.2%
Space Separator
ValueCountFrequency (%)
506
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 229
100.0%
Math Symbol
ValueCountFrequency (%)
~ 142
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23118
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5869
25.4%
. 4310
18.6%
1 4206
18.2%
2 3909
16.9%
7 1016
 
4.4%
6 703
 
3.0%
3 685
 
3.0%
9 523
 
2.3%
506
 
2.2%
8 461
 
2.0%
Other values (6) 930
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23118
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5869
25.4%
. 4310
18.6%
1 4206
18.2%
2 3909
16.9%
7 1016
 
4.4%
6 703
 
3.0%
3 685
 
3.0%
9 523
 
2.3%
506
 
2.2%
8 461
 
2.0%
Other values (6) 930
 
4.0%

조사정보
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
<NA>
1546 
석면실태조사
499 
주차계획과
 
17
도로관리과
 
12
도로시설과
 
6
Other values (2)
 
2

Length

Max length6
Median length4
Mean length4.4975985
Min length4

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1546
74.3%
석면실태조사 499
 
24.0%
주차계획과 17
 
0.8%
도로관리과 12
 
0.6%
도로시설과 6
 
0.3%
보행자전거과 1
 
< 0.1%
체육진흥과 1
 
< 0.1%

Length

2024-05-18T16:28:05.641551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T16:28:05.918135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1546
74.3%
석면실태조사 499
 
24.0%
주차계획과 17
 
0.8%
도로관리과 12
 
0.6%
도로시설과 6
 
0.3%
보행자전거과 1
 
< 0.1%
체육진흥과 1
 
< 0.1%

건물용도
Categorical

Distinct12
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
업무시설
832 
물재생시설
467 
문화/복지시설
393 
<NA>
208 
주거시설
 
46
Other values (7)
136 

Length

Max length7
Median length4
Mean length4.8232469
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row주거시설
2nd row물재생시설
3rd row주거시설
4th row주거시설
5th row업무시설

Common Values

ValueCountFrequency (%)
업무시설 832
40.0%
물재생시설 467
22.4%
문화/복지시설 393
18.9%
<NA> 208
 
10.0%
주거시설 46
 
2.2%
문화복지 30
 
1.4%
의료시설 28
 
1.3%
체육시설 26
 
1.2%
빗물펌프장 26
 
1.2%
상수도시설 10
 
0.5%
Other values (2) 16
 
0.8%

Length

2024-05-18T16:28:06.163619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
업무시설 832
40.0%
물재생시설 467
22.4%
문화/복지시설 393
18.9%
na 208
 
10.0%
주거시설 46
 
2.2%
문화복지 30
 
1.4%
의료시설 28
 
1.3%
체육시설 26
 
1.2%
빗물펌프장 26
 
1.2%
상수도시설 10
 
0.5%
Other values (2) 16
 
0.8%

전체면적
Text

MISSING 

Distinct1474
Distinct (%)77.3%
Missing176
Missing (%)8.5%
Memory size16.4 KiB
2024-05-18T16:28:06.768376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length6.021511
Min length2

Characters and Unicode

Total characters11477
Distinct characters14
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1297 ?
Unique (%)68.0%

Sample

1st row479.14
2nd row5,215.4 ㎡
3rd row479.14
4th row476.29
5th row379.16
ValueCountFrequency (%)
0.00 38
 
2.0%
36.00 26
 
1.4%
27.00 21
 
1.1%
27.68 17
 
0.9%
6.60 12
 
0.6%
14.85 12
 
0.6%
23.00 12
 
0.6%
21.45 12
 
0.6%
4.00 10
 
0.5%
20.85 9
 
0.5%
Other values (1402) 1739
91.1%
2024-05-18T16:28:07.639293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1527
13.3%
1525
13.3%
. 1396
12.2%
1 999
8.7%
2 991
8.6%
6 731
6.4%
4 730
6.4%
5 711
6.2%
3 671
5.8%
8 668
5.8%
Other values (4) 1528
13.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8236
71.8%
Other Punctuation 1714
 
14.9%
Space Separator 1525
 
13.3%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1527
18.5%
1 999
12.1%
2 991
12.0%
6 731
8.9%
4 730
8.9%
5 711
8.6%
3 671
8.1%
8 668
8.1%
7 624
7.6%
9 584
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 1396
81.4%
, 318
 
18.6%
Space Separator
ValueCountFrequency (%)
1525
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11477
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1527
13.3%
1525
13.3%
. 1396
12.2%
1 999
8.7%
2 991
8.6%
6 731
6.4%
4 730
6.4%
5 711
6.2%
3 671
5.8%
8 668
5.8%
Other values (4) 1528
13.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11475
> 99.9%
CJK Compat 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1527
13.3%
1525
13.3%
. 1396
12.2%
1 999
8.7%
2 991
8.6%
6 731
6.4%
4 730
6.4%
5 711
6.2%
3 671
5.8%
8 668
5.8%
Other values (3) 1526
13.3%
CJK Compat
ValueCountFrequency (%)
2
100.0%

구조물
Text

MISSING 

Distinct71
Distinct (%)3.9%
Missing239
Missing (%)11.5%
Memory size16.4 KiB
2024-05-18T16:28:07.978066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length7
Mean length6.6673901
Min length2

Characters and Unicode

Total characters12288
Distinct characters79
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)1.6%

Sample

1st row철근콘크리트조
2nd row철근콘크리트조
3rd row철근콘크리트
4th row철근콘크리트
5th row철근콘크리트
ValueCountFrequency (%)
철근콘크리트조 1223
64.4%
시멘트벽돌조 116
 
6.1%
철골조 70
 
3.7%
철근콘크리트 66
 
3.5%
경량철골조 45
 
2.4%
조적조 37
 
1.9%
연와조 31
 
1.6%
철근콘크리트조/슬라브 29
 
1.5%
목조 26
 
1.4%
철근 23
 
1.2%
Other values (59) 233
 
12.3%
2024-05-18T16:28:08.592042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1771
14.4%
1565
12.7%
1539
12.5%
1426
11.6%
1416
11.5%
1413
11.5%
1394
11.3%
171
 
1.4%
144
 
1.2%
144
 
1.2%
Other values (69) 1305
10.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12070
98.2%
Other Punctuation 122
 
1.0%
Space Separator 61
 
0.5%
Uppercase Letter 30
 
0.2%
Dash Punctuation 4
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1771
14.7%
1565
13.0%
1539
12.8%
1426
11.8%
1416
11.7%
1413
11.7%
1394
11.5%
171
 
1.4%
144
 
1.2%
144
 
1.2%
Other values (60) 1087
9.0%
Other Punctuation
ValueCountFrequency (%)
/ 102
83.6%
. 16
 
13.1%
, 4
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
C 15
50.0%
R 13
43.3%
P 2
 
6.7%
Space Separator
ValueCountFrequency (%)
61
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12070
98.2%
Common 188
 
1.5%
Latin 30
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1771
14.7%
1565
13.0%
1539
12.8%
1426
11.8%
1416
11.7%
1413
11.7%
1394
11.5%
171
 
1.4%
144
 
1.2%
144
 
1.2%
Other values (60) 1087
9.0%
Common
ValueCountFrequency (%)
/ 102
54.3%
61
32.4%
. 16
 
8.5%
- 4
 
2.1%
, 4
 
2.1%
+ 1
 
0.5%
Latin
ValueCountFrequency (%)
C 15
50.0%
R 13
43.3%
P 2
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12070
98.2%
ASCII 218
 
1.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1771
14.7%
1565
13.0%
1539
12.8%
1426
11.8%
1416
11.7%
1413
11.7%
1394
11.5%
171
 
1.4%
144
 
1.2%
144
 
1.2%
Other values (60) 1087
9.0%
ASCII
ValueCountFrequency (%)
/ 102
46.8%
61
28.0%
. 16
 
7.3%
C 15
 
6.9%
R 13
 
6.0%
- 4
 
1.8%
, 4
 
1.8%
P 2
 
0.9%
+ 1
 
0.5%

준공일
Text

MISSING 

Distinct205
Distinct (%)11.2%
Missing256
Missing (%)12.3%
Memory size16.4 KiB
2024-05-18T16:28:09.024210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length4
Mean length4.6308872
Min length1

Characters and Unicode

Total characters8456
Distinct characters14
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

Unique138 ?
Unique (%)7.6%

Sample

1st row1995
2nd row1989.10.10
3rd row1988.01.30
4th row1989
5th row1988
ValueCountFrequency (%)
1988 171
 
9.4%
1999 117
 
6.4%
1997 111
 
6.1%
1984 81
 
4.4%
1998 65
 
3.6%
1995 61
 
3.3%
2005 53
 
2.9%
2009 52
 
2.8%
1983 51
 
2.8%
1980 49
 
2.7%
Other values (194) 1015
55.6%
2024-05-18T16:28:09.830622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 2261
26.7%
1 1765
20.9%
0 1237
14.6%
8 970
11.5%
2 685
 
8.1%
. 386
 
4.6%
7 359
 
4.2%
5 230
 
2.7%
3 197
 
2.3%
6 197
 
2.3%
Other values (4) 169
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8067
95.4%
Other Punctuation 386
 
4.6%
Dash Punctuation 1
 
< 0.1%
Connector Punctuation 1
 
< 0.1%
Other Letter 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 2261
28.0%
1 1765
21.9%
0 1237
15.3%
8 970
12.0%
2 685
 
8.5%
7 359
 
4.5%
5 230
 
2.9%
3 197
 
2.4%
6 197
 
2.4%
4 166
 
2.1%
Other Punctuation
ValueCountFrequency (%)
. 386
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Other Letter
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8455
> 99.9%
Hangul 1
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
9 2261
26.7%
1 1765
20.9%
0 1237
14.6%
8 970
11.5%
2 685
 
8.1%
. 386
 
4.6%
7 359
 
4.2%
5 230
 
2.7%
3 197
 
2.3%
6 197
 
2.3%
Other values (3) 168
 
2.0%
Hangul
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8455
> 99.9%
Hangul 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 2261
26.7%
1 1765
20.9%
0 1237
14.6%
8 970
11.5%
2 685
 
8.1%
. 386
 
4.6%
7 359
 
4.2%
5 230
 
2.7%
3 197
 
2.3%
6 197
 
2.3%
Other values (3) 168
 
2.0%
Hangul
ValueCountFrequency (%)
1
100.0%

이름
Text

Distinct1819
Distinct (%)87.4%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
2024-05-18T16:28:10.415626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length23
Mean length9.1777137
Min length2

Characters and Unicode

Total characters19108
Distinct characters527
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

Unique1747 ?
Unique (%)83.9%

Sample

1st row관사3
2nd row제1유입펌프동
3rd row관사2
4th row관사1
5th row본관
ValueCountFrequency (%)
중랑물재생센터 119
 
3.3%
제1 99
 
2.8%
본관 83
 
2.3%
제3처리장 74
 
2.1%
제2처리장 73
 
2.0%
제1처리장 72
 
2.0%
화장실 50
 
1.4%
최초침전지계단실 43
 
1.2%
청사 39
 
1.1%
계단실 32
 
0.9%
Other values (1832) 2893
80.9%
2024-05-18T16:28:11.426449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1529
 
8.0%
686
 
3.6%
670
 
3.5%
576
 
3.0%
1 575
 
3.0%
500
 
2.6%
449
 
2.3%
442
 
2.3%
346
 
1.8%
341
 
1.8%
Other values (517) 12994
68.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14830
77.6%
Space Separator 1529
 
8.0%
Decimal Number 1374
 
7.2%
Uppercase Letter 532
 
2.8%
Close Punctuation 279
 
1.5%
Open Punctuation 278
 
1.5%
Dash Punctuation 119
 
0.6%
Other Punctuation 87
 
0.5%
Lowercase Letter 69
 
0.4%
Math Symbol 6
 
< 0.1%
Other values (2) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
686
 
4.6%
670
 
4.5%
576
 
3.9%
500
 
3.4%
449
 
3.0%
442
 
3.0%
346
 
2.3%
341
 
2.3%
326
 
2.2%
321
 
2.2%
Other values (457) 10173
68.6%
Uppercase Letter
ValueCountFrequency (%)
B 182
34.2%
L 87
16.4%
A 74
13.9%
C 57
 
10.7%
D 34
 
6.4%
E 16
 
3.0%
S 12
 
2.3%
T 12
 
2.3%
G 9
 
1.7%
F 9
 
1.7%
Other values (13) 40
 
7.5%
Lowercase Letter
ValueCountFrequency (%)
e 13
18.8%
a 8
11.6%
t 8
11.6%
w 6
8.7%
n 5
 
7.2%
r 5
 
7.2%
o 4
 
5.8%
y 3
 
4.3%
i 3
 
4.3%
g 3
 
4.3%
Other values (7) 11
15.9%
Decimal Number
ValueCountFrequency (%)
1 575
41.8%
2 289
21.0%
3 173
 
12.6%
9 104
 
7.6%
4 75
 
5.5%
5 48
 
3.5%
0 41
 
3.0%
6 36
 
2.6%
7 20
 
1.5%
8 13
 
0.9%
Other Punctuation
ValueCountFrequency (%)
, 60
69.0%
/ 27
31.0%
Math Symbol
ValueCountFrequency (%)
+ 4
66.7%
~ 2
33.3%
Space Separator
ValueCountFrequency (%)
1529
100.0%
Close Punctuation
ValueCountFrequency (%)
) 279
100.0%
Open Punctuation
ValueCountFrequency (%)
( 278
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 119
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14831
77.6%
Common 3676
 
19.2%
Latin 601
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
686
 
4.6%
670
 
4.5%
576
 
3.9%
500
 
3.4%
449
 
3.0%
442
 
3.0%
346
 
2.3%
341
 
2.3%
326
 
2.2%
321
 
2.2%
Other values (458) 10174
68.6%
Latin
ValueCountFrequency (%)
B 182
30.3%
L 87
14.5%
A 74
12.3%
C 57
 
9.5%
D 34
 
5.7%
E 16
 
2.7%
e 13
 
2.2%
S 12
 
2.0%
T 12
 
2.0%
G 9
 
1.5%
Other values (30) 105
17.5%
Common
ValueCountFrequency (%)
1529
41.6%
1 575
 
15.6%
2 289
 
7.9%
) 279
 
7.6%
( 278
 
7.6%
3 173
 
4.7%
- 119
 
3.2%
9 104
 
2.8%
4 75
 
2.0%
, 60
 
1.6%
Other values (9) 195
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14830
77.6%
ASCII 4277
 
22.4%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1529
35.7%
1 575
 
13.4%
2 289
 
6.8%
) 279
 
6.5%
( 278
 
6.5%
B 182
 
4.3%
3 173
 
4.0%
- 119
 
2.8%
9 104
 
2.4%
L 87
 
2.0%
Other values (49) 662
15.5%
Hangul
ValueCountFrequency (%)
686
 
4.6%
670
 
4.5%
576
 
3.9%
500
 
3.4%
449
 
3.0%
442
 
3.0%
346
 
2.3%
341
 
2.3%
326
 
2.2%
321
 
2.2%
Other values (457) 10173
68.6%
None
ValueCountFrequency (%)
1
100.0%

지상층고
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8731988
Minimum0
Maximum15
Zeros30
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size18.4 KiB
2024-05-18T16:28:11.800858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q32
95-th percentile5
Maximum15
Range15
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3778164
Coefficient of variation (CV)0.73554197
Kurtosis14.617222
Mean1.8731988
Median Absolute Deviation (MAD)0
Skewness2.7321436
Sum3900
Variance1.8983779
MonotonicityNot monotonic
2024-05-18T16:28:12.227910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 1109
53.3%
2 458
22.0%
3 281
 
13.5%
4 90
 
4.3%
5 69
 
3.3%
0 30
 
1.4%
6 27
 
1.3%
8 9
 
0.4%
7 4
 
0.2%
15 3
 
0.1%
Other values (2) 2
 
0.1%
ValueCountFrequency (%)
0 30
 
1.4%
1 1109
53.3%
2 458
22.0%
3 281
 
13.5%
4 90
 
4.3%
5 69
 
3.3%
6 27
 
1.3%
7 4
 
0.2%
8 9
 
0.4%
9 1
 
< 0.1%
ValueCountFrequency (%)
15 3
 
0.1%
11 1
 
< 0.1%
9 1
 
< 0.1%
8 9
 
0.4%
7 4
 
0.2%
6 27
 
1.3%
5 69
 
3.3%
4 90
 
4.3%
3 281
13.5%
2 458
22.0%

지하층고
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.42603266
Minimum0
Maximum6
Zeros1317
Zeros (%)63.3%
Negative0
Negative (%)0.0%
Memory size18.4 KiB
2024-05-18T16:28:12.465910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.64252215
Coefficient of variation (CV)1.5081523
Kurtosis8.0409358
Mean0.42603266
Median Absolute Deviation (MAD)0
Skewness2.0671808
Sum887
Variance0.41283471
MonotonicityNot monotonic
2024-05-18T16:28:12.704189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 1317
63.3%
1 678
32.6%
2 65
 
3.1%
3 13
 
0.6%
4 6
 
0.3%
5 2
 
0.1%
6 1
 
< 0.1%
ValueCountFrequency (%)
0 1317
63.3%
1 678
32.6%
2 65
 
3.1%
3 13
 
0.6%
4 6
 
0.3%
5 2
 
0.1%
6 1
 
< 0.1%
ValueCountFrequency (%)
6 1
 
< 0.1%
5 2
 
0.1%
4 6
 
0.3%
3 13
 
0.6%
2 65
 
3.1%
1 678
32.6%
0 1317
63.3%

조사기관
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
ETS Consulting
1034 
KTR
759 
<NA>
237 
환경컨설팅(주)
 
44
한국석면안전관리원(주)
 
2
Other values (6)
 
6

Length

Max length14
Median length13
Mean length8.7127762
Min length3

Unique

Unique6 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
ETS Consulting 1034
49.7%
KTR 759
36.5%
<NA> 237
 
11.4%
환경컨설팅(주) 44
 
2.1%
한국석면안전관리원(주) 2
 
0.1%
대한석면조사기관(주) 1
 
< 0.1%
(주)한국보건환경연구소 1
 
< 0.1%
환경컨설팅 1
 
< 0.1%
한국RMS(주) 1
 
< 0.1%
한국환경보전 안전과학연구소 1
 
< 0.1%

Length

2024-05-18T16:28:13.234244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ets 1034
33.2%
consulting 1034
33.2%
ktr 759
24.4%
na 237
 
7.6%
환경컨설팅(주 44
 
1.4%
한국석면안전관리원(주 2
 
0.1%
대한석면조사기관(주 1
 
< 0.1%
주)한국보건환경연구소 1
 
< 0.1%
환경컨설팅 1
 
< 0.1%
한국rms(주 1
 
< 0.1%
Other values (3) 3
 
0.1%

옥탑
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
0
1636 
1
425 
2
 
19
3
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1636
78.6%
1 425
 
20.4%
2 19
 
0.9%
3 2
 
0.1%

Length

2024-05-18T16:28:13.570893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T16:28:13.876740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1636
78.6%
1 425
 
20.4%
2 19
 
0.9%
3 2
 
0.1%

주소2
Text

MISSING 

Distinct409
Distinct (%)30.5%
Missing742
Missing (%)35.6%
Memory size16.4 KiB
2024-05-18T16:28:14.412242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length26
Mean length5.6335821
Min length1

Characters and Unicode

Total characters7549
Distinct characters176
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique314 ?
Unique (%)23.4%

Sample

1st row 양천로 201
2nd row행당로79
3rd row봉은사로114길 13
4th row봉은사로114길 13
5th row봉은사로114길 13
ValueCountFrequency (%)
74 144
 
7.4%
248-4 100
 
5.1%
673-2 83
 
4.2%
159-1 83
 
4.2%
397 55
 
2.8%
580번지 54
 
2.8%
18 49
 
2.5%
41
 
2.1%
양천로 28
 
1.4%
산37 27
 
1.4%
Other values (576) 1290
66.0%
2024-05-18T16:28:15.599029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 804
 
10.7%
656
 
8.7%
4 582
 
7.7%
- 578
 
7.7%
2 519
 
6.9%
7 502
 
6.6%
3 428
 
5.7%
8 395
 
5.2%
5 385
 
5.1%
6 289
 
3.8%
Other values (166) 2411
31.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4440
58.8%
Other Letter 1850
24.5%
Space Separator 656
 
8.7%
Dash Punctuation 578
 
7.7%
Other Punctuation 15
 
0.2%
Open Punctuation 4
 
0.1%
Close Punctuation 4
 
0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
263
 
14.2%
114
 
6.2%
108
 
5.8%
91
 
4.9%
72
 
3.9%
70
 
3.8%
63
 
3.4%
47
 
2.5%
41
 
2.2%
38
 
2.1%
Other values (148) 943
51.0%
Decimal Number
ValueCountFrequency (%)
1 804
18.1%
4 582
13.1%
2 519
11.7%
7 502
11.3%
3 428
9.6%
8 395
8.9%
5 385
8.7%
6 289
 
6.5%
9 286
 
6.4%
0 250
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 14
93.3%
/ 1
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
r 1
50.0%
o 1
50.0%
Space Separator
ValueCountFrequency (%)
656
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 578
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5697
75.5%
Hangul 1850
 
24.5%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
263
 
14.2%
114
 
6.2%
108
 
5.8%
91
 
4.9%
72
 
3.9%
70
 
3.8%
63
 
3.4%
47
 
2.5%
41
 
2.2%
38
 
2.1%
Other values (148) 943
51.0%
Common
ValueCountFrequency (%)
1 804
14.1%
656
11.5%
4 582
10.2%
- 578
10.1%
2 519
9.1%
7 502
8.8%
3 428
7.5%
8 395
6.9%
5 385
6.8%
6 289
 
5.1%
Other values (6) 559
9.8%
Latin
ValueCountFrequency (%)
r 1
50.0%
o 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5699
75.5%
Hangul 1850
 
24.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 804
14.1%
656
11.5%
4 582
10.2%
- 578
10.1%
2 519
9.1%
7 502
8.8%
3 428
7.5%
8 395
6.9%
5 385
6.8%
6 289
 
5.1%
Other values (8) 561
9.8%
Hangul
ValueCountFrequency (%)
263
 
14.2%
114
 
6.2%
108
 
5.8%
91
 
4.9%
72
 
3.9%
70
 
3.8%
63
 
3.4%
47
 
2.5%
41
 
2.2%
38
 
2.1%
Other values (148) 943
51.0%

보고서
Text

MISSING 

Distinct1083
Distinct (%)99.6%
Missing995
Missing (%)47.8%
Memory size16.4 KiB
2024-05-18T16:28:16.216244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length49
Mean length26.653174
Min length9

Characters and Unicode

Total characters28972
Distinct characters419
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1081 ?
Unique (%)99.4%

Sample

1st row13.북서울 꿈의숲-접촉산화제어실.pdf
2nd row25.수도박물관(경비실,화장실).pdf
3rd row3.어린이도서관.pdf
4th row1.보일러 및 변전실.pdf
5th row공중화장실.JPG
ValueCountFrequency (%)
서울대공원 81
 
3.2%
최초침전지계단실 44
 
1.7%
어린이대공원 40
 
1.6%
관랑환기실 28
 
1.1%
없는경우.pdf 25
 
1.0%
계단실)_ver1.pdf 18
 
0.7%
212 14
 
0.6%
232 13
 
0.5%
서울랜드 11
 
0.4%
186 10
 
0.4%
Other values (1711) 2247
88.8%
2024-05-18T16:28:17.284786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1940
 
6.7%
1 1891
 
6.5%
2 1825
 
6.3%
. 1612
 
5.6%
1444
 
5.0%
- 1325
 
4.6%
p 1086
 
3.7%
f 1086
 
3.7%
d 1085
 
3.7%
_ 882
 
3.0%
Other values (409) 14796
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10765
37.2%
Decimal Number 8188
28.3%
Lowercase Letter 3518
 
12.1%
Other Punctuation 1644
 
5.7%
Space Separator 1444
 
5.0%
Dash Punctuation 1325
 
4.6%
Connector Punctuation 882
 
3.0%
Uppercase Letter 501
 
1.7%
Close Punctuation 345
 
1.2%
Open Punctuation 345
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
406
 
3.8%
382
 
3.5%
254
 
2.4%
245
 
2.3%
227
 
2.1%
225
 
2.1%
223
 
2.1%
221
 
2.1%
216
 
2.0%
213
 
2.0%
Other values (353) 8153
75.7%
Uppercase Letter
ValueCountFrequency (%)
B 193
38.5%
L 85
17.0%
A 40
 
8.0%
C 39
 
7.8%
T 34
 
6.8%
H 32
 
6.4%
D 29
 
5.8%
E 17
 
3.4%
F 5
 
1.0%
P 5
 
1.0%
Other values (11) 22
 
4.4%
Lowercase Letter
ValueCountFrequency (%)
p 1086
30.9%
f 1086
30.9%
d 1085
30.8%
e 80
 
2.3%
r 80
 
2.3%
v 77
 
2.2%
a 4
 
0.1%
t 4
 
0.1%
c 3
 
0.1%
o 3
 
0.1%
Other values (7) 10
 
0.3%
Decimal Number
ValueCountFrequency (%)
0 1940
23.7%
1 1891
23.1%
2 1825
22.3%
3 578
 
7.1%
6 491
 
6.0%
4 365
 
4.5%
5 347
 
4.2%
8 320
 
3.9%
7 220
 
2.7%
9 211
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 1612
98.1%
, 32
 
1.9%
Space Separator
ValueCountFrequency (%)
1444
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1325
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 882
100.0%
Close Punctuation
ValueCountFrequency (%)
) 345
100.0%
Open Punctuation
ValueCountFrequency (%)
( 345
100.0%
Math Symbol
ValueCountFrequency (%)
~ 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14188
49.0%
Hangul 10765
37.2%
Latin 4019
 
13.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
406
 
3.8%
382
 
3.5%
254
 
2.4%
245
 
2.3%
227
 
2.1%
225
 
2.1%
223
 
2.1%
221
 
2.1%
216
 
2.0%
213
 
2.0%
Other values (353) 8153
75.7%
Latin
ValueCountFrequency (%)
p 1086
27.0%
f 1086
27.0%
d 1085
27.0%
B 193
 
4.8%
L 85
 
2.1%
e 80
 
2.0%
r 80
 
2.0%
v 77
 
1.9%
A 40
 
1.0%
C 39
 
1.0%
Other values (28) 168
 
4.2%
Common
ValueCountFrequency (%)
0 1940
13.7%
1 1891
13.3%
2 1825
12.9%
. 1612
11.4%
1444
10.2%
- 1325
9.3%
_ 882
6.2%
3 578
 
4.1%
6 491
 
3.5%
4 365
 
2.6%
Other values (8) 1835
12.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18207
62.8%
Hangul 10765
37.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1940
10.7%
1 1891
10.4%
2 1825
10.0%
. 1612
 
8.9%
1444
 
7.9%
- 1325
 
7.3%
p 1086
 
6.0%
f 1086
 
6.0%
d 1085
 
6.0%
_ 882
 
4.8%
Other values (46) 4031
22.1%
Hangul
ValueCountFrequency (%)
406
 
3.8%
382
 
3.5%
254
 
2.4%
245
 
2.3%
227
 
2.1%
225
 
2.1%
223
 
2.1%
221
 
2.1%
216
 
2.0%
213
 
2.0%
Other values (353) 8153
75.7%

TMPNO
Real number (ℝ)

MISSING 

Distinct74
Distinct (%)26.7%
Missing1805
Missing (%)86.7%
Infinite0
Infinite (%)0.0%
Mean429.55596
Minimum319
Maximum481
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.4 KiB
2024-05-18T16:28:17.681988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum319
5-th percentile333.2
Q1371
median452
Q3479
95-th percentile481
Maximum481
Range162
Interquartile range (IQR)108

Descriptive statistics

Standard deviation55.871111
Coefficient of variation (CV)0.13006713
Kurtosis-1.2834432
Mean429.55596
Median Absolute Deviation (MAD)29
Skewness-0.55870074
Sum118987
Variance3121.5811
MonotonicityNot monotonic
2024-05-18T16:28:18.074639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
479 65
 
3.1%
481 40
 
1.9%
480 20
 
1.0%
361 12
 
0.6%
393 9
 
0.4%
348 9
 
0.4%
425 7
 
0.3%
344 7
 
0.3%
439 6
 
0.3%
412 5
 
0.2%
Other values (64) 97
 
4.7%
(Missing) 1805
86.7%
ValueCountFrequency (%)
319 1
 
< 0.1%
320 1
 
< 0.1%
322 1
 
< 0.1%
323 4
0.2%
324 1
 
< 0.1%
328 1
 
< 0.1%
330 5
0.2%
334 2
 
0.1%
336 1
 
< 0.1%
338 1
 
< 0.1%
ValueCountFrequency (%)
481 40
1.9%
480 20
 
1.0%
479 65
3.1%
478 1
 
< 0.1%
474 1
 
< 0.1%
472 1
 
< 0.1%
471 1
 
< 0.1%
469 2
 
0.1%
467 1
 
< 0.1%
465 1
 
< 0.1%
Distinct441
Distinct (%)21.2%
Missing1
Missing (%)< 0.1%
Memory size16.4 KiB
2024-05-18T16:28:18.722895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length3.1653051
Min length1

Characters and Unicode

Total characters6587
Distinct characters14
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique376 ?
Unique (%)18.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row1.33
ValueCountFrequency (%)
0 985
47.3%
0.00 540
25.9%
0.01 14
 
0.7%
1.00 13
 
0.6%
0.10 9
 
0.4%
0.02 7
 
0.3%
0.05 6
 
0.3%
0.11 5
 
0.2%
0.50 5
 
0.2%
0.16 4
 
0.2%
Other values (421) 494
23.7%
2024-05-18T16:28:19.869047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3205
48.7%
. 1061
 
16.1%
716
 
10.9%
1 319
 
4.8%
2 209
 
3.2%
5 185
 
2.8%
3 180
 
2.7%
4 157
 
2.4%
6 146
 
2.2%
8 141
 
2.1%
Other values (4) 268
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4806
73.0%
Other Punctuation 1064
 
16.2%
Space Separator 716
 
10.9%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3205
66.7%
1 319
 
6.6%
2 209
 
4.3%
5 185
 
3.8%
3 180
 
3.7%
4 157
 
3.3%
6 146
 
3.0%
8 141
 
2.9%
7 136
 
2.8%
9 128
 
2.7%
Other Punctuation
ValueCountFrequency (%)
. 1061
99.7%
, 3
 
0.3%
Space Separator
ValueCountFrequency (%)
716
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6587
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3205
48.7%
. 1061
 
16.1%
716
 
10.9%
1 319
 
4.8%
2 209
 
3.2%
5 185
 
2.8%
3 180
 
2.7%
4 157
 
2.4%
6 146
 
2.2%
8 141
 
2.1%
Other values (4) 268
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6586
> 99.9%
CJK Compat 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3205
48.7%
. 1061
 
16.1%
716
 
10.9%
1 319
 
4.8%
2 209
 
3.2%
5 185
 
2.8%
3 180
 
2.7%
4 157
 
2.4%
6 146
 
2.2%
8 141
 
2.1%
Other values (3) 267
 
4.1%
CJK Compat
ValueCountFrequency (%)
1
100.0%
Distinct158
Distinct (%)7.6%
Missing7
Missing (%)0.3%
Memory size16.4 KiB
2024-05-18T16:28:20.377104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length6.5850602
Min length1

Characters and Unicode

Total characters13664
Distinct characters176
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)1.8%

Sample

1st row서부공원녹지사업소
2nd row도시안전실 물재생시설과
3rd row서부공원녹지사업소
4th row서부공원녹지사업소
5th row일자리정책과
ValueCountFrequency (%)
물재생시설과 272
 
12.6%
서울대공원 204
 
9.4%
중랑물재생센터 120
 
5.6%
자산관리과 105
 
4.9%
난지물재생센터 86
 
4.0%
주차계획과 66
 
3.1%
강북아리수정수센터 56
 
2.6%
공원녹지정책과 47
 
2.2%
재산관리과 46
 
2.1%
어르신복지과 46
 
2.1%
Other values (156) 1114
51.5%
2024-05-18T16:28:21.250315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
928
 
6.8%
580
 
4.2%
499
 
3.7%
487
 
3.6%
481
 
3.5%
429
 
3.1%
422
 
3.1%
408
 
3.0%
407
 
3.0%
403
 
2.9%
Other values (166) 8620
63.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13563
99.3%
Space Separator 94
 
0.7%
Close Punctuation 2
 
< 0.1%
Math Symbol 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
928
 
6.8%
580
 
4.3%
499
 
3.7%
487
 
3.6%
481
 
3.5%
429
 
3.2%
422
 
3.1%
408
 
3.0%
407
 
3.0%
403
 
3.0%
Other values (161) 8519
62.8%
Space Separator
ValueCountFrequency (%)
94
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Math Symbol
ValueCountFrequency (%)
2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13563
99.3%
Common 101
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
928
 
6.8%
580
 
4.3%
499
 
3.7%
487
 
3.6%
481
 
3.5%
429
 
3.2%
422
 
3.1%
408
 
3.0%
407
 
3.0%
403
 
3.0%
Other values (161) 8519
62.8%
Common
ValueCountFrequency (%)
94
93.1%
) 2
 
2.0%
2
 
2.0%
( 2
 
2.0%
- 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13563
99.3%
ASCII 99
 
0.7%
Arrows 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
928
 
6.8%
580
 
4.3%
499
 
3.7%
487
 
3.6%
481
 
3.5%
429
 
3.2%
422
 
3.1%
408
 
3.0%
407
 
3.0%
403
 
3.0%
Other values (161) 8519
62.8%
ASCII
ValueCountFrequency (%)
94
94.9%
) 2
 
2.0%
( 2
 
2.0%
- 1
 
1.0%
Arrows
ValueCountFrequency (%)
2
100.0%

해체제거면적
Text

MISSING 

Distinct384
Distinct (%)86.5%
Missing1638
Missing (%)78.7%
Memory size16.4 KiB
2024-05-18T16:28:21.856539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length26
Mean length8.3806306
Min length1

Characters and Unicode

Total characters3721
Distinct characters36
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique353 ?
Unique (%)79.5%

Sample

1st row99.82
2nd row93.62
3rd row70.68
4th row(2016년 석면해체 349.75)
5th row(2016년 석면추가 489)
ValueCountFrequency (%)
석면해체 137
 
17.9%
2016년 136
 
17.8%
1 10
 
1.3%
석면추가 7
 
0.9%
5 7
 
0.9%
개스킷 6
 
0.8%
44 5
 
0.7%
18 5
 
0.7%
0 5
 
0.7%
35 5
 
0.7%
Other values (380) 443
57.8%
2024-05-18T16:28:22.991041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 396
 
10.6%
330
 
8.9%
2 311
 
8.4%
0 289
 
7.8%
6 279
 
7.5%
. 213
 
5.7%
4 181
 
4.9%
152
 
4.1%
150
 
4.0%
149
 
4.0%
Other values (26) 1271
34.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2084
56.0%
Other Letter 788
 
21.2%
Space Separator 330
 
8.9%
Other Punctuation 230
 
6.2%
Open Punctuation 145
 
3.9%
Close Punctuation 144
 
3.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
152
19.3%
150
19.0%
149
18.9%
139
17.6%
139
17.6%
9
 
1.1%
9
 
1.1%
6
 
0.8%
6
 
0.8%
6
 
0.8%
Other values (11) 23
 
2.9%
Decimal Number
ValueCountFrequency (%)
1 396
19.0%
2 311
14.9%
0 289
13.9%
6 279
13.4%
4 181
8.7%
3 141
 
6.8%
5 139
 
6.7%
7 125
 
6.0%
8 116
 
5.6%
9 107
 
5.1%
Other Punctuation
ValueCountFrequency (%)
. 213
92.6%
, 17
 
7.4%
Space Separator
ValueCountFrequency (%)
330
100.0%
Open Punctuation
ValueCountFrequency (%)
( 145
100.0%
Close Punctuation
ValueCountFrequency (%)
) 144
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2933
78.8%
Hangul 788
 
21.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
152
19.3%
150
19.0%
149
18.9%
139
17.6%
139
17.6%
9
 
1.1%
9
 
1.1%
6
 
0.8%
6
 
0.8%
6
 
0.8%
Other values (11) 23
 
2.9%
Common
ValueCountFrequency (%)
1 396
13.5%
330
11.3%
2 311
10.6%
0 289
9.9%
6 279
9.5%
. 213
7.3%
4 181
 
6.2%
( 145
 
4.9%
) 144
 
4.9%
3 141
 
4.8%
Other values (5) 504
17.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2933
78.8%
Hangul 788
 
21.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 396
13.5%
330
11.3%
2 311
10.6%
0 289
9.9%
6 279
9.5%
. 213
7.3%
4 181
 
6.2%
( 145
 
4.9%
) 144
 
4.9%
3 141
 
4.8%
Other values (5) 504
17.2%
Hangul
ValueCountFrequency (%)
152
19.3%
150
19.0%
149
18.9%
139
17.6%
139
17.6%
9
 
1.1%
9
 
1.1%
6
 
0.8%
6
 
0.8%
6
 
0.8%
Other values (11) 23
 
2.9%
Distinct478
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
2024-05-18T16:28:23.445044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length7.6392891
Min length3

Characters and Unicode

Total characters15905
Distinct characters348
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

Unique290 ?
Unique (%)13.9%

Sample

1st row서부공원녹지사업소
2nd row서남환경㈜
3rd row서부공원녹지사업소
4th row서부공원녹지사업소
5th row북부기술교육원
ValueCountFrequency (%)
서남환경㈜ 182
 
8.4%
서울대공원 133
 
6.1%
중랑물재생센터 120
 
5.5%
서울물재생시설공단(탄천센터 91
 
4.2%
난지물재생센터 86
 
4.0%
서울랜드 71
 
3.3%
강북아리수정수센터 57
 
2.6%
어린이대공원 51
 
2.4%
시설관리공단 42
 
1.9%
서부공원녹지사업소 39
 
1.8%
Other values (505) 1298
59.8%
2024-05-18T16:28:24.308053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1110
 
7.0%
546
 
3.4%
525
 
3.3%
521
 
3.3%
513
 
3.2%
466
 
2.9%
462
 
2.9%
403
 
2.5%
361
 
2.3%
355
 
2.2%
Other values (338) 10643
66.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15106
95.0%
Close Punctuation 190
 
1.2%
Open Punctuation 190
 
1.2%
Other Symbol 182
 
1.1%
Space Separator 94
 
0.6%
Decimal Number 47
 
0.3%
Uppercase Letter 42
 
0.3%
Lowercase Letter 38
 
0.2%
Letter Number 7
 
< 0.1%
Other Punctuation 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1110
 
7.3%
546
 
3.6%
525
 
3.5%
521
 
3.4%
513
 
3.4%
466
 
3.1%
462
 
3.1%
403
 
2.7%
361
 
2.4%
355
 
2.4%
Other values (295) 9844
65.2%
Uppercase Letter
ValueCountFrequency (%)
S 10
23.8%
H 8
19.0%
C 5
11.9%
E 3
 
7.1%
D 2
 
4.8%
M 2
 
4.8%
B 2
 
4.8%
P 2
 
4.8%
O 2
 
4.8%
A 2
 
4.8%
Other values (4) 4
 
9.5%
Lowercase Letter
ValueCountFrequency (%)
o 7
18.4%
l 6
15.8%
e 6
15.8%
u 6
15.8%
i 6
15.8%
t 2
 
5.3%
r 2
 
5.3%
y 1
 
2.6%
c 1
 
2.6%
a 1
 
2.6%
Decimal Number
ValueCountFrequency (%)
1 16
34.0%
2 14
29.8%
4 6
 
12.8%
5 3
 
6.4%
3 3
 
6.4%
9 2
 
4.3%
7 1
 
2.1%
6 1
 
2.1%
0 1
 
2.1%
Close Punctuation
ValueCountFrequency (%)
) 189
99.5%
] 1
 
0.5%
Open Punctuation
ValueCountFrequency (%)
( 189
99.5%
[ 1
 
0.5%
Other Punctuation
ValueCountFrequency (%)
/ 6
85.7%
, 1
 
14.3%
Other Symbol
ValueCountFrequency (%)
182
100.0%
Space Separator
ValueCountFrequency (%)
94
100.0%
Letter Number
ValueCountFrequency (%)
7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15288
96.1%
Common 530
 
3.3%
Latin 87
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1110
 
7.3%
546
 
3.6%
525
 
3.4%
521
 
3.4%
513
 
3.4%
466
 
3.0%
462
 
3.0%
403
 
2.6%
361
 
2.4%
355
 
2.3%
Other values (296) 10026
65.6%
Latin
ValueCountFrequency (%)
S 10
11.5%
H 8
 
9.2%
o 7
 
8.0%
7
 
8.0%
l 6
 
6.9%
e 6
 
6.9%
u 6
 
6.9%
i 6
 
6.9%
C 5
 
5.7%
E 3
 
3.4%
Other values (15) 23
26.4%
Common
ValueCountFrequency (%)
) 189
35.7%
( 189
35.7%
94
17.7%
1 16
 
3.0%
2 14
 
2.6%
4 6
 
1.1%
/ 6
 
1.1%
5 3
 
0.6%
3 3
 
0.6%
- 2
 
0.4%
Other values (7) 8
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15106
95.0%
ASCII 610
 
3.8%
None 182
 
1.1%
Number Forms 7
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1110
 
7.3%
546
 
3.6%
525
 
3.5%
521
 
3.4%
513
 
3.4%
466
 
3.1%
462
 
3.1%
403
 
2.7%
361
 
2.4%
355
 
2.4%
Other values (295) 9844
65.2%
ASCII
ValueCountFrequency (%)
) 189
31.0%
( 189
31.0%
94
15.4%
1 16
 
2.6%
2 14
 
2.3%
S 10
 
1.6%
H 8
 
1.3%
o 7
 
1.1%
4 6
 
1.0%
/ 6
 
1.0%
Other values (31) 71
 
11.6%
None
ValueCountFrequency (%)
182
100.0%
Number Forms
ValueCountFrequency (%)
7
100.0%

석면함유량
Real number (ℝ)

ZEROS 

Distinct972
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean390.99616
Minimum0
Maximum2595
Zeros1111
Zeros (%)53.4%
Negative0
Negative (%)0.0%
Memory size18.4 KiB
2024-05-18T16:28:24.678879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3626.75
95-th percentile1694.95
Maximum2595
Range2595
Interquartile range (IQR)626.75

Descriptive statistics

Standard deviation590.90294
Coefficient of variation (CV)1.5112756
Kurtosis1.1896245
Mean390.99616
Median Absolute Deviation (MAD)0
Skewness1.4885396
Sum814054
Variance349166.29
MonotonicityNot monotonic
2024-05-18T16:28:24.947409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1111
53.4%
226 1
 
< 0.1%
237 1
 
< 0.1%
610 1
 
< 0.1%
611 1
 
< 0.1%
266 1
 
< 0.1%
471 1
 
< 0.1%
456 1
 
< 0.1%
455 1
 
< 0.1%
452 1
 
< 0.1%
Other values (962) 962
46.2%
ValueCountFrequency (%)
0 1111
53.4%
1 1
 
< 0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
2595 1
< 0.1%
2440 1
< 0.1%
2392 1
< 0.1%
2371 1
< 0.1%
2351 1
< 0.1%
2331 1
< 0.1%
2311 1
< 0.1%
2293 1
< 0.1%
2292 1
< 0.1%
2291 1
< 0.1%

Sample

건물 번호기관 번호주소1소유자조사일자조사정보건물용도전체면적구조물준공일이름지상층고지하층고조사기관옥탑주소2보고서TMPNO석면함유면적재산관리부서해체제거면적기관명석면함유량
02273458서울시 마포구 중동 38-6시설과<NA><NA>주거시설479.14<NA><NA>관사320<NA>0<NA><NA><NA>0서부공원녹지사업소99.82서부공원녹지사업소0
12311210강서구(주)서남환경<NA><NA>물재생시설5,215.4 ㎡철근콘크리트조1995제1유입펌프동20<NA>0양천로 201<NA><NA>0도시안전실 물재생시설과<NA>서남환경㈜2311
22272458서울시 마포구 중동 38-6시설과<NA><NA>주거시설479.14<NA><NA>관사220<NA>0<NA><NA><NA>0서부공원녹지사업소93.62서부공원녹지사업소0
32271458서울시 마포구 중동 38-6시설과<NA><NA>주거시설476.29<NA><NA>관사120<NA>0<NA><NA><NA>0서부공원녹지사업소70.68서부공원녹지사업소0
42391191서울특별시북부기술교육원 운영지원팀<NA><NA>업무시설<NA>철근콘크리트조1989.10.10본관00<NA>0<NA><NA><NA>1.33일자리정책과<NA>북부기술교육원0
52595767서울특별시 성동구남경종합관리㈜<NA><NA>업무시설379.16철근콘크리트<NA>튼튼삐아제어린이집20<NA>0행당로79<NA><NA>352.51공공주택과<NA>튼튼삐아제어린이집2595
62594766서울특별시 강남구공공의료추진반<NA><NA>의료시설2283.65철근콘크리트<NA>장례식장00<NA>0봉은사로114길 13<NA><NA>119.97공공의료추진반<NA>서울특별시 서울의료원강남분원0
72593766서울특별시 강남구공공의료추진반<NA><NA>의료시설3490.97철근콘크리트<NA>창업지원센터00<NA>0봉은사로114길 13<NA><NA>2255.32공공의료추진반<NA>서울특별시 서울의료원강남분원0
82592766서울특별시 강남구공공의료추진반<NA><NA>의료시설3616.94철근콘크리트<NA>본관동00<NA>0봉은사로114길 13<NA><NA>2329공공의료추진반<NA>서울특별시 서울의료원강남분원0
92591765서울특별시 영등포구영등포문화원<NA><NA>문화/복지시설3356.83철근콘크리트<NA>영등포문화원31<NA>1신길로 275<NA><NA>1436.45문화정책과<NA>영등포문화원0
건물 번호기관 번호주소1소유자조사일자조사정보건물용도전체면적구조물준공일이름지상층고지하층고조사기관옥탑주소2보고서TMPNO석면함유면적재산관리부서해체제거면적기관명석면함유량
20727731서울시 노원구 상계1동 산51총무과 관리팀2010.01.08석면실태조사문화/복지시설1167.84철근콘크리트1991.10.30본관21<NA>1<NA>77. 서울시립노인요양원.pdf<NA>0어르신복지과711서울시립노인요양원77
207310843서울특별시 성북구 종암동 66-25총무과2010.01.08<NA>문화/복지시설2595.02철근콘크리트조1997.12.27본관51<NA>1<NA><NA><NA>0어르신복지과<NA>서울시립성북노인종합복지관0
207415531서울시 노원구 상계1동 산51총무과 관리팀2010.01.08석면실태조사문화/복지시설353.28철근콘크리트1991.10.30신관20<NA>0<NA>77. 서울시립노인요양원1.pdf<NA>0어르신복지과<NA>서울시립노인요양원0
2075655307성동구 응봉동 269-4성동구청 공원녹지과2010..07.26석면실태조사업무시설121.81철근콘크리트조2000암벽등반관리사무소20ETS Consulting0<NA>364. 응봉공원 암벽등반 관리사무소.pdf<NA>0공원조성과60응봉공원655
2076852서울특별시 경기도 과천시운영기획부2010-03-19<NA>업무시설846.72철근콘크리트조1980.09.08관리동31<NA>0주암동 1<NA><NA>1636.72서울시 보건환경연구원<NA>보건환경연구원8
2077318경기도 과천시 대공원광장로 102시설과2010-02-09<NA>업무시설2722.6철근콘크리트조1983.04.09종합관리사무소20<NA>0<NA><NA><NA>0서울대공원(2016년석면 제거 210.6)서울대공원3
20782394경기도 군포시 고산로 589시설과2010-01-14~15<NA>문화/복지시설1766.81철근콘크리트조1988.07.25엘림직업전문학교-교직원숙소61<NA>0<NA><NA><NA>0일자리정책과<NA>엘림복지회23
207916078서울특별시 중구 태평로1가 60-1의정담당관2009.12.28~29<NA>업무시설<NA>철근콘크리트조<NA>부속동40<NA>0<NA><NA><NA>15시의회 의정담당관<NA>서울특별시의회160
208015178서울특별시 중구시설관리팀2009.12.28~29<NA>업무시설7,175.36철근콘크리트조1935.03.20본관91<NA>0세종대로 125<NA><NA>786.64시의회 의정담당관<NA>서울특별시의회151
208113778서울특별시 중구 서소문동 37-1의정담당관2009.12.28<NA>업무시설7587.8철근콘크리트조1971.11.15서울특별시의회 의원회관81<NA>3<NA><NA><NA>0.01시의회 의정담당관55.45서울특별시의회137