Overview

Dataset statistics

Number of variables9
Number of observations429
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory31.5 KiB
Average record size in memory75.3 B

Variable types

Numeric3
Categorical2
Text4

Dataset

Description화재의 예방 및 안전관리에 관한 법률에 근거한 관련 화재안전 중점관리대상 선정 및 관리규칙에 따라 중점관리대상 선정, 공공데이터 개방
URLhttps://www.data.go.kr/data/15105990/fileData.do

Alerts

지상층 is highly overall correlated with 지하층High correlation
지하층 is highly overall correlated with 지상층High correlation
연번 has unique valuesUnique
연면적 has unique valuesUnique
지상층 has 14 (3.3%) zerosZeros
지하층 has 43 (10.0%) zerosZeros

Reproduction

Analysis started2023-12-12 04:49:56.107893
Analysis finished2023-12-12 04:49:58.116437
Duration2.01 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct429
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean215
Minimum1
Maximum429
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2023-12-12T13:49:58.212183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile22.4
Q1108
median215
Q3322
95-th percentile407.6
Maximum429
Range428
Interquartile range (IQR)214

Descriptive statistics

Standard deviation123.98589
Coefficient of variation (CV)0.57667854
Kurtosis-1.2
Mean215
Median Absolute Deviation (MAD)107
Skewness0
Sum92235
Variance15372.5
MonotonicityStrictly increasing
2023-12-12T13:49:58.406126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
296 1
 
0.2%
294 1
 
0.2%
293 1
 
0.2%
292 1
 
0.2%
291 1
 
0.2%
290 1
 
0.2%
289 1
 
0.2%
288 1
 
0.2%
287 1
 
0.2%
Other values (419) 419
97.7%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
429 1
0.2%
428 1
0.2%
427 1
0.2%
426 1
0.2%
425 1
0.2%
424 1
0.2%
423 1
0.2%
422 1
0.2%
421 1
0.2%
420 1
0.2%

구분
Categorical

Distinct19
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
복합건축물
187 
공장
42 
의료시설
40 
판매시설
31 
노유자시설
24 
Other values (14)
105 

Length

Max length13
Median length8
Mean length4.7062937
Min length2

Unique

Unique3 ?
Unique (%)0.7%

Sample

1st row의료시설
2nd row숙박시설
3rd row노유자시설
4th row지하가
5th row지하가

Common Values

ValueCountFrequency (%)
복합건축물 187
43.6%
공장 42
 
9.8%
의료시설 40
 
9.3%
판매시설 31
 
7.2%
노유자시설 24
 
5.6%
숙박시설 23
 
5.4%
위험물 저장 및 처리시설 15
 
3.5%
근린생활시설 14
 
3.3%
창고시설 14
 
3.3%
지하가 14
 
3.3%
Other values (9) 25
 
5.8%

Length

2023-12-12T13:49:58.575726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
복합건축물 187
39.5%
공장 42
 
8.9%
의료시설 40
 
8.4%
판매시설 31
 
6.5%
노유자시설 24
 
5.1%
숙박시설 23
 
4.9%
위험물 15
 
3.2%
저장 15
 
3.2%
및 15
 
3.2%
처리시설 15
 
3.2%
Other values (12) 67
 
14.1%

대상명
Text

Distinct428
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2023-12-12T13:49:58.848341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length19
Mean length8.2051282
Min length2

Characters and Unicode

Total characters3520
Distinct characters406
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

Unique427 ?
Unique (%)99.5%

Sample

1st row인하대병원
2nd row하버파크호텔
3rd row수요양원
4th row신포지하상가
5th row중앙로지하상가
ValueCountFrequency (%)
홈플러스 5
 
1.0%
건물 4
 
0.8%
지식산업센터 3
 
0.6%
물류센터 3
 
0.6%
오피스텔 3
 
0.6%
대우프라자 2
 
0.4%
㈜셀트리온 2
 
0.4%
종합어시장 2
 
0.4%
중앙시장 2
 
0.4%
이마트 2
 
0.4%
Other values (481) 482
94.5%
2023-12-12T13:49:59.262843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 103
 
2.9%
원 83
 
2.4%
82
 
2.3%
인 76
 
2.2%
) 66
 
1.9%
라 65
 
1.8%
트 63
 
1.8%
지 61
 
1.7%
리 61
 
1.7%
이 58
 
1.6%
Other values (396) 2802
79.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3151
89.5%
Uppercase Letter 92
 
2.6%
Space Separator 82
 
2.3%
Close Punctuation 67
 
1.9%
Open Punctuation 59
 
1.7%
Decimal Number 35
 
1.0%
Other Symbol 14
 
0.4%
Lowercase Letter 10
 
0.3%
Other Punctuation 6
 
0.2%
Dash Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 103
 
3.3%
원 83
 
2.6%
인 76
 
2.4%
라 65
 
2.1%
트 63
 
2.0%
지 61
 
1.9%
리 61
 
1.9%
이 58
 
1.8%
병 55
 
1.7%
천 52
 
1.7%
Other values (351) 2474
78.5%
Uppercase Letter
ValueCountFrequency (%)
E 10
 
10.9%
C 10
 
10.9%
G 9
 
9.8%
S 8
 
8.7%
L 6
 
6.5%
I 5
 
5.4%
A 5
 
5.4%
D 5
 
5.4%
R 5
 
5.4%
B 4
 
4.3%
Other values (11) 25
27.2%
Lowercase Letter
ValueCountFrequency (%)
k 2
20.0%
i 2
20.0%
v 1
10.0%
g 1
10.0%
c 1
10.0%
n 1
10.0%
m 1
10.0%
o 1
10.0%
Decimal Number
ValueCountFrequency (%)
1 15
42.9%
2 12
34.3%
3 3
 
8.6%
5 2
 
5.7%
7 1
 
2.9%
4 1
 
2.9%
6 1
 
2.9%
Close Punctuation
ValueCountFrequency (%)
) 66
98.5%
] 1
 
1.5%
Open Punctuation
ValueCountFrequency (%)
( 58
98.3%
[ 1
 
1.7%
Other Punctuation
ValueCountFrequency (%)
, 4
66.7%
& 2
33.3%
Space Separator
ValueCountFrequency (%)
82
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3165
89.9%
Common 253
 
7.2%
Latin 102
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 103
 
3.3%
원 83
 
2.6%
인 76
 
2.4%
라 65
 
2.1%
트 63
 
2.0%
지 61
 
1.9%
리 61
 
1.9%
이 58
 
1.8%
병 55
 
1.7%
천 52
 
1.6%
Other values (352) 2488
78.6%
Latin
ValueCountFrequency (%)
E 10
 
9.8%
C 10
 
9.8%
G 9
 
8.8%
S 8
 
7.8%
L 6
 
5.9%
I 5
 
4.9%
A 5
 
4.9%
D 5
 
4.9%
R 5
 
4.9%
B 4
 
3.9%
Other values (19) 35
34.3%
Common
ValueCountFrequency (%)
82
32.4%
) 66
26.1%
( 58
22.9%
1 15
 
5.9%
2 12
 
4.7%
- 4
 
1.6%
, 4
 
1.6%
3 3
 
1.2%
5 2
 
0.8%
& 2
 
0.8%
Other values (5) 5
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3151
89.5%
ASCII 355
 
10.1%
None 14
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 103
 
3.3%
원 83
 
2.6%
인 76
 
2.4%
라 65
 
2.1%
트 63
 
2.0%
지 61
 
1.9%
리 61
 
1.9%
이 58
 
1.8%
병 55
 
1.7%
천 52
 
1.7%
Other values (351) 2474
78.5%
ASCII
ValueCountFrequency (%)
82
23.1%
) 66
18.6%
( 58
16.3%
1 15
 
4.2%
2 12
 
3.4%
E 10
 
2.8%
C 10
 
2.8%
G 9
 
2.5%
S 8
 
2.3%
L 6
 
1.7%
Other values (34) 79
22.3%
None
ValueCountFrequency (%)
㈜ 14
100.0%

주소_구 주소
Text

Distinct417
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2023-12-12T13:49:59.485875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19
Mean length13.04662
Min length8

Characters and Unicode

Total characters5597
Distinct characters123
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

Unique409 ?
Unique (%)95.3%

Sample

1st row중구 신흥동 3가 7-206
2nd row중구 항동 3가 5
3rd row중구 용동 87
4th row 중구 답동 24-3
5th row중구 인현동 01-000
ValueCountFrequency (%)
연수구 76
 
5.8%
남동구 73
 
5.5%
중구 68
 
5.2%
부평구 54
 
4.1%
서구 54
 
4.1%
송도동 53
 
4.0%
미추홀구 42
 
3.2%
계양구 35
 
2.7%
구월동 25
 
1.9%
부평동 21
 
1.6%
Other values (528) 815
61.9%
2023-12-12T13:49:59.883580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
904
16.2%
동 510
 
9.1%
구 443
 
7.9%
1 391
 
7.0%
- 338
 
6.0%
2 230
 
4.1%
3 194
 
3.5%
4 176
 
3.1%
5 160
 
2.9%
0 154
 
2.8%
Other values (113) 2097
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2546
45.5%
Decimal Number 1799
32.1%
Space Separator 904
 
16.2%
Dash Punctuation 338
 
6.0%
Other Punctuation 10
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 510
20.0%
구 443
17.4%
수 87
 
3.4%
연 80
 
3.1%
부 77
 
3.0%
남 77
 
3.0%
평 76
 
3.0%
서 74
 
2.9%
중 74
 
2.9%
송 65
 
2.6%
Other values (100) 983
38.6%
Decimal Number
ValueCountFrequency (%)
1 391
21.7%
2 230
12.8%
3 194
10.8%
4 176
9.8%
5 160
8.9%
0 154
 
8.6%
6 144
 
8.0%
7 133
 
7.4%
8 110
 
6.1%
9 107
 
5.9%
Space Separator
ValueCountFrequency (%)
904
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 338
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3051
54.5%
Hangul 2546
45.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 510
20.0%
구 443
17.4%
수 87
 
3.4%
연 80
 
3.1%
부 77
 
3.0%
남 77
 
3.0%
평 76
 
3.0%
서 74
 
2.9%
중 74
 
2.9%
송 65
 
2.6%
Other values (100) 983
38.6%
Common
ValueCountFrequency (%)
904
29.6%
1 391
12.8%
- 338
 
11.1%
2 230
 
7.5%
3 194
 
6.4%
4 176
 
5.8%
5 160
 
5.2%
0 154
 
5.0%
6 144
 
4.7%
7 133
 
4.4%
Other values (3) 227
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3051
54.5%
Hangul 2546
45.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
904
29.6%
1 391
12.8%
- 338
 
11.1%
2 230
 
7.5%
3 194
 
6.4%
4 176
 
5.8%
5 160
 
5.2%
0 154
 
5.0%
6 144
 
4.7%
7 133
 
4.4%
Other values (3) 227
 
7.4%
Hangul
ValueCountFrequency (%)
동 510
20.0%
구 443
17.4%
수 87
 
3.4%
연 80
 
3.1%
부 77
 
3.0%
남 77
 
3.0%
평 76
 
3.0%
서 74
 
2.9%
중 74
 
2.9%
송 65
 
2.6%
Other values (100) 983
38.6%

주소_새 주소
Text

Distinct420
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2023-12-12T13:50:00.203639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length23
Mean length13.107226
Min length8

Characters and Unicode

Total characters5623
Distinct characters247
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

Unique415 ?
Unique (%)96.7%

Sample

1st row중구 인항로 27
2nd row중구 제물량로 217
3rd row중구 큰우물로 18
4th row중구 우현로 67
5th row중구 참외전로 17-15
ValueCountFrequency (%)
연수구 77
 
5.9%
남동구 72
 
5.5%
중구 68
 
5.2%
부평구 54
 
4.1%
서구 54
 
4.1%
미추홀구 42
 
3.2%
계양구 35
 
2.7%
동구 16
 
1.2%
부평대로 11
 
0.8%
강화군 10
 
0.8%
Other values (546) 864
66.3%
2023-12-12T13:50:00.704392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
899
 
16.0%
로 427
 
7.6%
구 424
 
7.5%
1 258
 
4.6%
2 197
 
3.5%
3 157
 
2.8%
길 133
 
2.4%
4 129
 
2.3%
대 126
 
2.2%
6 125
 
2.2%
Other values (237) 2748
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3253
57.9%
Decimal Number 1422
25.3%
Space Separator 899
 
16.0%
Dash Punctuation 37
 
0.7%
Uppercase Letter 8
 
0.1%
Math Symbol 2
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 427
 
13.1%
구 424
 
13.0%
길 133
 
4.1%
대 126
 
3.9%
번 123
 
3.8%
동 111
 
3.4%
남 103
 
3.2%
수 88
 
2.7%
중 85
 
2.6%
연 81
 
2.5%
Other values (214) 1552
47.7%
Decimal Number
ValueCountFrequency (%)
1 258
18.1%
2 197
13.9%
3 157
11.0%
4 129
9.1%
6 125
8.8%
7 124
8.7%
0 119
8.4%
5 118
8.3%
8 102
 
7.2%
9 93
 
6.5%
Uppercase Letter
ValueCountFrequency (%)
I 1
12.5%
B 1
12.5%
S 1
12.5%
R 1
12.5%
A 1
12.5%
E 1
12.5%
M 1
12.5%
T 1
12.5%
Space Separator
ValueCountFrequency (%)
899
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3253
57.9%
Common 2362
42.0%
Latin 8
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 427
 
13.1%
구 424
 
13.0%
길 133
 
4.1%
대 126
 
3.9%
번 123
 
3.8%
동 111
 
3.4%
남 103
 
3.2%
수 88
 
2.7%
중 85
 
2.6%
연 81
 
2.5%
Other values (214) 1552
47.7%
Common
ValueCountFrequency (%)
899
38.1%
1 258
 
10.9%
2 197
 
8.3%
3 157
 
6.6%
4 129
 
5.5%
6 125
 
5.3%
7 124
 
5.2%
0 119
 
5.0%
5 118
 
5.0%
8 102
 
4.3%
Other values (5) 134
 
5.7%
Latin
ValueCountFrequency (%)
I 1
12.5%
B 1
12.5%
S 1
12.5%
R 1
12.5%
A 1
12.5%
E 1
12.5%
M 1
12.5%
T 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3253
57.9%
ASCII 2370
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
899
37.9%
1 258
 
10.9%
2 197
 
8.3%
3 157
 
6.6%
4 129
 
5.4%
6 125
 
5.3%
7 124
 
5.2%
0 119
 
5.0%
5 118
 
5.0%
8 102
 
4.3%
Other values (13) 142
 
6.0%
Hangul
ValueCountFrequency (%)
로 427
 
13.1%
구 424
 
13.0%
길 133
 
4.1%
대 126
 
3.9%
번 123
 
3.8%
동 111
 
3.4%
남 103
 
3.2%
수 88
 
2.7%
중 85
 
2.6%
연 81
 
2.5%
Other values (214) 1552
47.7%

지상층
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct49
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.624709
Minimum0
Maximum68
Zeros14
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2023-12-12T13:50:00.899369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q14
median7
Q311
95-th percentile37
Maximum68
Range68
Interquartile range (IQR)7

Descriptive statistics

Standard deviation11.205658
Coefficient of variation (CV)1.0546791
Kurtosis6.4670778
Mean10.624709
Median Absolute Deviation (MAD)3
Skewness2.4704404
Sum4558
Variance125.56677
MonotonicityNot monotonic
2023-12-12T13:50:01.129825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
7 42
 
9.8%
4 40
 
9.3%
5 39
 
9.1%
6 39
 
9.1%
3 32
 
7.5%
8 31
 
7.2%
9 24
 
5.6%
10 23
 
5.4%
2 16
 
3.7%
0 14
 
3.3%
Other values (39) 129
30.1%
ValueCountFrequency (%)
0 14
 
3.3%
1 9
 
2.1%
2 16
 
3.7%
3 32
7.5%
4 40
9.3%
5 39
9.1%
6 39
9.1%
7 42
9.8%
8 31
7.2%
9 24
5.6%
ValueCountFrequency (%)
68 1
 
0.2%
64 1
 
0.2%
60 1
 
0.2%
55 1
 
0.2%
53 2
0.5%
51 1
 
0.2%
50 1
 
0.2%
49 3
0.7%
47 1
 
0.2%
45 2
0.5%

지하층
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct11
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0629371
Minimum0
Maximum15
Zeros43
Zeros (%)10.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2023-12-12T13:50:01.295817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum15
Range15
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.766313
Coefficient of variation (CV)0.85621272
Kurtosis11.469295
Mean2.0629371
Median Absolute Deviation (MAD)1
Skewness2.4215634
Sum885
Variance3.1198614
MonotonicityNot monotonic
2023-12-12T13:50:01.420649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 161
37.5%
2 95
22.1%
3 67
15.6%
0 43
 
10.0%
4 27
 
6.3%
5 19
 
4.4%
6 7
 
1.6%
7 5
 
1.2%
8 3
 
0.7%
15 1
 
0.2%
ValueCountFrequency (%)
0 43
 
10.0%
1 161
37.5%
2 95
22.1%
3 67
15.6%
4 27
 
6.3%
5 19
 
4.4%
6 7
 
1.6%
7 5
 
1.2%
8 3
 
0.7%
14 1
 
0.2%
ValueCountFrequency (%)
15 1
 
0.2%
14 1
 
0.2%
8 3
 
0.7%
7 5
 
1.2%
6 7
 
1.6%
5 19
 
4.4%
4 27
 
6.3%
3 67
15.6%
2 95
22.1%
1 161
37.5%

연면적
Text

UNIQUE 

Distinct429
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2023-12-12T13:50:01.767765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length7.5477855
Min length3

Characters and Unicode

Total characters3238
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique429 ?
Unique (%)100.0%

Sample

1st row107190
2nd row20067
3rd row4822
4th row4938.1
5th row4066.31
ValueCountFrequency (%)
107190 1
 
0.2%
104230.88 1
 
0.2%
2065.66 1
 
0.2%
20508.23 1
 
0.2%
14811.47 1
 
0.2%
7849.3 1
 
0.2%
36379.21 1
 
0.2%
4237.27 1
 
0.2%
49129.85 1
 
0.2%
1597.27 1
 
0.2%
Other values (419) 419
97.7%
2023-12-12T13:50:02.286323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 385
11.9%
. 383
11.8%
2 314
9.7%
6 309
9.5%
4 297
9.2%
5 279
8.6%
8 262
8.1%
9 260
8.0%
3 249
7.7%
7 246
7.6%
Other values (3) 254
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2827
87.3%
Other Punctuation 383
 
11.8%
Open Punctuation 14
 
0.4%
Close Punctuation 14
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 385
13.6%
2 314
11.1%
6 309
10.9%
4 297
10.5%
5 279
9.9%
8 262
9.3%
9 260
9.2%
3 249
8.8%
7 246
8.7%
0 226
8.0%
Other Punctuation
ValueCountFrequency (%)
. 383
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3238
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 385
11.9%
. 383
11.8%
2 314
9.7%
6 309
9.5%
4 297
9.2%
5 279
8.6%
8 262
8.1%
9 260
8.0%
3 249
7.7%
7 246
7.6%
Other values (3) 254
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3238
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 385
11.9%
. 383
11.8%
2 314
9.7%
6 309
9.5%
4 297
9.2%
5 279
8.6%
8 262
8.1%
9 260
8.0%
3 249
7.7%
7 246
7.6%
Other values (3) 254
7.8%

등급
Categorical

Distinct8
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
1급
208 
2급
167 
특급
37 
일반
 
7
공공(1급)
 
4
Other values (3)
 
6

Length

Max length6
Median length2
Mean length2.0536131
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row1급
2nd row1급
3rd row2급
4th row2급
5th row2급

Common Values

ValueCountFrequency (%)
1급 208
48.5%
2급 167
38.9%
특급 37
 
8.6%
일반 7
 
1.6%
공공(1급) 4
 
0.9%
1급 3
 
0.7%
3급 2
 
0.5%
공공(특급) 1
 
0.2%

Length

2023-12-12T13:50:02.458520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:50:02.585525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1급 211
49.2%
2급 167
38.9%
특급 37
 
8.6%
일반 7
 
1.6%
공공(1급 4
 
0.9%
3급 2
 
0.5%
공공(특급 1
 
0.2%

Interactions

2023-12-12T13:49:57.491616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:49:56.788279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:49:57.106453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:49:57.588322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:49:56.897149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:49:57.208114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:49:57.728478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:49:56.998806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:49:57.359064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:50:02.687931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분지상층지하층등급
연번1.0000.4540.4170.2170.361
구분0.4541.0000.5720.3320.782
지상층0.4170.5721.0000.4300.610
지하층0.2170.3320.4301.0000.318
등급0.3610.7820.6100.3181.000
2023-12-12T13:50:02.791180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분등급
구분1.0000.468
등급0.4681.000
2023-12-12T13:50:02.886642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번지상층지하층구분등급
연번1.0000.2160.2020.1850.181
지상층0.2161.0000.5360.2510.346
지하층0.2020.5361.0000.1430.145
구분0.1850.2510.1431.0000.468
등급0.1810.3460.1450.4681.000

Missing values

2023-12-12T13:49:57.918407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:49:58.060005image/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

연번구분대상명주소_구 주소주소_새 주소지상층지하층연면적등급
01의료시설인하대병원중구 신흥동 3가 7-206중구 인항로 271641071901급
12숙박시설하버파크호텔중구 항동 3가 5중구 제물량로 217152200671급
23노유자시설수요양원중구 용동 87중구 큰우물로 187248222급
34지하가신포지하상가중구 답동 24-3중구 우현로 67014938.12급
45지하가중앙로지하상가중구 인현동 01-000중구 참외전로 17-15014066.312급
56공장대한제분㈜중구 북성동1가 4중구 월미로 509157725.42급
67공장CJ1공장중구 신흥동 3가 7-121중구 아암대로205046974.582급
78문화및집회시설애관극장중구 경동 238, 238 -1중구 개항로 63-2301151.252급
89판매시설동인천신세계이마트중구 신생동 38중구 인중로 134 동인천 E-MART5139947.081급
910판매시설신포시장중구 신포동 3-2중구 우현로49번길 11-253178002급
연번구분대상명주소_구 주소주소_새 주소지상층지하층연면적등급
419420업무시설부영송도타워연수구 송도동 36연수구 인천타워대로 241395148789.92특급
420421숙박시설송도센트럴파크호텔연수구 송도동 38연수구 테크노파크로 19316348780.621급
421422복합건축물송도센트로드연수구 송도동 30-3연수구 인천타워대로 323454201951.97특급
422423복합건축물아트센터인천연수구 송도동 80-1연수구 아트센터대로 2227251977.07공공(1급)
423424숙박시설오라카이송도파크호텔연수구 송도동 93-1연수구 테크노파크로 15120226450.671급
424425판매시설코스트코송도점연수구 송도동 98연수구 컨벤시아대로230번길 604146873.41급
425426복합건축물송도ok센터(홀리데이인)연수구 송도동 33-1연수구 인천타워대로 25120330246.391급
426427복합건축물송도테크노파크AT센터연수구 송도동 172-5연수구 송도과학로 70332108161.73특급
427428복합건축물씨워크 인테라스 한라연수구 송도동 29-8연수구 센트럴로 31325493383.491급
428429복합건축물리치센트럴연수구 송도동 96연수구 인천타워대로197번길 168279913.161급