Overview

Dataset statistics

Number of variables17
Number of observations4283
Missing cells196
Missing cells (%)0.3%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory594.1 KiB
Average record size in memory142.0 B

Variable types

Text8
Categorical4
Numeric5

Dataset

Description공공데이터 제공 표준데이터 속성정보(허용값, 표현형식/단위 등)는 [공공데이터 제공 표준] 전문을 참고하시기 바랍니다.(공공데이터포털&gt;정보공유&gt;자료실) 각 기관에서 등록한 표준데이터를 취합하여 제공하기 때문에 갱신주기는 개별 파일마다 다릅니다.(기관에서 등록한 데이터를 취합한 것으로 개별 파일별 갱신시점이 다름)
Author지방자치단체
URLhttps://www.data.go.kr/data/15034536/standard.do

Alerts

Dataset has 1 (< 0.1%) duplicate rowsDuplicates
제공기관명 is highly overall correlated with 시군구코드 and 5 other fieldsHigh correlation
시도명 is highly overall correlated with 시군구코드 and 5 other fieldsHigh correlation
데이터기준일자 is highly overall correlated with 시군구코드 and 5 other fieldsHigh correlation
시군구코드 is highly overall correlated with 제공기관코드 and 3 other fieldsHigh correlation
위도 is highly overall correlated with 시도명 and 2 other fieldsHigh correlation
경도 is highly overall correlated with 전용주차단위구획수 and 3 other fieldsHigh correlation
전용주차단위구획수 is highly overall correlated with 경도High correlation
제공기관코드 is highly overall correlated with 시군구코드 and 3 other fieldsHigh correlation
소재지도로명주소 has 73 (1.7%) missing valuesMissing
소재지지번주소 has 108 (2.5%) missing valuesMissing
전용주차단위구획수 has 69 (1.6%) zerosZeros

Reproduction

Analysis started2024-04-13 12:39:57.546476
Analysis finished2024-04-13 12:40:07.015637
Duration9.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공동주택명
Text

Distinct1261
Distinct (%)29.4%
Missing0
Missing (%)0.0%
Memory size33.6 KiB
2024-04-13T21:40:07.671299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length21
Mean length10.017511
Min length3

Characters and Unicode

Total characters42905
Distinct characters475
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique731 ?
Unique (%)17.1%

Sample

1st row평창리비에르1차 아파트
2nd row평창리비에르1차 아파트
3rd row평창리비에르1차 아파트
4th row평창리비에르1차 아파트
5th row평창리비에르1차 아파트
ValueCountFrequency (%)
아파트 192
 
3.0%
검단신도시 128
 
2.0%
2차 123
 
1.9%
1단지 113
 
1.8%
2단지 84
 
1.3%
1차 75
 
1.2%
e편한세상 47
 
0.7%
lh 40
 
0.6%
에일린의뜰 39
 
0.6%
아이파크 39
 
0.6%
Other values (1497) 5549
86.3%
2024-04-13T21:40:08.665425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2146
 
5.0%
아 1784
 
4.2%
파 1779
 
4.1%
트 1767
 
4.1%
지 1270
 
3.0%
단 1012
 
2.4%
스 857
 
2.0%
차 712
 
1.7%
1 705
 
1.6%
이 669
 
1.6%
Other values (465) 30204
70.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36983
86.2%
Space Separator 2146
 
5.0%
Decimal Number 2121
 
4.9%
Uppercase Letter 893
 
2.1%
Open Punctuation 253
 
0.6%
Close Punctuation 253
 
0.6%
Lowercase Letter 142
 
0.3%
Dash Punctuation 52
 
0.1%
Other Symbol 36
 
0.1%
Other Punctuation 26
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 1784
 
4.8%
파 1779
 
4.8%
트 1767
 
4.8%
지 1270
 
3.4%
단 1012
 
2.7%
스 857
 
2.3%
차 712
 
1.9%
이 669
 
1.8%
동 620
 
1.7%
시 600
 
1.6%
Other values (415) 25913
70.1%
Uppercase Letter
ValueCountFrequency (%)
L 207
23.2%
H 146
16.3%
A 115
12.9%
C 77
 
8.6%
K 76
 
8.5%
S 68
 
7.6%
B 44
 
4.9%
T 30
 
3.4%
P 27
 
3.0%
D 25
 
2.8%
Other values (11) 78
 
8.7%
Decimal Number
ValueCountFrequency (%)
1 705
33.2%
2 652
30.7%
3 308
14.5%
0 135
 
6.4%
4 126
 
5.9%
6 68
 
3.2%
5 65
 
3.1%
7 45
 
2.1%
9 10
 
0.5%
8 7
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
e 94
66.2%
c 16
 
11.3%
k 8
 
5.6%
a 5
 
3.5%
n 4
 
2.8%
r 4
 
2.8%
l 4
 
2.8%
t 4
 
2.8%
p 2
 
1.4%
o 1
 
0.7%
Other Punctuation
ValueCountFrequency (%)
, 16
61.5%
. 4
 
15.4%
? 3
 
11.5%
/ 3
 
11.5%
Space Separator
ValueCountFrequency (%)
2146
100.0%
Open Punctuation
ValueCountFrequency (%)
( 253
100.0%
Close Punctuation
ValueCountFrequency (%)
) 253
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37018
86.3%
Common 4851
 
11.3%
Latin 1035
 
2.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 1784
 
4.8%
파 1779
 
4.8%
트 1767
 
4.8%
지 1270
 
3.4%
단 1012
 
2.7%
스 857
 
2.3%
차 712
 
1.9%
이 669
 
1.8%
동 620
 
1.7%
시 600
 
1.6%
Other values (415) 25948
70.1%
Latin
ValueCountFrequency (%)
L 207
20.0%
H 146
14.1%
A 115
11.1%
e 94
9.1%
C 77
 
7.4%
K 76
 
7.3%
S 68
 
6.6%
B 44
 
4.3%
T 30
 
2.9%
P 27
 
2.6%
Other values (21) 151
14.6%
Common
ValueCountFrequency (%)
2146
44.2%
1 705
 
14.5%
2 652
 
13.4%
3 308
 
6.3%
( 253
 
5.2%
) 253
 
5.2%
0 135
 
2.8%
4 126
 
2.6%
6 68
 
1.4%
5 65
 
1.3%
Other values (8) 140
 
2.9%
Han
ValueCountFrequency (%)
愛 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 36982
86.2%
ASCII 5886
 
13.7%
None 36
 
0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2146
36.5%
1 705
 
12.0%
2 652
 
11.1%
3 308
 
5.2%
( 253
 
4.3%
) 253
 
4.3%
L 207
 
3.5%
H 146
 
2.5%
0 135
 
2.3%
4 126
 
2.1%
Other values (39) 955
16.2%
Hangul
ValueCountFrequency (%)
아 1784
 
4.8%
파 1779
 
4.8%
트 1767
 
4.8%
지 1270
 
3.4%
단 1012
 
2.7%
스 857
 
2.3%
차 712
 
1.9%
이 669
 
1.8%
동 620
 
1.7%
시 600
 
1.6%
Other values (414) 25912
70.1%
None
ValueCountFrequency (%)
㈜ 36
100.0%
CJK
ValueCountFrequency (%)
愛 1
100.0%

동번호
Text

Distinct440
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size33.6 KiB
2024-04-13T21:40:09.558989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length3
Mean length3.335746
Min length1

Characters and Unicode

Total characters14287
Distinct characters62
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique298 ?
Unique (%)7.0%

Sample

1st row101
2nd row102
3rd row103
4th row103
5th row104
ValueCountFrequency (%)
101 595
 
13.8%
102 399
 
9.3%
103 309
 
7.2%
104 246
 
5.7%
105 205
 
4.8%
106 163
 
3.8%
1 148
 
3.4%
107 131
 
3.0%
201 106
 
2.5%
108 103
 
2.4%
Other values (422) 1904
44.2%
2024-04-13T21:40:10.881597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4688
32.8%
0 4137
29.0%
2 1677
 
11.7%
3 904
 
6.3%
4 581
 
4.1%
5 461
 
3.2%
+ 402
 
2.8%
6 380
 
2.7%
7 360
 
2.5%
8 226
 
1.6%
Other values (52) 471
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13609
95.3%
Math Symbol 404
 
2.8%
Other Letter 117
 
0.8%
Other Punctuation 49
 
0.3%
Space Separator 48
 
0.3%
Dash Punctuation 31
 
0.2%
Uppercase Letter 17
 
0.1%
Open Punctuation 6
 
< 0.1%
Close Punctuation 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 28
23.9%
사 15
12.8%
기 13
11.1%
숙 13
11.1%
다 5
 
4.3%
관 3
 
2.6%
본 3
 
2.6%
리 3
 
2.6%
아 2
 
1.7%
가 2
 
1.7%
Other values (29) 30
25.6%
Decimal Number
ValueCountFrequency (%)
1 4688
34.4%
0 4137
30.4%
2 1677
 
12.3%
3 904
 
6.6%
4 581
 
4.3%
5 461
 
3.4%
6 380
 
2.8%
7 360
 
2.6%
8 226
 
1.7%
9 195
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
B 6
35.3%
A 5
29.4%
D 3
17.6%
C 2
 
11.8%
E 1
 
5.9%
Math Symbol
ValueCountFrequency (%)
+ 402
99.5%
~ 2
 
0.5%
Other Punctuation
ValueCountFrequency (%)
, 48
98.0%
/ 1
 
2.0%
Space Separator
ValueCountFrequency (%)
48
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14153
99.1%
Hangul 117
 
0.8%
Latin 17
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 28
23.9%
사 15
12.8%
기 13
11.1%
숙 13
11.1%
다 5
 
4.3%
관 3
 
2.6%
본 3
 
2.6%
리 3
 
2.6%
아 2
 
1.7%
가 2
 
1.7%
Other values (29) 30
25.6%
Common
ValueCountFrequency (%)
1 4688
33.1%
0 4137
29.2%
2 1677
 
11.8%
3 904
 
6.4%
4 581
 
4.1%
5 461
 
3.3%
+ 402
 
2.8%
6 380
 
2.7%
7 360
 
2.5%
8 226
 
1.6%
Other values (8) 337
 
2.4%
Latin
ValueCountFrequency (%)
B 6
35.3%
A 5
29.4%
D 3
17.6%
C 2
 
11.8%
E 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14170
99.2%
Hangul 117
 
0.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4688
33.1%
0 4137
29.2%
2 1677
 
11.8%
3 904
 
6.4%
4 581
 
4.1%
5 461
 
3.3%
+ 402
 
2.8%
6 380
 
2.7%
7 360
 
2.5%
8 226
 
1.6%
Other values (13) 354
 
2.5%
Hangul
ValueCountFrequency (%)
동 28
23.9%
사 15
12.8%
기 13
11.1%
숙 13
11.1%
다 5
 
4.3%
관 3
 
2.6%
본 3
 
2.6%
리 3
 
2.6%
아 2
 
1.7%
가 2
 
1.7%
Other values (29) 30
25.6%

전용구역위치구분코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.6 KiB
1
3189 
2
1094 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row1
4th row2
5th row1

Common Values

ValueCountFrequency (%)
1 3189
74.5%
2 1094
 
25.5%

Length

2024-04-13T21:40:11.277183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T21:40:11.590856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3189
74.5%
2 1094
 
25.5%

시도명
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size33.6 KiB
울산광역시
2421 
인천광역시
376 
경기도
373 
강원도
243 
경상남도
 
213
Other values (14)
657 

Length

Max length7
Median length5
Mean length4.6577166
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
울산광역시 2421
56.5%
인천광역시 376
 
8.8%
경기도 373
 
8.7%
강원도 243
 
5.7%
경상남도 213
 
5.0%
대전광역시 115
 
2.7%
충청북도 111
 
2.6%
서울특별시 77
 
1.8%
부산광역시 57
 
1.3%
대구광역시 54
 
1.3%
Other values (9) 243
 
5.7%

Length

2024-04-13T21:40:11.974738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
울산광역시 2421
56.5%
인천광역시 376
 
8.8%
경기도 373
 
8.7%
강원도 243
 
5.7%
경상남도 213
 
5.0%
대전광역시 115
 
2.7%
충청북도 111
 
2.6%
서울특별시 77
 
1.8%
부산광역시 57
 
1.3%
대구광역시 54
 
1.3%
Other values (9) 243
 
5.7%

시군구명
Text

Distinct146
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size33.6 KiB
2024-04-13T21:40:12.990420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length2
Mean length2.5071212
Min length2

Characters and Unicode

Total characters10738
Distinct characters112
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)0.6%

Sample

1st row북구
2nd row북구
3rd row북구
4th row북구
5th row북구
ValueCountFrequency (%)
북구 730
17.0%
남구 670
15.6%
울주군 533
12.4%
중구 394
 
9.2%
서구 246
 
5.7%
동구 233
 
5.4%
양산시 125
 
2.9%
의왕시 108
 
2.5%
유성구 79
 
1.8%
동해시 78
 
1.8%
Other values (138) 1109
25.8%
2024-04-13T21:40:14.139460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 2628
24.5%
시 934
 
8.7%
군 773
 
7.2%
북 730
 
6.8%
남 717
 
6.7%
주 704
 
6.6%
울 533
 
5.0%
중 400
 
3.7%
동 338
 
3.1%
서 259
 
2.4%
Other values (102) 2722
25.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10716
99.8%
Space Separator 22
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 2628
24.5%
시 934
 
8.7%
군 773
 
7.2%
북 730
 
6.8%
남 717
 
6.7%
주 704
 
6.6%
울 533
 
5.0%
중 400
 
3.7%
동 338
 
3.2%
서 259
 
2.4%
Other values (101) 2700
25.2%
Space Separator
ValueCountFrequency (%)
22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10716
99.8%
Common 22
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 2628
24.5%
시 934
 
8.7%
군 773
 
7.2%
북 730
 
6.8%
남 717
 
6.7%
주 704
 
6.6%
울 533
 
5.0%
중 400
 
3.7%
동 338
 
3.2%
서 259
 
2.4%
Other values (101) 2700
25.2%
Common
ValueCountFrequency (%)
22
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10716
99.8%
ASCII 22
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 2628
24.5%
시 934
 
8.7%
군 773
 
7.2%
북 730
 
6.8%
남 717
 
6.7%
주 704
 
6.6%
울 533
 
5.0%
중 400
 
3.7%
동 338
 
3.2%
서 259
 
2.4%
Other values (101) 2700
25.2%
ASCII
ValueCountFrequency (%)
22
100.0%

시군구코드
Real number (ℝ)

HIGH CORRELATION 

Distinct184
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34150.846
Minimum11110
Maximum57100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.8 KiB
2024-04-13T21:40:14.381551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11110
5-th percentile28110
Q131140
median31200
Q341280
95-th percentile48330
Maximum57100
Range45990
Interquartile range (IQR)10140

Descriptive statistics

Standard deviation7269.4334
Coefficient of variation (CV)0.21286247
Kurtosis1.6121488
Mean34150.846
Median Absolute Deviation (MAD)510
Skewness0.61294477
Sum1.4626807 × 108
Variance52844662
MonotonicityNot monotonic
2024-04-13T21:40:14.621674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
31140 964
22.5%
31200 617
14.4%
31110 318
 
7.4%
31710 234
 
5.5%
28260 234
 
5.5%
31170 195
 
4.6%
48330 125
 
2.9%
41430 108
 
2.5%
32100 92
 
2.1%
30200 79
 
1.8%
Other values (174) 1317
30.7%
ValueCountFrequency (%)
11110 1
 
< 0.1%
11170 2
 
< 0.1%
11215 3
0.1%
11230 1
 
< 0.1%
11260 6
0.1%
11320 2
 
< 0.1%
11380 3
0.1%
11500 3
0.1%
11530 2
 
< 0.1%
11545 4
0.1%
ValueCountFrequency (%)
57100 42
1.0%
55700 19
0.4%
55615 3
 
0.1%
55422 2
 
< 0.1%
52800 2
 
< 0.1%
52710 9
 
0.2%
52210 1
 
< 0.1%
52190 2
 
< 0.1%
52180 2
 
< 0.1%
52140 5
 
0.1%

소재지도로명주소
Text

MISSING 

Distinct1222
Distinct (%)29.0%
Missing73
Missing (%)1.7%
Memory size33.6 KiB
2024-04-13T21:40:15.798108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length40
Mean length19.974347
Min length7

Characters and Unicode

Total characters84092
Distinct characters368
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

Unique704 ?
Unique (%)16.7%

Sample

1st row울산광역시 북구 명촌10길22
2nd row울산광역시 북구 명촌10길22
3rd row울산광역시 북구 명촌10길22
4th row울산광역시 북구 명촌10길22
5th row울산광역시 북구 명촌10길22
ValueCountFrequency (%)
울산광역시 2417
 
13.3%
북구 728
 
4.0%
남구 669
 
3.7%
울주군 533
 
2.9%
중구 394
 
2.2%
인천광역시 330
 
1.8%
경기도 284
 
1.6%
강원도 243
 
1.3%
서구 242
 
1.3%
동구 226
 
1.2%
Other values (1866) 12079
66.6%
2024-04-13T21:40:17.318768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13935
 
16.6%
시 3976
 
4.7%
로 3246
 
3.9%
산 3154
 
3.8%
울 3059
 
3.6%
광 3055
 
3.6%
역 3014
 
3.6%
구 2895
 
3.4%
1 2596
 
3.1%
2 1885
 
2.2%
Other values (358) 43277
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54243
64.5%
Space Separator 13935
 
16.6%
Decimal Number 12952
 
15.4%
Open Punctuation 1132
 
1.3%
Close Punctuation 1132
 
1.3%
Dash Punctuation 431
 
0.5%
Other Punctuation 188
 
0.2%
Uppercase Letter 79
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 3976
 
7.3%
로 3246
 
6.0%
산 3154
 
5.8%
울 3059
 
5.6%
광 3055
 
5.6%
역 3014
 
5.6%
구 2895
 
5.3%
길 1722
 
3.2%
동 1648
 
3.0%
남 1301
 
2.4%
Other values (334) 27173
50.1%
Decimal Number
ValueCountFrequency (%)
1 2596
20.0%
2 1885
14.6%
3 1542
11.9%
5 1308
10.1%
0 1202
9.3%
4 1112
8.6%
7 893
 
6.9%
9 860
 
6.6%
6 855
 
6.6%
8 699
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
B 16
20.3%
L 16
20.3%
A 9
11.4%
R 9
11.4%
I 9
11.4%
K 9
11.4%
P 9
11.4%
W 2
 
2.5%
Other Punctuation
ValueCountFrequency (%)
, 180
95.7%
@ 8
 
4.3%
Space Separator
ValueCountFrequency (%)
13935
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1132
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1132
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 431
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54243
64.5%
Common 29770
35.4%
Latin 79
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 3976
 
7.3%
로 3246
 
6.0%
산 3154
 
5.8%
울 3059
 
5.6%
광 3055
 
5.6%
역 3014
 
5.6%
구 2895
 
5.3%
길 1722
 
3.2%
동 1648
 
3.0%
남 1301
 
2.4%
Other values (334) 27173
50.1%
Common
ValueCountFrequency (%)
13935
46.8%
1 2596
 
8.7%
2 1885
 
6.3%
3 1542
 
5.2%
5 1308
 
4.4%
0 1202
 
4.0%
( 1132
 
3.8%
) 1132
 
3.8%
4 1112
 
3.7%
7 893
 
3.0%
Other values (6) 3033
 
10.2%
Latin
ValueCountFrequency (%)
B 16
20.3%
L 16
20.3%
A 9
11.4%
R 9
11.4%
I 9
11.4%
K 9
11.4%
P 9
11.4%
W 2
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54243
64.5%
ASCII 29849
35.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13935
46.7%
1 2596
 
8.7%
2 1885
 
6.3%
3 1542
 
5.2%
5 1308
 
4.4%
0 1202
 
4.0%
( 1132
 
3.8%
) 1132
 
3.8%
4 1112
 
3.7%
7 893
 
3.0%
Other values (14) 3112
 
10.4%
Hangul
ValueCountFrequency (%)
시 3976
 
7.3%
로 3246
 
6.0%
산 3154
 
5.8%
울 3059
 
5.6%
광 3055
 
5.6%
역 3014
 
5.6%
구 2895
 
5.3%
길 1722
 
3.2%
동 1648
 
3.0%
남 1301
 
2.4%
Other values (334) 27173
50.1%

소재지지번주소
Text

MISSING 

Distinct1269
Distinct (%)30.4%
Missing108
Missing (%)2.5%
Memory size33.6 KiB
2024-04-13T21:40:18.430839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length38
Mean length19.233293
Min length11

Characters and Unicode

Total characters80299
Distinct characters322
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

Unique764 ?
Unique (%)18.3%

Sample

1st row울산광역시 북구명촌동895-3
2nd row울산광역시 북구명촌동895-3
3rd row울산광역시 북구명촌동895-3
4th row울산광역시 북구명촌동895-3
5th row울산광역시 북구명촌동895-3
ValueCountFrequency (%)
울산광역시 2421
 
13.5%
남구 669
 
3.7%
울주군 533
 
3.0%
중구 394
 
2.2%
인천광역시 363
 
2.0%
북구 344
 
1.9%
경기도 290
 
1.6%
서구 243
 
1.4%
강원도 243
 
1.4%
동구 226
 
1.3%
Other values (1888) 12270
68.2%
2024-04-13T21:40:19.792593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13821
 
17.2%
시 4037
 
5.0%
동 4023
 
5.0%
1 3775
 
4.7%
산 3095
 
3.9%
광 3089
 
3.8%
역 3057
 
3.8%
울 3033
 
3.8%
구 2869
 
3.6%
- 1956
 
2.4%
Other values (312) 37544
46.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 48106
59.9%
Decimal Number 16301
 
20.3%
Space Separator 13821
 
17.2%
Dash Punctuation 1956
 
2.4%
Uppercase Letter 100
 
0.1%
Other Punctuation 8
 
< 0.1%
Math Symbol 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 4037
 
8.4%
동 4023
 
8.4%
산 3095
 
6.4%
광 3089
 
6.4%
역 3057
 
6.4%
울 3033
 
6.3%
구 2869
 
6.0%
남 1146
 
2.4%
도 1133
 
2.4%
리 1009
 
2.1%
Other values (288) 21615
44.9%
Decimal Number
ValueCountFrequency (%)
1 3775
23.2%
2 1722
10.6%
5 1670
10.2%
8 1447
 
8.9%
7 1416
 
8.7%
3 1392
 
8.5%
6 1335
 
8.2%
4 1319
 
8.1%
0 1200
 
7.4%
9 1025
 
6.3%
Uppercase Letter
ValueCountFrequency (%)
A 29
29.0%
B 18
18.0%
L 17
17.0%
R 9
 
9.0%
P 9
 
9.0%
K 9
 
9.0%
I 9
 
9.0%
Space Separator
ValueCountFrequency (%)
13821
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1956
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 48107
59.9%
Common 32092
40.0%
Latin 100
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 4037
 
8.4%
동 4023
 
8.4%
산 3095
 
6.4%
광 3089
 
6.4%
역 3057
 
6.4%
울 3033
 
6.3%
구 2869
 
6.0%
남 1146
 
2.4%
도 1133
 
2.4%
리 1009
 
2.1%
Other values (289) 21616
44.9%
Common
ValueCountFrequency (%)
13821
43.1%
1 3775
 
11.8%
- 1956
 
6.1%
2 1722
 
5.4%
5 1670
 
5.2%
8 1447
 
4.5%
7 1416
 
4.4%
3 1392
 
4.3%
6 1335
 
4.2%
4 1319
 
4.1%
Other values (6) 2239
 
7.0%
Latin
ValueCountFrequency (%)
A 29
29.0%
B 18
18.0%
L 17
17.0%
R 9
 
9.0%
P 9
 
9.0%
K 9
 
9.0%
I 9
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 48106
59.9%
ASCII 32192
40.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13821
42.9%
1 3775
 
11.7%
- 1956
 
6.1%
2 1722
 
5.3%
5 1670
 
5.2%
8 1447
 
4.5%
7 1416
 
4.4%
3 1392
 
4.3%
6 1335
 
4.1%
4 1319
 
4.1%
Other values (13) 2339
 
7.3%
Hangul
ValueCountFrequency (%)
시 4037
 
8.4%
동 4023
 
8.4%
산 3095
 
6.4%
광 3089
 
6.4%
역 3057
 
6.4%
울 3033
 
6.3%
구 2869
 
6.0%
남 1146
 
2.4%
도 1133
 
2.4%
리 1009
 
2.1%
Other values (288) 21615
44.9%
None
ValueCountFrequency (%)
㈜ 1
100.0%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct1697
Distinct (%)39.7%
Missing4
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean36.129127
Minimum31.319619
Maximum38.380166
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.8 KiB
2024-04-13T21:40:20.037410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31.319619
5-th percentile35.313506
Q135.532696
median35.583351
Q337.201002
95-th percentile37.744203
Maximum38.380166
Range7.0605466
Interquartile range (IQR)1.6683056

Descriptive statistics

Standard deviation0.92456619
Coefficient of variation (CV)0.025590604
Kurtosis-0.62205074
Mean36.129127
Median Absolute Deviation (MAD)0.0789952
Skewness0.85834361
Sum154596.54
Variance0.85482263
MonotonicityNot monotonic
2024-04-13T21:40:20.297580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.495597 23
 
0.5%
35.64706042 21
 
0.5%
35.55283269 21
 
0.5%
35.52742805 20
 
0.5%
35.56912776 19
 
0.4%
35.58830636 19
 
0.4%
35.63618784 19
 
0.4%
37.37059003 18
 
0.4%
35.53197913 18
 
0.4%
35.580382 18
 
0.4%
Other values (1687) 4083
95.3%
ValueCountFrequency (%)
31.319619 1
< 0.1%
33.254521893 1
< 0.1%
33.45095145 1
< 0.1%
33.5174951009 1
< 0.1%
34.32726857 1
< 0.1%
34.48074485 1
< 0.1%
34.533055 1
< 0.1%
34.605386 1
< 0.1%
34.605529 1
< 0.1%
34.7559435 1
< 0.1%
ValueCountFrequency (%)
38.38016559 2
 
< 0.1%
38.38001994 2
 
< 0.1%
38.37997201 2
 
< 0.1%
38.37982764 2
 
< 0.1%
38.37965384 1
 
< 0.1%
38.37965341 2
 
< 0.1%
38.3744331825 5
0.1%
38.24821827 4
0.1%
38.24726973 4
0.1%
38.22842092 6
0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct1700
Distinct (%)39.8%
Missing11
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean128.55805
Minimum123.42896
Maximum129.50236
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.8 KiB
2024-04-13T21:40:20.548348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum123.42896
5-th percentile126.69016
Q1127.43057
median129.24527
Q3129.33482
95-th percentile129.41793
Maximum129.50236
Range6.073397
Interquartile range (IQR)1.9042564

Descriptive statistics

Standard deviation1.0499902
Coefficient of variation (CV)0.0081674403
Kurtosis-0.94044173
Mean128.55805
Median Absolute Deviation (MAD)0.1315298
Skewness-0.87009835
Sum549199.98
Variance1.1024794
MonotonicityNot monotonic
2024-04-13T21:40:20.792827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.237272 23
 
0.5%
129.3530613 21
 
0.5%
129.3547645 21
 
0.5%
129.429738 20
 
0.5%
129.3628915 19
 
0.4%
129.3355895 19
 
0.4%
129.3455623 19
 
0.4%
129.3416768 18
 
0.4%
127.0040435 18
 
0.4%
129.3348248 18
 
0.4%
Other values (1690) 4076
95.2%
ValueCountFrequency (%)
123.428964 1
< 0.1%
126.2715218 1
< 0.1%
126.360656 1
< 0.1%
126.418858 1
< 0.1%
126.422996 1
< 0.1%
126.427339 1
< 0.1%
126.432159275 1
< 0.1%
126.4348029 1
< 0.1%
126.4382829 1
< 0.1%
126.4518402 1
< 0.1%
ValueCountFrequency (%)
129.502361 1
 
< 0.1%
129.4477644 1
 
< 0.1%
129.4426379 6
0.1%
129.4410455 5
0.1%
129.4386724 3
 
0.1%
129.4384103 11
0.3%
129.4379044 3
 
0.1%
129.4377922 10
0.2%
129.4356267 6
0.1%
129.4320508 8
0.2%

전용주차단위구획수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct46
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5577866
Minimum0
Maximum54
Zeros69
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size37.8 KiB
2024-04-13T21:40:21.041993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q32
95-th percentile12
Maximum54
Range54
Interquartile range (IQR)1

Descriptive statistics

Standard deviation4.8606564
Coefficient of variation (CV)1.9003369
Kurtosis26.763264
Mean2.5577866
Median Absolute Deviation (MAD)0
Skewness4.7452995
Sum10955
Variance23.62598
MonotonicityNot monotonic
2024-04-13T21:40:21.510895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
1 2939
68.6%
2 557
 
13.0%
3 229
 
5.3%
4 129
 
3.0%
0 69
 
1.6%
5 32
 
0.7%
10 24
 
0.6%
6 21
 
0.5%
12 19
 
0.4%
14 19
 
0.4%
Other values (36) 245
 
5.7%
ValueCountFrequency (%)
0 69
 
1.6%
1 2939
68.6%
2 557
 
13.0%
3 229
 
5.3%
4 129
 
3.0%
5 32
 
0.7%
6 21
 
0.5%
7 15
 
0.4%
8 15
 
0.4%
9 16
 
0.4%
ValueCountFrequency (%)
54 1
 
< 0.1%
50 1
 
< 0.1%
46 1
 
< 0.1%
45 2
< 0.1%
44 1
 
< 0.1%
43 1
 
< 0.1%
42 1
 
< 0.1%
41 3
0.1%
40 1
 
< 0.1%
36 1
 
< 0.1%

공동주택관리소전화번호
Text

Distinct1164
Distinct (%)27.2%
Missing0
Missing (%)0.0%
Memory size33.6 KiB
2024-04-13T21:40:22.285839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.997899
Min length11

Characters and Unicode

Total characters51387
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

Unique641 ?
Unique (%)15.0%

Sample

1st row052-289-7041
2nd row052-289-7041
3rd row052-289-7041
4th row052-289-7041
5th row052-289-7041
ValueCountFrequency (%)
000-000-0000 60
 
1.4%
032-723-5519 52
 
1.2%
033-255-1556 38
 
0.9%
055-372-1473 33
 
0.8%
055-381-3907 26
 
0.6%
052-222-3093 23
 
0.5%
031-8441-0214 22
 
0.5%
052-291-3224 21
 
0.5%
032-568-9740 21
 
0.5%
052-287-7293 21
 
0.5%
Other values (1154) 3966
92.6%
2024-04-13T21:40:23.293304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 8566
16.7%
2 8355
16.3%
0 7610
14.8%
5 5891
11.5%
3 4471
8.7%
7 3154
 
6.1%
1 2856
 
5.6%
4 2826
 
5.5%
6 2683
 
5.2%
8 2493
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 42821
83.3%
Dash Punctuation 8566
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 8355
19.5%
0 7610
17.8%
5 5891
13.8%
3 4471
10.4%
7 3154
 
7.4%
1 2856
 
6.7%
4 2826
 
6.6%
6 2683
 
6.3%
8 2493
 
5.8%
9 2482
 
5.8%
Dash Punctuation
ValueCountFrequency (%)
- 8566
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 51387
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 8566
16.7%
2 8355
16.3%
0 7610
14.8%
5 5891
11.5%
3 4471
8.7%
7 3154
 
6.1%
1 2856
 
5.6%
4 2826
 
5.5%
6 2683
 
5.2%
8 2493
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51387
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 8566
16.7%
2 8355
16.3%
0 7610
14.8%
5 5891
11.5%
3 4471
8.7%
7 3154
 
6.1%
1 2856
 
5.6%
4 2826
 
5.5%
6 2683
 
5.2%
8 2493
 
4.9%

관할소방서명
Text

Distinct174
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size33.6 KiB
2024-04-13T21:40:24.235810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length5
Mean length5.2523932
Min length5

Characters and Unicode

Total characters22496
Distinct characters123
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)0.8%

Sample

1st row북부소방서
2nd row북부소방서
3rd row북부소방서
4th row북부소방서
5th row북부소방서
ValueCountFrequency (%)
북부소방서 704
16.2%
남부소방서 647
14.9%
중부소방서 627
14.4%
온산소방서 234
 
5.4%
검단소방서 187
 
4.3%
동부소방서 172
 
4.0%
양산소방서 125
 
2.9%
의왕소방서 108
 
2.5%
동해소방서 78
 
1.8%
대전유성소방서 76
 
1.8%
Other values (163) 1382
31.8%
2024-04-13T21:40:25.377612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
서 4393
19.5%
소 4283
19.0%
방 4283
19.0%
부 2480
11.0%
북 736
 
3.3%
남 715
 
3.2%
중 642
 
2.9%
산 552
 
2.5%
동 365
 
1.6%
단 248
 
1.1%
Other values (113) 3799
16.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22439
99.7%
Space Separator 57
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 4393
19.6%
소 4283
19.1%
방 4283
19.1%
부 2480
11.1%
북 736
 
3.3%
남 715
 
3.2%
중 642
 
2.9%
산 552
 
2.5%
동 365
 
1.6%
단 248
 
1.1%
Other values (112) 3742
16.7%
Space Separator
ValueCountFrequency (%)
57
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22439
99.7%
Common 57
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 4393
19.6%
소 4283
19.1%
방 4283
19.1%
부 2480
11.1%
북 736
 
3.3%
남 715
 
3.2%
중 642
 
2.9%
산 552
 
2.5%
동 365
 
1.6%
단 248
 
1.1%
Other values (112) 3742
16.7%
Common
ValueCountFrequency (%)
57
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22439
99.7%
ASCII 57
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
서 4393
19.6%
소 4283
19.1%
방 4283
19.1%
부 2480
11.1%
북 736
 
3.3%
남 715
 
3.2%
중 642
 
2.9%
산 552
 
2.5%
동 365
 
1.6%
단 248
 
1.1%
Other values (112) 3742
16.7%
ASCII
ValueCountFrequency (%)
57
100.0%

관할소방서전화번호
Text

Distinct244
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size33.6 KiB
2024-04-13T21:40:26.217320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.01004
Min length11

Characters and Unicode

Total characters51439
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

Unique68 ?
Unique (%)1.6%

Sample

1st row052-229-8132
2nd row052-229-8132
3rd row052-229-8132
4th row052-229-8132
5th row052-229-8132
ValueCountFrequency (%)
052-229-8132 695
 
16.2%
052-210-4752 640
 
14.9%
052-241-2502 213
 
5.0%
032-590-2794 187
 
4.4%
052-279-6361 169
 
3.9%
052-241-2440 154
 
3.6%
052-210-4772 135
 
3.2%
055-379-9275 125
 
2.9%
052-241-2460 86
 
2.0%
052-241-6681 77
 
1.8%
Other values (234) 1802
42.1%
2024-04-13T21:40:27.293250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 10079
19.6%
- 8566
16.7%
0 7073
13.8%
5 5219
10.1%
1 4656
9.1%
3 3714
 
7.2%
4 3466
 
6.7%
9 2609
 
5.1%
7 2533
 
4.9%
6 2042
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 42873
83.3%
Dash Punctuation 8566
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 10079
23.5%
0 7073
16.5%
5 5219
12.2%
1 4656
10.9%
3 3714
 
8.7%
4 3466
 
8.1%
9 2609
 
6.1%
7 2533
 
5.9%
6 2042
 
4.8%
8 1482
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 8566
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 51439
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 10079
19.6%
- 8566
16.7%
0 7073
13.8%
5 5219
10.1%
1 4656
9.1%
3 3714
 
7.2%
4 3466
 
6.7%
9 2609
 
5.1%
7 2533
 
4.9%
6 2042
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51439
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 10079
19.6%
- 8566
16.7%
0 7073
13.8%
5 5219
10.1%
1 4656
9.1%
3 3714
 
7.2%
4 3466
 
6.7%
9 2609
 
5.1%
7 2533
 
4.9%
6 2042
 
4.0%

데이터기준일자
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size33.6 KiB
2021-01-21
1381 
2021-01-01
792 
2023-07-31
316 
2024-02-29
259 
2021-01-18
234 
Other values (26)
1301 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2021-01-21
2nd row2021-01-21
3rd row2021-01-21
4th row2021-01-21
5th row2021-01-21

Common Values

ValueCountFrequency (%)
2021-01-21 1381
32.2%
2021-01-01 792
18.5%
2023-07-31 316
 
7.4%
2024-02-29 259
 
6.0%
2021-01-18 234
 
5.5%
2024-01-26 195
 
4.6%
2021-11-01 151
 
3.5%
2024-02-01 114
 
2.7%
2021-09-16 106
 
2.5%
2023-12-04 93
 
2.2%
Other values (21) 642
15.0%

Length

2024-04-13T21:40:27.513260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2021-01-21 1381
32.2%
2021-01-01 792
18.5%
2023-07-31 316
 
7.4%
2024-02-29 259
 
6.0%
2021-01-18 234
 
5.5%
2024-01-26 195
 
4.6%
2021-11-01 151
 
3.5%
2024-02-01 114
 
2.7%
2021-09-16 106
 
2.5%
2023-12-04 93
 
2.2%
Other values (21) 642
15.0%

제공기관코드
Real number (ℝ)

HIGH CORRELATION 

Distinct38
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6331773.4
Minimum5670000
Maximum6540000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.8 KiB
2024-04-13T21:40:27.714729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5670000
5-th percentile6270000
Q16310052
median6310059
Q36410000
95-th percentile6480000
Maximum6540000
Range870000
Interquartile range (IQR)99948

Descriptive statistics

Standard deviation90208.61
Coefficient of variation (CV)0.014246974
Kurtosis19.075566
Mean6331773.4
Median Absolute Deviation (MAD)408
Skewness-2.4836002
Sum2.7118986 × 1010
Variance8.1375933 × 109
MonotonicityNot monotonic
2024-04-13T21:40:27.935559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
6310467 695
16.2%
6310059 640
14.9%
6310052 622
14.5%
6280000 316
 
7.4%
6310197 234
 
5.5%
6410000 221
 
5.2%
6480000 195
 
4.6%
6310056 169
 
3.9%
6420883 151
 
3.5%
6300000 114
 
2.7%
Other values (28) 926
21.6%
ValueCountFrequency (%)
5670000 15
 
0.4%
5690000 17
 
0.4%
6110000 77
 
1.8%
6260000 57
 
1.3%
6270000 51
 
1.2%
6270804 4
 
0.1%
6280000 316
7.4%
6280270 5
 
0.1%
6285728 3
 
0.1%
6285754 52
 
1.2%
ValueCountFrequency (%)
6540000 31
 
0.7%
6530000 50
 
1.2%
6500000 3
 
0.1%
6480050 3
 
0.1%
6480000 195
4.6%
6470000 16
 
0.4%
6460000 38
 
0.9%
6451443 5
 
0.1%
6450698 1
 
< 0.1%
6450619 18
 
0.4%

제공기관명
Categorical

HIGH CORRELATION 

Distinct38
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size33.6 KiB
울산광역시 북부소방서
695 
울산광역시 남부소방서
640 
울산광역시 중부소방서
622 
인천광역시
316 
울산광역시 온산소방서
234 
Other values (33)
1776 

Length

Max length12
Median length11
Mean length8.5591875
Min length3

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row울산광역시 북부소방서
2nd row울산광역시 북부소방서
3rd row울산광역시 북부소방서
4th row울산광역시 북부소방서
5th row울산광역시 북부소방서

Common Values

ValueCountFrequency (%)
울산광역시 북부소방서 695
16.2%
울산광역시 남부소방서 640
14.9%
울산광역시 중부소방서 622
14.5%
인천광역시 316
 
7.4%
울산광역시 온산소방서 234
 
5.5%
경기도 221
 
5.2%
경상남도 195
 
4.6%
울산광역시 동부소방서 169
 
3.9%
강원도 소방본부 151
 
3.5%
대전광역시 114
 
2.7%
Other values (28) 926
21.6%

Length

2024-04-13T21:40:28.152541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
울산광역시 2421
34.2%
북부소방서 695
 
9.8%
남부소방서 640
 
9.0%
중부소방서 622
 
8.8%
인천광역시 376
 
5.3%
경기도 373
 
5.3%
강원도 243
 
3.4%
온산소방서 234
 
3.3%
경상남도 213
 
3.0%
소방본부 172
 
2.4%
Other values (26) 1084
15.3%

Interactions

2024-04-13T21:40:05.275466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:02.076622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:02.899620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:03.714117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:04.495678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:05.418950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:02.282561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:03.058830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:03.862874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:04.646462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:05.582744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:02.449763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:03.235464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:04.035010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:04.814965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:05.733546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:02.601941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:03.399553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:04.189479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:04.972571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:05.884882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:02.754782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:03.561041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:04.349690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:40:05.125241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-13T21:40:28.299068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전용구역위치구분코드시도명시군구코드위도경도전용주차단위구획수데이터기준일자제공기관코드제공기관명
전용구역위치구분코드1.0000.3690.2630.2010.1840.1050.4220.3550.461
시도명0.3691.0000.9640.9130.8770.5290.9960.9991.000
시군구코드0.2630.9641.0000.8410.6710.3720.9750.9360.985
위도0.2010.9130.8411.0000.7500.2720.9120.6310.947
경도0.1840.8770.6710.7501.0000.2650.8990.5520.917
전용주차단위구획수0.1050.5290.3720.2720.2651.0000.6230.4330.649
데이터기준일자0.4220.9960.9750.9120.8990.6231.0000.9931.000
제공기관코드0.3550.9990.9360.6310.5520.4330.9931.0001.000
제공기관명0.4611.0000.9850.9470.9170.6491.0001.0001.000
2024-04-13T21:40:28.500511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전용구역위치구분코드제공기관명시도명데이터기준일자
전용구역위치구분코드1.0000.3670.3270.359
제공기관명0.3671.0000.9970.995
시도명0.3270.9971.0000.938
데이터기준일자0.3590.9950.9381.000
2024-04-13T21:40:28.667904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구코드위도경도전용주차단위구획수제공기관코드전용구역위치구분코드시도명데이터기준일자제공기관명
시군구코드1.0000.027-0.0630.1670.8960.2630.8240.8490.892
위도0.0271.000-0.4930.2260.0480.2010.6710.6450.732
경도-0.063-0.4931.000-0.5260.0350.1960.6430.6530.683
전용주차단위구획수0.1670.226-0.5261.0000.0970.0820.2280.2710.286
제공기관코드0.8960.0480.0350.0971.0000.2580.9480.9190.996
전용구역위치구분코드0.2630.2010.1960.0820.2581.0000.3270.3590.367
시도명0.8240.6710.6430.2280.9480.3271.0000.9380.997
데이터기준일자0.8490.6450.6530.2710.9190.3590.9381.0000.995
제공기관명0.8920.7320.6830.2860.9960.3670.9970.9951.000

Missing values

2024-04-13T21:40:06.275548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-13T21:40:06.658271image/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.
2024-04-13T21:40:06.904351image/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

공동주택명동번호전용구역위치구분코드시도명시군구명시군구코드소재지도로명주소소재지지번주소위도경도전용주차단위구획수공동주택관리소전화번호관할소방서명관할소방서전화번호데이터기준일자제공기관코드제공기관명
0평창리비에르1차 아파트1012울산광역시북구32100울산광역시 북구 명촌10길22울산광역시 북구명촌동895-335.551975129.3567881052-289-7041북부소방서052-229-81322021-01-216310467울산광역시 북부소방서
1평창리비에르1차 아파트1021울산광역시북구32100울산광역시 북구 명촌10길22울산광역시 북구명촌동895-335.551975129.3567881052-289-7041북부소방서052-229-81322021-01-216310467울산광역시 북부소방서
2평창리비에르1차 아파트1031울산광역시북구32100울산광역시 북구 명촌10길22울산광역시 북구명촌동895-335.551975129.3567881052-289-7041북부소방서052-229-81322021-01-216310467울산광역시 북부소방서
3평창리비에르1차 아파트1032울산광역시북구32100울산광역시 북구 명촌10길22울산광역시 북구명촌동895-335.551975129.3567881052-289-7041북부소방서052-229-81322021-01-216310467울산광역시 북부소방서
4평창리비에르1차 아파트1041울산광역시북구32100울산광역시 북구 명촌10길22울산광역시 북구명촌동895-335.551975129.3567881052-289-7041북부소방서052-229-81322021-01-216310467울산광역시 북부소방서
5평창리비에르1차 아파트1051울산광역시북구32100울산광역시 북구 명촌10길22울산광역시 북구명촌동895-335.551975129.3567881052-289-7041북부소방서052-229-81322021-01-216310467울산광역시 북부소방서
6평창리비에르1차 아파트1052울산광역시북구32100울산광역시 북구 명촌10길22울산광역시 북구명촌동895-335.551975129.3567881052-289-7041북부소방서052-229-81322021-01-216310467울산광역시 북부소방서
7평창리비에르1차 아파트1062울산광역시북구32100울산광역시 북구 명촌10길22울산광역시 북구명촌동895-335.551975129.3567881052-289-7041북부소방서052-229-81322021-01-216310467울산광역시 북부소방서
8평창리비에르1차 아파트1072울산광역시북구32100울산광역시 북구 명촌10길22울산광역시 북구명촌동895-335.551975129.3567881052-289-7041북부소방서052-229-81322021-01-216310467울산광역시 북부소방서
9평창리비에르1차 아파트1081울산광역시북구32100울산광역시 북구 명촌10길22울산광역시 북구명촌동895-335.551975129.3567881052-289-7041북부소방서052-229-81322021-01-216310467울산광역시 북부소방서
공동주택명동번호전용구역위치구분코드시도명시군구명시군구코드소재지도로명주소소재지지번주소위도경도전용주차단위구획수공동주택관리소전화번호관할소방서명관할소방서전화번호데이터기준일자제공기관코드제공기관명
4273동양아트맨션아파트1011울산광역시울주군31140울산광역시 울주군 범서읍 점촌5길 13-19(구영리)울산광역시 울주군 범서읍 구영리 100835.5694129.2404251052-248-8501중부소방서052-241-25022021-01-016310052울산광역시 중부소방서
4274동양한신아파트2011울산광역시울주군31140울산광역시 울주군 범서읍 점촌4길 77(구영리)울산광역시 울주군 범서읍 구영리 796-235.571836129.2409951052-211-5484중부소방서052-241-25022021-01-016310052울산광역시 중부소방서
4275동양한신아파트2021울산광역시울주군31140울산광역시 울주군 범서읍 점촌4길 77(구영리)울산광역시 울주군 범서읍 구영리 796-235.571836129.2409951052-211-5484중부소방서052-241-25022021-01-016310052울산광역시 중부소방서
4276동양한신아파트2031울산광역시울주군31140울산광역시 울주군 범서읍 점촌4길 77(구영리)울산광역시 울주군 범서읍 구영리 796-235.571836129.2409951052-211-5484중부소방서052-241-25022021-01-016310052울산광역시 중부소방서
4277드림파크01울산광역시울주군31140울산광역시 울주군 범서읍 천상4길 1(천상리)울산광역시 울주군 범서읍 구영리 841-235.563909129.2264091000-000-0000중부소방서052-241-25022021-01-016310052울산광역시 중부소방서
4278무거좋은하이빌01울산광역시울주군31140울산광역시 울주군 범서읍 백천2길 88(굴화리)울산광역시 울주군 범서읍 굴화리 286-335.555881129.2523531052-277-3002중부소방서052-241-25022021-01-016310052울산광역시 중부소방서
4279문수그린아파트2011울산광역시울주군31140울산광역시 울주군 범서읍 천상3길 11(천상리)울산광역시 울주군 범서읍 천상리 610-135.563268129.2276271000-000-0000중부소방서052-241-25022021-01-016310052울산광역시 중부소방서
4280문수산 신동아 파밀리에아파트1011울산광역시울주군31140울산광역시 울주군 범서읍 장검길 143(굴화리)울산광역시 울주군 범서읍 굴화리 74335.547636129.2497081052-221-2687중부소방서052-241-25022021-01-016310052울산광역시 중부소방서
4281문수산 신동아 파밀리에아파트1021울산광역시울주군31140울산광역시 울주군 범서읍 장검길 143(굴화리)울산광역시 울주군 범서읍 굴화리 74335.547636129.2497081052-221-2687중부소방서052-241-25022021-01-016310052울산광역시 중부소방서
4282정읍첨단 A1-3 행복주택3041전라북도정읍시45180전라북도 정읍시 첨단1로 47전라북도 정읍시 신정동 1494-535.507091126.8408671063-538-1220정읍소방서063-570-12002021-10-206450619전라북도 정읍소방서

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공동주택명동번호전용구역위치구분코드시도명시군구명시군구코드소재지도로명주소소재지지번주소위도경도전용주차단위구획수공동주택관리소전화번호관할소방서명관할소방서전화번호데이터기준일자제공기관코드제공기관명# duplicates
0주문진벽산블루밍오션힐스 아파트1032강원도강릉시42150강원도 강릉시 주문진읍 장성로 25강원도 강릉시 주문진읍 교항리 1269 주문진벽산블루밍오션힐스37.888548128.8230611033-662-7775강릉소방서033-645-01192022-11-156420000강원도2