Overview

Dataset statistics

Number of variables11
Number of observations8723
Missing cells48727
Missing cells (%)50.8%
Duplicate rows82
Duplicate rows (%)0.9%
Total size in memory783.8 KiB
Average record size in memory92.0 B

Variable types

Categorical1
Text5
Numeric4
DateTime1

Dataset

Description경기도_실내공기질 관리법 적용대상 다중이용시설 현황
Author가평군
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=RHQGQ30LD4PGDBJTTSCX29097029&infSeq=1

Alerts

Dataset has 82 (0.9%) duplicate rowsDuplicates
연면적 is highly overall correlated with 객석수또는관람석수또는병상수High correlation
객석수또는관람석수또는병상수 is highly overall correlated with 연면적High correlation
위도 is highly overall correlated with 시군명High correlation
경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
소재지도로명주소 has 7345 (84.2%) missing valuesMissing
소재지지번주소 has 7878 (90.3%) missing valuesMissing
전화번호 has 6686 (76.6%) missing valuesMissing
연면적 has 2844 (32.6%) missing valuesMissing
객석수또는관람석수또는병상수 has 8642 (99.1%) missing valuesMissing
위도 has 7666 (87.9%) missing valuesMissing
경도 has 7666 (87.9%) missing valuesMissing
연면적 is highly skewed (γ1 = 53.92458305)Skewed

Reproduction

Analysis started2024-05-10 21:54:53.159363
Analysis finished2024-05-10 21:55:04.415804
Duration11.26 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size68.3 KiB
파주시
2604 
고양시
727 
성남시
705 
수원시
568 
용인시
534 
Other values (25)
3585 

Length

Max length4
Median length3
Mean length3.0577783
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
파주시 2604
29.9%
고양시 727
 
8.3%
성남시 705
 
8.1%
수원시 568
 
6.5%
용인시 534
 
6.1%
화성시 367
 
4.2%
부천시 352
 
4.0%
안산시 350
 
4.0%
안양시 302
 
3.5%
남양주시 240
 
2.8%
Other values (20) 1974
22.6%

Length

2024-05-10T21:55:04.779875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
파주시 2604
29.9%
고양시 727
 
8.3%
성남시 705
 
8.1%
수원시 568
 
6.5%
용인시 534
 
6.1%
화성시 367
 
4.2%
부천시 352
 
4.0%
안산시 350
 
4.0%
안양시 302
 
3.5%
남양주시 240
 
2.8%
Other values (20) 1974
22.6%

시설구분
Text

Distinct69
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size68.3 KiB
2024-05-10T21:55:05.270274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length8.7195919
Min length2

Characters and Unicode

Total characters76061
Distinct characters105
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)0.1%

Sample

1st row건축물(둘 이상 용도에 사용)
2nd row건축물(둘 이상 용도에 사용)
3rd row건축물(둘 이상 용도에 사용)
4th row노인요양시설
5th row노인요양시설
ValueCountFrequency (%)
이상 2323
14.6%
연면적 2320
14.6%
2천제곱미터 2274
14.3%
복합용도 2274
14.3%
실내주차장 2049
12.9%
어린이집 958
6.0%
노인요양시설 695
 
4.4%
의료기관 577
 
3.6%
대규모점포 299
 
1.9%
보육시설 200
 
1.3%
Other values (67) 1953
12.3%
2024-05-10T21:55:06.194608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7199
 
9.5%
이 3474
 
4.6%
터 3040
 
4.0%
제 2660
 
3.5%
상 2467
 
3.2%
도 2412
 
3.2%
장 2386
 
3.1%
미 2339
 
3.1%
면 2320
 
3.1%
연 2320
 
3.1%
Other values (95) 45444
59.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66186
87.0%
Space Separator 7199
 
9.5%
Decimal Number 2320
 
3.1%
Uppercase Letter 140
 
0.2%
Close Punctuation 99
 
0.1%
Open Punctuation 99
 
0.1%
Lowercase Letter 18
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 3474
 
5.2%
터 3040
 
4.6%
제 2660
 
4.0%
상 2467
 
3.7%
도 2412
 
3.6%
장 2386
 
3.6%
미 2339
 
3.5%
면 2320
 
3.5%
연 2320
 
3.5%
곱 2320
 
3.5%
Other values (86) 40448
61.1%
Decimal Number
ValueCountFrequency (%)
2 2274
98.0%
3 46
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
P 70
50.0%
C 70
50.0%
Lowercase Letter
ValueCountFrequency (%)
c 9
50.0%
p 9
50.0%
Space Separator
ValueCountFrequency (%)
7199
100.0%
Close Punctuation
ValueCountFrequency (%)
) 99
100.0%
Open Punctuation
ValueCountFrequency (%)
( 99
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66186
87.0%
Common 9717
 
12.8%
Latin 158
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 3474
 
5.2%
터 3040
 
4.6%
제 2660
 
4.0%
상 2467
 
3.7%
도 2412
 
3.6%
장 2386
 
3.6%
미 2339
 
3.5%
면 2320
 
3.5%
연 2320
 
3.5%
곱 2320
 
3.5%
Other values (86) 40448
61.1%
Common
ValueCountFrequency (%)
7199
74.1%
2 2274
 
23.4%
) 99
 
1.0%
( 99
 
1.0%
3 46
 
0.5%
Latin
ValueCountFrequency (%)
P 70
44.3%
C 70
44.3%
c 9
 
5.7%
p 9
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66186
87.0%
ASCII 9875
 
13.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7199
72.9%
2 2274
 
23.0%
) 99
 
1.0%
( 99
 
1.0%
P 70
 
0.7%
C 70
 
0.7%
3 46
 
0.5%
c 9
 
0.1%
p 9
 
0.1%
Hangul
ValueCountFrequency (%)
이 3474
 
5.2%
터 3040
 
4.6%
제 2660
 
4.0%
상 2467
 
3.7%
도 2412
 
3.6%
장 2386
 
3.6%
미 2339
 
3.5%
면 2320
 
3.5%
연 2320
 
3.5%
곱 2320
 
3.5%
Other values (86) 40448
61.1%

시설명
Text

Distinct7993
Distinct (%)91.6%
Missing0
Missing (%)0.0%
Memory size68.3 KiB
2024-05-10T21:55:06.783646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length44
Mean length10.186862
Min length1

Characters and Unicode

Total characters88860
Distinct characters836
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7452 ?
Unique (%)85.4%

Sample

1st row가평군자원순환센터
2nd row가평잣고을시장 창업경제타운
3rd row산림생태문화체험단지
4th row가평산속요양병원
5th row평화의집 노인요양원
ValueCountFrequency (%)
공장 571
 
3.9%
pc 96
 
0.7%
탄현면 91
 
0.6%
문산읍 83
 
0.6%
pc방 73
 
0.5%
광탄면 73
 
0.5%
파주읍 71
 
0.5%
제1종근린생활시설 69
 
0.5%
창고시설 69
 
0.5%
월롱면 62
 
0.4%
Other values (9249) 13351
91.4%
2024-05-10T21:55:07.871708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5905
 
6.6%
이 2370
 
2.7%
원 2084
 
2.3%
) 1815
 
2.0%
( 1811
 
2.0%
리 1707
 
1.9%
주 1601
 
1.8%
어 1529
 
1.7%
스 1521
 
1.7%
린 1494
 
1.7%
Other values (826) 67023
75.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 70993
79.9%
Space Separator 5905
 
6.6%
Decimal Number 4418
 
5.0%
Uppercase Letter 2504
 
2.8%
Close Punctuation 1816
 
2.0%
Open Punctuation 1812
 
2.0%
Dash Punctuation 719
 
0.8%
Lowercase Letter 379
 
0.4%
Other Punctuation 197
 
0.2%
Other Symbol 73
 
0.1%
Other values (3) 44
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 2370
 
3.3%
원 2084
 
2.9%
리 1707
 
2.4%
주 1601
 
2.3%
어 1529
 
2.2%
스 1521
 
2.1%
린 1494
 
2.1%
장 1366
 
1.9%
집 1299
 
1.8%
공 1251
 
1.8%
Other values (738) 54771
77.1%
Uppercase Letter
ValueCountFrequency (%)
C 572
22.8%
P 474
18.9%
A 147
 
5.9%
S 125
 
5.0%
G 105
 
4.2%
I 102
 
4.1%
E 99
 
4.0%
B 87
 
3.5%
T 87
 
3.5%
K 83
 
3.3%
Other values (16) 623
24.9%
Lowercase Letter
ValueCountFrequency (%)
e 47
12.4%
p 45
11.9%
c 43
11.3%
a 31
 
8.2%
o 26
 
6.9%
n 21
 
5.5%
r 20
 
5.3%
l 17
 
4.5%
s 15
 
4.0%
k 15
 
4.0%
Other values (15) 99
26.1%
Other Punctuation
ValueCountFrequency (%)
. 83
42.1%
, 41
20.8%
& 26
 
13.2%
: 18
 
9.1%
? 10
 
5.1%
/ 7
 
3.6%
" 4
 
2.0%
' 4
 
2.0%
· 2
 
1.0%
% 1
 
0.5%
Decimal Number
ValueCountFrequency (%)
1 958
21.7%
2 699
15.8%
3 525
11.9%
4 399
9.0%
0 383
 
8.7%
5 344
 
7.8%
7 293
 
6.6%
8 292
 
6.6%
6 277
 
6.3%
9 248
 
5.6%
Letter Number
ValueCountFrequency (%)
Ⅱ 15
51.7%
Ⅲ 6
 
20.7%
Ⅰ 6
 
20.7%
Ⅸ 1
 
3.4%
ⅱ 1
 
3.4%
Math Symbol
ValueCountFrequency (%)
~ 8
66.7%
+ 3
 
25.0%
> 1
 
8.3%
Close Punctuation
ValueCountFrequency (%)
) 1815
99.9%
] 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 1811
99.9%
[ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
5905
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 719
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 73
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 71066
80.0%
Common 14882
 
16.7%
Latin 2912
 
3.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 2370
 
3.3%
원 2084
 
2.9%
리 1707
 
2.4%
주 1601
 
2.3%
어 1529
 
2.2%
스 1521
 
2.1%
린 1494
 
2.1%
장 1366
 
1.9%
집 1299
 
1.8%
공 1251
 
1.8%
Other values (739) 54844
77.2%
Latin
ValueCountFrequency (%)
C 572
19.6%
P 474
16.3%
A 147
 
5.0%
S 125
 
4.3%
G 105
 
3.6%
I 102
 
3.5%
E 99
 
3.4%
B 87
 
3.0%
T 87
 
3.0%
K 83
 
2.9%
Other values (46) 1031
35.4%
Common
ValueCountFrequency (%)
5905
39.7%
) 1815
 
12.2%
( 1811
 
12.2%
1 958
 
6.4%
- 719
 
4.8%
2 699
 
4.7%
3 525
 
3.5%
4 399
 
2.7%
0 383
 
2.6%
5 344
 
2.3%
Other values (21) 1324
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 70993
79.9%
ASCII 17763
 
20.0%
None 75
 
0.1%
Number Forms 29
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5905
33.2%
) 1815
 
10.2%
( 1811
 
10.2%
1 958
 
5.4%
- 719
 
4.0%
2 699
 
3.9%
C 572
 
3.2%
3 525
 
3.0%
P 474
 
2.7%
4 399
 
2.2%
Other values (71) 3886
21.9%
Hangul
ValueCountFrequency (%)
이 2370
 
3.3%
원 2084
 
2.9%
리 1707
 
2.4%
주 1601
 
2.3%
어 1529
 
2.2%
스 1521
 
2.1%
린 1494
 
2.1%
장 1366
 
1.9%
집 1299
 
1.8%
공 1251
 
1.8%
Other values (738) 54771
77.1%
None
ValueCountFrequency (%)
㈜ 73
97.3%
· 2
 
2.7%
Number Forms
ValueCountFrequency (%)
Ⅱ 15
51.7%
Ⅲ 6
 
20.7%
Ⅰ 6
 
20.7%
Ⅸ 1
 
3.4%
ⅱ 1
 
3.4%

소재지도로명주소
Text

MISSING 

Distinct1222
Distinct (%)88.7%
Missing7345
Missing (%)84.2%
Memory size68.3 KiB
2024-05-10T21:55:08.498031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length72
Median length52
Mean length24.553701
Min length14

Characters and Unicode

Total characters33835
Distinct characters292
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1097 ?
Unique (%)79.6%

Sample

1st row경기도 광명시 소하로 86, 5층 (소하동, 제일프라자)
2nd row경기도 광명시 오리로 613 (하안동)
3rd row경기도 광명시 오리로381번길 3 (소하동)
4th row경기도 광명시 도덕로54번길 10 (광명동)
5th row경기도 광명시 소하로109번길 12 (소하동)
ValueCountFrequency (%)
경기도 1378
 
18.4%
성남시 705
 
9.4%
수원시 550
 
7.3%
분당구 481
 
6.4%
영통구 164
 
2.2%
권선구 161
 
2.1%
팔달구 140
 
1.9%
수정구 130
 
1.7%
광명시 124
 
1.7%
중원구 94
 
1.3%
Other values (1416) 3578
47.7%
2024-05-10T21:55:09.592091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6130
 
18.1%
경 1431
 
4.2%
도 1398
 
4.1%
기 1394
 
4.1%
시 1388
 
4.1%
로 1382
 
4.1%
구 1283
 
3.8%
1 1047
 
3.1%
성 856
 
2.5%
수 825
 
2.4%
Other values (282) 16701
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20719
61.2%
Space Separator 6130
 
18.1%
Decimal Number 5321
 
15.7%
Open Punctuation 619
 
1.8%
Close Punctuation 619
 
1.8%
Other Punctuation 244
 
0.7%
Dash Punctuation 118
 
0.3%
Math Symbol 39
 
0.1%
Uppercase Letter 15
 
< 0.1%
Lowercase Letter 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 1431
 
6.9%
도 1398
 
6.7%
기 1394
 
6.7%
시 1388
 
6.7%
로 1382
 
6.7%
구 1283
 
6.2%
성 856
 
4.1%
수 825
 
4.0%
남 810
 
3.9%
원 775
 
3.7%
Other values (249) 9177
44.3%
Decimal Number
ValueCountFrequency (%)
1 1047
19.7%
2 755
14.2%
3 561
10.5%
5 514
9.7%
0 505
9.5%
4 453
8.5%
6 444
8.3%
7 362
 
6.8%
9 344
 
6.5%
8 336
 
6.3%
Uppercase Letter
ValueCountFrequency (%)
A 3
20.0%
K 3
20.0%
B 3
20.0%
P 2
13.3%
L 1
 
6.7%
D 1
 
6.7%
S 1
 
6.7%
U 1
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
a 4
40.0%
z 2
20.0%
l 2
20.0%
w 1
 
10.0%
e 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 241
98.8%
· 2
 
0.8%
. 1
 
0.4%
Math Symbol
ValueCountFrequency (%)
~ 37
94.9%
∼ 2
 
5.1%
Space Separator
ValueCountFrequency (%)
6130
100.0%
Open Punctuation
ValueCountFrequency (%)
( 619
100.0%
Close Punctuation
ValueCountFrequency (%)
) 619
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 118
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20719
61.2%
Common 13090
38.7%
Latin 26
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 1431
 
6.9%
도 1398
 
6.7%
기 1394
 
6.7%
시 1388
 
6.7%
로 1382
 
6.7%
구 1283
 
6.2%
성 856
 
4.1%
수 825
 
4.0%
남 810
 
3.9%
원 775
 
3.7%
Other values (249) 9177
44.3%
Common
ValueCountFrequency (%)
6130
46.8%
1 1047
 
8.0%
2 755
 
5.8%
( 619
 
4.7%
) 619
 
4.7%
3 561
 
4.3%
5 514
 
3.9%
0 505
 
3.9%
4 453
 
3.5%
6 444
 
3.4%
Other values (9) 1443
 
11.0%
Latin
ValueCountFrequency (%)
a 4
15.4%
A 3
11.5%
K 3
11.5%
B 3
11.5%
z 2
7.7%
l 2
7.7%
P 2
7.7%
Ⅱ 1
 
3.8%
L 1
 
3.8%
D 1
 
3.8%
Other values (4) 4
15.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20719
61.2%
ASCII 13111
38.7%
Math Operators 2
 
< 0.1%
None 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6130
46.8%
1 1047
 
8.0%
2 755
 
5.8%
( 619
 
4.7%
) 619
 
4.7%
3 561
 
4.3%
5 514
 
3.9%
0 505
 
3.9%
4 453
 
3.5%
6 444
 
3.4%
Other values (20) 1464
 
11.2%
Hangul
ValueCountFrequency (%)
경 1431
 
6.9%
도 1398
 
6.7%
기 1394
 
6.7%
시 1388
 
6.7%
로 1382
 
6.7%
구 1283
 
6.2%
성 856
 
4.1%
수 825
 
4.0%
남 810
 
3.9%
원 775
 
3.7%
Other values (249) 9177
44.3%
Math Operators
ValueCountFrequency (%)
∼ 2
100.0%
None
ValueCountFrequency (%)
· 2
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

소재지지번주소
Text

MISSING 

Distinct714
Distinct (%)84.5%
Missing7878
Missing (%)90.3%
Memory size68.3 KiB
2024-05-10T21:55:10.097857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length41
Mean length20.04142
Min length14

Characters and Unicode

Total characters16935
Distinct characters172
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique603 ?
Unique (%)71.4%

Sample

1st row경기도 김포시 풍무동740번지 장릉마을 상가동 201 202호
2nd row경기도 김포시 통진읍 도사리406번지
3rd row경기도 김포시 월곶면 고막리376-4번지
4th row경기도 김포시 양촌읍 석모리376-1번지
5th row경기도 김포시 대곶면 대능리172-2번지
ValueCountFrequency (%)
경기도 845
20.7%
성남시 705
17.3%
분당구 463
 
11.3%
김포시 121
 
3.0%
수정구 121
 
3.0%
중원구 92
 
2.3%
서현동 79
 
1.9%
삼평동 77
 
1.9%
정자동 75
 
1.8%
야탑동 64
 
1.6%
Other values (780) 1439
35.3%
2024-05-10T21:55:11.023575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3236
19.1%
기 859
 
5.1%
도 854
 
5.0%
시 853
 
5.0%
경 846
 
5.0%
동 830
 
4.9%
구 753
 
4.4%
성 734
 
4.3%
남 723
 
4.3%
1 580
 
3.4%
Other values (162) 6667
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10233
60.4%
Space Separator 3236
 
19.1%
Decimal Number 3020
 
17.8%
Dash Punctuation 431
 
2.5%
Close Punctuation 7
 
< 0.1%
Open Punctuation 7
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 859
 
8.4%
도 854
 
8.3%
시 853
 
8.3%
경 846
 
8.3%
동 830
 
8.1%
구 753
 
7.4%
성 734
 
7.2%
남 723
 
7.1%
분 469
 
4.6%
당 469
 
4.6%
Other values (147) 2843
27.8%
Decimal Number
ValueCountFrequency (%)
1 580
19.2%
2 435
14.4%
6 357
11.8%
3 313
10.4%
5 310
10.3%
4 267
8.8%
9 212
 
7.0%
0 186
 
6.2%
8 184
 
6.1%
7 176
 
5.8%
Space Separator
ValueCountFrequency (%)
3236
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 431
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
E 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10233
60.4%
Common 6701
39.6%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 859
 
8.4%
도 854
 
8.3%
시 853
 
8.3%
경 846
 
8.3%
동 830
 
8.1%
구 753
 
7.4%
성 734
 
7.2%
남 723
 
7.1%
분 469
 
4.6%
당 469
 
4.6%
Other values (147) 2843
27.8%
Common
ValueCountFrequency (%)
3236
48.3%
1 580
 
8.7%
2 435
 
6.5%
- 431
 
6.4%
6 357
 
5.3%
3 313
 
4.7%
5 310
 
4.6%
4 267
 
4.0%
9 212
 
3.2%
0 186
 
2.8%
Other values (4) 374
 
5.6%
Latin
ValueCountFrequency (%)
E 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10233
60.4%
ASCII 6702
39.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3236
48.3%
1 580
 
8.7%
2 435
 
6.5%
- 431
 
6.4%
6 357
 
5.3%
3 313
 
4.7%
5 310
 
4.6%
4 267
 
4.0%
9 212
 
3.2%
0 186
 
2.8%
Other values (5) 375
 
5.6%
Hangul
ValueCountFrequency (%)
기 859
 
8.4%
도 854
 
8.3%
시 853
 
8.3%
경 846
 
8.3%
동 830
 
8.1%
구 753
 
7.4%
성 734
 
7.2%
남 723
 
7.1%
분 469
 
4.6%
당 469
 
4.6%
Other values (147) 2843
27.8%

전화번호
Text

MISSING 

Distinct1888
Distinct (%)92.7%
Missing6686
Missing (%)76.6%
Memory size68.3 KiB
2024-05-10T21:55:11.608590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.055965
Min length9

Characters and Unicode

Total characters24558
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

Unique1803 ?
Unique (%)88.5%

Sample

1st row02-502-2093
2nd row02-3679-1403
3rd row02-509-5118
4th row02-503-5101
5th row02-3677-0374
ValueCountFrequency (%)
000-0000-0000 18
 
0.9%
000-000-0000 14
 
0.7%
032-340-0923 13
 
0.6%
031-357-6548 6
 
0.3%
032-620-3535 5
 
0.2%
031-390-7685 5
 
0.2%
031-828-6842 4
 
0.2%
031-000-0000 4
 
0.2%
031-550-3769 4
 
0.2%
032-344-8900 3
 
0.1%
Other values (1878) 1961
96.3%
2024-05-10T21:55:12.514417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4188
17.1%
- 4057
16.5%
3 3499
14.2%
1 2820
11.5%
2 1727
7.0%
8 1640
 
6.7%
7 1525
 
6.2%
5 1498
 
6.1%
6 1419
 
5.8%
9 1138
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20501
83.5%
Dash Punctuation 4057
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4188
20.4%
3 3499
17.1%
1 2820
13.8%
2 1727
8.4%
8 1640
 
8.0%
7 1525
 
7.4%
5 1498
 
7.3%
6 1419
 
6.9%
9 1138
 
5.6%
4 1047
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 4057
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24558
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4188
17.1%
- 4057
16.5%
3 3499
14.2%
1 2820
11.5%
2 1727
7.0%
8 1640
 
6.7%
7 1525
 
6.2%
5 1498
 
6.1%
6 1419
 
5.8%
9 1138
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24558
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4188
17.1%
- 4057
16.5%
3 3499
14.2%
1 2820
11.5%
2 1727
7.0%
8 1640
 
6.7%
7 1525
 
6.2%
5 1498
 
6.1%
6 1419
 
5.8%
9 1138
 
4.6%

연면적
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED 

Distinct4981
Distinct (%)84.7%
Missing2844
Missing (%)32.6%
Infinite0
Infinite (%)0.0%
Mean10934.632
Minimum2.332
Maximum10871952
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size76.8 KiB
2024-05-10T21:55:12.891602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.332
5-th percentile460
Q11568
median2969.55
Q35888.115
95-th percentile25090.898
Maximum10871952
Range10871950
Interquartile range (IQR)4320.115

Descriptive statistics

Standard deviation177484.44
Coefficient of variation (CV)16.231405
Kurtosis3043.0537
Mean10934.632
Median Absolute Deviation (MAD)1892.45
Skewness53.924583
Sum64284701
Variance3.1500725 × 1010
MonotonicityNot monotonic
2024-05-10T21:55:13.311230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8422.15 10
 
0.1%
5464.15 10
 
0.1%
495.0 9
 
0.1%
480.0 9
 
0.1%
18585.64 8
 
0.1%
16337.1 8
 
0.1%
5628.29 8
 
0.1%
15054.94 7
 
0.1%
11781.23 7
 
0.1%
491.0 7
 
0.1%
Other values (4971) 5796
66.4%
(Missing) 2844
32.6%
ValueCountFrequency (%)
2.332 1
< 0.1%
7.885 1
< 0.1%
14.109 1
< 0.1%
27.0 1
< 0.1%
28.052 1
< 0.1%
29.6 1
< 0.1%
30.69 1
< 0.1%
46.489 1
< 0.1%
71.07 1
< 0.1%
81.891 1
< 0.1%
ValueCountFrequency (%)
10871952.0 1
< 0.1%
7878092.0 1
< 0.1%
996959.4 1
< 0.1%
996778.22 1
< 0.1%
990941.38 1
< 0.1%
544245.0 1
< 0.1%
506333.0 1
< 0.1%
459518.0 1
< 0.1%
331555.0 1
< 0.1%
302715.0 1
< 0.1%

객석수또는관람석수또는병상수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct53
Distinct (%)65.4%
Missing8642
Missing (%)99.1%
Infinite0
Infinite (%)0.0%
Mean261.30864
Minimum6
Maximum1890
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size76.8 KiB
2024-05-10T21:55:13.792327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile20
Q186
median122
Q3250
95-th percentile1200
Maximum1890
Range1884
Interquartile range (IQR)164

Descriptive statistics

Standard deviation364.57597
Coefficient of variation (CV)1.3951929
Kurtosis7.3761753
Mean261.30864
Median Absolute Deviation (MAD)78
Skewness2.7361987
Sum21166
Variance132915.64
MonotonicityNot monotonic
2024-05-10T21:55:14.145260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200 7
 
0.1%
90 4
 
< 0.1%
100 3
 
< 0.1%
110 3
 
< 0.1%
120 3
 
< 0.1%
10 3
 
< 0.1%
300 2
 
< 0.1%
99 2
 
< 0.1%
320 2
 
< 0.1%
250 2
 
< 0.1%
Other values (43) 50
 
0.6%
(Missing) 8642
99.1%
ValueCountFrequency (%)
6 1
 
< 0.1%
10 3
< 0.1%
20 2
< 0.1%
21 1
 
< 0.1%
30 1
 
< 0.1%
40 2
< 0.1%
50 1
 
< 0.1%
53 1
 
< 0.1%
60 1
 
< 0.1%
67 1
 
< 0.1%
ValueCountFrequency (%)
1890 1
< 0.1%
1500 1
< 0.1%
1360 1
< 0.1%
1331 1
< 0.1%
1200 1
< 0.1%
1057 1
< 0.1%
1000 1
< 0.1%
728 1
< 0.1%
600 1
< 0.1%
406 1
< 0.1%

위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct897
Distinct (%)84.9%
Missing7666
Missing (%)87.9%
Infinite0
Infinite (%)0.0%
Mean37.399212
Minimum37.23738
Maximum37.725703
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size76.8 KiB
2024-05-10T21:55:14.486277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.23738
5-th percentile37.259674
Q137.344386
median37.388203
Q337.439999
95-th percentile37.637689
Maximum37.725703
Range0.48832367
Interquartile range (IQR)0.09561358

Descriptive statistics

Standard deviation0.1052573
Coefficient of variation (CV)0.0028144255
Kurtosis0.81371071
Mean37.399212
Median Absolute Deviation (MAD)0.04923865
Skewness0.96070873
Sum39530.968
Variance0.011079099
MonotonicityNot monotonic
2024-05-10T21:55:14.931318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.34161305 6
 
0.1%
37.41309076 5
 
0.1%
37.39541952 4
 
< 0.1%
37.40396781 3
 
< 0.1%
37.39279354 3
 
< 0.1%
37.37657408 3
 
< 0.1%
37.37844712 3
 
< 0.1%
37.36133939 3
 
< 0.1%
37.2545155 3
 
< 0.1%
37.37683887 3
 
< 0.1%
Other values (887) 1021
 
11.7%
(Missing) 7666
87.9%
ValueCountFrequency (%)
37.2373796 1
< 0.1%
37.2377132 1
< 0.1%
37.2386317 1
< 0.1%
37.2388762 1
< 0.1%
37.2389238 1
< 0.1%
37.2394628 1
< 0.1%
37.242116 1
< 0.1%
37.2450627 1
< 0.1%
37.2452411 2
< 0.1%
37.2459534 1
< 0.1%
ValueCountFrequency (%)
37.72570327 1
< 0.1%
37.72410641 1
< 0.1%
37.72194821 1
< 0.1%
37.71932311 1
< 0.1%
37.70053322 1
< 0.1%
37.69492592 1
< 0.1%
37.69395769 1
< 0.1%
37.6909247 1
< 0.1%
37.6896714 1
< 0.1%
37.68944096 1
< 0.1%

경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct898
Distinct (%)85.0%
Missing7666
Missing (%)87.9%
Infinite0
Infinite (%)0.0%
Mean127.0557
Minimum126.54061
Maximum127.17863
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size76.8 KiB
2024-05-10T21:55:15.346304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.54061
5-th percentile126.68214
Q1127.04455
median127.11038
Q3127.12821
95-th percentile127.15945
Maximum127.17863
Range0.6380257
Interquartile range (IQR)0.0836541

Descriptive statistics

Standard deviation0.14204455
Coefficient of variation (CV)0.0011179707
Kurtosis3.3674983
Mean127.0557
Median Absolute Deviation (MAD)0.0290633
Skewness-2.1474508
Sum134297.87
Variance0.020176654
MonotonicityNot monotonic
2024-05-10T21:55:15.808401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1066901 6
 
0.1%
127.127282 5
 
0.1%
127.1135557 4
 
< 0.1%
127.1347209 3
 
< 0.1%
127.1120882 3
 
< 0.1%
127.113175 3
 
< 0.1%
127.1143159 3
 
< 0.1%
127.1055439 3
 
< 0.1%
127.0734722 3
 
< 0.1%
127.1114005 3
 
< 0.1%
Other values (888) 1021
 
11.7%
(Missing) 7666
87.9%
ValueCountFrequency (%)
126.5406051 1
< 0.1%
126.5534372 1
< 0.1%
126.5686703 1
< 0.1%
126.5829049 1
< 0.1%
126.5871013 1
< 0.1%
126.591493 1
< 0.1%
126.5920293 1
< 0.1%
126.5921725 1
< 0.1%
126.5976082 1
< 0.1%
126.5978515 1
< 0.1%
ValueCountFrequency (%)
127.1786308 1
< 0.1%
127.1784657 1
< 0.1%
127.1784141 1
< 0.1%
127.1780378 1
< 0.1%
127.1775591 1
< 0.1%
127.1774439 1
< 0.1%
127.1764589 1
< 0.1%
127.1764229 1
< 0.1%
127.1751335 1
< 0.1%
127.1745282 1
< 0.1%

데이터기준일자
Date

Distinct25
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size68.3 KiB
Minimum2020-02-24 00:00:00
Maximum2024-04-30 00:00:00
2024-05-10T21:55:16.198328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:55:16.529513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)

Interactions

2024-05-10T21:55:02.037155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:54:58.874854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:54:59.924485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:55:00.961123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:55:02.309021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:54:59.153059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:55:00.171079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:55:01.243568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:55:02.568542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:54:59.418770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:55:00.452436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:55:01.510800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:55:02.833268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:54:59.697227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:55:00.732398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:55:01.751866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-10T21:55:16.746856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명시설구분연면적객석수또는관람석수또는병상수위도경도데이터기준일자
시군명1.0000.8400.0000.2841.0000.9221.000
시설구분0.8401.0000.0000.7640.5050.3350.832
연면적0.0000.0001.000NaNNaNNaN0.000
객석수또는관람석수또는병상수0.2840.764NaN1.000NaNNaN0.284
위도1.0000.505NaNNaN1.0000.9451.000
경도0.9220.335NaNNaN0.9451.0000.922
데이터기준일자1.0000.8320.0000.2841.0000.9221.000
2024-05-10T21:55:17.026227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연면적객석수또는관람석수또는병상수위도경도시군명
연면적1.0000.576-0.1760.2090.000
객석수또는관람석수또는병상수0.5761.000NaNNaN0.171
위도-0.176NaN1.0000.2860.998
경도0.209NaN0.2861.0000.917
시군명0.0000.1710.9980.9171.000

Missing values

2024-05-10T21:55:03.275932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-10T21:55:03.782129image/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.
2024-05-10T21:55:04.169441image/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

시군명시설구분시설명소재지도로명주소소재지지번주소전화번호연면적객석수또는관람석수또는병상수위도경도데이터기준일자
0가평군건축물(둘 이상 용도에 사용)가평군자원순환센터<NA><NA><NA>7706.43<NA><NA><NA>2023-08-07
1가평군건축물(둘 이상 용도에 사용)가평잣고을시장 창업경제타운<NA><NA><NA>5436.45<NA><NA><NA>2023-08-07
2가평군건축물(둘 이상 용도에 사용)산림생태문화체험단지<NA><NA><NA>4412.79<NA><NA><NA>2023-08-07
3가평군노인요양시설가평산속요양병원<NA><NA><NA>2250.62<NA><NA><NA>2023-08-07
4가평군노인요양시설평화의집 노인요양원<NA><NA><NA>5921.0<NA><NA><NA>2023-08-07
5가평군도서관한석봉도서관<NA><NA><NA>3602.25<NA><NA><NA>2023-08-07
6가평군목욕장업㈜DFD인터내셔널 더스테이힐링파크<NA><NA><NA>1544.99<NA><NA><NA>2023-08-07
7가평군목욕장업민성사우나<NA><NA><NA>1349.48<NA><NA><NA>2023-08-07
8가평군목욕장업에덴스포츠텔 사우나<NA><NA><NA>1187.6<NA><NA><NA>2023-08-07
9가평군목욕장업청평백암천<NA><NA><NA>2210.72<NA><NA><NA>2023-08-07
시군명시설구분시설명소재지도로명주소소재지지번주소전화번호연면적객석수또는관람석수또는병상수위도경도데이터기준일자
8713화성시장례식장원광종합병원 장례식장<NA><NA>031-226-44451653.0<NA><NA><NA>2024-01-01
8714화성시장례식장한림대학교 동탄성심병원 장례식장<NA><NA>031-8003-44102869.0<NA><NA><NA>2024-01-01
8715화성시장례식장현대장례문화원<NA><NA>031-379-60401556.0<NA><NA><NA>2024-01-01
8716화성시장례식장화성유일병원 장례식장<NA><NA>031-355-47441495.0<NA><NA><NA>2024-01-01
8717화성시장례식장효원장례문화센터<NA><NA>031-222-09991930.0<NA><NA><NA>2024-01-01
8718화성시전시시설시립 반석산 에코스쿨<NA><NA>031-8003-60302806.0<NA><NA><NA>2024-01-01
8719화성시지하역사동탄역사<NA><NA>031-234-778848986.0<NA><NA><NA>2024-01-01
8720화성시학원디와이비최선어학원<NA><NA><NA>1305.11<NA><NA><NA>2024-01-01
8721화성시학원아는공부학원<NA><NA><NA>4513.54<NA><NA><NA>2024-01-01
8722화성시학원폴리어학원<NA><NA>031-8003-76591478.61<NA><NA><NA>2024-01-01

Duplicate rows

Most frequently occurring

시군명시설구분시설명소재지도로명주소소재지지번주소전화번호연면적객석수또는관람석수또는병상수위도경도데이터기준일자# duplicates
36파주시연면적 2천제곱미터 이상 복합용도삼성메디컬프라자<NA><NA><NA>11781.23<NA><NA><NA>2024-03-046
75파주시연면적 2천제곱미터 이상 복합용도트리플메디칼타워<NA><NA><NA>12981.78<NA><NA><NA>2024-03-046
13파주시연면적 2천제곱미터 이상 복합용도교하일번가<NA><NA><NA>15054.94<NA><NA><NA>2024-03-045
41파주시연면적 2천제곱미터 이상 복합용도센타프라자1<NA><NA><NA>16337.1<NA><NA><NA>2024-03-045
63파주시연면적 2천제곱미터 이상 복합용도월드타워<NA><NA><NA>5628.29<NA><NA><NA>2024-03-045
69파주시연면적 2천제곱미터 이상 복합용도제일메디컬<NA><NA><NA>5464.15<NA><NA><NA>2024-03-045
18파주시연면적 2천제곱미터 이상 복합용도금촌프라자<NA><NA><NA>6039.09<NA><NA><NA>2024-03-044
49파주시연면적 2천제곱미터 이상 복합용도야당동 1070 제1종근린생활시설 (주식회사운정명동)<NA><NA><NA>18585.64<NA><NA><NA>2024-03-044
58파주시연면적 2천제곱미터 이상 복합용도우평프라자<NA><NA><NA>7426.89<NA><NA><NA>2024-03-044
15파주시연면적 2천제곱미터 이상 복합용도금촌동 255-4 노유자시설 (유정규)<NA><NA><NA>2718.76<NA><NA><NA>2024-03-043