Overview

Dataset statistics

Number of variables20
Number of observations2665
Missing cells18535
Missing cells (%)34.8%
Duplicate rows4
Duplicate rows (%)0.2%
Total size in memory440.0 KiB
Average record size in memory169.0 B

Variable types

Categorical5
Text6
DateTime1
Unsupported2
Numeric6

Dataset

Description민방위 급수시설 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=6GSKP6LCB432QZG42845911150&infSeq=1

Alerts

Dataset has 4 (0.2%) duplicate rowsDuplicates
영업상태명 is highly overall correlated with 인허가취소일자 and 1 other fieldsHigh correlation
영업상태구분코드 is highly overall correlated with 소재지우편번호 and 3 other fieldsHigh correlation
인허가취소일자 is highly overall correlated with 소재지우편번호 and 8 other fieldsHigh correlation
소재지우편번호 is highly overall correlated with WGS84위도 and 4 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 3 other fieldsHigh correlation
WGS84경도 is highly overall correlated with X좌표값 and 2 other fieldsHigh correlation
X좌표값 is highly overall correlated with WGS84경도 and 2 other fieldsHigh correlation
Y좌표값 is highly overall correlated with 소재지우편번호 and 3 other fieldsHigh correlation
시군명 is highly overall correlated with 소재지우편번호 and 6 other fieldsHigh correlation
시설구분명 is highly overall correlated with 인허가취소일자High correlation
인허가취소일자 is highly imbalanced (94.6%)Imbalance
소재지시설전화번호 has 2665 (100.0%) missing valuesMissing
소재지면적정보(㎡) has 1928 (72.3%) missing valuesMissing
도로명우편번호 has 2048 (76.8%) missing valuesMissing
소재지도로명주소 has 515 (19.3%) missing valuesMissing
소재지우편번호 has 265 (9.9%) missing valuesMissing
WGS84위도 has 336 (12.6%) missing valuesMissing
WGS84경도 has 336 (12.6%) missing valuesMissing
업태구분명정보 has 2665 (100.0%) missing valuesMissing
X좌표값 has 1960 (73.5%) missing valuesMissing
Y좌표값 has 1960 (73.5%) missing valuesMissing
비상시설위치 has 1928 (72.3%) missing valuesMissing
시설명건물명정보 has 1928 (72.3%) missing valuesMissing
소재지시설전화번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명정보 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 22:33:05.493158
Analysis finished2023-12-10 22:33:10.744886
Duration5.25 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size20.9 KiB
성남시
407 
수원시
282 
부천시
252 
용인시
200 
안산시
 
134
Other values (26)
1390 

Length

Max length4
Median length3
Mean length3.0461538
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
성남시 407
15.3%
수원시 282
 
10.6%
부천시 252
 
9.5%
용인시 200
 
7.5%
안산시 134
 
5.0%
고양시 127
 
4.8%
파주시 124
 
4.7%
화성시 123
 
4.6%
시흥시 105
 
3.9%
안양시 89
 
3.3%
Other values (21) 822
30.8%

Length

2023-12-11T07:33:10.802431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
성남시 407
15.3%
수원시 282
 
10.6%
부천시 252
 
9.5%
용인시 200
 
7.5%
안산시 134
 
5.0%
고양시 127
 
4.8%
파주시 124
 
4.7%
화성시 123
 
4.6%
시흥시 105
 
3.9%
안양시 89
 
3.3%
Other values (21) 822
30.8%
Distinct2102
Distinct (%)78.9%
Missing0
Missing (%)0.0%
Memory size20.9 KiB
2023-12-11T07:33:11.091553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length25
Mean length9.3223265
Min length2

Characters and Unicode

Total characters24844
Distinct characters594
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

Unique1574 ?
Unique (%)59.1%

Sample

1st row농업기술센터
2nd row프리스틴밸리
3rd row백암천
4th row농업기술센터
5th row조종초등학교
ValueCountFrequency (%)
비상급수시설 179
 
4.5%
민방위 60
 
1.5%
비상급수 45
 
1.1%
주엽동 20
 
0.5%
일산구 20
 
0.5%
민방위비상급수시설 19
 
0.5%
19
 
0.5%
문촌마을 19
 
0.5%
약수터 18
 
0.4%
지하수 14
 
0.3%
Other values (2445) 3589
89.7%
2023-12-11T07:33:11.534657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1345
 
5.4%
( 882
 
3.6%
) 882
 
3.6%
738
 
3.0%
542
 
2.2%
518
 
2.1%
492
 
2.0%
445
 
1.8%
440
 
1.8%
417
 
1.7%
Other values (584) 18143
73.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19987
80.5%
Space Separator 1345
 
5.4%
Decimal Number 1274
 
5.1%
Open Punctuation 882
 
3.6%
Close Punctuation 882
 
3.6%
Dash Punctuation 255
 
1.0%
Uppercase Letter 151
 
0.6%
Other Punctuation 45
 
0.2%
Lowercase Letter 19
 
0.1%
Letter Number 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
738
 
3.7%
542
 
2.7%
518
 
2.6%
492
 
2.5%
445
 
2.2%
440
 
2.2%
417
 
2.1%
414
 
2.1%
414
 
2.1%
367
 
1.8%
Other values (532) 15200
76.0%
Uppercase Letter
ValueCountFrequency (%)
C 45
29.8%
S 22
14.6%
K 20
13.2%
H 9
 
6.0%
T 9
 
6.0%
G 8
 
5.3%
I 6
 
4.0%
L 6
 
4.0%
N 5
 
3.3%
P 3
 
2.0%
Other values (10) 18
 
11.9%
Decimal Number
ValueCountFrequency (%)
1 349
27.4%
2 213
16.7%
3 169
13.3%
6 107
 
8.4%
4 106
 
8.3%
5 90
 
7.1%
8 78
 
6.1%
0 62
 
4.9%
7 60
 
4.7%
9 40
 
3.1%
Other Punctuation
ValueCountFrequency (%)
* 15
33.3%
. 14
31.1%
, 8
17.8%
/ 3
 
6.7%
· 2
 
4.4%
? 1
 
2.2%
& 1
 
2.2%
: 1
 
2.2%
Lowercase Letter
ValueCountFrequency (%)
c 12
63.2%
e 2
 
10.5%
k 1
 
5.3%
s 1
 
5.3%
a 1
 
5.3%
n 1
 
5.3%
d 1
 
5.3%
Letter Number
ValueCountFrequency (%)
2
66.7%
1
33.3%
Space Separator
ValueCountFrequency (%)
1345
100.0%
Open Punctuation
ValueCountFrequency (%)
( 882
100.0%
Close Punctuation
ValueCountFrequency (%)
) 882
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 255
100.0%
Math Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19987
80.5%
Common 4684
 
18.9%
Latin 173
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
738
 
3.7%
542
 
2.7%
518
 
2.6%
492
 
2.5%
445
 
2.2%
440
 
2.2%
417
 
2.1%
414
 
2.1%
414
 
2.1%
367
 
1.8%
Other values (532) 15200
76.0%
Latin
ValueCountFrequency (%)
C 45
26.0%
S 22
12.7%
K 20
11.6%
c 12
 
6.9%
H 9
 
5.2%
T 9
 
5.2%
G 8
 
4.6%
I 6
 
3.5%
L 6
 
3.5%
N 5
 
2.9%
Other values (19) 31
17.9%
Common
ValueCountFrequency (%)
1345
28.7%
( 882
18.8%
) 882
18.8%
1 349
 
7.5%
- 255
 
5.4%
2 213
 
4.5%
3 169
 
3.6%
6 107
 
2.3%
4 106
 
2.3%
5 90
 
1.9%
Other values (13) 286
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19987
80.5%
ASCII 4851
 
19.5%
Number Forms 3
 
< 0.1%
None 2
 
< 0.1%
Arrows 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1345
27.7%
( 882
18.2%
) 882
18.2%
1 349
 
7.2%
- 255
 
5.3%
2 213
 
4.4%
3 169
 
3.5%
6 107
 
2.2%
4 106
 
2.2%
5 90
 
1.9%
Other values (38) 453
 
9.3%
Hangul
ValueCountFrequency (%)
738
 
3.7%
542
 
2.7%
518
 
2.6%
492
 
2.5%
445
 
2.2%
440
 
2.2%
417
 
2.1%
414
 
2.1%
414
 
2.1%
367
 
1.8%
Other values (532) 15200
76.0%
None
ValueCountFrequency (%)
· 2
100.0%
Number Forms
ValueCountFrequency (%)
2
66.7%
1
33.3%
Arrows
ValueCountFrequency (%)
1
100.0%
Distinct923
Distinct (%)34.6%
Missing0
Missing (%)0.0%
Memory size20.9 KiB
Minimum1900-01-01 00:00:00
Maximum2023-09-21 00:00:00
2023-12-11T07:33:11.673166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:11.826077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct32
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size20.9 KiB
<NA>
2599 
2023-11-17
 
17
2023-04-11
 
10
2023-09-07
 
5
2023-07-27
 
3
Other values (27)
 
31

Length

Max length10
Median length4
Mean length4.1485929
Min length4

Unique

Unique23 ?
Unique (%)0.9%

Sample

1st row2023-05-09
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2599
97.5%
2023-11-17 17
 
0.6%
2023-04-11 10
 
0.4%
2023-09-07 5
 
0.2%
2023-07-27 3
 
0.1%
2023-09-12 2
 
0.1%
2023-05-24 2
 
0.1%
2023-09-08 2
 
0.1%
2021-09-08 2
 
0.1%
2021-08-06 1
 
< 0.1%
Other values (22) 22
 
0.8%

Length

2023-12-11T07:33:11.988942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2599
97.5%
2023-11-17 17
 
0.6%
2023-04-11 10
 
0.4%
2023-09-07 5
 
0.2%
2023-07-27 3
 
0.1%
2023-09-12 2
 
0.1%
2023-05-24 2
 
0.1%
2023-09-08 2
 
0.1%
2021-09-08 2
 
0.1%
2023-11-13 1
 
< 0.1%
Other values (22) 22
 
0.8%

영업상태구분코드
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.9 KiB
<NA>
1928 
18
671 
19
 
66

Length

Max length4
Median length4
Mean length3.4469043
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row19
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1928
72.3%
18 671
 
25.2%
19 66
 
2.5%

Length

2023-12-11T07:33:12.121500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:33:12.231738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1928
72.3%
18 671
 
25.2%
19 66
 
2.5%

영업상태명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size20.9 KiB
운영중
1224 
폐업 등
704 
사용중
671 
사용중지
 
66

Length

Max length4
Median length3
Mean length3.2889306
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row사용중지
2nd row운영중
3rd row운영중
4th row운영중
5th row운영중

Common Values

ValueCountFrequency (%)
운영중 1224
45.9%
폐업 등 704
26.4%
사용중 671
25.2%
사용중지 66
 
2.5%

Length

2023-12-11T07:33:12.333918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:33:12.438252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영중 1224
36.3%
폐업 704
20.9%
704
20.9%
사용중 671
19.9%
사용중지 66
 
2.0%

소재지시설전화번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2665
Missing (%)100.0%
Memory size23.6 KiB

소재지면적정보(㎡)
Real number (ℝ)

MISSING 

Distinct210
Distinct (%)28.5%
Missing1928
Missing (%)72.3%
Infinite0
Infinite (%)0.0%
Mean221.07341
Minimum10
Maximum8500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.6 KiB
2023-12-11T07:33:12.565464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile36.8
Q187
median120
Q3200
95-th percentile542.8
Maximum8500
Range8490
Interquartile range (IQR)113

Descriptive statistics

Standard deviation458.09089
Coefficient of variation (CV)2.0721212
Kurtosis160.95692
Mean221.07341
Median Absolute Deviation (MAD)53
Skewness10.711942
Sum162931.1
Variance209847.27
MonotonicityNot monotonic
2023-12-11T07:33:12.704927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 87
 
3.3%
200.0 46
 
1.7%
150.0 42
 
1.6%
50.0 29
 
1.1%
60.0 24
 
0.9%
120.0 24
 
0.9%
30.0 18
 
0.7%
80.0 17
 
0.6%
90.0 15
 
0.6%
130.0 15
 
0.6%
Other values (200) 420
 
15.8%
(Missing) 1928
72.3%
ValueCountFrequency (%)
10.0 1
 
< 0.1%
15.0 1
 
< 0.1%
20.0 6
 
0.2%
25.0 1
 
< 0.1%
28.0 2
 
0.1%
29.0 1
 
< 0.1%
30.0 18
0.7%
32.0 1
 
< 0.1%
35.0 5
 
0.2%
36.0 1
 
< 0.1%
ValueCountFrequency (%)
8500.0 1
< 0.1%
4000.0 2
0.1%
2940.0 1
< 0.1%
2633.0 1
< 0.1%
2536.0 1
< 0.1%
2000.0 1
< 0.1%
1935.0 1
< 0.1%
1814.0 1
< 0.1%
1700.0 1
< 0.1%
1560.0 1
< 0.1%

도로명우편번호
Text

MISSING 

Distinct502
Distinct (%)81.4%
Missing2048
Missing (%)76.8%
Memory size20.9 KiB
2023-12-11T07:33:13.037410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.3824959
Min length5

Characters and Unicode

Total characters3321
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

Unique430 ?
Unique (%)69.7%

Sample

1st row12408
2nd row412-480
3rd row10512
4th row10528
5th row10472
ValueCountFrequency (%)
426-819 7
 
1.1%
18255 6
 
1.0%
13105 6
 
1.0%
18279 6
 
1.0%
13103 5
 
0.8%
18545 5
 
0.8%
16803 5
 
0.8%
482-845 3
 
0.5%
13451 3
 
0.5%
13445 3
 
0.5%
Other values (492) 568
92.1%
2023-12-11T07:33:13.497040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 758
22.8%
4 393
11.8%
6 338
10.2%
5 280
 
8.4%
8 272
 
8.2%
3 269
 
8.1%
0 267
 
8.0%
2 261
 
7.9%
7 216
 
6.5%
9 149
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3203
96.4%
Dash Punctuation 118
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 758
23.7%
4 393
12.3%
6 338
10.6%
5 280
 
8.7%
8 272
 
8.5%
3 269
 
8.4%
0 267
 
8.3%
2 261
 
8.1%
7 216
 
6.7%
9 149
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 118
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3321
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 758
22.8%
4 393
11.8%
6 338
10.2%
5 280
 
8.4%
8 272
 
8.2%
3 269
 
8.1%
0 267
 
8.0%
2 261
 
7.9%
7 216
 
6.5%
9 149
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3321
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 758
22.8%
4 393
11.8%
6 338
10.2%
5 280
 
8.4%
8 272
 
8.2%
3 269
 
8.1%
0 267
 
8.0%
2 261
 
7.9%
7 216
 
6.5%
9 149
 
4.5%
Distinct1537
Distinct (%)71.5%
Missing515
Missing (%)19.3%
Memory size20.9 KiB
2023-12-11T07:33:13.923024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length39
Mean length27.097209
Min length14

Characters and Unicode

Total characters58259
Distinct characters482
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

Unique992 ?
Unique (%)46.1%

Sample

1st row경기도 가평군 가평읍 아랫마장길 59 (농업기술센터)
2nd row경기도 가평군 설악면 유명로 1243-199
3rd row경기도 가평군 청평면 경춘로 699 (청평백암천)
4th row경기도 가평군 가평읍 아랫마장길 59
5th row경기도 가평군 조종면 조종새싹로 13-9 (조종초등학교)
ValueCountFrequency (%)
경기도 2150
 
17.4%
성남시 317
 
2.6%
수원시 255
 
2.1%
부천시 211
 
1.7%
용인시 173
 
1.4%
수정구 158
 
1.3%
분당구 101
 
0.8%
파주시 100
 
0.8%
안산시 94
 
0.8%
권선구 86
 
0.7%
Other values (2764) 8712
70.5%
2023-12-11T07:33:14.542745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10237
 
17.6%
2286
 
3.9%
2282
 
3.9%
2276
 
3.9%
2266
 
3.9%
1984
 
3.4%
1792
 
3.1%
( 1637
 
2.8%
) 1637
 
2.8%
1 1511
 
2.6%
Other values (472) 30351
52.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35753
61.4%
Space Separator 10237
 
17.6%
Decimal Number 7743
 
13.3%
Open Punctuation 1637
 
2.8%
Close Punctuation 1637
 
2.8%
Other Punctuation 709
 
1.2%
Dash Punctuation 395
 
0.7%
Uppercase Letter 147
 
0.3%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2286
 
6.4%
2282
 
6.4%
2276
 
6.4%
2266
 
6.3%
1984
 
5.5%
1792
 
5.0%
1087
 
3.0%
883
 
2.5%
681
 
1.9%
671
 
1.9%
Other values (433) 19545
54.7%
Uppercase Letter
ValueCountFrequency (%)
C 38
25.9%
S 14
 
9.5%
K 11
 
7.5%
T 9
 
6.1%
G 8
 
5.4%
H 7
 
4.8%
N 7
 
4.8%
A 7
 
4.8%
L 7
 
4.8%
I 6
 
4.1%
Other values (11) 33
22.4%
Decimal Number
ValueCountFrequency (%)
1 1511
19.5%
2 1093
14.1%
3 861
11.1%
4 677
8.7%
5 674
8.7%
0 617
8.0%
6 599
 
7.7%
8 589
 
7.6%
7 577
 
7.5%
9 545
 
7.0%
Other Punctuation
ValueCountFrequency (%)
, 686
96.8%
. 22
 
3.1%
& 1
 
0.1%
Space Separator
ValueCountFrequency (%)
10237
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1637
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1637
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 395
100.0%
Lowercase Letter
ValueCountFrequency (%)
l 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35753
61.4%
Common 22358
38.4%
Latin 148
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2286
 
6.4%
2282
 
6.4%
2276
 
6.4%
2266
 
6.3%
1984
 
5.5%
1792
 
5.0%
1087
 
3.0%
883
 
2.5%
681
 
1.9%
671
 
1.9%
Other values (433) 19545
54.7%
Latin
ValueCountFrequency (%)
C 38
25.7%
S 14
 
9.5%
K 11
 
7.4%
T 9
 
6.1%
G 8
 
5.4%
H 7
 
4.7%
N 7
 
4.7%
A 7
 
4.7%
L 7
 
4.7%
I 6
 
4.1%
Other values (12) 34
23.0%
Common
ValueCountFrequency (%)
10237
45.8%
( 1637
 
7.3%
) 1637
 
7.3%
1 1511
 
6.8%
2 1093
 
4.9%
3 861
 
3.9%
, 686
 
3.1%
4 677
 
3.0%
5 674
 
3.0%
0 617
 
2.8%
Other values (7) 2728
 
12.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35753
61.4%
ASCII 22506
38.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10237
45.5%
( 1637
 
7.3%
) 1637
 
7.3%
1 1511
 
6.7%
2 1093
 
4.9%
3 861
 
3.8%
, 686
 
3.0%
4 677
 
3.0%
5 674
 
3.0%
0 617
 
2.7%
Other values (29) 2876
 
12.8%
Hangul
ValueCountFrequency (%)
2286
 
6.4%
2282
 
6.4%
2276
 
6.4%
2266
 
6.3%
1984
 
5.5%
1792
 
5.0%
1087
 
3.0%
883
 
2.5%
681
 
1.9%
671
 
1.9%
Other values (433) 19545
54.7%
Distinct1996
Distinct (%)74.9%
Missing1
Missing (%)< 0.1%
Memory size20.9 KiB
2023-12-11T07:33:14.869791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length39
Mean length21.831081
Min length4

Characters and Unicode

Total characters58158
Distinct characters384
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1409 ?
Unique (%)52.9%

Sample

1st row경기도 가평군 가평읍 100번지
2nd row경기도 가평군 설악면 2번지 12호
3rd row경기도 가평군 청평면 650번지 5호
4th row경기도 가평군 가평읍 100번지
5th row경기도 가평군 조종면 276번지
ValueCountFrequency (%)
경기도 2655
 
19.2%
1호 393
 
2.8%
성남시 307
 
2.2%
수원시 263
 
1.9%
2호 198
 
1.4%
용인시 189
 
1.4%
부천시 174
 
1.3%
수정구 140
 
1.0%
화성시 123
 
0.9%
파주시 122
 
0.9%
Other values (2201) 9256
67.0%
2023-12-11T07:33:15.425204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11775
20.2%
2740
 
4.7%
2734
 
4.7%
2710
 
4.7%
2667
 
4.6%
2520
 
4.3%
2357
 
4.1%
2255
 
3.9%
1 1970
 
3.4%
1434
 
2.5%
Other values (374) 24996
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36515
62.8%
Space Separator 11775
 
20.2%
Decimal Number 9576
 
16.5%
Dash Punctuation 137
 
0.2%
Close Punctuation 52
 
0.1%
Open Punctuation 52
 
0.1%
Uppercase Letter 40
 
0.1%
Other Punctuation 9
 
< 0.1%
Lowercase Letter 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2740
 
7.5%
2734
 
7.5%
2710
 
7.4%
2667
 
7.3%
2520
 
6.9%
2357
 
6.5%
2255
 
6.2%
1434
 
3.9%
1319
 
3.6%
640
 
1.8%
Other values (340) 15139
41.5%
Uppercase Letter
ValueCountFrequency (%)
C 13
32.5%
A 5
 
12.5%
J 3
 
7.5%
D 2
 
5.0%
K 2
 
5.0%
I 2
 
5.0%
O 2
 
5.0%
E 2
 
5.0%
L 2
 
5.0%
F 2
 
5.0%
Other values (5) 5
 
12.5%
Decimal Number
ValueCountFrequency (%)
1 1970
20.6%
2 1167
12.2%
3 1088
11.4%
4 974
10.2%
5 872
9.1%
6 815
8.5%
7 714
 
7.5%
0 688
 
7.2%
8 659
 
6.9%
9 629
 
6.6%
Other Punctuation
ValueCountFrequency (%)
. 7
77.8%
: 1
 
11.1%
, 1
 
11.1%
Space Separator
ValueCountFrequency (%)
11775
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 137
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%
Lowercase Letter
ValueCountFrequency (%)
l 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 36515
62.8%
Common 21602
37.1%
Latin 41
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2740
 
7.5%
2734
 
7.5%
2710
 
7.4%
2667
 
7.3%
2520
 
6.9%
2357
 
6.5%
2255
 
6.2%
1434
 
3.9%
1319
 
3.6%
640
 
1.8%
Other values (340) 15139
41.5%
Common
ValueCountFrequency (%)
11775
54.5%
1 1970
 
9.1%
2 1167
 
5.4%
3 1088
 
5.0%
4 974
 
4.5%
5 872
 
4.0%
6 815
 
3.8%
7 714
 
3.3%
0 688
 
3.2%
8 659
 
3.1%
Other values (8) 880
 
4.1%
Latin
ValueCountFrequency (%)
C 13
31.7%
A 5
 
12.2%
J 3
 
7.3%
D 2
 
4.9%
K 2
 
4.9%
I 2
 
4.9%
O 2
 
4.9%
E 2
 
4.9%
L 2
 
4.9%
F 2
 
4.9%
Other values (6) 6
14.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 36515
62.8%
ASCII 21643
37.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11775
54.4%
1 1970
 
9.1%
2 1167
 
5.4%
3 1088
 
5.0%
4 974
 
4.5%
5 872
 
4.0%
6 815
 
3.8%
7 714
 
3.3%
0 688
 
3.2%
8 659
 
3.0%
Other values (24) 921
 
4.3%
Hangul
ValueCountFrequency (%)
2740
 
7.5%
2734
 
7.5%
2710
 
7.4%
2667
 
7.3%
2520
 
6.9%
2357
 
6.5%
2255
 
6.2%
1434
 
3.9%
1319
 
3.6%
640
 
1.8%
Other values (340) 15139
41.5%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1211
Distinct (%)50.5%
Missing265
Missing (%)9.9%
Infinite0
Infinite (%)0.0%
Mean14403.35
Minimum10000
Maximum18635
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.6 KiB
2023-12-11T07:33:15.625666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10000
5-th percentile10458.75
Q112728
median14533.5
Q316461
95-th percentile18124.35
Maximum18635
Range8635
Interquartile range (IQR)3733

Descriptive statistics

Standard deviation2336.4408
Coefficient of variation (CV)0.1622151
Kurtosis-0.99625965
Mean14403.35
Median Absolute Deviation (MAD)1872
Skewness-0.098333318
Sum34568039
Variance5458955.8
MonotonicityNot monotonic
2023-12-11T07:33:16.067255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13451 17
 
0.6%
13103 15
 
0.6%
13509 13
 
0.5%
10949 12
 
0.5%
13102 12
 
0.5%
17167 12
 
0.5%
16947 11
 
0.4%
13443 9
 
0.3%
18545 9
 
0.3%
10830 9
 
0.3%
Other values (1201) 2281
85.6%
(Missing) 265
 
9.9%
ValueCountFrequency (%)
10000 1
< 0.1%
10002 2
0.1%
10005 2
0.1%
10011 1
< 0.1%
10012 2
0.1%
10017 1
< 0.1%
10020 2
0.1%
10022 1
< 0.1%
10024 2
0.1%
10025 2
0.1%
ValueCountFrequency (%)
18635 2
 
0.1%
18633 1
 
< 0.1%
18630 1
 
< 0.1%
18623 3
0.1%
18608 4
0.2%
18592 1
 
< 0.1%
18584 2
 
0.1%
18583 3
0.1%
18582 1
 
< 0.1%
18577 6
0.2%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1639
Distinct (%)70.4%
Missing336
Missing (%)12.6%
Infinite0
Infinite (%)0.0%
Mean37.427571
Minimum36.943305
Maximum38.19452
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.6 KiB
2023-12-11T07:33:16.203676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.943305
5-th percentile37.119229
Q137.293039
median37.398291
Q337.507136
95-th percentile37.823266
Maximum38.19452
Range1.2512156
Interquartile range (IQR)0.21409716

Descriptive statistics

Standard deviation0.20680349
Coefficient of variation (CV)0.0055254318
Kurtosis0.34164295
Mean37.427571
Median Absolute Deviation (MAD)0.10716311
Skewness0.61660735
Sum87168.813
Variance0.042767685
MonotonicityNot monotonic
2023-12-11T07:33:16.380496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4379942214 12
 
0.5%
37.3302001597 8
 
0.3%
37.7143636826 8
 
0.3%
37.2785710892 6
 
0.2%
37.3548369375 6
 
0.2%
37.3867224073 6
 
0.2%
37.408906697 6
 
0.2%
37.7932075303 6
 
0.2%
37.320664353 6
 
0.2%
37.8167937925 6
 
0.2%
Other values (1629) 2259
84.8%
(Missing) 336
 
12.6%
ValueCountFrequency (%)
36.9433047732 2
0.1%
36.966257422 2
0.1%
36.9775420916 2
0.1%
36.9852325445 2
0.1%
36.9889196835 1
< 0.1%
36.9892840117 2
0.1%
36.9895489439 1
< 0.1%
36.9900310614 1
< 0.1%
36.9915459577 1
< 0.1%
36.9939846962 2
0.1%
ValueCountFrequency (%)
38.1945203475 1
< 0.1%
38.1071229181 2
0.1%
38.1038166235 1
< 0.1%
38.099556144 1
< 0.1%
38.0894446557 1
< 0.1%
38.0709206119 1
< 0.1%
38.0653856554 1
< 0.1%
38.030722086 2
0.1%
38.0284032776 1
< 0.1%
38.0280814416 2
0.1%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1639
Distinct (%)70.4%
Missing336
Missing (%)12.6%
Infinite0
Infinite (%)0.0%
Mean127.00616
Minimum126.52982
Maximum127.70043
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.6 KiB
2023-12-11T07:33:16.560871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.52982
5-th percentile126.75683
Q1126.84148
median127.00747
Q3127.12604
95-th percentile127.37673
Maximum127.70043
Range1.1706151
Interquartile range (IQR)0.28455827

Descriptive statistics

Standard deviation0.19354958
Coefficient of variation (CV)0.0015239385
Kurtosis0.36964596
Mean127.00616
Median Absolute Deviation (MAD)0.13639477
Skewness0.54756373
Sum295797.35
Variance0.037461439
MonotonicityNot monotonic
2023-12-11T07:33:16.690691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1068822087 12
 
0.5%
126.8643211129 8
 
0.3%
126.7766859345 8
 
0.3%
127.0890835842 6
 
0.2%
126.9377339878 6
 
0.2%
127.0380558108 6
 
0.2%
127.1200571369 6
 
0.2%
126.9104631482 6
 
0.2%
126.8495373023 6
 
0.2%
126.8960396511 6
 
0.2%
Other values (1629) 2259
84.8%
(Missing) 336
 
12.6%
ValueCountFrequency (%)
126.5298197278 2
0.1%
126.5298521644 1
< 0.1%
126.5341928032 1
< 0.1%
126.54660312 2
0.1%
126.5494942369 1
< 0.1%
126.5522797507 1
< 0.1%
126.5560224786 2
0.1%
126.5632274084 1
< 0.1%
126.567548385 1
< 0.1%
126.5763164914 1
< 0.1%
ValueCountFrequency (%)
127.7004348715 1
< 0.1%
127.6476557365 1
< 0.1%
127.6474222786 1
< 0.1%
127.6473084745 1
< 0.1%
127.6470272581 1
< 0.1%
127.6312854633 2
0.1%
127.6228994282 2
0.1%
127.6155245365 2
0.1%
127.6153549727 2
0.1%
127.593153731 2
0.1%

업태구분명정보
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2665
Missing (%)100.0%
Memory size23.6 KiB

X좌표값
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct665
Distinct (%)94.3%
Missing1960
Missing (%)73.5%
Infinite0
Infinite (%)0.0%
Mean199759.22
Minimum158494.47
Maximum257528.95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.6 KiB
2023-12-11T07:33:16.853468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum158494.47
5-th percentile178386.4
Q1186852.34
median198906.89
Q3207377.56
95-th percentile234070.19
Maximum257528.95
Range99034.485
Interquartile range (IQR)20525.228

Descriptive statistics

Standard deviation16526.869
Coefficient of variation (CV)0.082733946
Kurtosis1.3607329
Mean199759.22
Median Absolute Deviation (MAD)10403.642
Skewness0.81328155
Sum1.4083025 × 108
Variance2.7313739 × 108
MonotonicityNot monotonic
2023-12-11T07:33:16.995363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
188207.367078952 4
 
0.2%
180151.113447963 4
 
0.2%
210612.690133161 3
 
0.1%
203301.431173851 3
 
0.1%
192100.337744514 3
 
0.1%
190925.28431765 3
 
0.1%
186403.240447222 3
 
0.1%
194295.966116662 2
 
0.1%
202580.167830727 2
 
0.1%
186474.793685706 2
 
0.1%
Other values (655) 676
 
25.4%
(Missing) 1960
73.5%
ValueCountFrequency (%)
158494.469062727 1
< 0.1%
159126.2084733 1
< 0.1%
159973.6598814 1
< 0.1%
160231.406024092 1
< 0.1%
160789.174471939 1
< 0.1%
161444.734434547 1
< 0.1%
162602.184191942 1
< 0.1%
163192.286675743 1
< 0.1%
164790.389437515 1
< 0.1%
170549.314055678 1
< 0.1%
ValueCountFrequency (%)
257528.954133111 1
< 0.1%
257327.254191863 1
< 0.1%
255279.776768242 1
< 0.1%
254673.17622021 1
< 0.1%
254615.6517314 1
< 0.1%
254596.363643569 1
< 0.1%
254335.209704916 1
< 0.1%
252634.22400982 1
< 0.1%
251876.953910445 1
< 0.1%
251743.990723393 1
< 0.1%

Y좌표값
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct665
Distinct (%)94.3%
Missing1960
Missing (%)73.5%
Infinite0
Infinite (%)0.0%
Mean432624.56
Minimum384951
Maximum511585.94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.6 KiB
2023-12-11T07:33:17.133497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum384951
5-th percentile397583.54
Q1418471.29
median427775.88
Q3438755.57
95-th percentile484962.48
Maximum511585.94
Range126634.95
Interquartile range (IQR)20284.289

Descriptive statistics

Standard deviation23743.013
Coefficient of variation (CV)0.054881334
Kurtosis0.86868053
Mean432624.56
Median Absolute Deviation (MAD)9909.2626
Skewness0.99623728
Sum3.0500031 × 108
Variance5.6373066 × 108
MonotonicityNot monotonic
2023-12-11T07:33:17.265474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
424931.170599678 4
 
0.2%
468006.041498468 4
 
0.2%
434262.298020582 3
 
0.1%
431635.333128216 3
 
0.1%
477127.820905632 3
 
0.1%
479931.786057688 3
 
0.1%
471942.044802885 3
 
0.1%
418992.317691086 2
 
0.1%
475473.716454176 2
 
0.1%
407650.106800131 2
 
0.1%
Other values (655) 676
 
25.4%
(Missing) 1960
73.5%
ValueCountFrequency (%)
384950.998602313 1
< 0.1%
386228.483809253 1
< 0.1%
387061.078858972 1
< 0.1%
387474.984117223 1
< 0.1%
388129.261505456 1
< 0.1%
388244.280613602 1
< 0.1%
388260.565687432 1
< 0.1%
388692.547785171 1
< 0.1%
388930.51904406 1
< 0.1%
389314.001472674 1
< 0.1%
ValueCountFrequency (%)
511585.944737878 1
< 0.1%
509642.681873571 1
< 0.1%
503159.355428128 1
< 0.1%
502759.990114911 1
< 0.1%
502601.701418297 1
< 0.1%
500387.82323695 1
< 0.1%
498927.089338887 1
< 0.1%
495420.375306143 1
< 0.1%
494990.649741092 1
< 0.1%
493836.683307746 1
< 0.1%

비상시설위치
Text

MISSING 

Distinct698
Distinct (%)94.7%
Missing1928
Missing (%)72.3%
Memory size20.9 KiB
2023-12-11T07:33:17.581138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length36
Mean length21.747626
Min length15

Characters and Unicode

Total characters16028
Distinct characters286
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

Unique669 ?
Unique (%)90.8%

Sample

1st row경기도 가평군 가평읍 100번지
2nd row경기도 고양시 덕양구 도내동 980 (도래울바람물공원)
3rd row경기도 고양시 덕양구 대자동 1170번지
4th row경기도 고양시 덕양구 토당동 3-39 (지도공원)
5th row경기도 고양시 덕양구 행신동 772
ValueCountFrequency (%)
경기도 737
 
19.0%
수원시 123
 
3.2%
1호 101
 
2.6%
성남시 91
 
2.3%
용인시 62
 
1.6%
수정구 60
 
1.5%
2호 52
 
1.3%
안산시 49
 
1.3%
화성시 49
 
1.3%
시흥시 48
 
1.2%
Other values (1057) 2515
64.7%
2023-12-11T07:33:18.039222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3164
19.7%
791
 
4.9%
757
 
4.7%
749
 
4.7%
741
 
4.6%
663
 
4.1%
622
 
3.9%
598
 
3.7%
1 550
 
3.4%
375
 
2.3%
Other values (276) 7018
43.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10055
62.7%
Space Separator 3164
 
19.7%
Decimal Number 2674
 
16.7%
Dash Punctuation 93
 
0.6%
Uppercase Letter 24
 
0.1%
Open Punctuation 6
 
< 0.1%
Close Punctuation 6
 
< 0.1%
Other Punctuation 5
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
791
 
7.9%
757
 
7.5%
749
 
7.4%
741
 
7.4%
663
 
6.6%
622
 
6.2%
598
 
5.9%
375
 
3.7%
355
 
3.5%
221
 
2.2%
Other values (246) 4183
41.6%
Uppercase Letter
ValueCountFrequency (%)
C 6
25.0%
A 4
16.7%
J 3
12.5%
E 2
 
8.3%
D 1
 
4.2%
L 1
 
4.2%
I 1
 
4.2%
N 1
 
4.2%
P 1
 
4.2%
S 1
 
4.2%
Other values (3) 3
12.5%
Decimal Number
ValueCountFrequency (%)
1 550
20.6%
2 314
11.7%
3 295
11.0%
4 259
9.7%
5 245
9.2%
6 227
8.5%
7 203
 
7.6%
0 199
 
7.4%
9 192
 
7.2%
8 190
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 4
80.0%
: 1
 
20.0%
Space Separator
ValueCountFrequency (%)
3164
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 93
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Lowercase Letter
ValueCountFrequency (%)
l 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10055
62.7%
Common 5948
37.1%
Latin 25
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
791
 
7.9%
757
 
7.5%
749
 
7.4%
741
 
7.4%
663
 
6.6%
622
 
6.2%
598
 
5.9%
375
 
3.7%
355
 
3.5%
221
 
2.2%
Other values (246) 4183
41.6%
Common
ValueCountFrequency (%)
3164
53.2%
1 550
 
9.2%
2 314
 
5.3%
3 295
 
5.0%
4 259
 
4.4%
5 245
 
4.1%
6 227
 
3.8%
7 203
 
3.4%
0 199
 
3.3%
9 192
 
3.2%
Other values (6) 300
 
5.0%
Latin
ValueCountFrequency (%)
C 6
24.0%
A 4
16.0%
J 3
12.0%
E 2
 
8.0%
D 1
 
4.0%
l 1
 
4.0%
L 1
 
4.0%
I 1
 
4.0%
N 1
 
4.0%
P 1
 
4.0%
Other values (4) 4
16.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10055
62.7%
ASCII 5973
37.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3164
53.0%
1 550
 
9.2%
2 314
 
5.3%
3 295
 
4.9%
4 259
 
4.3%
5 245
 
4.1%
6 227
 
3.8%
7 203
 
3.4%
0 199
 
3.3%
9 192
 
3.2%
Other values (20) 325
 
5.4%
Hangul
ValueCountFrequency (%)
791
 
7.9%
757
 
7.5%
749
 
7.4%
741
 
7.4%
663
 
6.6%
622
 
6.2%
598
 
5.9%
375
 
3.7%
355
 
3.5%
221
 
2.2%
Other values (246) 4183
41.6%

시설구분명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size20.9 KiB
<NA>
1928 
공공용시설
236 
민간시설
228 
정부지원시설
 
167
지자체시설
 
106

Length

Max length6
Median length4
Mean length4.2536585
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1928
72.3%
공공용시설 236
 
8.9%
민간시설 228
 
8.6%
정부지원시설 167
 
6.3%
지자체시설 106
 
4.0%

Length

2023-12-11T07:33:18.165377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:33:18.288446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1928
72.3%
공공용시설 236
 
8.9%
민간시설 228
 
8.6%
정부지원시설 167
 
6.3%
지자체시설 106
 
4.0%
Distinct732
Distinct (%)99.3%
Missing1928
Missing (%)72.3%
Memory size20.9 KiB
2023-12-11T07:33:18.528270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length22
Mean length9.5753053
Min length3

Characters and Unicode

Total characters7057
Distinct characters452
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

Unique727 ?
Unique (%)98.6%

Sample

1st row농업기술센터
2nd row도래울바람물공원
3rd row필리핀참전비
4th row지도공원
5th row차장공원
ValueCountFrequency (%)
비상급수시설 51
 
4.6%
비상급수 9
 
0.8%
남양읍 8
 
0.7%
민방위 8
 
0.7%
서원레저(주 6
 
0.5%
약수터 6
 
0.5%
6
 
0.5%
수지구 5
 
0.5%
5
 
0.5%
광적면 4
 
0.4%
Other values (923) 1000
90.3%
2023-12-11T07:33:18.889719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
371
 
5.3%
( 269
 
3.8%
) 269
 
3.8%
204
 
2.9%
190
 
2.7%
143
 
2.0%
142
 
2.0%
130
 
1.8%
122
 
1.7%
120
 
1.7%
Other values (442) 5097
72.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5590
79.2%
Space Separator 371
 
5.3%
Decimal Number 370
 
5.2%
Open Punctuation 269
 
3.8%
Close Punctuation 269
 
3.8%
Dash Punctuation 100
 
1.4%
Uppercase Letter 50
 
0.7%
Other Punctuation 29
 
0.4%
Lowercase Letter 7
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
204
 
3.6%
190
 
3.4%
143
 
2.6%
142
 
2.5%
130
 
2.3%
122
 
2.2%
120
 
2.1%
118
 
2.1%
109
 
1.9%
98
 
1.8%
Other values (404) 4214
75.4%
Uppercase Letter
ValueCountFrequency (%)
C 19
38.0%
K 6
 
12.0%
S 6
 
12.0%
T 4
 
8.0%
G 2
 
4.0%
I 2
 
4.0%
H 2
 
4.0%
N 2
 
4.0%
L 2
 
4.0%
Z 1
 
2.0%
Other values (4) 4
 
8.0%
Decimal Number
ValueCountFrequency (%)
1 104
28.1%
2 58
15.7%
3 46
12.4%
5 35
 
9.5%
6 33
 
8.9%
4 32
 
8.6%
8 19
 
5.1%
0 17
 
4.6%
7 14
 
3.8%
9 12
 
3.2%
Other Punctuation
ValueCountFrequency (%)
* 15
51.7%
. 8
27.6%
/ 2
 
6.9%
, 2
 
6.9%
· 1
 
3.4%
? 1
 
3.4%
Lowercase Letter
ValueCountFrequency (%)
c 6
85.7%
e 1
 
14.3%
Space Separator
ValueCountFrequency (%)
371
100.0%
Open Punctuation
ValueCountFrequency (%)
( 269
100.0%
Close Punctuation
ValueCountFrequency (%)
) 269
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 100
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%
Math Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5590
79.2%
Common 1409
 
20.0%
Latin 58
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
204
 
3.6%
190
 
3.4%
143
 
2.6%
142
 
2.5%
130
 
2.3%
122
 
2.2%
120
 
2.1%
118
 
2.1%
109
 
1.9%
98
 
1.8%
Other values (404) 4214
75.4%
Common
ValueCountFrequency (%)
371
26.3%
( 269
19.1%
) 269
19.1%
1 104
 
7.4%
- 100
 
7.1%
2 58
 
4.1%
3 46
 
3.3%
5 35
 
2.5%
6 33
 
2.3%
4 32
 
2.3%
Other values (11) 92
 
6.5%
Latin
ValueCountFrequency (%)
C 19
32.8%
K 6
 
10.3%
S 6
 
10.3%
c 6
 
10.3%
T 4
 
6.9%
G 2
 
3.4%
I 2
 
3.4%
H 2
 
3.4%
N 2
 
3.4%
L 2
 
3.4%
Other values (7) 7
 
12.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5590
79.2%
ASCII 1464
 
20.7%
None 1
 
< 0.1%
Number Forms 1
 
< 0.1%
Arrows 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
371
25.3%
( 269
18.4%
) 269
18.4%
1 104
 
7.1%
- 100
 
6.8%
2 58
 
4.0%
3 46
 
3.1%
5 35
 
2.4%
6 33
 
2.3%
4 32
 
2.2%
Other values (25) 147
 
10.0%
Hangul
ValueCountFrequency (%)
204
 
3.6%
190
 
3.4%
143
 
2.6%
142
 
2.5%
130
 
2.3%
122
 
2.2%
120
 
2.1%
118
 
2.1%
109
 
1.9%
98
 
1.8%
Other values (404) 4214
75.4%
None
ValueCountFrequency (%)
· 1
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%
Arrows
ValueCountFrequency (%)
1
100.0%

Interactions

2023-12-11T07:33:09.654116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:06.959883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:07.430225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:07.865807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:08.635996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:09.126924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:09.733210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:07.023500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:07.497895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:07.937146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:08.711213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:09.198706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:09.815787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:07.103926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:07.566960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:08.033235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:08.794924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:09.271524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:09.907907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:07.189643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:07.644010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:08.353005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:08.880651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:09.354159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:09.993097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:07.285017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:07.719932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:08.447266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:08.967475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:09.446770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:10.070640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:07.359063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:07.793595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:08.542557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:09.044696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:09.540217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:33:18.975897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명인허가취소일자영업상태구분코드영업상태명소재지면적정보(㎡)소재지우편번호WGS84위도WGS84경도X좌표값Y좌표값시설구분명
시군명1.0001.0000.6580.5280.1790.9890.9580.9270.9430.9560.708
인허가취소일자1.0001.000NaNNaN0.3091.0000.9330.9920.9820.9730.994
영업상태구분코드0.658NaN1.0001.0000.0000.6650.4250.2080.2220.4280.282
영업상태명0.528NaN1.0001.0000.0000.3710.2920.2380.2220.4280.282
소재지면적정보(㎡)0.1790.3090.0000.0001.0000.0000.0710.1620.2180.1130.086
소재지우편번호0.9891.0000.6650.3710.0001.0000.9260.8400.8700.9110.462
WGS84위도0.9580.9330.4250.2920.0710.9261.0000.6100.6440.9870.416
WGS84경도0.9270.9920.2080.2380.1620.8400.6101.0000.9930.6400.233
X좌표값0.9430.9820.2220.2220.2180.8700.6440.9931.0000.6630.312
Y좌표값0.9560.9730.4280.4280.1130.9110.9870.6400.6631.0000.446
시설구분명0.7080.9940.2820.2820.0860.4620.4160.2330.3120.4461.000
2023-12-11T07:33:19.111946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명영업상태명영업상태구분코드인허가취소일자시설구분명
시군명1.0000.2990.5640.8200.450
영업상태명0.2991.0000.9921.0000.187
영업상태구분코드0.5640.9921.0001.0000.187
인허가취소일자0.8201.0001.0001.0000.730
시설구분명0.4500.1870.1870.7301.000
2023-12-11T07:33:19.200661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지면적정보(㎡)소재지우편번호WGS84위도WGS84경도X좌표값Y좌표값시군명인허가취소일자영업상태구분코드영업상태명시설구분명
소재지면적정보(㎡)1.0000.063-0.116-0.022-0.047-0.1170.0780.1770.0000.0000.055
소재지우편번호0.0631.000-0.9020.0710.117-0.9160.9120.7890.5140.2290.293
WGS84위도-0.116-0.9021.000-0.224-0.2301.0000.7600.5510.3250.1780.259
WGS84경도-0.0220.071-0.2241.0001.000-0.2320.6610.6550.1580.1440.141
X좌표값-0.0470.117-0.2301.0001.000-0.2170.7170.6830.1690.1690.191
Y좌표값-0.117-0.9161.000-0.232-0.2171.0000.7630.6550.3270.3270.283
시군명0.0780.9120.7600.6610.7170.7631.0000.8200.5640.2990.450
인허가취소일자0.1770.7890.5510.6550.6830.6550.8201.0001.0001.0000.730
영업상태구분코드0.0000.5140.3250.1580.1690.3270.5641.0001.0000.9920.187
영업상태명0.0000.2290.1780.1440.1690.3270.2991.0000.9921.0000.187
시설구분명0.0550.2930.2590.1410.1910.2830.4500.7300.1870.1871.000

Missing values

2023-12-11T07:33:10.197317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:33:10.407931image/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.
2023-12-11T07:33:10.601511image/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

시군명급수시설명인허가일자인허가취소일자영업상태구분코드영업상태명소재지시설전화번호소재지면적정보(㎡)도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값비상시설위치시설구분명시설명건물명정보
0가평군농업기술센터2005-06-302023-05-0919사용중지<NA>100.012408경기도 가평군 가평읍 아랫마장길 59 (농업기술센터)경기도 가평군 가평읍 100번지1240837.845967127.498647<NA>243869.005545482723.107531경기도 가평군 가평읍 100번지지자체시설농업기술센터
1가평군프리스틴밸리20050630<NA><NA>운영중<NA><NA><NA>경기도 가평군 설악면 유명로 1243-199경기도 가평군 설악면 2번지 12호1246837.660746127.456395<NA><NA><NA><NA><NA><NA>
2가평군백암천20050630<NA><NA>운영중<NA><NA><NA>경기도 가평군 청평면 경춘로 699 (청평백암천)경기도 가평군 청평면 650번지 5호1245437.731311127.408587<NA><NA><NA><NA><NA><NA>
3가평군농업기술센터20040510<NA><NA>운영중<NA><NA><NA>경기도 가평군 가평읍 아랫마장길 59경기도 가평군 가평읍 100번지1240837.845967127.498647<NA><NA><NA><NA><NA><NA>
4가평군조종초등학교20040130<NA><NA>운영중<NA><NA><NA>경기도 가평군 조종면 조종새싹로 13-9 (조종초등학교)경기도 가평군 조종면 276번지1243737.821517127.348937<NA><NA><NA><NA><NA><NA>
5가평군경춘도로약수터19960501<NA><NA>운영중<NA><NA><NA>경기도 가평군 가평읍 보납로 305경기도 가평군 가평읍 읍내리 산 6번지 1호<NA>37.845649127.532047<NA><NA><NA><NA><NA><NA>
6가평군가평수덕원19960501<NA><NA>운영중<NA><NA><NA>경기도 가평군 가평읍 북한강변로 238경기도 가평군 가평읍 531번지 2호1242837.751486127.533442<NA><NA><NA><NA><NA><NA>
7가평군삼성에버랜드가평베네스트20080509<NA><NA>운영중<NA><NA><NA>경기도 가평군 상면 둔덕말길 232 (가평베네스트골프클럽)경기도 가평군 상면 52번지1244337.797145127.305438<NA><NA><NA><NA><NA><NA>
8가평군농업기술센터20050630<NA><NA>운영중<NA><NA><NA>경기도 가평군 가평읍 아랫마장길 59 (농업기술센터)경기도 가평군 가평읍 100번지1240837.845967127.498647<NA><NA><NA><NA><NA><NA>
9가평군가평고등학교19980216<NA><NA>운영중<NA><NA><NA>경기도 가평군 가평읍 호반로 2601경기도 가평군 가평읍 66번지 2호1242137.817476127.511407<NA><NA><NA><NA><NA><NA>
시군명급수시설명인허가일자인허가취소일자영업상태구분코드영업상태명소재지시설전화번호소재지면적정보(㎡)도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값비상시설위치시설구분명시설명건물명정보
2655화성시팔탄초등학교19840101<NA><NA>폐업 등<NA><NA><NA><NA>경기도 화성시 팔탄면 구장리 536번지 1호18527<NA><NA><NA><NA><NA><NA><NA><NA>
2656화성시청원초등학교20001205<NA><NA>폐업 등<NA><NA><NA>경기도 화성시 마도면 해운로 794 (청원초등학교)경기도 화성시 마도면 청원리 228번지 4호 청원초등학교1854337.188208126.760892<NA><NA><NA><NA><NA><NA>
2657화성시비봉면사무소19920101<NA><NA>폐업 등<NA><NA><NA>경기도 화성시 비봉면 양노로 103경기도 화성시 비봉면 양노리 263번지1828437.236536126.872572<NA><NA><NA><NA><NA><NA>
2658화성시검단이(마을대형관정)20080506<NA><NA>폐업 등<NA><NA><NA><NA>경기도 화성시 정남면 계향리 564번지 2호18523<NA><NA><NA><NA><NA><NA><NA><NA>
2659화성시용수리(마을대형관정)20080506<NA><NA>폐업 등<NA><NA><NA><NA>경기도 화성시 정남면 용수리 53번지 14호18512<NA><NA><NA><NA><NA><NA><NA><NA>
2660화성시보금울(마을대형관정)20080506<NA><NA>폐업 등<NA><NA><NA>경기도 화성시 송산면 공룡로281번길 31-10경기도 화성시 송산면 쌍정리 137번지1854737.237279126.732386<NA><NA><NA><NA><NA><NA>
2661화성시활초초등학교 간이급수시설20080506<NA><NA>폐업 등<NA><NA><NA><NA>경기도 화성시 안석동 252번지 1호18278<NA><NA><NA><NA><NA><NA><NA><NA>
2662화성시용포(마을간이급수시설)20080506<NA><NA>폐업 등<NA><NA><NA><NA>경기도 화성시 송산면 용포리 산 13번지<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2663화성시독정3리 (마을간이급수시설)20080506<NA><NA>폐업 등<NA><NA><NA>경기도 화성시 장안면 거묵골길 11경기도 화성시 장안면 독정리 121번지 2호1858337.079481126.860165<NA><NA><NA><NA><NA><NA>
2664화성시뱃골(마을대형관정)20080506<NA><NA>폐업 등<NA><NA><NA>경기도 화성시 우정읍 이화뱃골길 42-4경기도 화성시 우정읍 이화리 680번지1857337.04144126.794635<NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

시군명급수시설명인허가일자인허가취소일자영업상태구분코드영업상태명소재지면적정보(㎡)도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도X좌표값Y좌표값비상시설위치시설구분명시설명건물명정보# duplicates
0고양시주님의 유치원20080618<NA><NA>폐업 등<NA><NA><NA>경기도 고양시덕양구 성사동 108번지 3호10481<NA><NA><NA><NA><NA><NA><NA>3
2용인시코리아퍼블릭20041101<NA><NA>폐업 등<NA><NA>경기도 용인시 기흥구 기흥단지로 224 (고매동, 코리아퍼블릭코스)경기도 용인시 기흥구 고매동 279-13번지 코리아퍼블릭코스1708737.223533127.119084<NA><NA><NA><NA><NA>3
3용인시태광컨트리클럽20070827<NA><NA>폐업 등<NA><NA><NA>경기도 용인시기흥구 신갈동 501번지 11호 (11호공)16947<NA><NA><NA><NA><NA><NA><NA>3
1용인시단국대학교20150630<NA><NA>폐업 등<NA><NA>경기도 용인시 기흥구 마북로247번길 124 (보정동)경기도 용인시 기흥구 보정동 31번지 2호1689137.317893127.125493<NA><NA><NA><NA><NA>2