Overview

Dataset statistics

Number of variables19
Number of observations3352
Missing cells4210
Missing cells (%)6.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory520.6 KiB
Average record size in memory159.0 B

Variable types

Categorical2
Text9
Numeric6
Boolean1
DateTime1

Dataset

Description공공데이터 제공 표준데이터 속성정보(허용값, 표현형식/단위 등)는 [공공데이터 제공 표준] 전문을 참고하시기 바랍니다.(공공데이터포털>정보공유>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/15034532/standard.do

Alerts

시군구코드 is highly overall correlated with 제공기관코드 and 1 other fieldsHigh correlation
위도 is highly overall correlated with 시도명High correlation
경도 is highly overall correlated with 시도명High correlation
CCTV설치대수 is highly overall correlated with CCTV설치여부High correlation
제공기관코드 is highly overall correlated with 시군구코드 and 1 other fieldsHigh correlation
시도명 is highly overall correlated with 시군구코드 and 3 other fieldsHigh correlation
CCTV설치여부 is highly overall correlated with CCTV설치대수High correlation
장소유형코드 is highly imbalanced (60.4%)Imbalance
소재지도로명주소 has 114 (3.4%) missing valuesMissing
소재지지번주소 has 660 (19.7%) missing valuesMissing
CCTV설치대수 has 1970 (58.8%) missing valuesMissing
보호구역도로폭 has 1466 (43.7%) missing valuesMissing
제한속도 is highly skewed (γ1 = 33.29845407)Skewed
CCTV설치대수 has 843 (25.1%) zerosZeros

Reproduction

Analysis started2024-05-11 10:18:38.313461
Analysis finished2024-05-11 10:18:56.843770
Duration18.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

장소유형코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size26.3 KiB
1
3090 
2
 
262

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 3090
92.2%
2 262
 
7.8%

Length

2024-05-11T10:18:57.042470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:18:57.487039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3090
92.2%
2 262
 
7.8%

대상시설명
Text

Distinct3048
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size26.3 KiB
2024-05-11T10:18:58.102530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length7.752685
Min length1

Characters and Unicode

Total characters25987
Distinct characters492
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2760 ?
Unique (%)82.3%

Sample

1st row대포1리 경로당
2nd row상촌1리 마을회관
3rd row북장리 경로당
4th row북장리 팔각정
5th row북장리(사기점) 경로당
ValueCountFrequency (%)
경로당 1063
 
20.4%
노인회관 141
 
2.7%
마을회관 122
 
2.3%
집 24
 
0.5%
요양원 21
 
0.4%
논산시 20
 
0.4%
노인복지회관 19
 
0.4%
노인복지관 14
 
0.3%
복지회관 14
 
0.3%
경로회관 13
 
0.2%
Other values (3232) 3759
72.1%
2024-05-11T10:18:59.517491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 1985
 
7.6%
당 1978
 
7.6%
경 1972
 
7.6%
1859
 
7.2%
리 1601
 
6.2%
관 810
 
3.1%
인 673
 
2.6%
노 646
 
2.5%
회 597
 
2.3%
1 546
 
2.1%
Other values (482) 13320
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22712
87.4%
Space Separator 1859
 
7.2%
Decimal Number 1271
 
4.9%
Close Punctuation 57
 
0.2%
Open Punctuation 54
 
0.2%
Uppercase Letter 18
 
0.1%
Other Punctuation 14
 
0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 1985
 
8.7%
당 1978
 
8.7%
경 1972
 
8.7%
리 1601
 
7.0%
관 810
 
3.6%
인 673
 
3.0%
노 646
 
2.8%
회 597
 
2.6%
지 527
 
2.3%
복 455
 
2.0%
Other values (453) 11468
50.5%
Uppercase Letter
ValueCountFrequency (%)
S 3
16.7%
L 3
16.7%
T 2
11.1%
P 2
11.1%
H 2
11.1%
A 1
 
5.6%
I 1
 
5.6%
V 1
 
5.6%
K 1
 
5.6%
N 1
 
5.6%
Decimal Number
ValueCountFrequency (%)
1 546
43.0%
2 446
35.1%
3 168
 
13.2%
4 58
 
4.6%
5 18
 
1.4%
6 14
 
1.1%
7 10
 
0.8%
8 8
 
0.6%
0 2
 
0.2%
9 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 12
85.7%
. 1
 
7.1%
· 1
 
7.1%
Lowercase Letter
ValueCountFrequency (%)
h 1
50.0%
e 1
50.0%
Space Separator
ValueCountFrequency (%)
1859
100.0%
Close Punctuation
ValueCountFrequency (%)
) 57
100.0%
Open Punctuation
ValueCountFrequency (%)
( 54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22712
87.4%
Common 3255
 
12.5%
Latin 20
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 1985
 
8.7%
당 1978
 
8.7%
경 1972
 
8.7%
리 1601
 
7.0%
관 810
 
3.6%
인 673
 
3.0%
노 646
 
2.8%
회 597
 
2.6%
지 527
 
2.3%
복 455
 
2.0%
Other values (453) 11468
50.5%
Common
ValueCountFrequency (%)
1859
57.1%
1 546
 
16.8%
2 446
 
13.7%
3 168
 
5.2%
4 58
 
1.8%
) 57
 
1.8%
( 54
 
1.7%
5 18
 
0.6%
6 14
 
0.4%
, 12
 
0.4%
Other values (6) 23
 
0.7%
Latin
ValueCountFrequency (%)
S 3
15.0%
L 3
15.0%
T 2
10.0%
P 2
10.0%
H 2
10.0%
A 1
 
5.0%
h 1
 
5.0%
e 1
 
5.0%
I 1
 
5.0%
V 1
 
5.0%
Other values (3) 3
15.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22712
87.4%
ASCII 3274
 
12.6%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 1985
 
8.7%
당 1978
 
8.7%
경 1972
 
8.7%
리 1601
 
7.0%
관 810
 
3.6%
인 673
 
3.0%
노 646
 
2.8%
회 597
 
2.6%
지 527
 
2.3%
복 455
 
2.0%
Other values (453) 11468
50.5%
ASCII
ValueCountFrequency (%)
1859
56.8%
1 546
 
16.7%
2 446
 
13.6%
3 168
 
5.1%
4 58
 
1.8%
) 57
 
1.7%
( 54
 
1.6%
5 18
 
0.5%
6 14
 
0.4%
, 12
 
0.4%
Other values (18) 42
 
1.3%
None
ValueCountFrequency (%)
· 1
100.0%

시도명
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size26.3 KiB
충청남도
667 
경기도
514 
충청북도
300 
경상북도
298 
강원도
197 
Other values (14)
1376 

Length

Max length7
Median length5
Mean length4.327864
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
충청남도 667
19.9%
경기도 514
15.3%
충청북도 300
8.9%
경상북도 298
8.9%
강원도 197
 
5.9%
인천광역시 172
 
5.1%
서울특별시 165
 
4.9%
제주특별자치도 152
 
4.5%
강원특별자치도 138
 
4.1%
대전광역시 128
 
3.8%
Other values (9) 621
18.5%

Length

2024-05-11T10:19:00.079431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충청남도 667
19.9%
경기도 514
15.3%
충청북도 300
8.9%
경상북도 298
8.9%
강원도 197
 
5.9%
인천광역시 172
 
5.1%
서울특별시 165
 
4.9%
제주특별자치도 152
 
4.5%
강원특별자치도 138
 
4.1%
대전광역시 128
 
3.8%
Other values (9) 621
18.5%

시군구명
Text

Distinct165
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size26.3 KiB
2024-05-11T10:19:00.994687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.0435561
Min length2

Characters and Unicode

Total characters10202
Distinct characters120
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

Unique8 ?
Unique (%)0.2%

Sample

1st row상주시
2nd row상주시
3rd row상주시
4th row상주시
5th row상주시
ValueCountFrequency (%)
홍천군 160
 
4.7%
서산시 107
 
3.1%
보령시 91
 
2.7%
서구 87
 
2.5%
제주시 84
 
2.5%
금산군 80
 
2.3%
상주시 79
 
2.3%
충주시 78
 
2.3%
음성군 70
 
2.0%
서귀포시 68
 
2.0%
Other values (157) 2514
73.6%
2024-05-11T10:19:02.409365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 1675
 
16.4%
군 1010
 
9.9%
구 782
 
7.7%
주 496
 
4.9%
산 455
 
4.5%
천 413
 
4.0%
성 318
 
3.1%
서 312
 
3.1%
동 252
 
2.5%
홍 217
 
2.1%
Other values (110) 4272
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10136
99.4%
Space Separator 66
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 1675
 
16.5%
군 1010
 
10.0%
구 782
 
7.7%
주 496
 
4.9%
산 455
 
4.5%
천 413
 
4.1%
성 318
 
3.1%
서 312
 
3.1%
동 252
 
2.5%
홍 217
 
2.1%
Other values (109) 4206
41.5%
Space Separator
ValueCountFrequency (%)
66
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10136
99.4%
Common 66
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 1675
 
16.5%
군 1010
 
10.0%
구 782
 
7.7%
주 496
 
4.9%
산 455
 
4.5%
천 413
 
4.1%
성 318
 
3.1%
서 312
 
3.1%
동 252
 
2.5%
홍 217
 
2.1%
Other values (109) 4206
41.5%
Common
ValueCountFrequency (%)
66
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10136
99.4%
ASCII 66
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 1675
 
16.5%
군 1010
 
10.0%
구 782
 
7.7%
주 496
 
4.9%
산 455
 
4.5%
천 413
 
4.1%
성 318
 
3.1%
서 312
 
3.1%
동 252
 
2.5%
홍 217
 
2.1%
Other values (109) 4206
41.5%
ASCII
ValueCountFrequency (%)
66
100.0%

시군구코드
Real number (ℝ)

HIGH CORRELATION 

Distinct210
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40924.447
Minimum11140
Maximum56800
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.6 KiB
2024-05-11T10:19:02.822908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11140
5-th percentile26230
Q141150
median43740
Q346135
95-th percentile51720
Maximum56800
Range45660
Interquartile range (IQR)4985

Descriptive statistics

Standard deviation9436.7819
Coefficient of variation (CV)0.23059033
Kurtosis2.0826738
Mean40924.447
Median Absolute Deviation (MAD)2546
Skewness-1.4285358
Sum1.3717875 × 108
Variance89052852
MonotonicityNot monotonic
2024-05-11T10:19:03.564615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
44210 107
 
3.2%
45100 91
 
2.7%
50110 85
 
2.5%
44710 80
 
2.4%
42720 80
 
2.4%
51720 80
 
2.4%
47250 79
 
2.4%
43130 78
 
2.3%
41800 71
 
2.1%
43770 70
 
2.1%
Other values (200) 2531
75.5%
ValueCountFrequency (%)
11140 7
0.2%
11200 4
 
0.1%
11215 5
0.1%
11230 9
0.3%
11260 3
 
0.1%
11305 2
 
0.1%
11350 6
0.2%
11380 10
0.3%
11410 6
0.2%
11470 7
0.2%
ValueCountFrequency (%)
56800 67
2.0%
56700 14
 
0.4%
53900 3
 
0.1%
52730 1
 
< 0.1%
52720 2
 
0.1%
52113 5
 
0.1%
52111 13
 
0.4%
51720 80
2.4%
51700 16
 
0.5%
51230 21
 
0.6%

소재지도로명주소
Text

MISSING 

Distinct3144
Distinct (%)97.1%
Missing114
Missing (%)3.4%
Memory size26.3 KiB
2024-05-11T10:19:04.410115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length38
Mean length21.149475
Min length13

Characters and Unicode

Total characters68482
Distinct characters464
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

Unique3069 ?
Unique (%)94.8%

Sample

1st row경상북도 상주시 모서면 대포1길 16
2nd row경상북도 상주시 함창읍 용곡로 351
3rd row경상북도 상주시 모서면 대포1길 12-2
4th row경상북도 상주시 낙동면 삼봉로 360-1
5th row경상북도 상주시 내서면 북장1길 17
ValueCountFrequency (%)
충청남도 634
 
4.1%
경기도 501
 
3.2%
경상북도 296
 
1.9%
충청북도 257
 
1.6%
강원도 188
 
1.2%
인천광역시 172
 
1.1%
서울특별시 164
 
1.1%
홍천군 156
 
1.0%
제주특별자치도 151
 
1.0%
강원특별자치도 132
 
0.8%
Other values (4858) 12933
83.0%
2024-05-11T10:19:05.842960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12346
 
18.0%
도 2600
 
3.8%
시 2463
 
3.6%
로 2296
 
3.4%
1 2217
 
3.2%
길 1677
 
2.4%
면 1609
 
2.3%
2 1443
 
2.1%
남 1328
 
1.9%
3 1248
 
1.8%
Other values (454) 39255
57.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 44306
64.7%
Space Separator 12346
 
18.0%
Decimal Number 10675
 
15.6%
Dash Punctuation 690
 
1.0%
Open Punctuation 212
 
0.3%
Close Punctuation 211
 
0.3%
Other Punctuation 39
 
0.1%
Uppercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 2600
 
5.9%
시 2463
 
5.6%
로 2296
 
5.2%
길 1677
 
3.8%
면 1609
 
3.6%
남 1328
 
3.0%
산 1107
 
2.5%
청 1082
 
2.4%
구 1074
 
2.4%
경 1064
 
2.4%
Other values (436) 28006
63.2%
Decimal Number
ValueCountFrequency (%)
1 2217
20.8%
2 1443
13.5%
3 1248
11.7%
5 990
9.3%
4 976
9.1%
6 877
 
8.2%
7 852
 
8.0%
8 714
 
6.7%
0 683
 
6.4%
9 675
 
6.3%
Other Punctuation
ValueCountFrequency (%)
, 38
97.4%
. 1
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
S 2
66.7%
O 1
33.3%
Space Separator
ValueCountFrequency (%)
12346
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 690
100.0%
Open Punctuation
ValueCountFrequency (%)
( 212
100.0%
Close Punctuation
ValueCountFrequency (%)
) 211
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 44306
64.7%
Common 24173
35.3%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 2600
 
5.9%
시 2463
 
5.6%
로 2296
 
5.2%
길 1677
 
3.8%
면 1609
 
3.6%
남 1328
 
3.0%
산 1107
 
2.5%
청 1082
 
2.4%
구 1074
 
2.4%
경 1064
 
2.4%
Other values (436) 28006
63.2%
Common
ValueCountFrequency (%)
12346
51.1%
1 2217
 
9.2%
2 1443
 
6.0%
3 1248
 
5.2%
5 990
 
4.1%
4 976
 
4.0%
6 877
 
3.6%
7 852
 
3.5%
8 714
 
3.0%
- 690
 
2.9%
Other values (6) 1820
 
7.5%
Latin
ValueCountFrequency (%)
S 2
66.7%
O 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 44306
64.7%
ASCII 24176
35.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12346
51.1%
1 2217
 
9.2%
2 1443
 
6.0%
3 1248
 
5.2%
5 990
 
4.1%
4 976
 
4.0%
6 877
 
3.6%
7 852
 
3.5%
8 714
 
3.0%
- 690
 
2.9%
Other values (8) 1823
 
7.5%
Hangul
ValueCountFrequency (%)
도 2600
 
5.9%
시 2463
 
5.6%
로 2296
 
5.2%
길 1677
 
3.8%
면 1609
 
3.6%
남 1328
 
3.0%
산 1107
 
2.5%
청 1082
 
2.4%
구 1074
 
2.4%
경 1064
 
2.4%
Other values (436) 28006
63.2%

소재지지번주소
Text

MISSING 

Distinct2619
Distinct (%)97.3%
Missing660
Missing (%)19.7%
Memory size26.3 KiB
2024-05-11T10:19:06.884393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length36
Mean length21.10847
Min length14

Characters and Unicode

Total characters56824
Distinct characters347
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2550 ?
Unique (%)94.7%

Sample

1st row경상북도 상주시 모서면 대포리 796-1
2nd row경상북도 상주시 함창읍 신흥리 331-16
3rd row경상북도 상주시 모서면 대포리 142-6
4th row경상북도 상주시 낙동면 상촌리 885-3
5th row경상북도 상주시 내서면 북장리 487-70
ValueCountFrequency (%)
경기도 505
 
4.0%
충청남도 461
 
3.6%
경상북도 271
 
2.1%
충청북도 184
 
1.4%
제주특별자치도 152
 
1.2%
인천광역시 148
 
1.2%
서울특별시 140
 
1.1%
경상남도 118
 
0.9%
강원도 113
 
0.9%
울산광역시 103
 
0.8%
Other values (4674) 10532
82.8%
2024-05-11T10:19:08.558894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10040
 
17.7%
시 2180
 
3.8%
도 2176
 
3.8%
1 2164
 
3.8%
- 2095
 
3.7%
리 1715
 
3.0%
동 1449
 
2.5%
2 1404
 
2.5%
면 1261
 
2.2%
3 1241
 
2.2%
Other values (337) 31099
54.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34011
59.9%
Decimal Number 10676
 
18.8%
Space Separator 10040
 
17.7%
Dash Punctuation 2095
 
3.7%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 2180
 
6.4%
도 2176
 
6.4%
리 1715
 
5.0%
동 1449
 
4.3%
면 1261
 
3.7%
경 997
 
2.9%
남 990
 
2.9%
구 886
 
2.6%
주 802
 
2.4%
청 796
 
2.3%
Other values (324) 20759
61.0%
Decimal Number
ValueCountFrequency (%)
1 2164
20.3%
2 1404
13.2%
3 1241
11.6%
4 1038
9.7%
5 1030
9.6%
6 919
8.6%
7 785
 
7.4%
8 752
 
7.0%
9 690
 
6.5%
0 653
 
6.1%
Space Separator
ValueCountFrequency (%)
10040
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2095
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34011
59.9%
Common 22813
40.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 2180
 
6.4%
도 2176
 
6.4%
리 1715
 
5.0%
동 1449
 
4.3%
면 1261
 
3.7%
경 997
 
2.9%
남 990
 
2.9%
구 886
 
2.6%
주 802
 
2.4%
청 796
 
2.3%
Other values (324) 20759
61.0%
Common
ValueCountFrequency (%)
10040
44.0%
1 2164
 
9.5%
- 2095
 
9.2%
2 1404
 
6.2%
3 1241
 
5.4%
4 1038
 
4.6%
5 1030
 
4.5%
6 919
 
4.0%
7 785
 
3.4%
8 752
 
3.3%
Other values (3) 1345
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34011
59.9%
ASCII 22813
40.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10040
44.0%
1 2164
 
9.5%
- 2095
 
9.2%
2 1404
 
6.2%
3 1241
 
5.4%
4 1038
 
4.6%
5 1030
 
4.5%
6 919
 
4.0%
7 785
 
3.4%
8 752
 
3.3%
Other values (3) 1345
 
5.9%
Hangul
ValueCountFrequency (%)
시 2180
 
6.4%
도 2176
 
6.4%
리 1715
 
5.0%
동 1449
 
4.3%
면 1261
 
3.7%
경 997
 
2.9%
남 990
 
2.9%
구 886
 
2.6%
주 802
 
2.4%
청 796
 
2.3%
Other values (324) 20759
61.0%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct3197
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.543988
Minimum33.221644
Maximum38.281132
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.6 KiB
2024-05-11T10:19:09.015261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.221644
5-th percentile34.729751
Q136.048724
median36.744426
Q337.407857
95-th percentile37.850949
Maximum38.281132
Range5.0594881
Interquartile range (IQR)1.3591332

Descriptive statistics

Standard deviation1.0767194
Coefficient of variation (CV)0.029463655
Kurtosis1.222491
Mean36.543988
Median Absolute Deviation (MAD)0.67508289
Skewness-1.0981548
Sum122495.45
Variance1.1593247
MonotonicityNot monotonic
2024-05-11T10:19:09.712604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.17201665 3
 
0.1%
35.17201602 3
 
0.1%
35.57955111 3
 
0.1%
35.172016654 3
 
0.1%
37.34323642 2
 
0.1%
35.332499 2
 
0.1%
35.15356394 2
 
0.1%
37.711041 2
 
0.1%
37.6915 2
 
0.1%
37.694732 2
 
0.1%
Other values (3187) 3328
99.3%
ValueCountFrequency (%)
33.22164367 1
< 0.1%
33.22637138 1
< 0.1%
33.22838318 1
< 0.1%
33.24057235 1
< 0.1%
33.24199075 1
< 0.1%
33.24686998 1
< 0.1%
33.24751764 1
< 0.1%
33.24779863 1
< 0.1%
33.24959972 1
< 0.1%
33.25115977 1
< 0.1%
ValueCountFrequency (%)
38.28113176 2
0.1%
38.24805171 2
0.1%
38.2434871 2
0.1%
38.22619016 2
0.1%
38.20834324 2
0.1%
38.19649142 2
0.1%
38.1916628 2
0.1%
38.18427271 2
0.1%
38.18258194 2
0.1%
38.17925543 2
0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct3197
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.4285
Minimum125.92917
Maximum129.5442
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.6 KiB
2024-05-11T10:19:10.276569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum125.92917
5-th percentile126.43319
Q1126.78032
median127.19426
Q3127.92554
95-th percentile129.14559
Maximum129.5442
Range3.6150295
Interquartile range (IQR)1.1452118

Descriptive statistics

Standard deviation0.82800863
Coefficient of variation (CV)0.006497829
Kurtosis-0.27022951
Mean127.4285
Median Absolute Deviation (MAD)0.51518175
Skewness0.80603445
Sum427140.35
Variance0.68559829
MonotonicityNot monotonic
2024-05-11T10:19:11.272404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.6800066 3
 
0.1%
129.4316893 3
 
0.1%
126.6800079 3
 
0.1%
127.1588977 2
 
0.1%
128.444892 2
 
0.1%
128.5659554 2
 
0.1%
127.409909 2
 
0.1%
127.603952 2
 
0.1%
126.5708829 2
 
0.1%
127.99128319 2
 
0.1%
Other values (3187) 3329
99.3%
ValueCountFrequency (%)
125.9291745 1
< 0.1%
125.9885069 1
< 0.1%
126.0244803 1
< 0.1%
126.0465135 1
< 0.1%
126.0469551 1
< 0.1%
126.0515123 1
< 0.1%
126.0650245 1
< 0.1%
126.0763203766 1
< 0.1%
126.0935195 1
< 0.1%
126.111607 1
< 0.1%
ValueCountFrequency (%)
129.544204 1
< 0.1%
129.5257293 1
< 0.1%
129.4998881 1
< 0.1%
129.4656017 1
< 0.1%
129.462961 1
< 0.1%
129.4581153 1
< 0.1%
129.456293 1
< 0.1%
129.455205 1
< 0.1%
129.452411 1
< 0.1%
129.450421 1
< 0.1%

제한속도
Real number (ℝ)

SKEWED 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.493437
Minimum20
Maximum3050
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.6 KiB
2024-05-11T10:19:11.871791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile30
Q130
median30
Q330
95-th percentile30
Maximum3050
Range3030
Interquartile range (IQR)0

Descriptive statistics

Standard deviation90.385612
Coefficient of variation (CV)2.6986067
Kurtosis1109.6109
Mean33.493437
Median Absolute Deviation (MAD)0
Skewness33.298454
Sum112270
Variance8169.5589
MonotonicityNot monotonic
2024-05-11T10:19:12.469051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
30 3206
95.6%
50 96
 
2.9%
40 28
 
0.8%
60 16
 
0.5%
20 3
 
0.1%
3050 3
 
0.1%
ValueCountFrequency (%)
20 3
 
0.1%
30 3206
95.6%
40 28
 
0.8%
50 96
 
2.9%
60 16
 
0.5%
3050 3
 
0.1%
ValueCountFrequency (%)
3050 3
 
0.1%
60 16
 
0.5%
50 96
 
2.9%
40 28
 
0.8%
30 3206
95.6%
20 3
 
0.1%

관리기관명
Text

Distinct200
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size26.3 KiB
2024-05-11T10:19:13.390086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length9.1825776
Min length4

Characters and Unicode

Total characters30780
Distinct characters140
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

Unique16 ?
Unique (%)0.5%

Sample

1st row경상북도 상주시
2nd row경상북도 상주시
3rd row경상북도 상주시
4th row경상북도 상주시
5th row경상북도 상주시
ValueCountFrequency (%)
충청남도 667
 
9.9%
경기도 514
 
7.6%
경상북도 298
 
4.4%
충청북도 282
 
4.2%
인천광역시 172
 
2.5%
홍천군청 160
 
2.4%
강원도 155
 
2.3%
자치경찰단 152
 
2.2%
제주특별자치도 152
 
2.2%
서울특별시 146
 
2.2%
Other values (197) 4066
60.1%
2024-05-11T10:19:14.533783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3412
 
11.1%
청 3006
 
9.8%
도 2626
 
8.5%
시 2260
 
7.3%
경 1164
 
3.8%
충 1027
 
3.3%
군 992
 
3.2%
남 979
 
3.2%
광 787
 
2.6%
북 727
 
2.4%
Other values (130) 13800
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27368
88.9%
Space Separator 3412
 
11.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 3006
 
11.0%
도 2626
 
9.6%
시 2260
 
8.3%
경 1164
 
4.3%
충 1027
 
3.8%
군 992
 
3.6%
남 979
 
3.6%
광 787
 
2.9%
북 727
 
2.7%
구 716
 
2.6%
Other values (129) 13084
47.8%
Space Separator
ValueCountFrequency (%)
3412
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27368
88.9%
Common 3412
 
11.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 3006
 
11.0%
도 2626
 
9.6%
시 2260
 
8.3%
경 1164
 
4.3%
충 1027
 
3.8%
군 992
 
3.6%
남 979
 
3.6%
광 787
 
2.9%
북 727
 
2.7%
구 716
 
2.6%
Other values (129) 13084
47.8%
Common
ValueCountFrequency (%)
3412
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27368
88.9%
ASCII 3412
 
11.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3412
100.0%
Hangul
ValueCountFrequency (%)
청 3006
 
11.0%
도 2626
 
9.6%
시 2260
 
8.3%
경 1164
 
4.3%
충 1027
 
3.8%
군 992
 
3.6%
남 979
 
3.6%
광 787
 
2.9%
북 727
 
2.7%
구 716
 
2.6%
Other values (129) 13084
47.8%

관리기관전화번호
Text

Distinct279
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size26.3 KiB
2024-05-11T10:19:15.144065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.023866
Min length11

Characters and Unicode

Total characters40304
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

Unique91 ?
Unique (%)2.7%

Sample

1st row054-537-7548
2nd row054-537-7548
3rd row054-537-7548
4th row054-537-7548
5th row054-537-7548
ValueCountFrequency (%)
033-430-2102 160
 
4.8%
064-710-6413 152
 
4.5%
041-660-2735 107
 
3.2%
041-930-3981 91
 
2.7%
062-613-4488 79
 
2.4%
054-537-7548 79
 
2.4%
043-850-6333 78
 
2.3%
041-750-2713 78
 
2.3%
043-871-3873 70
 
2.1%
041-540-2737 68
 
2.0%
Other values (269) 2390
71.3%
2024-05-11T10:19:16.230563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 6704
16.6%
0 6026
15.0%
3 5404
13.4%
4 4246
10.5%
2 3534
8.8%
1 3097
7.7%
5 3061
7.6%
8 2397
 
5.9%
6 2388
 
5.9%
7 1991
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33600
83.4%
Dash Punctuation 6704
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6026
17.9%
3 5404
16.1%
4 4246
12.6%
2 3534
10.5%
1 3097
9.2%
5 3061
9.1%
8 2397
 
7.1%
6 2388
 
7.1%
7 1991
 
5.9%
9 1456
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 6704
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 40304
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 6704
16.6%
0 6026
15.0%
3 5404
13.4%
4 4246
10.5%
2 3534
8.8%
1 3097
7.7%
5 3061
7.6%
8 2397
 
5.9%
6 2388
 
5.9%
7 1991
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40304
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 6704
16.6%
0 6026
15.0%
3 5404
13.4%
4 4246
10.5%
2 3534
8.8%
1 3097
7.7%
5 3061
7.6%
8 2397
 
5.9%
6 2388
 
5.9%
7 1991
 
4.9%

관할경찰서명
Text

Distinct204
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size26.3 KiB
2024-05-11T10:19:16.815302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length5
Mean length6.0548926
Min length5

Characters and Unicode

Total characters20296
Distinct characters132
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

Unique12 ?
Unique (%)0.4%

Sample

1st row상주경찰서
2nd row상주경찰서
3rd row상주경찰서
4th row상주경찰서
5th row상주경찰서
ValueCountFrequency (%)
홍천경찰서 160
 
4.5%
서산경찰서 107
 
3.0%
대전광역시 100
 
2.8%
충남보령경찰서 91
 
2.5%
충남금산경찰서 80
 
2.2%
상주경찰서 79
 
2.2%
충주경찰서 78
 
2.2%
음성경찰서 70
 
2.0%
서부경찰서 70
 
2.0%
충남아산경찰서 68
 
1.9%
Other values (196) 2669
74.7%
2024-05-11T10:19:17.676526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
서 3907
19.3%
경 3428
16.9%
찰 3344
16.5%
부 679
 
3.3%
산 623
 
3.1%
주 532
 
2.6%
남 505
 
2.5%
천 502
 
2.5%
충 474
 
2.3%
성 317
 
1.6%
Other values (122) 5985
29.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20076
98.9%
Space Separator 220
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 3907
19.5%
경 3428
17.1%
찰 3344
16.7%
부 679
 
3.4%
산 623
 
3.1%
주 532
 
2.6%
남 505
 
2.5%
천 502
 
2.5%
충 474
 
2.4%
성 317
 
1.6%
Other values (121) 5765
28.7%
Space Separator
ValueCountFrequency (%)
220
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20076
98.9%
Common 220
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 3907
19.5%
경 3428
17.1%
찰 3344
16.7%
부 679
 
3.4%
산 623
 
3.1%
주 532
 
2.6%
남 505
 
2.5%
천 502
 
2.5%
충 474
 
2.4%
성 317
 
1.6%
Other values (121) 5765
28.7%
Common
ValueCountFrequency (%)
220
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20076
98.9%
ASCII 220
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
서 3907
19.5%
경 3428
17.1%
찰 3344
16.7%
부 679
 
3.4%
산 623
 
3.1%
주 532
 
2.6%
남 505
 
2.5%
천 502
 
2.5%
충 474
 
2.4%
성 317
 
1.6%
Other values (121) 5765
28.7%
ASCII
ValueCountFrequency (%)
220
100.0%

CCTV설치여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
False
2715 
True
637 
ValueCountFrequency (%)
False 2715
81.0%
True 637
 
19.0%
2024-05-11T10:19:18.007848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

CCTV설치대수
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct13
Distinct (%)0.9%
Missing1970
Missing (%)58.8%
Infinite0
Infinite (%)0.0%
Mean0.7105644
Minimum0
Maximum12
Zeros843
Zeros (%)25.1%
Negative0
Negative (%)0.0%
Memory size29.6 KiB
2024-05-11T10:19:18.400024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum12
Range12
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3428346
Coefficient of variation (CV)1.8898141
Kurtosis18.465609
Mean0.7105644
Median Absolute Deviation (MAD)0
Skewness3.6410138
Sum982
Variance1.8032048
MonotonicityNot monotonic
2024-05-11T10:19:18.796868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 843
25.1%
1 338
 
10.1%
2 112
 
3.3%
3 31
 
0.9%
4 27
 
0.8%
5 13
 
0.4%
8 5
 
0.1%
10 4
 
0.1%
7 3
 
0.1%
9 2
 
0.1%
Other values (3) 4
 
0.1%
(Missing) 1970
58.8%
ValueCountFrequency (%)
0 843
25.1%
1 338
10.1%
2 112
 
3.3%
3 31
 
0.9%
4 27
 
0.8%
5 13
 
0.4%
6 2
 
0.1%
7 3
 
0.1%
8 5
 
0.1%
9 2
 
0.1%
ValueCountFrequency (%)
12 1
 
< 0.1%
11 1
 
< 0.1%
10 4
 
0.1%
9 2
 
0.1%
8 5
 
0.1%
7 3
 
0.1%
6 2
 
0.1%
5 13
0.4%
4 27
0.8%
3 31
0.9%

보호구역도로폭
Text

MISSING 

Distinct115
Distinct (%)6.1%
Missing1466
Missing (%)43.7%
Memory size26.3 KiB
2024-05-11T10:19:19.278705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.8430541
Min length1

Characters and Unicode

Total characters3476
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)2.6%

Sample

1st row3
2nd row16~20
3rd row16~20
4th row16~20
5th row8.5
ValueCountFrequency (%)
6 392
20.8%
8 314
16.6%
7 240
12.7%
7~11 165
8.7%
10 86
 
4.6%
6.5 75
 
4.0%
6~8 64
 
3.4%
4 63
 
3.3%
3 45
 
2.4%
5 39
 
2.1%
Other values (105) 403
21.4%
2024-05-11T10:19:20.194352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 665
19.1%
6 586
16.9%
8 445
12.8%
7 430
12.4%
~ 368
10.6%
5 245
 
7.0%
0 197
 
5.7%
2 163
 
4.7%
4 121
 
3.5%
. 120
 
3.5%
Other values (3) 136
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2985
85.9%
Math Symbol 368
 
10.6%
Other Punctuation 120
 
3.5%
Lowercase Letter 3
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 665
22.3%
6 586
19.6%
8 445
14.9%
7 430
14.4%
5 245
 
8.2%
0 197
 
6.6%
2 163
 
5.5%
4 121
 
4.1%
3 103
 
3.5%
9 30
 
1.0%
Math Symbol
ValueCountFrequency (%)
~ 368
100.0%
Other Punctuation
ValueCountFrequency (%)
. 120
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3473
99.9%
Latin 3
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 665
19.1%
6 586
16.9%
8 445
12.8%
7 430
12.4%
~ 368
10.6%
5 245
 
7.1%
0 197
 
5.7%
2 163
 
4.7%
4 121
 
3.5%
. 120
 
3.5%
Other values (2) 133
 
3.8%
Latin
ValueCountFrequency (%)
m 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3476
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 665
19.1%
6 586
16.9%
8 445
12.8%
7 430
12.4%
~ 368
10.6%
5 245
 
7.0%
0 197
 
5.7%
2 163
 
4.7%
4 121
 
3.5%
. 120
 
3.5%
Other values (3) 136
 
3.9%

데이터기준일자
Date

Distinct139
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size26.3 KiB
Minimum2021-06-01 00:00:00
Maximum2024-04-17 00:00:00
2024-05-11T10:19:20.594842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:19:21.014179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

제공기관코드
Real number (ℝ)

HIGH CORRELATION 

Distinct193
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4504198.4
Minimum3000000
Maximum6500000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.6 KiB
2024-05-11T10:19:21.377270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3260000
Q13990000
median4470000
Q35020000
95-th percentile6290000
Maximum6500000
Range3500000
Interquartile range (IQR)1030000

Descriptive statistics

Standard deviation812374.72
Coefficient of variation (CV)0.18035944
Kurtosis0.15172983
Mean4504198.4
Median Absolute Deviation (MAD)540000
Skewness0.62315696
Sum1.5098073 × 1010
Variance6.5995268 × 1011
MonotonicityNot monotonic
2024-05-11T10:19:21.761657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6500000 152
 
4.5%
4530000 107
 
3.2%
4510000 91
 
2.7%
4251000 80
 
2.4%
4550000 80
 
2.4%
4250000 80
 
2.4%
5110000 79
 
2.4%
4390000 78
 
2.3%
4470000 70
 
2.1%
4520000 68
 
2.0%
Other values (183) 2467
73.6%
ValueCountFrequency (%)
3000000 6
0.2%
3020000 5
0.1%
3030000 4
 
0.1%
3040000 5
0.1%
3050000 9
0.3%
3060000 3
 
0.1%
3070000 7
0.2%
3080000 2
 
0.1%
3100000 6
0.2%
3110000 10
0.3%
ValueCountFrequency (%)
6500000 152
4.5%
6290000 67
2.0%
5700000 8
 
0.2%
5690000 9
 
0.3%
5680000 67
2.0%
5670000 14
 
0.4%
5600000 15
 
0.4%
5590000 25
 
0.7%
5570000 1
 
< 0.1%
5540000 19
 
0.6%

제공기관명
Text

Distinct193
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size26.3 KiB
2024-05-11T10:19:22.328279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length8.0528043
Min length5

Characters and Unicode

Total characters26993
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

Unique16 ?
Unique (%)0.5%

Sample

1st row경상북도 상주시
2nd row경상북도 상주시
3rd row경상북도 상주시
4th row경상북도 상주시
5th row경상북도 상주시
ValueCountFrequency (%)
충청남도 667
 
10.3%
경기도 514
 
7.9%
충청북도 300
 
4.6%
경상북도 298
 
4.6%
인천광역시 172
 
2.7%
강원특별자치도 170
 
2.6%
강원도 165
 
2.5%
서울특별시 165
 
2.5%
홍천군 160
 
2.5%
제주특별자치도 152
 
2.3%
Other values (166) 3713
57.3%
2024-05-11T10:19:23.520267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3124
 
11.6%
도 2584
 
9.6%
시 2323
 
8.6%
충 1045
 
3.9%
청 1026
 
3.8%
군 1010
 
3.7%
경 1000
 
3.7%
남 979
 
3.6%
광 787
 
2.9%
북 745
 
2.8%
Other values (113) 12370
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23869
88.4%
Space Separator 3124
 
11.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 2584
 
10.8%
시 2323
 
9.7%
충 1045
 
4.4%
청 1026
 
4.3%
군 1010
 
4.2%
경 1000
 
4.2%
남 979
 
4.1%
광 787
 
3.3%
북 745
 
3.1%
주 679
 
2.8%
Other values (112) 11691
49.0%
Space Separator
ValueCountFrequency (%)
3124
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23869
88.4%
Common 3124
 
11.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 2584
 
10.8%
시 2323
 
9.7%
충 1045
 
4.4%
청 1026
 
4.3%
군 1010
 
4.2%
경 1000
 
4.2%
남 979
 
4.1%
광 787
 
3.3%
북 745
 
3.1%
주 679
 
2.8%
Other values (112) 11691
49.0%
Common
ValueCountFrequency (%)
3124
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23869
88.4%
ASCII 3124
 
11.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3124
100.0%
Hangul
ValueCountFrequency (%)
도 2584
 
10.8%
시 2323
 
9.7%
충 1045
 
4.4%
청 1026
 
4.3%
군 1010
 
4.2%
경 1000
 
4.2%
남 979
 
4.1%
광 787
 
3.3%
북 745
 
3.1%
주 679
 
2.8%
Other values (112) 11691
49.0%

Interactions

2024-05-11T10:18:52.934201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:42.809245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:45.296459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:47.045316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:48.713463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:50.664636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:53.228417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:43.175808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:45.605839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:47.312510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:48.966199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:51.034591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:53.563139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:43.667627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:45.957038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:47.594129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:49.242101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:51.439837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:53.900801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:44.124464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:46.274885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:47.978244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:49.538201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:51.826485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:54.227691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:44.472066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:46.492485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:48.180640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:49.875582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:52.219846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:54.585599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:44.878549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:46.765471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:48.424159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:50.308024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:18:52.598328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T10:19:23.916386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
장소유형코드시도명시군구코드위도경도제한속도CCTV설치여부CCTV설치대수제공기관코드
장소유형코드1.0000.2500.1700.2160.2970.0690.0000.0000.187
시도명0.2501.0000.9490.9280.8500.1240.4400.4650.960
시군구코드0.1700.9491.0000.8680.5540.1320.3650.3180.844
위도0.2160.9280.8681.0000.5510.0290.2730.2620.888
경도0.2970.8500.5540.5511.0000.0000.3400.2010.636
제한속도0.0690.1240.1320.0290.0001.0000.0720.0000.108
CCTV설치여부0.0000.4400.3650.2730.3400.0721.0000.6570.328
CCTV설치대수0.0000.4650.3180.2620.2010.0000.6571.0000.430
제공기관코드0.1870.9600.8440.8880.6360.1080.3280.4301.000
2024-05-11T10:19:24.369777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도명장소유형코드CCTV설치여부
시도명1.0000.2210.390
장소유형코드0.2211.0000.000
CCTV설치여부0.3900.0001.000
2024-05-11T10:19:24.745797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구코드위도경도제한속도CCTV설치대수제공기관코드장소유형코드시도명CCTV설치여부
시군구코드1.000-0.3450.045-0.050-0.2980.7660.1700.7730.358
위도-0.3451.000-0.025-0.052-0.214-0.4560.2160.7100.272
경도0.045-0.0251.000-0.043-0.307-0.0950.2280.5280.260
제한속도-0.050-0.052-0.0431.0000.101-0.0410.0440.1090.046
CCTV설치대수-0.298-0.214-0.3070.1011.000-0.0490.0000.1920.509
제공기관코드0.766-0.456-0.095-0.041-0.0491.0000.1860.8090.332
장소유형코드0.1700.2160.2280.0440.0000.1861.0000.2210.000
시도명0.7730.7100.5280.1090.1920.8090.2211.0000.390
CCTV설치여부0.3580.2720.2600.0460.5090.3320.0000.3901.000

Missing values

2024-05-11T10:18:55.103713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T10:18:56.029891image/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.
2024-05-11T10:18:56.620324image/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

장소유형코드대상시설명시도명시군구명시군구코드소재지도로명주소소재지지번주소위도경도제한속도관리기관명관리기관전화번호관할경찰서명CCTV설치여부CCTV설치대수보호구역도로폭데이터기준일자제공기관코드제공기관명
01대포1리 경로당경상북도상주시47250경상북도 상주시 모서면 대포1길 16경상북도 상주시 모서면 대포리 796-136.356237128.01451530경상북도 상주시054-537-7548상주경찰서N<NA><NA>2022-11-165110000경상북도 상주시
11상촌1리 마을회관경상북도상주시47250경상북도 상주시 함창읍 용곡로 351경상북도 상주시 함창읍 신흥리 331-1636.541398128.19360530경상북도 상주시054-537-7548상주경찰서N<NA><NA>2022-11-165110000경상북도 상주시
21북장리 경로당경상북도상주시47250경상북도 상주시 모서면 대포1길 12-2경상북도 상주시 모서면 대포리 142-636.356326128.01392230경상북도 상주시054-537-7548상주경찰서N<NA><NA>2022-11-165110000경상북도 상주시
31북장리 팔각정경상북도상주시47250경상북도 상주시 낙동면 삼봉로 360-1경상북도 상주시 낙동면 상촌리 885-336.369854128.24614130경상북도 상주시054-537-7548상주경찰서N<NA><NA>2022-11-165110000경상북도 상주시
41북장리(사기점) 경로당경상북도상주시47250경상북도 상주시 내서면 북장1길 17경상북도 상주시 내서면 북장리 487-7036.421691128.06167830경상북도 상주시054-537-7548상주경찰서N<NA><NA>2022-11-165110000경상북도 상주시
51하덕가 경로당경상북도상주시47250경상북도 상주시 사벌국면 사벌로 362경상북도 상주시 사벌국면 덕가리 872-7436.496835128.20197130경상북도 상주시054-537-7548상주경찰서N<NA><NA>2022-11-165110000경상북도 상주시
61초산6통 경로당경상북도상주시47250경상북도 상주시 내서면 북장1길 98경상북도 상주시 내서면 북장리 216-336.426622128.06763630경상북도 상주시054-537-7548상주경찰서N<NA><NA>2022-11-165110000경상북도 상주시
71우기2리 마을회관경상북도상주시47250경상북도 상주시 은척면 우기2길 8-1경상북도 상주시 은척면 우기리 18436.546178128.0769430경상북도 상주시054-537-7548상주경찰서N<NA><NA>2022-11-165110000경상북도 상주시
81장암1리 마을회관경상북도상주시47250경상북도 상주시 화북면 문장대2길 26경상북도 상주시 화북면 장암리 20736.570257127.90799930경상북도 상주시054-537-7548상주경찰서N<NA><NA>2022-11-165110000경상북도 상주시
91백학2리 경로당경상북도상주시47250경상북도 상주시 모서면 백학2길 6경상북도 상주시 모서면 백학리 34236.322285127.88945730경상북도 상주시054-537-7548상주경찰서N<NA><NA>2022-11-165110000경상북도 상주시
장소유형코드대상시설명시도명시군구명시군구코드소재지도로명주소소재지지번주소위도경도제한속도관리기관명관리기관전화번호관할경찰서명CCTV설치여부CCTV설치대수보호구역도로폭데이터기준일자제공기관코드제공기관명
33421노인종합복지관경상남도김해시48250경상남도 김해시 김해대로 1902번길 12경상남도 김해시 구산동 75635.256372128.86479230경상남도 김해시청055-330-4668김해중부경찰서N0<NA>2024-01-055350000경상남도 김해시
33431동부치매안심센터경상남도김해시48250경상남도 김해시 분성로727번길 8-33경상남도 김해시 지내동 327-235.230025128.92244530경상남도 김해시청055-330-4668김해중부경찰서Y1<NA>2024-01-055350000경상남도 김해시
33441김해시립요양원경상남도김해시48250경상남도 김해시 대동면 대동로 62경상남도 김해시 대동면 수안리 349-1735.224192128.93262430경상남도 김해시청055-330-4668김해중부경찰서N0<NA>2024-01-055350000경상남도 김해시
33451장유더샵아파트 경로당경상남도김해시48250경상남도 김해시 장유로288번길 13경상남도 김해시 무계동 288-235.199309128.81389830경상남도 김해시청055-330-4668김해서부경찰서N0<NA>2024-01-055350000경상남도 김해시
33461어은경로당경상남도김해시48250경상남도 김해시 한림면 한림로252번길 58경상남도 김해시 한림면 안하리 977-135.314542128.81412130경상남도 김해시청055-330-4668김해서부경찰서N0<NA>2024-01-055350000경상남도 김해시
33471대현경로당경상남도김해시48250경상남도 김해시 한림면 장방로 87경상남도 김해시 한림면 가산리 608-335.321155128.76538230경상남도 김해시청055-330-4668김해서부경찰서N0<NA>2024-01-055350000경상남도 김해시
33481곡성읍 사회복지회관전라남도곡성군48600전라남도 곡성군 곡성읍 읍내14길 14전라남도 곡성군 곡성읍 읍내리 261-935.280299127.29635730전라남도 곡성군061-360-2671곡성경찰서N<NA><NA>2023-12-014860000전라남도 곡성군
33491목사동면 노인분회전라남도곡성군48600전라남도 곡성군 목사동면 주목로 756전라남도 곡성군 목사동면 평리 257-435.12034127.3003930전라남도 곡성군061-360-2671곡성경찰서N<NA><NA>2023-12-014860000전라남도 곡성군
33502곡성삼강원전라남도곡성군48600전라남도 곡성군 곡성읍 중앙로 33전라남도 곡성군 곡성읍 죽동리 6-235.278779127.28700630전라남도 곡성군061-360-2671곡성경찰서N<NA><NA>2023-12-014860000전라남도 곡성군
33511순창군장애인노인종합복지관전라북도순창군47700전라북도 순창군 순창읍 순창5길 11-4전라북도 순창군 순창읍 남계리 62635.37301127.14095930전라북도 순창군063-650-1283순창경찰서Y142022-06-154771000전북특별자치도 순창군