Overview

Dataset statistics

Number of variables18
Number of observations347
Missing cells7
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory51.3 KiB
Average record size in memory151.4 B

Variable types

Text9
Categorical4
Numeric5

Dataset

Description서비스 id,시설코드,시군구 코드,시군구명,읍면동 코드,읍면동명,관리기관,전화번호,경도,위도,세부위치,운영시간,운영요일,안심귀갓길 id,안심귀갓길 명,비고,데이터 기준일자,이미지명
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21697/S/1/datasetView.do

Alerts

운영요일 has constant value ""Constant
시군구 코드 is highly overall correlated with 읍면동 코드 and 2 other fieldsHigh correlation
읍면동 코드 is highly overall correlated with 시군구 코드 and 2 other fieldsHigh correlation
경도 is highly overall correlated with 시군구명High correlation
위도 is highly overall correlated with 시군구 코드 and 2 other fieldsHigh correlation
시군구명 is highly overall correlated with 시군구 코드 and 3 other fieldsHigh correlation
운영시간 is highly imbalanced (87.4%)Imbalance
비고 has 7 (2.0%) missing valuesMissing
서비스 id has unique valuesUnique
위도 has unique valuesUnique
세부위치 has unique valuesUnique
이미지명 has unique valuesUnique

Reproduction

Analysis started2023-12-11 10:04:00.344541
Analysis finished2023-12-11 10:04:04.076620
Duration3.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

서비스 id
Text

UNIQUE 

Distinct347
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2023-12-11T19:04:04.212189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters5899
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique347 ?
Unique (%)100.0%

Sample

1st row1111017400_06_S01
2nd row1111017400_06_S02
3rd row1111017400_06_S03
4th row1114016500_08_S01
5th row1114016200_05_S01
ValueCountFrequency (%)
1111017400_06_s01 1
 
0.3%
1153010200_01_s01 1
 
0.3%
1121510100_07_s01 1
 
0.3%
1121510100_08_s02 1
 
0.3%
1121510100_08_s01 1
 
0.3%
1121510500_09_s01 1
 
0.3%
1121510500_10_s01 1
 
0.3%
1121510500_11_s01 1
 
0.3%
1121510500_12_s02 1
 
0.3%
1121510700_01_s01 1
 
0.3%
Other values (337) 337
97.1%
2023-12-11T19:04:04.493262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1878
31.8%
1 1574
26.7%
_ 694
 
11.8%
S 347
 
5.9%
2 311
 
5.3%
3 244
 
4.1%
5 222
 
3.8%
4 174
 
2.9%
6 150
 
2.5%
7 122
 
2.1%
Other values (2) 183
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4858
82.4%
Connector Punctuation 694
 
11.8%
Uppercase Letter 347
 
5.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1878
38.7%
1 1574
32.4%
2 311
 
6.4%
3 244
 
5.0%
5 222
 
4.6%
4 174
 
3.6%
6 150
 
3.1%
7 122
 
2.5%
8 94
 
1.9%
9 89
 
1.8%
Connector Punctuation
ValueCountFrequency (%)
_ 694
100.0%
Uppercase Letter
ValueCountFrequency (%)
S 347
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5552
94.1%
Latin 347
 
5.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1878
33.8%
1 1574
28.4%
_ 694
 
12.5%
2 311
 
5.6%
3 244
 
4.4%
5 222
 
4.0%
4 174
 
3.1%
6 150
 
2.7%
7 122
 
2.2%
8 94
 
1.7%
Latin
ValueCountFrequency (%)
S 347
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5899
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1878
31.8%
1 1574
26.7%
_ 694
 
11.8%
S 347
 
5.9%
2 311
 
5.3%
3 244
 
4.1%
5 222
 
3.8%
4 174
 
2.9%
6 150
 
2.5%
7 122
 
2.1%
Other values (2) 183
 
3.1%

시설코드
Categorical

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
402
203 
401
139 
403
 
5

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row402
2nd row402
3rd row402
4th row402
5th row402

Common Values

ValueCountFrequency (%)
402 203
58.5%
401 139
40.1%
403 5
 
1.4%

Length

2023-12-11T19:04:04.602530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T19:04:04.700253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
402 203
58.5%
401 139
40.1%
403 5
 
1.4%

시군구 코드
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1441772 × 109
Minimum1.111 × 109
Maximum1.174 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-11T19:04:04.789888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111 × 109
5-th percentile1.114 × 109
Q11.1275 × 109
median1.15 × 109
Q31.162 × 109
95-th percentile1.171 × 109
Maximum1.174 × 109
Range63000000
Interquartile range (IQR)34500000

Descriptive statistics

Standard deviation19725819
Coefficient of variation (CV)0.017240178
Kurtosis-1.3902826
Mean1.1441772 × 109
Median Absolute Deviation (MAD)18000000
Skewness-0.11135209
Sum3.970295 × 1011
Variance3.8910795 × 1014
MonotonicityNot monotonic
2023-12-11T19:04:04.902073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1162000000 27
 
7.8%
1117000000 22
 
6.3%
1130500000 20
 
5.8%
1150000000 20
 
5.8%
1168000000 20
 
5.8%
1165000000 19
 
5.5%
1171000000 19
 
5.5%
1121500000 18
 
5.2%
1129000000 17
 
4.9%
1159000000 17
 
4.9%
Other values (14) 148
42.7%
ValueCountFrequency (%)
1111000000 11
3.2%
1114000000 13
3.7%
1117000000 22
6.3%
1120000000 6
 
1.7%
1121500000 18
5.2%
1123000000 11
3.2%
1126000000 6
 
1.7%
1129000000 17
4.9%
1130500000 20
5.8%
1132000000 14
4.0%
ValueCountFrequency (%)
1174000000 16
4.6%
1171000000 19
5.5%
1168000000 20
5.8%
1165000000 19
5.5%
1162000000 27
7.8%
1159000000 17
4.9%
1156000000 8
 
2.3%
1154500000 15
4.3%
1153000000 13
3.7%
1150000000 20
5.8%

시군구명
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
서울특별시 관악구
27 
서울특별시 용산구
 
22
서울특별시 강남구
 
20
서울특별시 강북구
 
20
서울특별시 강서구
 
20
Other values (19)
238 

Length

Max length10
Median length9
Mean length9.0317003
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시 종로구
2nd row서울특별시 종로구
3rd row서울특별시 종로구
4th row서울특별시 중구
5th row서울특별시 중구

Common Values

ValueCountFrequency (%)
서울특별시 관악구 27
 
7.8%
서울특별시 용산구 22
 
6.3%
서울특별시 강남구 20
 
5.8%
서울특별시 강북구 20
 
5.8%
서울특별시 강서구 20
 
5.8%
서울특별시 서초구 19
 
5.5%
서울특별시 송파구 19
 
5.5%
서울특별시 광진구 18
 
5.2%
서울특별시 성북구 17
 
4.9%
서울특별시 동작구 17
 
4.9%
Other values (14) 148
42.7%

Length

2023-12-11T19:04:05.031955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 347
50.0%
관악구 27
 
3.9%
용산구 22
 
3.2%
강남구 20
 
2.9%
강북구 20
 
2.9%
강서구 20
 
2.9%
서초구 19
 
2.7%
송파구 19
 
2.7%
광진구 18
 
2.6%
성북구 17
 
2.4%
Other values (15) 165
23.8%

읍면동 코드
Real number (ℝ)

HIGH CORRELATION 

Distinct130
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1441883 × 109
Minimum1.111011 × 109
Maximum1.1740109 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-11T19:04:05.141935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111011 × 109
5-th percentile1.1140145 × 109
Q11.1275102 × 109
median1.1500102 × 109
Q31.1620102 × 109
95-th percentile1.1710113 × 109
Maximum1.1740109 × 109
Range62999900
Interquartile range (IQR)34500050

Descriptive statistics

Standard deviation19725122
Coefficient of variation (CV)0.017239402
Kurtosis-1.3903483
Mean1.1441883 × 109
Median Absolute Deviation (MAD)17999900
Skewness-0.11129603
Sum3.9703335 × 1011
Variance3.8908044 × 1014
MonotonicityNot monotonic
2023-12-11T19:04:05.266245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1162010200 17
 
4.9%
1150010300 14
 
4.0%
1130510300 12
 
3.5%
1154510200 9
 
2.6%
1168010100 8
 
2.3%
1153010200 8
 
2.3%
1162010100 7
 
2.0%
1132010700 7
 
2.0%
1174010900 7
 
2.0%
1123010600 6
 
1.7%
Other values (120) 252
72.6%
ValueCountFrequency (%)
1111011000 1
 
0.3%
1111011100 1
 
0.3%
1111011300 2
0.6%
1111011400 1
 
0.3%
1111016400 3
0.9%
1111017300 1
 
0.3%
1111018300 1
 
0.3%
1111018500 1
 
0.3%
1114012300 1
 
0.3%
1114012900 1
 
0.3%
ValueCountFrequency (%)
1174010900 7
2.0%
1174010800 2
 
0.6%
1174010700 3
0.9%
1174010500 3
0.9%
1174010100 1
 
0.3%
1171011400 1
 
0.3%
1171011300 2
 
0.6%
1171011200 2
 
0.6%
1171010700 1
 
0.3%
1171010600 3
0.9%

읍면동명
Text

Distinct130
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2023-12-11T19:04:05.514800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.1412104
Min length2

Characters and Unicode

Total characters1090
Distinct characters143
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

Unique57 ?
Unique (%)16.4%

Sample

1st row종로6가
2nd row종로6가
3rd row종로6가
4th row황학동
5th row신당동
ValueCountFrequency (%)
신림동 17
 
4.9%
화곡동 14
 
4.0%
수유동 12
 
3.5%
독산동 9
 
2.6%
역삼동 8
 
2.3%
구로동 8
 
2.3%
봉천동 7
 
2.0%
천호동 7
 
2.0%
창동 7
 
2.0%
잠실동 6
 
1.7%
Other values (120) 252
72.6%
2023-12-11T19:04:05.875960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 339
31.1%
가 32
 
2.9%
신 27
 
2.5%
화 22
 
2.0%
곡 21
 
1.9%
림 21
 
1.9%
산 16
 
1.5%
로 16
 
1.5%
삼 15
 
1.4%
천 15
 
1.4%
Other values (133) 566
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1065
97.7%
Decimal Number 25
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 339
31.8%
가 32
 
3.0%
신 27
 
2.5%
화 22
 
2.1%
곡 21
 
2.0%
림 21
 
2.0%
산 16
 
1.5%
로 16
 
1.5%
삼 15
 
1.4%
천 15
 
1.4%
Other values (127) 541
50.8%
Decimal Number
ValueCountFrequency (%)
2 11
44.0%
3 5
20.0%
1 3
 
12.0%
6 3
 
12.0%
5 2
 
8.0%
4 1
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1065
97.7%
Common 25
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 339
31.8%
가 32
 
3.0%
신 27
 
2.5%
화 22
 
2.1%
곡 21
 
2.0%
림 21
 
2.0%
산 16
 
1.5%
로 16
 
1.5%
삼 15
 
1.4%
천 15
 
1.4%
Other values (127) 541
50.8%
Common
ValueCountFrequency (%)
2 11
44.0%
3 5
20.0%
1 3
 
12.0%
6 3
 
12.0%
5 2
 
8.0%
4 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1065
97.7%
ASCII 25
 
2.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 339
31.8%
가 32
 
3.0%
신 27
 
2.5%
화 22
 
2.1%
곡 21
 
2.0%
림 21
 
2.0%
산 16
 
1.5%
로 16
 
1.5%
삼 15
 
1.4%
천 15
 
1.4%
Other values (127) 541
50.8%
ASCII
ValueCountFrequency (%)
2 11
44.0%
3 5
20.0%
1 3
 
12.0%
6 3
 
12.0%
5 2
 
8.0%
4 1
 
4.0%

관리기관
Text

Distinct102
Distinct (%)29.4%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2023-12-11T19:04:06.121024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length5
Mean length6.6368876
Min length4

Characters and Unicode

Total characters2303
Distinct characters165
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)16.7%

Sample

1st row혜화경찰서
2nd row혜화경찰서
3rd row혜화경찰서
4th row중부(광희)지구대
5th row중부(약수)지구대
ValueCountFrequency (%)
스마트큐브 62
 
14.2%
여성가족과 32
 
7.3%
서울특별시 31
 
7.1%
관악경찰서 19
 
4.4%
강남경찰서 18
 
4.1%
강서경찰서 10
 
2.3%
서울마포경찰서 10
 
2.3%
강북구 10
 
2.3%
서초경찰서 10
 
2.3%
강북경찰서 10
 
2.3%
Other values (105) 224
51.4%
2023-12-11T19:04:06.501958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
서 207
 
9.0%
경 135
 
5.9%
찰 135
 
5.9%
구 91
 
4.0%
89
 
3.9%
마 74
 
3.2%
스 65
 
2.8%
트 63
 
2.7%
브 62
 
2.7%
큐 62
 
2.7%
Other values (155) 1320
57.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2158
93.7%
Space Separator 89
 
3.9%
Decimal Number 22
 
1.0%
Uppercase Letter 14
 
0.6%
Open Punctuation 8
 
0.3%
Close Punctuation 8
 
0.3%
Other Symbol 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 207
 
9.6%
경 135
 
6.3%
찰 135
 
6.3%
구 91
 
4.2%
마 74
 
3.4%
스 65
 
3.0%
트 63
 
2.9%
브 62
 
2.9%
큐 62
 
2.9%
대 62
 
2.9%
Other values (141) 1202
55.7%
Decimal Number
ValueCountFrequency (%)
2 7
31.8%
1 6
27.3%
5 4
18.2%
0 2
 
9.1%
3 2
 
9.1%
4 1
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
G 4
28.6%
S 4
28.6%
C 3
21.4%
U 3
21.4%
Space Separator
ValueCountFrequency (%)
89
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2162
93.9%
Common 127
 
5.5%
Latin 14
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 207
 
9.6%
경 135
 
6.2%
찰 135
 
6.2%
구 91
 
4.2%
마 74
 
3.4%
스 65
 
3.0%
트 63
 
2.9%
브 62
 
2.9%
큐 62
 
2.9%
대 62
 
2.9%
Other values (142) 1206
55.8%
Common
ValueCountFrequency (%)
89
70.1%
( 8
 
6.3%
) 8
 
6.3%
2 7
 
5.5%
1 6
 
4.7%
5 4
 
3.1%
0 2
 
1.6%
3 2
 
1.6%
4 1
 
0.8%
Latin
ValueCountFrequency (%)
G 4
28.6%
S 4
28.6%
C 3
21.4%
U 3
21.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2158
93.7%
ASCII 141
 
6.1%
None 4
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
서 207
 
9.6%
경 135
 
6.3%
찰 135
 
6.3%
구 91
 
4.2%
마 74
 
3.4%
스 65
 
3.0%
트 63
 
2.9%
브 62
 
2.9%
큐 62
 
2.9%
대 62
 
2.9%
Other values (141) 1202
55.7%
ASCII
ValueCountFrequency (%)
89
63.1%
( 8
 
5.7%
) 8
 
5.7%
2 7
 
5.0%
1 6
 
4.3%
G 4
 
2.8%
S 4
 
2.8%
5 4
 
2.8%
C 3
 
2.1%
U 3
 
2.1%
Other values (3) 5
 
3.5%
None
ValueCountFrequency (%)
㈜ 4
100.0%

전화번호
Text

Distinct106
Distinct (%)30.5%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2023-12-11T19:04:06.793786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.118156
Min length3

Characters and Unicode

Total characters3858
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

Unique63 ?
Unique (%)18.2%

Sample

1st row02-762-4400
2nd row02-762-4400
3rd row02-762-4400
4th row02-2233-1444
5th row02-2234-8112
ValueCountFrequency (%)
02-1666-0339 46
 
13.3%
02-876-3021 19
 
5.5%
02-557-7000 18
 
5.2%
182 14
 
4.0%
02-450-7544 13
 
3.7%
02-901-6693 10
 
2.9%
02-532-0112 10
 
2.9%
02-2698-7000 10
 
2.9%
1566-0112 10
 
2.9%
02-2627-1438 9
 
2.6%
Other values (96) 188
54.2%
2023-12-11T19:04:07.209665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 678
17.6%
- 654
17.0%
2 632
16.4%
1 327
8.5%
3 327
8.5%
6 301
7.8%
4 251
 
6.5%
9 188
 
4.9%
7 180
 
4.7%
8 161
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3204
83.0%
Dash Punctuation 654
 
17.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 678
21.2%
2 632
19.7%
1 327
10.2%
3 327
10.2%
6 301
9.4%
4 251
 
7.8%
9 188
 
5.9%
7 180
 
5.6%
8 161
 
5.0%
5 159
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 654
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3858
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 678
17.6%
- 654
17.0%
2 632
16.4%
1 327
8.5%
3 327
8.5%
6 301
7.8%
4 251
 
6.5%
9 188
 
4.9%
7 180
 
4.7%
8 161
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3858
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 678
17.6%
- 654
17.0%
2 632
16.4%
1 327
8.5%
3 327
8.5%
6 301
7.8%
4 251
 
6.5%
9 188
 
4.9%
7 180
 
4.7%
8 161
 
4.2%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct344
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.99362
Minimum126.81007
Maximum127.14854
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-11T19:04:07.656064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.81007
5-th percentile126.85438
Q1126.92994
median127.00497
Q3127.04831
95-th percentile127.12504
Maximum127.14854
Range0.338466
Interquartile range (IQR)0.118372

Descriptive statistics

Standard deviation0.078428307
Coefficient of variation (CV)0.00061757674
Kurtosis-0.6795185
Mean126.99362
Median Absolute Deviation (MAD)0.06175
Skewness-0.16580463
Sum44066.787
Variance0.0061509993
MonotonicityNot monotonic
2023-12-11T19:04:07.793547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.93215 2
 
0.6%
127.02899 2
 
0.6%
127.06672 2
 
0.6%
126.8834 1
 
0.3%
127.0848 1
 
0.3%
127.09312 1
 
0.3%
127.09078 1
 
0.3%
127.08439 1
 
0.3%
127.07523 1
 
0.3%
127.07679 1
 
0.3%
Other values (334) 334
96.3%
ValueCountFrequency (%)
126.810074 1
0.3%
126.81331 1
0.3%
126.813545 1
0.3%
126.81398 1
0.3%
126.81784 1
0.3%
126.834724 1
0.3%
126.836494 1
0.3%
126.83702 1
0.3%
126.83919 1
0.3%
126.839874 1
0.3%
ValueCountFrequency (%)
127.14854 1
0.3%
127.147575 1
0.3%
127.14683 1
0.3%
127.14546 1
0.3%
127.1433 1
0.3%
127.14122 1
0.3%
127.13931 1
0.3%
127.13874 1
0.3%
127.13472 1
0.3%
127.13381 1
0.3%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct347
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.542598
Minimum37.440258
Maximum37.67869
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-11T19:04:07.954531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.440258
5-th percentile37.470199
Q137.499448
median37.540306
Q337.573952
95-th percentile37.638909
Maximum37.67869
Range0.238432
Interquartile range (IQR)0.0745045

Descriptive statistics

Standard deviation0.052910911
Coefficient of variation (CV)0.0014093567
Kurtosis-0.55293362
Mean37.542598
Median Absolute Deviation (MAD)0.037634
Skewness0.45625395
Sum13027.282
Variance0.0027995645
MonotonicityNot monotonic
2023-12-11T19:04:08.118694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.573204 1
 
0.3%
37.539402 1
 
0.3%
37.56067 1
 
0.3%
37.559338 1
 
0.3%
37.56778 1
 
0.3%
37.553093 1
 
0.3%
37.556965 1
 
0.3%
37.5288 1
 
0.3%
37.532898 1
 
0.3%
37.538708 1
 
0.3%
Other values (337) 337
97.1%
ValueCountFrequency (%)
37.440258 1
0.3%
37.452667 1
0.3%
37.452988 1
0.3%
37.453636 1
0.3%
37.457066 1
0.3%
37.45898 1
0.3%
37.46202 1
0.3%
37.463146 1
0.3%
37.467045 1
0.3%
37.46768 1
0.3%
ValueCountFrequency (%)
37.67869 1
0.3%
37.669678 1
0.3%
37.66931 1
0.3%
37.668716 1
0.3%
37.66742 1
0.3%
37.662876 1
0.3%
37.654167 1
0.3%
37.653217 1
0.3%
37.65301 1
0.3%
37.65222 1
0.3%

세부위치
Text

UNIQUE 

Distinct347
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2023-12-11T19:04:08.626274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length34
Mean length20.175793
Min length15

Characters and Unicode

Total characters7001
Distinct characters238
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

Unique347 ?
Unique (%)100.0%

Sample

1st row서울특별시 종로구 율곡로 271
2nd row서울특별시 종로구 종로39길 40
3rd row서울특별시 종로구 종로41길 3
4th row서울특별시 중구 황학동 마장로 89
5th row서울특별시 중구 다산로 175(신당동)
ValueCountFrequency (%)
서울특별시 346
 
23.9%
관악구 27
 
1.9%
용산구 22
 
1.5%
강북구 20
 
1.4%
강남구 20
 
1.4%
강서구 20
 
1.4%
송파구 19
 
1.3%
서초구 19
 
1.3%
광진구 18
 
1.2%
성북구 17
 
1.2%
Other values (559) 919
63.5%
2023-12-11T19:04:09.263538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1108
 
15.8%
서 404
 
5.8%
구 372
 
5.3%
시 358
 
5.1%
로 354
 
5.1%
울 348
 
5.0%
별 346
 
4.9%
특 346
 
4.9%
1 287
 
4.1%
길 222
 
3.2%
Other values (228) 2856
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4425
63.2%
Decimal Number 1332
 
19.0%
Space Separator 1108
 
15.8%
Dash Punctuation 47
 
0.7%
Close Punctuation 37
 
0.5%
Open Punctuation 37
 
0.5%
Other Punctuation 14
 
0.2%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 404
 
9.1%
구 372
 
8.4%
시 358
 
8.1%
로 354
 
8.0%
울 348
 
7.9%
별 346
 
7.8%
특 346
 
7.8%
길 222
 
5.0%
동 119
 
2.7%
강 88
 
2.0%
Other values (210) 1468
33.2%
Decimal Number
ValueCountFrequency (%)
1 287
21.5%
2 214
16.1%
3 147
11.0%
4 133
10.0%
6 116
8.7%
5 101
 
7.6%
7 92
 
6.9%
8 90
 
6.8%
9 78
 
5.9%
0 74
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 12
85.7%
. 1
 
7.1%
@ 1
 
7.1%
Space Separator
ValueCountFrequency (%)
1108
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4425
63.2%
Common 2575
36.8%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 404
 
9.1%
구 372
 
8.4%
시 358
 
8.1%
로 354
 
8.0%
울 348
 
7.9%
별 346
 
7.8%
특 346
 
7.8%
길 222
 
5.0%
동 119
 
2.7%
강 88
 
2.0%
Other values (210) 1468
33.2%
Common
ValueCountFrequency (%)
1108
43.0%
1 287
 
11.1%
2 214
 
8.3%
3 147
 
5.7%
4 133
 
5.2%
6 116
 
4.5%
5 101
 
3.9%
7 92
 
3.6%
8 90
 
3.5%
9 78
 
3.0%
Other values (7) 209
 
8.1%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4425
63.2%
ASCII 2576
36.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1108
43.0%
1 287
 
11.1%
2 214
 
8.3%
3 147
 
5.7%
4 133
 
5.2%
6 116
 
4.5%
5 101
 
3.9%
7 92
 
3.6%
8 90
 
3.5%
9 78
 
3.0%
Other values (8) 210
 
8.2%
Hangul
ValueCountFrequency (%)
서 404
 
9.1%
구 372
 
8.4%
시 358
 
8.1%
로 354
 
8.0%
울 348
 
7.9%
별 346
 
7.8%
특 346
 
7.8%
길 222
 
5.0%
동 119
 
2.7%
강 88
 
2.0%
Other values (210) 1468
33.2%

운영시간
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
0000_2400
335 
<NA>
 
9
0730_2330
 
2
0900_2100
 
1

Length

Max length9
Median length9
Mean length8.870317
Min length4

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row0000_2400
2nd row0000_2400
3rd row0000_2400
4th row0000_2400
5th row0000_2400

Common Values

ValueCountFrequency (%)
0000_2400 335
96.5%
<NA> 9
 
2.6%
0730_2330 2
 
0.6%
0900_2100 1
 
0.3%

Length

2023-12-11T19:04:09.494080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T19:04:09.618941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0000_2400 335
96.5%
na 9
 
2.6%
0730_2330 2
 
0.6%
0900_2100 1
 
0.3%

운영요일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
501
347 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row501
2nd row501
3rd row501
4th row501
5th row501

Common Values

ValueCountFrequency (%)
501 347
100.0%

Length

2023-12-11T19:04:09.759251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T19:04:09.869742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
501 347
100.0%

안심귀갓길 id
Text

Distinct188
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2023-12-11T19:04:10.122775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length13.005764
Min length13

Characters and Unicode

Total characters4513
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique104 ?
Unique (%)30.0%

Sample

1st row1111017400_06
2nd row1111017400_06
3rd row1111017400_06
4th row1114016500_08
5th row1114016200_05
ValueCountFrequency (%)
1162010200_09 9
 
2.6%
1123010600_14 9
 
2.6%
1168010800_05 7
 
2.0%
1154510200_04 6
 
1.7%
1174010900_01 5
 
1.4%
1144012100_09 5
 
1.4%
1121510700_01 5
 
1.4%
1154510300_06 4
 
1.2%
1165010200_09 4
 
1.2%
1165010700_01 4
 
1.2%
Other values (178) 289
83.3%
2023-12-11T19:04:10.515622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1531
33.9%
1 1394
30.9%
_ 347
 
7.7%
2 227
 
5.0%
5 209
 
4.6%
3 201
 
4.5%
4 159
 
3.5%
6 145
 
3.2%
7 119
 
2.6%
8 92
 
2.0%
Other values (2) 89
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4164
92.3%
Connector Punctuation 347
 
7.7%
Space Separator 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1531
36.8%
1 1394
33.5%
2 227
 
5.5%
5 209
 
5.0%
3 201
 
4.8%
4 159
 
3.8%
6 145
 
3.5%
7 119
 
2.9%
8 92
 
2.2%
9 87
 
2.1%
Connector Punctuation
ValueCountFrequency (%)
_ 347
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4513
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1531
33.9%
1 1394
30.9%
_ 347
 
7.7%
2 227
 
5.0%
5 209
 
4.6%
3 201
 
4.5%
4 159
 
3.5%
6 145
 
3.2%
7 119
 
2.6%
8 92
 
2.0%
Other values (2) 89
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4513
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1531
33.9%
1 1394
30.9%
_ 347
 
7.7%
2 227
 
5.0%
5 209
 
4.6%
3 201
 
4.5%
4 159
 
3.5%
6 145
 
3.2%
7 119
 
2.6%
8 92
 
2.0%
Other values (2) 89
 
2.0%

안심귀갓길 명
Text

Distinct188
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2023-12-11T19:04:10.866400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0893372
Min length6

Characters and Unicode

Total characters2113
Distinct characters53
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

Unique104 ?
Unique (%)30.0%

Sample

1st row혜화안심06
2nd row혜화안심06
3rd row혜화안심06
4th row중부안심08
5th row중부안심05
ValueCountFrequency (%)
관악안심09 9
 
2.6%
동대문안심14 9
 
2.6%
강남안심05 7
 
2.0%
금천안심04 6
 
1.7%
강동안심01 5
 
1.4%
마포안심09 5
 
1.4%
광진안심01 5
 
1.4%
금천안심06 4
 
1.2%
서초안심09 4
 
1.2%
서초안심01 4
 
1.2%
Other values (178) 289
83.3%
2023-12-11T19:04:11.355142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
안 347
16.4%
심 347
16.4%
0 237
 
11.2%
1 156
 
7.4%
강 75
 
3.5%
4 58
 
2.7%
2 51
 
2.4%
동 49
 
2.3%
서 47
 
2.2%
3 42
 
2.0%
Other values (43) 704
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1419
67.2%
Decimal Number 694
32.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 347
24.5%
심 347
24.5%
강 75
 
5.3%
동 49
 
3.5%
서 47
 
3.3%
북 29
 
2.0%
포 26
 
1.8%
악 26
 
1.8%
관 26
 
1.8%
남 25
 
1.8%
Other values (33) 422
29.7%
Decimal Number
ValueCountFrequency (%)
0 237
34.1%
1 156
22.5%
4 58
 
8.4%
2 51
 
7.3%
3 42
 
6.1%
5 36
 
5.2%
9 34
 
4.9%
6 31
 
4.5%
8 26
 
3.7%
7 23
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1419
67.2%
Common 694
32.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 347
24.5%
심 347
24.5%
강 75
 
5.3%
동 49
 
3.5%
서 47
 
3.3%
북 29
 
2.0%
포 26
 
1.8%
악 26
 
1.8%
관 26
 
1.8%
남 25
 
1.8%
Other values (33) 422
29.7%
Common
ValueCountFrequency (%)
0 237
34.1%
1 156
22.5%
4 58
 
8.4%
2 51
 
7.3%
3 42
 
6.1%
5 36
 
5.2%
9 34
 
4.9%
6 31
 
4.5%
8 26
 
3.7%
7 23
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1419
67.2%
ASCII 694
32.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
안 347
24.5%
심 347
24.5%
강 75
 
5.3%
동 49
 
3.5%
서 47
 
3.3%
북 29
 
2.0%
포 26
 
1.8%
악 26
 
1.8%
관 26
 
1.8%
남 25
 
1.8%
Other values (33) 422
29.7%
ASCII
ValueCountFrequency (%)
0 237
34.1%
1 156
22.5%
4 58
 
8.4%
2 51
 
7.3%
3 42
 
6.1%
5 36
 
5.2%
9 34
 
4.9%
6 31
 
4.5%
8 26
 
3.7%
7 23
 
3.3%

비고
Text

MISSING 

Distinct338
Distinct (%)99.4%
Missing7
Missing (%)2.0%
Memory size2.8 KiB
2023-12-11T19:04:11.723063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length9.05
Min length2

Characters and Unicode

Total characters3077
Distinct characters298
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

Unique336 ?
Unique (%)98.8%

Sample

1st rowCU종로공원점
2nd row미니스톱종로효제점
3rd row미니스톱종로6가점
4th row세븐일레븐 중구황학동점
5th rowcu청구대로점
ValueCountFrequency (%)
gs25 47
 
8.5%
cu 47
 
8.5%
세븐일레븐 45
 
8.1%
주민센터 24
 
4.3%
미니스톱 15
 
2.7%
공영주차장 4
 
0.7%
b 3
 
0.5%
현대오일뱅크 3
 
0.5%
화곡 2
 
0.4%
신한은행 2
 
0.4%
Other values (360) 364
65.5%
2023-12-11T19:04:12.243231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
216
 
7.0%
점 171
 
5.6%
븐 108
 
3.5%
동 94
 
3.1%
2 77
 
2.5%
센 65
 
2.1%
일 65
 
2.1%
터 65
 
2.1%
주 63
 
2.0%
5 58
 
1.9%
Other values (288) 2095
68.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2421
78.7%
Uppercase Letter 217
 
7.1%
Space Separator 216
 
7.0%
Decimal Number 197
 
6.4%
Lowercase Letter 16
 
0.5%
Connector Punctuation 6
 
0.2%
Dash Punctuation 2
 
0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 171
 
7.1%
븐 108
 
4.5%
동 94
 
3.9%
센 65
 
2.7%
일 65
 
2.7%
터 65
 
2.7%
주 63
 
2.6%
레 55
 
2.3%
세 54
 
2.2%
민 52
 
2.1%
Other values (264) 1629
67.3%
Decimal Number
ValueCountFrequency (%)
2 77
39.1%
5 58
29.4%
1 24
 
12.2%
4 14
 
7.1%
3 13
 
6.6%
0 8
 
4.1%
8 2
 
1.0%
6 1
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
S 55
25.3%
G 55
25.3%
U 51
23.5%
C 51
23.5%
B 3
 
1.4%
T 1
 
0.5%
K 1
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
c 7
43.8%
u 7
43.8%
s 1
 
6.2%
g 1
 
6.2%
Space Separator
ValueCountFrequency (%)
216
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2421
78.7%
Common 423
 
13.7%
Latin 233
 
7.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 171
 
7.1%
븐 108
 
4.5%
동 94
 
3.9%
센 65
 
2.7%
일 65
 
2.7%
터 65
 
2.7%
주 63
 
2.6%
레 55
 
2.3%
세 54
 
2.2%
민 52
 
2.1%
Other values (264) 1629
67.3%
Common
ValueCountFrequency (%)
216
51.1%
2 77
 
18.2%
5 58
 
13.7%
1 24
 
5.7%
4 14
 
3.3%
3 13
 
3.1%
0 8
 
1.9%
_ 6
 
1.4%
- 2
 
0.5%
8 2
 
0.5%
Other values (3) 3
 
0.7%
Latin
ValueCountFrequency (%)
S 55
23.6%
G 55
23.6%
U 51
21.9%
C 51
21.9%
c 7
 
3.0%
u 7
 
3.0%
B 3
 
1.3%
T 1
 
0.4%
K 1
 
0.4%
s 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2421
78.7%
ASCII 656
 
21.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
216
32.9%
2 77
 
11.7%
5 58
 
8.8%
S 55
 
8.4%
G 55
 
8.4%
U 51
 
7.8%
C 51
 
7.8%
1 24
 
3.7%
4 14
 
2.1%
3 13
 
2.0%
Other values (14) 42
 
6.4%
Hangul
ValueCountFrequency (%)
점 171
 
7.1%
븐 108
 
4.5%
동 94
 
3.9%
센 65
 
2.7%
일 65
 
2.7%
터 65
 
2.7%
주 63
 
2.6%
레 55
 
2.3%
세 54
 
2.2%
민 52
 
2.1%
Other values (264) 1629
67.3%

데이터 기준일자
Real number (ℝ)

Distinct12
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20221106
Minimum20220727
Maximum20221118
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-11T19:04:12.422940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20220727
5-th percentile20221116
Q120221118
median20221118
Q320221118
95-th percentile20221118
Maximum20221118
Range391
Interquartile range (IQR)0

Descriptive statistics

Standard deviation59.017649
Coefficient of variation (CV)2.9186162 × 10-6
Kurtosis27.914038
Mean20221106
Median Absolute Deviation (MAD)0
Skewness-5.2717352
Sum7.0167238 × 109
Variance3483.0829
MonotonicityNot monotonic
2023-12-11T19:04:12.591660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
20221118 327
94.2%
20220727 5
 
1.4%
20221116 3
 
0.9%
20221108 2
 
0.6%
20220914 2
 
0.6%
20220902 2
 
0.6%
20220819 1
 
0.3%
20220809 1
 
0.3%
20220927 1
 
0.3%
20220923 1
 
0.3%
Other values (2) 2
 
0.6%
ValueCountFrequency (%)
20220727 5
1.4%
20220809 1
 
0.3%
20220819 1
 
0.3%
20220902 2
 
0.6%
20220914 2
 
0.6%
20220915 1
 
0.3%
20220923 1
 
0.3%
20220927 1
 
0.3%
20221006 1
 
0.3%
20221108 2
 
0.6%
ValueCountFrequency (%)
20221118 327
94.2%
20221116 3
 
0.9%
20221108 2
 
0.6%
20221006 1
 
0.3%
20220927 1
 
0.3%
20220923 1
 
0.3%
20220915 1
 
0.3%
20220914 2
 
0.6%
20220902 2
 
0.6%
20220819 1
 
0.3%

이미지명
Text

UNIQUE 

Distinct347
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2023-12-11T19:04:12.811404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length26
Mean length26
Min length26

Characters and Unicode

Total characters9022
Distinct characters17
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique347 ?
Unique (%)100.0%

Sample

1st row1111017400_06_S01_402.jpeg
2nd row1111017400_06_S02_402.jpeg
3rd row1111017400_06_S03_402.jpeg
4th row1114016500_08_S01_402.jpeg
5th row1114016200_05_S01_402.jpeg
ValueCountFrequency (%)
1111017400_06_s01_402.jpeg 1
 
0.3%
1153010200_01_s01_401.jpeg 1
 
0.3%
1121510100_07_s01_401.jpeg 1
 
0.3%
1121510100_08_s02_401.jpeg 1
 
0.3%
1121510100_08_s01_401.jpeg 1
 
0.3%
1121510500_09_s01_401.jpeg 1
 
0.3%
1121510500_10_s01_401.jpeg 1
 
0.3%
1121510500_11_s01_402.jpeg 1
 
0.3%
1121510500_12_s02_401.jpeg 1
 
0.3%
1121510700_01_s01_402.jpeg 1
 
0.3%
Other values (337) 337
97.1%
2023-12-11T19:04:13.198582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2225
24.7%
1 1713
19.0%
_ 1041
11.5%
4 521
 
5.8%
2 514
 
5.7%
j 347
 
3.8%
g 347
 
3.8%
e 347
 
3.8%
p 347
 
3.8%
. 347
 
3.8%
Other values (7) 1273
14.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5899
65.4%
Lowercase Letter 1388
 
15.4%
Connector Punctuation 1041
 
11.5%
Other Punctuation 347
 
3.8%
Uppercase Letter 347
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2225
37.7%
1 1713
29.0%
4 521
 
8.8%
2 514
 
8.7%
3 249
 
4.2%
5 222
 
3.8%
6 150
 
2.5%
7 122
 
2.1%
8 94
 
1.6%
9 89
 
1.5%
Lowercase Letter
ValueCountFrequency (%)
j 347
25.0%
g 347
25.0%
e 347
25.0%
p 347
25.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1041
100.0%
Other Punctuation
ValueCountFrequency (%)
. 347
100.0%
Uppercase Letter
ValueCountFrequency (%)
S 347
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7287
80.8%
Latin 1735
 
19.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2225
30.5%
1 1713
23.5%
_ 1041
14.3%
4 521
 
7.1%
2 514
 
7.1%
. 347
 
4.8%
3 249
 
3.4%
5 222
 
3.0%
6 150
 
2.1%
7 122
 
1.7%
Other values (2) 183
 
2.5%
Latin
ValueCountFrequency (%)
j 347
20.0%
g 347
20.0%
e 347
20.0%
p 347
20.0%
S 347
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9022
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2225
24.7%
1 1713
19.0%
_ 1041
11.5%
4 521
 
5.8%
2 514
 
5.7%
j 347
 
3.8%
g 347
 
3.8%
e 347
 
3.8%
p 347
 
3.8%
. 347
 
3.8%
Other values (7) 1273
14.1%

Interactions

2023-12-11T19:04:03.286556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:04:01.248780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:04:01.730519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:04:02.288486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:04:02.837816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:04:03.371528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:04:01.348586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:04:01.859317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:04:02.395944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:04:02.941930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:04:03.467174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:04:01.448104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:04:01.980295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:04:02.520920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:04:03.039807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:04:03.555057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:04:01.542506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:04:02.074786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:04:02.633663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:04:03.125887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:04:03.631659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:04:01.626245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:04:02.170226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:04:02.721000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T19:04:03.198640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T19:04:13.336568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설코드시군구 코드시군구명읍면동 코드경도위도운영시간데이터 기준일자
시설코드1.0000.2770.5270.2850.2200.1530.0750.408
시군구 코드0.2771.0001.0001.0000.9150.9190.0000.420
시군구명0.5271.0001.0001.0000.9380.9280.0000.639
읍면동 코드0.2851.0001.0001.0000.9180.9150.0000.425
경도0.2200.9150.9380.9181.0000.7140.1090.052
위도0.1530.9190.9280.9150.7141.0000.0000.326
운영시간0.0750.0000.0000.0000.1090.0001.0000.000
데이터 기준일자0.4080.4200.6390.4250.0520.3260.0001.000
2023-12-11T19:04:13.479719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명운영시간시설코드
시군구명1.0000.0000.279
운영시간0.0001.0000.022
시설코드0.2790.0221.000
2023-12-11T19:04:13.594162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구 코드읍면동 코드경도위도데이터 기준일자시설코드시군구명운영시간
시군구 코드1.0000.9990.050-0.6150.0780.1770.9790.000
읍면동 코드0.9991.0000.051-0.6150.0750.1770.9790.000
경도0.0500.0511.0000.280-0.2590.1320.7010.063
위도-0.615-0.6150.2801.000-0.1180.0910.6720.000
데이터 기준일자0.0780.075-0.259-0.1181.0000.3410.3820.000
시설코드0.1770.1770.1320.0910.3411.0000.2790.022
시군구명0.9790.9790.7010.6720.3820.2791.0000.000
운영시간0.0000.0000.0630.0000.0000.0220.0001.000

Missing values

2023-12-11T19:04:03.760149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T19:04:04.000534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

서비스 id시설코드시군구 코드시군구명읍면동 코드읍면동명관리기관전화번호경도위도세부위치운영시간운영요일안심귀갓길 id안심귀갓길 명비고데이터 기준일자이미지명
01111017400_06_S014021111000000서울특별시 종로구1111016400종로6가혜화경찰서02-762-4400127.0075937.573204서울특별시 종로구 율곡로 2710000_24005011111017400_06혜화안심06CU종로공원점202211181111017400_06_S01_402.jpeg
11111017400_06_S024021111000000서울특별시 종로구1111016400종로6가혜화경찰서02-762-4400127.0049737.572605서울특별시 종로구 종로39길 400000_24005011111017400_06혜화안심06미니스톱종로효제점202211181111017400_06_S02_402.jpeg
21111017400_06_S034021111000000서울특별시 종로구1111016400종로6가혜화경찰서02-762-4400127.0065437.571434서울특별시 종로구 종로41길 30000_24005011111017400_06혜화안심06미니스톱종로6가점202211181111017400_06_S03_402.jpeg
31114016500_08_S014021114000000서울특별시 중구1114016500황학동중부(광희)지구대02-2233-1444127.019837.56845서울특별시 중구 황학동 마장로 890000_24005011114016500_08중부안심08세븐일레븐 중구황학동점202211181114016500_08_S01_402.jpeg
41114016200_05_S014021114000000서울특별시 중구1114016200신당동중부(약수)지구대02-2234-8112127.0128537.55924서울특별시 중구 다산로 175(신당동)0000_24005011114016200_05중부안심05cu청구대로점202211181114016200_05_S01_402.jpeg
51114016200_05_S024021114000000서울특별시 중구1114016200신당동중부(약수)지구대02-2234-8112127.0179737.558163서울특별시 중구 청구로1길 23 삼성@ 2동B 101호0000_24005011114016200_05중부안심05GS25신당삼성202211181114016200_05_S02_402.jpeg
61114014400_02_S014011114000000서울특별시 중구1114014400장충동2가서울특별시 중구청 여성보육과02-3396-5402127.00667637.55864서울특별시 중구 동호로 2410000_24005011114014400_02중부안심02장충체육관 후문202211181114014400_02_S01_401.jpeg
71114014400_02_S024011114000000서울특별시 중구1114014400장충동2가서울특별시 중구청 여성보육과02-3396-5402127.0010237.55999서울특별시 중구 장충동2가 192-1290000_24005011114014400_02중부안심02장충공영주차장202211181114014400_02_S02_401.jpeg
81114013800_01_S024021114000000서울특별시 중구1114013200충무로4가중부(충무)파출소02-2278-7710126.9950237.561615서울특별시 중구 퇴계로 209(충무로4가)0000_24005011114013800_01중부안심01세븐일레븐충무퇴계점202211181114013800_01_S02_402.jpeg
91114013800_01_S014021114000000서울특별시 중구1114013900필동3가중부(충무)파출소02-2278-7710126.9974137.56036서울특별시 중구 서애로21 1층0000_24005011114013800_01중부안심01cu중구필동점202211181114013800_01_S01_402.jpeg
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3371168010500_20_S024021168000000서울특별시 강남구1168010500삼성동강남경찰서02-557-7000127.05154437.51074서울특별시 강남구 삼성로107길 31, 1층 (삼성동 123-4)0000_24005011168010500_20강남안심20GS25 삼성그린점202211181168010500_20_S02_402.jpeg
3381168010800_19_S044021168000000서울특별시 강남구1168010800논현동강남경찰서02-557-7000127.02830537.505917서울특별시 강남구 봉은사로 1290000_24005011168010800_19강남안심19세븐일레븐 거평타운점 B202211181168010800_19_S04_402.jpeg
3391168010800_19_S054021168000000서울특별시 강남구1168010800논현동강남경찰서02-557-7000127.032137.510532서울특별시 강남구 논현로 6390000_24005011168010800_19강남안심19미니스톱 논현힐탑점202211181168010800_19_S05_402.jpeg
3401168010800_19_S034021168000000서울특별시 강남구1168010800논현동강남경찰서02-557-7000127.0289937.50674서울특별시 강남구 봉은사로11길 120000_24005011168010800_19강남안심19GS25 논현이편한점202211181168010800_19_S03_402.jpeg
3411168010800_19_S014021168000000서울특별시 강남구1168010100역삼동강남경찰서02-557-7000127.0267337.501926서울특별시 강남구 강남대로102길 110000_24005011168010800_19강남안심19세븐일레븐 역삼8호점202211181168010800_19_S01_402.jpeg
3421168010100_18_S014021168000000서울특별시 강남구1168010800논현동강남경찰서02-557-7000127.0426837.510155서울특별시 강남구 봉은사로 3270000_24005011168010100_18강남안심18미니스톱 논현삼릉역점202211181168010100_18_S01_402.jpeg
3431168010700_17_S014021168000000서울특별시 강남구1168010700신사동강남경찰서02-557-7000127.0289937.526314서울특별시 강남구 압구정로30길 180000_24005011168010700_17강남안심17미니스톱 신사증권점202211181168010700_17_S01_402.jpeg
3441168010700_17_S024021168000000서울특별시 강남구1168010700신사동강남경찰서02-557-7000127.03010637.527206서울특별시 강남구 논현로176길 200000_24005011168010700_17강남안심17CU 신사현대점202211181168010700_17_S02_402.jpeg
3451168010700_15_S014021168000000서울특별시 강남구1168010700신사동강남경찰서02-557-7000127.0244337.52052서울특별시 강남구 논현로153길 46(신사동 555-13)0000_24005011168010700_15강남안심15GS25 신사초롱점202211181168010700_15_S01_402.jpeg
3461168010500_11_S014021168000000서울특별시 강남구1168010500삼성동강남경찰서02-557-7000127.04471637.510822서울특별시 강남구 봉은사로 4090000_24005011168010500_11강남안심11CU 선정릉역점202211181168010500_11_S01_402.jpeg