Overview

Dataset statistics

Number of variables31
Number of observations874
Missing cells95
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory218.6 KiB
Average record size in memory256.2 B

Variable types

Text12
Categorical13
Numeric4
DateTime2

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/15034534/standard.do

Alerts

평일운영시작시각 is highly imbalanced (82.3%)Imbalance
평일운영종료시각 is highly imbalanced (92.7%)Imbalance
토요일운영시작시각 is highly imbalanced (82.3%)Imbalance
토요일운영종료시각 is highly imbalanced (87.1%)Imbalance
공휴일운영시작시각 is highly imbalanced (82.3%)Imbalance
공휴일운영종료시각 is highly imbalanced (85.1%)Imbalance
무료이용시간 is highly imbalanced (54.2%)Imbalance
연체료 is highly imbalanced (63.6%)Imbalance
소재지지번주소 has 88 (10.1%) missing valuesMissing

Reproduction

Analysis started2024-05-11 10:33:33.994970
Analysis finished2024-05-11 10:33:36.966337
Duration2.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

Distinct796
Distinct (%)91.1%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2024-05-11T10:33:37.617037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length24
Mean length10.175057
Min length3

Characters and Unicode

Total characters8893
Distinct characters387
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique739 ?
Unique (%)84.6%

Sample

1st row지저동 행정복지센터
2nd row상봉2동주민센터
3rd row중화1치안센터
4th row상봉1동주민센터
5th row문흥동 청소년 수련관 별관
ValueCountFrequency (%)
행정복지센터 131
 
9.5%
여성안심택배함 38
 
2.8%
주민센터 27
 
2.0%
택배함 17
 
1.2%
여성안심택배함(이면도로 16
 
1.2%
옆 14
 
1.0%
공영주차장 11
 
0.8%
주차장 10
 
0.7%
입구 10
 
0.7%
앞 10
 
0.7%
Other values (925) 1093
79.4%
2024-05-11T10:33:38.986407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
503
 
5.7%
동 444
 
5.0%
터 428
 
4.8%
센 422
 
4.7%
지 323
 
3.6%
복 284
 
3.2%
정 278
 
3.1%
행 267
 
3.0%
주 176
 
2.0%
배 154
 
1.7%
Other values (377) 5614
63.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7894
88.8%
Space Separator 503
 
5.7%
Decimal Number 305
 
3.4%
Close Punctuation 86
 
1.0%
Open Punctuation 86
 
1.0%
Other Punctuation 7
 
0.1%
Uppercase Letter 6
 
0.1%
Dash Punctuation 5
 
0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 444
 
5.6%
터 428
 
5.4%
센 422
 
5.3%
지 323
 
4.1%
복 284
 
3.6%
정 278
 
3.5%
행 267
 
3.4%
주 176
 
2.2%
배 154
 
2.0%
택 149
 
1.9%
Other values (356) 4969
62.9%
Decimal Number
ValueCountFrequency (%)
1 120
39.3%
2 94
30.8%
3 37
 
12.1%
4 28
 
9.2%
6 9
 
3.0%
5 8
 
2.6%
9 4
 
1.3%
7 3
 
1.0%
8 2
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
C 3
50.0%
N 1
 
16.7%
V 1
 
16.7%
T 1
 
16.7%
Other Punctuation
ValueCountFrequency (%)
· 3
42.9%
. 3
42.9%
, 1
 
14.3%
Space Separator
ValueCountFrequency (%)
503
100.0%
Close Punctuation
ValueCountFrequency (%)
) 86
100.0%
Open Punctuation
ValueCountFrequency (%)
( 86
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7894
88.8%
Common 993
 
11.2%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 444
 
5.6%
터 428
 
5.4%
센 422
 
5.3%
지 323
 
4.1%
복 284
 
3.6%
정 278
 
3.5%
행 267
 
3.4%
주 176
 
2.2%
배 154
 
2.0%
택 149
 
1.9%
Other values (356) 4969
62.9%
Common
ValueCountFrequency (%)
503
50.7%
1 120
 
12.1%
2 94
 
9.5%
) 86
 
8.7%
( 86
 
8.7%
3 37
 
3.7%
4 28
 
2.8%
6 9
 
0.9%
5 8
 
0.8%
- 5
 
0.5%
Other values (7) 17
 
1.7%
Latin
ValueCountFrequency (%)
C 3
50.0%
N 1
 
16.7%
V 1
 
16.7%
T 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7894
88.8%
ASCII 996
 
11.2%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
503
50.5%
1 120
 
12.0%
2 94
 
9.4%
) 86
 
8.6%
( 86
 
8.6%
3 37
 
3.7%
4 28
 
2.8%
6 9
 
0.9%
5 8
 
0.8%
- 5
 
0.5%
Other values (10) 20
 
2.0%
Hangul
ValueCountFrequency (%)
동 444
 
5.6%
터 428
 
5.4%
센 422
 
5.3%
지 323
 
4.1%
복 284
 
3.6%
정 278
 
3.5%
행 267
 
3.4%
주 176
 
2.2%
배 154
 
2.0%
택 149
 
1.9%
Other values (356) 4969
62.9%
None
ValueCountFrequency (%)
· 3
100.0%

시도명
Categorical

Distinct18
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
서울특별시
243 
대구광역시
212 
경기도
145 
인천광역시
74 
충청북도
36 
Other values (13)
164 

Length

Max length7
Median length5
Mean length4.583524
Min length3

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row대구광역시
2nd row서울특별시
3rd row서울특별시
4th row서울특별시
5th row광주광역시

Common Values

ValueCountFrequency (%)
서울특별시 243
27.8%
대구광역시 212
24.3%
경기도 145
16.6%
인천광역시 74
 
8.5%
충청북도 36
 
4.1%
광주광역시 28
 
3.2%
경상남도 24
 
2.7%
부산광역시 20
 
2.3%
대전광역시 19
 
2.2%
경상북도 18
 
2.1%
Other values (8) 55
 
6.3%

Length

2024-05-11T10:33:39.494018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 243
27.8%
대구광역시 212
24.3%
경기도 145
16.6%
인천광역시 74
 
8.5%
충청북도 36
 
4.1%
광주광역시 28
 
3.2%
경상남도 24
 
2.7%
부산광역시 20
 
2.3%
대전광역시 19
 
2.2%
전라남도 18
 
2.1%
Other values (8) 55
 
6.3%

시군구명
Text

Distinct85
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2024-05-11T10:33:40.252297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length2.9702517
Min length2

Characters and Unicode

Total characters2596
Distinct characters79
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

Unique6 ?
Unique (%)0.7%

Sample

1st row동구
2nd row중랑구
3rd row중랑구
4th row중랑구
5th row북구
ValueCountFrequency (%)
북구 48
 
5.3%
서구 47
 
5.2%
달서구 39
 
4.3%
수성구 38
 
4.2%
남구 37
 
4.1%
중구 27
 
3.0%
부천시 25
 
2.8%
고양시 25
 
2.8%
달성군 24
 
2.7%
동구 23
 
2.6%
Other values (76) 566
63.0%
2024-05-11T10:33:41.515559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 635
24.5%
시 253
 
9.7%
서 136
 
5.2%
성 115
 
4.4%
남 73
 
2.8%
동 69
 
2.7%
수 66
 
2.5%
북 65
 
2.5%
달 63
 
2.4%
양 60
 
2.3%
Other values (69) 1061
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2571
99.0%
Space Separator 25
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 635
24.7%
시 253
 
9.8%
서 136
 
5.3%
성 115
 
4.5%
남 73
 
2.8%
동 69
 
2.7%
수 66
 
2.6%
북 65
 
2.5%
달 63
 
2.5%
양 60
 
2.3%
Other values (68) 1036
40.3%
Space Separator
ValueCountFrequency (%)
25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2571
99.0%
Common 25
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 635
24.7%
시 253
 
9.8%
서 136
 
5.3%
성 115
 
4.5%
남 73
 
2.8%
동 69
 
2.7%
수 66
 
2.6%
북 65
 
2.5%
달 63
 
2.5%
양 60
 
2.3%
Other values (68) 1036
40.3%
Common
ValueCountFrequency (%)
25
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2571
99.0%
ASCII 25
 
1.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 635
24.7%
시 253
 
9.8%
서 136
 
5.3%
성 115
 
4.5%
남 73
 
2.8%
동 69
 
2.7%
수 66
 
2.6%
북 65
 
2.5%
달 63
 
2.5%
양 60
 
2.3%
Other values (68) 1036
40.3%
ASCII
ValueCountFrequency (%)
25
100.0%

시군구코드
Real number (ℝ)

Distinct111
Distinct (%)12.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28792.038
Minimum11020
Maximum57350
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.8 KiB
2024-05-11T10:33:42.114246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11020
5-th percentile11230
Q111680
median27710
Q341196
95-th percentile48250
Maximum57350
Range46330
Interquartile range (IQR)29516

Descriptive statistics

Standard deviation12825.04
Coefficient of variation (CV)0.44543704
Kurtosis-0.97749528
Mean28792.038
Median Absolute Deviation (MAD)13510
Skewness0.0453869
Sum25164241
Variance1.6448165 × 108
MonotonicityNot monotonic
2024-05-11T10:33:42.632365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27290 58
 
6.6%
27230 40
 
4.6%
41280 25
 
2.9%
27710 24
 
2.7%
27170 24
 
2.7%
27200 22
 
2.5%
27260 19
 
2.2%
43130 18
 
2.1%
11650 17
 
1.9%
11620 16
 
1.8%
Other values (101) 611
69.9%
ValueCountFrequency (%)
11020 7
0.8%
11110 5
 
0.6%
11170 8
0.9%
11200 10
1.1%
11215 12
1.4%
11216 1
 
0.1%
11230 11
1.3%
11260 6
0.7%
11305 9
1.0%
11350 14
1.6%
ValueCountFrequency (%)
57350 2
 
0.2%
57300 4
0.5%
57250 1
 
0.1%
57200 1
 
0.1%
56700 7
0.8%
55700 1
 
0.1%
52200 6
0.7%
50629 1
 
0.1%
50619 1
 
0.1%
50570 1
 
0.1%

소재지도로명주소
Text

Distinct780
Distinct (%)90.0%
Missing7
Missing (%)0.8%
Memory size7.0 KiB
2024-05-11T10:33:43.505970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length34
Mean length19.770473
Min length14

Characters and Unicode

Total characters17141
Distinct characters321
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique693 ?
Unique (%)79.9%

Sample

1st row대구광역시 동구 해동로3길 80
2nd row서울특별시 중랑구 동일로114길 10
3rd row서울특별시 중랑구 동일로 792
4th row서울특별시 중랑구 상봉중앙로1길 6
5th row광주광역시 북구 대천로 86
ValueCountFrequency (%)
서울특별시 241
 
6.5%
대구광역시 212
 
5.7%
경기도 145
 
3.9%
인천광역시 73
 
2.0%
북구 48
 
1.3%
서구 44
 
1.2%
달서구 39
 
1.1%
수성구 38
 
1.0%
남구 37
 
1.0%
충청북도 35
 
0.9%
Other values (1292) 2801
75.4%
2024-05-11T10:33:44.990106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2846
 
16.6%
구 983
 
5.7%
시 869
 
5.1%
로 799
 
4.7%
1 598
 
3.5%
길 502
 
2.9%
서 428
 
2.5%
광 424
 
2.5%
2 424
 
2.5%
대 414
 
2.4%
Other values (311) 8854
51.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11041
64.4%
Decimal Number 2959
 
17.3%
Space Separator 2846
 
16.6%
Dash Punctuation 120
 
0.7%
Open Punctuation 83
 
0.5%
Close Punctuation 83
 
0.5%
Other Punctuation 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 983
 
8.9%
시 869
 
7.9%
로 799
 
7.2%
길 502
 
4.5%
서 428
 
3.9%
광 424
 
3.8%
대 414
 
3.7%
역 367
 
3.3%
도 295
 
2.7%
특 259
 
2.3%
Other values (295) 5701
51.6%
Decimal Number
ValueCountFrequency (%)
1 598
20.2%
2 424
14.3%
3 346
11.7%
4 302
10.2%
5 287
9.7%
6 233
 
7.9%
9 196
 
6.6%
0 192
 
6.5%
7 192
 
6.5%
8 189
 
6.4%
Other Punctuation
ValueCountFrequency (%)
, 8
88.9%
· 1
 
11.1%
Space Separator
ValueCountFrequency (%)
2846
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 120
100.0%
Open Punctuation
ValueCountFrequency (%)
( 83
100.0%
Close Punctuation
ValueCountFrequency (%)
) 83
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11041
64.4%
Common 6100
35.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 983
 
8.9%
시 869
 
7.9%
로 799
 
7.2%
길 502
 
4.5%
서 428
 
3.9%
광 424
 
3.8%
대 414
 
3.7%
역 367
 
3.3%
도 295
 
2.7%
특 259
 
2.3%
Other values (295) 5701
51.6%
Common
ValueCountFrequency (%)
2846
46.7%
1 598
 
9.8%
2 424
 
7.0%
3 346
 
5.7%
4 302
 
5.0%
5 287
 
4.7%
6 233
 
3.8%
9 196
 
3.2%
0 192
 
3.1%
7 192
 
3.1%
Other values (6) 484
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11041
64.4%
ASCII 6099
35.6%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2846
46.7%
1 598
 
9.8%
2 424
 
7.0%
3 346
 
5.7%
4 302
 
5.0%
5 287
 
4.7%
6 233
 
3.8%
9 196
 
3.2%
0 192
 
3.1%
7 192
 
3.1%
Other values (5) 483
 
7.9%
Hangul
ValueCountFrequency (%)
구 983
 
8.9%
시 869
 
7.9%
로 799
 
7.2%
길 502
 
4.5%
서 428
 
3.9%
광 424
 
3.8%
대 414
 
3.7%
역 367
 
3.3%
도 295
 
2.7%
특 259
 
2.3%
Other values (295) 5701
51.6%
None
ValueCountFrequency (%)
· 1
100.0%

소재지지번주소
Text

MISSING 

Distinct694
Distinct (%)88.3%
Missing88
Missing (%)10.1%
Memory size7.0 KiB
2024-05-11T10:33:45.961958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length31
Mean length19.223919
Min length14

Characters and Unicode

Total characters15110
Distinct characters254
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique604 ?
Unique (%)76.8%

Sample

1st row대구광역시 동구 지저동 779-5
2nd row서울특별시 중랑구 상봉동 126
3rd row서울특별시 중랑구 중화동 287-8
4th row서울특별시 중랑구 상봉동 204-1
5th row광주광역시 북구 문흥동 1009-1
ValueCountFrequency (%)
대구광역시 212
 
6.4%
서울특별시 194
 
5.9%
경기도 145
 
4.4%
인천광역시 74
 
2.2%
북구 48
 
1.4%
서구 45
 
1.4%
달서구 39
 
1.2%
수성구 38
 
1.1%
충청북도 36
 
1.1%
남구 28
 
0.8%
Other values (1211) 2456
74.1%
2024-05-11T10:33:47.583040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2529
 
16.7%
구 889
 
5.9%
동 813
 
5.4%
시 782
 
5.2%
1 656
 
4.3%
- 582
 
3.9%
2 395
 
2.6%
광 376
 
2.5%
역 345
 
2.3%
4 334
 
2.2%
Other values (244) 7409
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8789
58.2%
Decimal Number 3203
 
21.2%
Space Separator 2529
 
16.7%
Dash Punctuation 582
 
3.9%
Other Punctuation 3
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 889
 
10.1%
동 813
 
9.3%
시 782
 
8.9%
광 376
 
4.3%
역 345
 
3.9%
서 334
 
3.8%
대 306
 
3.5%
도 265
 
3.0%
울 200
 
2.3%
특 198
 
2.3%
Other values (228) 4281
48.7%
Decimal Number
ValueCountFrequency (%)
1 656
20.5%
2 395
12.3%
4 334
10.4%
3 321
10.0%
5 294
9.2%
8 263
8.2%
7 239
 
7.5%
0 238
 
7.4%
6 236
 
7.4%
9 227
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
· 1
33.3%
Space Separator
ValueCountFrequency (%)
2529
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 582
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8789
58.2%
Common 6321
41.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 889
 
10.1%
동 813
 
9.3%
시 782
 
8.9%
광 376
 
4.3%
역 345
 
3.9%
서 334
 
3.8%
대 306
 
3.5%
도 265
 
3.0%
울 200
 
2.3%
특 198
 
2.3%
Other values (228) 4281
48.7%
Common
ValueCountFrequency (%)
2529
40.0%
1 656
 
10.4%
- 582
 
9.2%
2 395
 
6.2%
4 334
 
5.3%
3 321
 
5.1%
5 294
 
4.7%
8 263
 
4.2%
7 239
 
3.8%
0 238
 
3.8%
Other values (6) 470
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8789
58.2%
ASCII 6320
41.8%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2529
40.0%
1 656
 
10.4%
- 582
 
9.2%
2 395
 
6.2%
4 334
 
5.3%
3 321
 
5.1%
5 294
 
4.7%
8 263
 
4.2%
7 239
 
3.8%
0 238
 
3.8%
Other values (5) 469
 
7.4%
Hangul
ValueCountFrequency (%)
구 889
 
10.1%
동 813
 
9.3%
시 782
 
8.9%
광 376
 
4.3%
역 345
 
3.9%
서 334
 
3.8%
대 306
 
3.5%
도 265
 
3.0%
울 200
 
2.3%
특 198
 
2.3%
Other values (228) 4281
48.7%
None
ValueCountFrequency (%)
· 1
100.0%

위도
Real number (ℝ)

Distinct815
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.681023
Minimum33.249598
Maximum38.187652
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.8 KiB
2024-05-11T10:33:48.129440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.249598
5-th percentile35.147288
Q135.859322
median37.282697
Q337.514829
95-th percentile37.637595
Maximum38.187652
Range4.9380539
Interquartile range (IQR)1.6555063

Descriptive statistics

Standard deviation0.99087796
Coefficient of variation (CV)0.027013368
Kurtosis-0.025987396
Mean36.681023
Median Absolute Deviation (MAD)0.3542574
Skewness-0.80732139
Sum32059.214
Variance0.98183914
MonotonicityNot monotonic
2024-05-11T10:33:48.675490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.84101712 2
 
0.2%
35.6980476 2
 
0.2%
35.9597718 2
 
0.2%
35.93800721 2
 
0.2%
35.83833677 2
 
0.2%
35.85069023 2
 
0.2%
36.6515325 2
 
0.2%
35.85639647 2
 
0.2%
35.85332896 2
 
0.2%
35.65375074 2
 
0.2%
Other values (805) 854
97.7%
ValueCountFrequency (%)
33.24959795 1
0.1%
33.25304804 1
0.1%
33.25785315 1
0.1%
33.32667927 1
0.1%
33.41019901 1
0.1%
33.4466856 1
0.1%
33.45531893 1
0.1%
33.4763337 1
0.1%
33.48782769 1
0.1%
33.49292626 1
0.1%
ValueCountFrequency (%)
38.18765185 2
0.2%
37.85458761 1
0.1%
37.83139226 1
0.1%
37.82166163 1
0.1%
37.76555845 1
0.1%
37.75678721 1
0.1%
37.75222661 1
0.1%
37.750597 1
0.1%
37.74520013 1
0.1%
37.74188108 1
0.1%

경도
Real number (ℝ)

Distinct818
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.51885
Minimum126.26719
Maximum129.33994
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.8 KiB
2024-05-11T10:33:49.237796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.26719
5-th percentile126.67637
Q1126.89632
median127.06807
Q3128.52997
95-th percentile128.71282
Maximum129.33994
Range3.0727515
Interquartile range (IQR)1.6336561

Descriptive statistics

Standard deviation0.80713797
Coefficient of variation (CV)0.0063295583
Kurtosis-1.2829612
Mean127.51885
Median Absolute Deviation (MAD)0.3125691
Skewness0.62083654
Sum111451.47
Variance0.6514717
MonotonicityNot monotonic
2024-05-11T10:33:49.812872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.8707528 2
 
0.2%
127.4502584782 2
 
0.2%
128.4547114 2
 
0.2%
128.6242151 2
 
0.2%
128.4168922 2
 
0.2%
128.4677471 2
 
0.2%
128.6310687 2
 
0.2%
128.619009 2
 
0.2%
128.7128212 2
 
0.2%
128.6473555 2
 
0.2%
Other values (808) 854
97.7%
ValueCountFrequency (%)
126.2671891 1
0.1%
126.4194164 1
0.1%
126.4321229 1
0.1%
126.4947821 1
0.1%
126.4988972 1
0.1%
126.5035018 1
0.1%
126.5067112 1
0.1%
126.5244384 1
0.1%
126.5251149 1
0.1%
126.5272453 1
0.1%
ValueCountFrequency (%)
129.3399406 1
0.1%
129.334804 1
0.1%
129.3295216 1
0.1%
129.3165325 1
0.1%
129.3163875 1
0.1%
129.2826999655 1
0.1%
129.1730233 1
0.1%
129.1055224 1
0.1%
129.1009997 1
0.1%
129.0976627 1
0.1%

평일운영시작시각
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
00:00
810 
0:00
 
25
09:00
 
19
04:00
 
13
05:00
 
2
Other values (3)
 
5

Length

Max length5
Median length5
Mean length4.9713959
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row00:00
2nd row00:00
3rd row00:00
4th row00:00
5th row00:00

Common Values

ValueCountFrequency (%)
00:00 810
92.7%
0:00 25
 
2.9%
09:00 19
 
2.2%
04:00 13
 
1.5%
05:00 2
 
0.2%
07:30 2
 
0.2%
07:00 2
 
0.2%
06:00 1
 
0.1%

Length

2024-05-11T10:33:50.478972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:33:50.873077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00 810
92.7%
0:00 25
 
2.9%
09:00 19
 
2.2%
04:00 13
 
1.5%
05:00 2
 
0.2%
07:30 2
 
0.2%
07:00 2
 
0.2%
06:00 1
 
0.1%

평일운영종료시각
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
23:59
856 
03:00
 
13
23:30
 
3
22:30
 
1
22:00
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row23:59
2nd row23:59
3rd row23:59
4th row23:59
5th row23:59

Common Values

ValueCountFrequency (%)
23:59 856
97.9%
03:00 13
 
1.5%
23:30 3
 
0.3%
22:30 1
 
0.1%
22:00 1
 
0.1%

Length

2024-05-11T10:33:51.263888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:33:51.632712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
23:59 856
97.9%
03:00 13
 
1.5%
23:30 3
 
0.3%
22:30 1
 
0.1%
22:00 1
 
0.1%

토요일운영시작시각
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
00:00
810 
0:00
 
25
09:00
 
19
04:00
 
13
05:00
 
2
Other values (3)
 
5

Length

Max length5
Median length5
Mean length4.9713959
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row00:00
2nd row00:00
3rd row00:00
4th row00:00
5th row00:00

Common Values

ValueCountFrequency (%)
00:00 810
92.7%
0:00 25
 
2.9%
09:00 19
 
2.2%
04:00 13
 
1.5%
05:00 2
 
0.2%
07:30 2
 
0.2%
07:00 2
 
0.2%
08:00 1
 
0.1%

Length

2024-05-11T10:33:52.118748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:33:52.592125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00 810
92.7%
0:00 25
 
2.9%
09:00 19
 
2.2%
04:00 13
 
1.5%
05:00 2
 
0.2%
07:30 2
 
0.2%
07:00 2
 
0.2%
08:00 1
 
0.1%

토요일운영종료시각
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
23:59
835 
00:00
 
21
03:00
 
13
23:30
 
3
18:30
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row23:59
2nd row23:59
3rd row23:59
4th row23:59
5th row23:59

Common Values

ValueCountFrequency (%)
23:59 835
95.5%
00:00 21
 
2.4%
03:00 13
 
1.5%
23:30 3
 
0.3%
18:30 1
 
0.1%
18:00 1
 
0.1%

Length

2024-05-11T10:33:53.012944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:33:53.360970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
23:59 835
95.5%
00:00 21
 
2.4%
03:00 13
 
1.5%
23:30 3
 
0.3%
18:30 1
 
0.1%
18:00 1
 
0.1%

공휴일운영시작시각
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
00:00
810 
0:00
 
25
09:00
 
19
04:00
 
13
05:00
 
2
Other values (3)
 
5

Length

Max length5
Median length5
Mean length4.9713959
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row00:00
2nd row00:00
3rd row00:00
4th row00:00
5th row00:00

Common Values

ValueCountFrequency (%)
00:00 810
92.7%
0:00 25
 
2.9%
09:00 19
 
2.2%
04:00 13
 
1.5%
05:00 2
 
0.2%
07:30 2
 
0.2%
07:00 2
 
0.2%
10:00 1
 
0.1%

Length

2024-05-11T10:33:53.776623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:33:54.230264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00 810
92.7%
0:00 25
 
2.9%
09:00 19
 
2.2%
04:00 13
 
1.5%
05:00 2
 
0.2%
07:30 2
 
0.2%
07:00 2
 
0.2%
10:00 1
 
0.1%

공휴일운영종료시각
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
23:59
826 
23:00
 
19
03:00
 
13
00:00
 
11
23:30
 
3
Other values (2)
 
2

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row23:59
2nd row23:59
3rd row23:59
4th row23:59
5th row23:59

Common Values

ValueCountFrequency (%)
23:59 826
94.5%
23:00 19
 
2.2%
03:00 13
 
1.5%
00:00 11
 
1.3%
23:30 3
 
0.3%
18:30 1
 
0.1%
18:00 1
 
0.1%

Length

2024-05-11T10:33:54.838877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:33:55.258907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
23:59 826
94.5%
23:00 19
 
2.2%
03:00 13
 
1.5%
00:00 11
 
1.3%
23:30 3
 
0.3%
18:30 1
 
0.1%
18:00 1
 
0.1%

무료이용시간
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
48
662 
0
162 
24
 
24
72
 
23
2400
 
3

Length

Max length4
Median length2
Mean length1.8215103
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row48
3rd row48
4th row48
5th row48

Common Values

ValueCountFrequency (%)
48 662
75.7%
0 162
 
18.5%
24 24
 
2.7%
72 23
 
2.6%
2400 3
 
0.3%

Length

2024-05-11T10:33:55.879589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:33:56.284259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48 662
75.7%
0 162
 
18.5%
24 24
 
2.7%
72 23
 
2.6%
2400 3
 
0.3%

연체료부과단위시간
Categorical

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
24
611 
48
167 
0
85 
1
 
9
72
 
2

Length

Max length2
Median length2
Mean length1.8924485
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48
2nd row24
3rd row24
4th row24
5th row24

Common Values

ValueCountFrequency (%)
24 611
69.9%
48 167
 
19.1%
0 85
 
9.7%
1 9
 
1.0%
72 2
 
0.2%

Length

2024-05-11T10:33:56.706350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:33:57.336258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
24 611
69.9%
48 167
 
19.1%
0 85
 
9.7%
1 9
 
1.0%
72 2
 
0.2%

연체료
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
1000
749 
0
86 
500
 
38
100
 
1

Length

Max length4
Median length4
Mean length3.6601831
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row1000
2nd row1000
3rd row1000
4th row1000
5th row1000

Common Values

ValueCountFrequency (%)
1000 749
85.7%
0 86
 
9.8%
500 38
 
4.3%
100 1
 
0.1%

Length

2024-05-11T10:33:57.900476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:33:58.247037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1000 749
85.7%
0 86
 
9.8%
500 38
 
4.3%
100 1
 
0.1%

제어방식구분코드
Categorical

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
1
462 
2
344 
99
 
41
3
 
27

Length

Max length2
Median length1
Mean length1.0469108
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 462
52.9%
2 344
39.4%
99 41
 
4.7%
3 27
 
3.1%

Length

2024-05-11T10:33:58.615722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:33:58.950023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 462
52.9%
2 344
39.4%
99 41
 
4.7%
3 27
 
3.1%

사용방법설명
Text

Distinct61
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2024-05-11T10:33:59.802782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length261
Median length259
Mean length85.26087
Min length11

Characters and Unicode

Total characters74518
Distinct characters169
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)0.9%

Sample

1st row물품배송시 휴대폰 문자로 전송되는 택배보관함 번호, 인증번호를 확인하여 해당 보관함에서 본인 휴대폰 번호와 전송받은 인증번호를 입력한 뒤 보관함을 열어 물품 수령
2nd row물품 배송 시 휴대폰 문자로 전송되는 인증번호를 입력하여 물품 수령
3rd row물품 배송 시 휴대폰 문자로 전송되는 인증번호를 입력하여 물품 수령
4th row물품 배송 시 휴대폰 문자로 전송되는 인증번호를 입력하여 물품 수령
5th row물품 배송 시 휴대폰 문자로 전송되는 택배보관함번호, 인증번호를 확인하여, 해당 보관함에서 본인 휴대폰 번호와 전송받은 인증번호를 입력한 뒤 보관함을 열어 물품 수령
ValueCountFrequency (%)
휴대폰 1233
 
7.1%
인증번호를 1211
 
7.0%
물품 1147
 
6.6%
수령 692
 
4.0%
문자로 627
 
3.6%
전송되는 624
 
3.6%
전송받은 619
 
3.6%
보관함을 612
 
3.5%
입력한 607
 
3.5%
뒤 607
 
3.5%
Other values (264) 9329
53.9%
2024-05-11T10:34:01.736856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16457
22.1%
인 3043
 
4.1%
호 2766
 
3.7%
번 2764
 
3.7%
함 2178
 
2.9%
관 2138
 
2.9%
보 2119
 
2.8%
송 2096
 
2.8%
배 1988
 
2.7%
물 1662
 
2.2%
Other values (159) 37307
50.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 55611
74.6%
Space Separator 16457
 
22.1%
Other Punctuation 1514
 
2.0%
Decimal Number 274
 
0.4%
Close Punctuation 265
 
0.4%
Open Punctuation 233
 
0.3%
Math Symbol 110
 
0.1%
Dash Punctuation 48
 
0.1%
Other Number 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 3043
 
5.5%
호 2766
 
5.0%
번 2764
 
5.0%
함 2178
 
3.9%
관 2138
 
3.8%
보 2119
 
3.8%
송 2096
 
3.8%
배 1988
 
3.6%
물 1662
 
3.0%
품 1652
 
3.0%
Other values (133) 33205
59.7%
Decimal Number
ValueCountFrequency (%)
4 75
27.4%
1 51
18.6%
2 51
18.6%
3 50
18.2%
8 31
11.3%
7 6
 
2.2%
0 5
 
1.8%
5 3
 
1.1%
6 1
 
0.4%
9 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 1203
79.5%
. 172
 
11.4%
: 121
 
8.0%
/ 18
 
1.2%
Math Symbol
ValueCountFrequency (%)
→ 62
56.4%
+ 46
41.8%
> 2
 
1.8%
Other Number
ValueCountFrequency (%)
① 2
33.3%
② 2
33.3%
③ 2
33.3%
Close Punctuation
ValueCountFrequency (%)
) 263
99.2%
] 2
 
0.8%
Open Punctuation
ValueCountFrequency (%)
( 231
99.1%
[ 2
 
0.9%
Space Separator
ValueCountFrequency (%)
16457
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 55611
74.6%
Common 18907
 
25.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 3043
 
5.5%
호 2766
 
5.0%
번 2764
 
5.0%
함 2178
 
3.9%
관 2138
 
3.8%
보 2119
 
3.8%
송 2096
 
3.8%
배 1988
 
3.6%
물 1662
 
3.0%
품 1652
 
3.0%
Other values (133) 33205
59.7%
Common
ValueCountFrequency (%)
16457
87.0%
, 1203
 
6.4%
) 263
 
1.4%
( 231
 
1.2%
. 172
 
0.9%
: 121
 
0.6%
4 75
 
0.4%
→ 62
 
0.3%
1 51
 
0.3%
2 51
 
0.3%
Other values (16) 221
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 55611
74.6%
ASCII 18839
 
25.3%
Arrows 62
 
0.1%
Enclosed Alphanum 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16457
87.4%
, 1203
 
6.4%
) 263
 
1.4%
( 231
 
1.2%
. 172
 
0.9%
: 121
 
0.6%
4 75
 
0.4%
1 51
 
0.3%
2 51
 
0.3%
3 50
 
0.3%
Other values (12) 165
 
0.9%
Hangul
ValueCountFrequency (%)
인 3043
 
5.5%
호 2766
 
5.0%
번 2764
 
5.0%
함 2178
 
3.9%
관 2138
 
3.8%
보 2119
 
3.8%
송 2096
 
3.8%
배 1988
 
3.6%
물 1662
 
3.0%
품 1652
 
3.0%
Other values (133) 33205
59.7%
Arrows
ValueCountFrequency (%)
→ 62
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
① 2
33.3%
② 2
33.3%
③ 2
33.3%

택배함종류코드
Categorical

Distinct46
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
중형/02+소형/04
178 
대형/01+중형/02+소형/04
142 
대형/01+중형/02+중소형/03+소형/04
94 
대형/01+중형/02+소형/03
87 
중소형/03
69 
Other values (41)
304 

Length

Max length34
Median length32
Mean length14.586957
Min length1

Unique

Unique10 ?
Unique (%)1.1%

Sample

1st row대형/01+중형/02+중소형/03+소형/04
2nd row대형/01+중형/02+소형/03
3rd row대형/01+중형/02+소형/03
4th row대형/01+중형/02+소형/03
5th row대형/01+중형/02+중소형/03+소형/04

Common Values

ValueCountFrequency (%)
중형/02+소형/04 178
20.4%
대형/01+중형/02+소형/04 142
16.2%
대형/01+중형/02+중소형/03+소형/04 94
10.8%
대형/01+중형/02+소형/03 87
10.0%
중소형/03 69
 
7.9%
대형/01+중형/02+중소형/03 49
 
5.6%
대형/01+중형/02 45
 
5.1%
중형/02+중소형/03 32
 
3.7%
대형/02 18
 
2.1%
소형/04+중형/02 14
 
1.6%
Other values (36) 146
16.7%

Length

2024-05-11T10:34:02.454070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
중형/02+소형/04 178
20.4%
대형/01+중형/02+소형/04 142
16.2%
대형/01+중형/02+중소형/03+소형/04 94
10.8%
대형/01+중형/02+소형/03 87
10.0%
중소형/03 69
 
7.9%
대형/01+중형/02+중소형/03 49
 
5.6%
대형/01+중형/02 45
 
5.1%
중형/02+중소형/03 32
 
3.7%
대형/02 18
 
2.1%
소형/04+중형/02 14
 
1.6%
Other values (36) 146
16.7%

칸개수
Text

Distinct186
Distinct (%)21.3%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2024-05-11T10:34:03.162460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length21
Mean length13.01373
Min length2

Characters and Unicode

Total characters11374
Distinct characters19
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)8.5%

Sample

1st row01/01+02/04+03/03+04/12
2nd row01/3+02/2+03/14
3rd row01/3+02/2+03/14
4th row01/3+02/2+03/12
5th row01/1+02/3+03/12+04/3
ValueCountFrequency (%)
02/03+04/08 77
 
8.8%
01/20+02/5 38
 
4.3%
01/3+02/2+04/14 33
 
3.8%
01/3+02/2+03/14 27
 
3.1%
01/20+02/40+03/40 25
 
2.9%
02/3+04/8 23
 
2.6%
03/11 22
 
2.5%
02/2+04/8 21
 
2.4%
01/2+02/1+04/9 21
 
2.4%
02/10 18
 
2.1%
Other values (178) 571
65.2%
2024-05-11T10:34:04.484571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2967
26.1%
/ 2180
19.2%
1 1437
12.6%
+ 1334
11.7%
2 1186
 
10.4%
3 818
 
7.2%
4 796
 
7.0%
8 207
 
1.8%
5 187
 
1.6%
6 102
 
0.9%
Other values (9) 160
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7829
68.8%
Other Punctuation 2180
 
19.2%
Math Symbol 1334
 
11.7%
Dash Punctuation 9
 
0.1%
Open Punctuation 7
 
0.1%
Close Punctuation 7
 
0.1%
Other Letter 6
 
0.1%
Space Separator 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2967
37.9%
1 1437
18.4%
2 1186
 
15.1%
3 818
 
10.4%
4 796
 
10.2%
8 207
 
2.6%
5 187
 
2.4%
6 102
 
1.3%
9 99
 
1.3%
7 30
 
0.4%
Other Letter
ValueCountFrequency (%)
개 2
33.3%
월 2
33.3%
일 2
33.3%
Other Punctuation
ValueCountFrequency (%)
/ 2180
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1334
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11368
99.9%
Hangul 6
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2967
26.1%
/ 2180
19.2%
1 1437
12.6%
+ 1334
11.7%
2 1186
 
10.4%
3 818
 
7.2%
4 796
 
7.0%
8 207
 
1.8%
5 187
 
1.6%
6 102
 
0.9%
Other values (6) 154
 
1.4%
Hangul
ValueCountFrequency (%)
개 2
33.3%
월 2
33.3%
일 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11368
99.9%
Hangul 6
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2967
26.1%
/ 2180
19.2%
1 1437
12.6%
+ 1334
11.7%
2 1186
 
10.4%
3 818
 
7.2%
4 796
 
7.0%
8 207
 
1.8%
5 187
 
1.6%
6 102
 
0.9%
Other values (6) 154
 
1.4%
Hangul
ValueCountFrequency (%)
개 2
33.3%
월 2
33.3%
일 2
33.3%

칸깊이
Text

Distinct73
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2024-05-11T10:34:05.140445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length29
Mean length14.212815
Min length2

Characters and Unicode

Total characters12422
Distinct characters15
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)1.3%

Sample

1st row01/50+02/50+03/50+04/50
2nd row01/53+02/53+03/53
3rd row01/53+02/53+03/53
4th row01/53+02/53+03/53
5th row01/60+02/60+03/60+04/60
ValueCountFrequency (%)
02/60+04/60 157
18.0%
01/60+02/60+04/60 83
 
9.5%
01/55+02/55+04/55 49
 
5.6%
01/55+02/55+03/55 45
 
5.1%
01/60+02/60+03/60+04/60 34
 
3.9%
03/60 33
 
3.8%
01/60+02/60+03/60 30
 
3.4%
01/30+02/30+03/50 28
 
3.2%
01/50+02/50+03/50+04/50 27
 
3.1%
02/60+03/60 26
 
3.0%
Other values (63) 362
41.4%
2024-05-11T10:34:06.352232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3860
31.1%
/ 2179
17.5%
+ 1332
 
10.7%
5 1293
 
10.4%
6 1257
 
10.1%
2 832
 
6.7%
1 549
 
4.4%
3 534
 
4.3%
4 527
 
4.2%
. 21
 
0.2%
Other values (5) 38
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8876
71.5%
Other Punctuation 2200
 
17.7%
Math Symbol 1332
 
10.7%
Open Punctuation 7
 
0.1%
Close Punctuation 7
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3860
43.5%
5 1293
 
14.6%
6 1257
 
14.2%
2 832
 
9.4%
1 549
 
6.2%
3 534
 
6.0%
4 527
 
5.9%
9 18
 
0.2%
8 3
 
< 0.1%
7 3
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 2179
99.0%
. 21
 
1.0%
Math Symbol
ValueCountFrequency (%)
+ 1332
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12422
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3860
31.1%
/ 2179
17.5%
+ 1332
 
10.7%
5 1293
 
10.4%
6 1257
 
10.1%
2 832
 
6.7%
1 549
 
4.4%
3 534
 
4.3%
4 527
 
4.2%
. 21
 
0.2%
Other values (5) 38
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12422
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3860
31.1%
/ 2179
17.5%
+ 1332
 
10.7%
5 1293
 
10.4%
6 1257
 
10.1%
2 832
 
6.7%
1 549
 
4.4%
3 534
 
4.3%
4 527
 
4.2%
. 21
 
0.2%
Other values (5) 38
 
0.3%

칸너비
Text

Distinct80
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2024-05-11T10:34:06.908254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length27
Mean length14.200229
Min length1

Characters and Unicode

Total characters12411
Distinct characters15
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)2.5%

Sample

1st row01/52+02/44+03/52+04/44
2nd row01/44+02/44+03/44
3rd row01/44+02/44+03/44
4th row01/44+02/44+03/44
5th row01/50+02/50+03/50+04/50
ValueCountFrequency (%)
02/50+04/50 98
 
11.2%
01/50+02/50+04/50 82
 
9.4%
01/50+02/50+03/50 49
 
5.6%
01/45+02/45+04/45 49
 
5.6%
02/45+04/23 45
 
5.1%
01/45+02/45+03/45 45
 
5.1%
01/40+02/50+03/70 28
 
3.2%
02/50+03/50 26
 
3.0%
01/52+02/44+03/52+04/44 25
 
2.9%
01/20+02/5 25
 
2.9%
Other values (70) 402
46.0%
2024-05-11T10:34:08.140452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3561
28.7%
/ 2179
17.6%
5 1874
15.1%
+ 1335
 
10.8%
4 1318
 
10.6%
2 958
 
7.7%
1 551
 
4.4%
3 496
 
4.0%
7 52
 
0.4%
6 39
 
0.3%
Other values (5) 48
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8874
71.5%
Other Punctuation 2188
 
17.6%
Math Symbol 1335
 
10.8%
Open Punctuation 7
 
0.1%
Close Punctuation 7
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3561
40.1%
5 1874
21.1%
4 1318
 
14.9%
2 958
 
10.8%
1 551
 
6.2%
3 496
 
5.6%
7 52
 
0.6%
6 39
 
0.4%
9 14
 
0.2%
8 11
 
0.1%
Other Punctuation
ValueCountFrequency (%)
/ 2179
99.6%
. 9
 
0.4%
Math Symbol
ValueCountFrequency (%)
+ 1335
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12411
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3561
28.7%
/ 2179
17.6%
5 1874
15.1%
+ 1335
 
10.8%
4 1318
 
10.6%
2 958
 
7.7%
1 551
 
4.4%
3 496
 
4.0%
7 52
 
0.4%
6 39
 
0.3%
Other values (5) 48
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12411
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3561
28.7%
/ 2179
17.6%
5 1874
15.1%
+ 1335
 
10.8%
4 1318
 
10.6%
2 958
 
7.7%
1 551
 
4.4%
3 496
 
4.0%
7 52
 
0.4%
6 39
 
0.3%
Other values (5) 48
 
0.4%

칸높이
Text

Distinct113
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2024-05-11T10:34:08.844620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length29
Mean length14.961098
Min length2

Characters and Unicode

Total characters13076
Distinct characters18
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)3.5%

Sample

1st row01/44+02/35+03/22+04/17
2nd row01/51+02/37+03/18
3rd row01/51+02/37+03/18
4th row01/51+02/37+03/18
5th row01/90+02/45+03/30+04/22.5
ValueCountFrequency (%)
02/45+04/22.5 92
 
10.5%
02/50+04/50 59
 
6.7%
01/67.5+02/45+04/22.5 43
 
4.9%
01/51+02/37+03/18 41
 
4.7%
01/51+02/37+04/18 31
 
3.5%
01/40+02/50+03/70 28
 
3.2%
01/44+02/35+03/22+04/17 27
 
3.1%
01/20+02/5 25
 
2.9%
01/67.5+02/45+03/22.5 23
 
2.6%
03/2890 20
 
2.3%
Other values (104) 486
55.5%
2024-05-11T10:34:10.040349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3080
23.6%
/ 2200
16.8%
2 1532
11.7%
+ 1336
10.2%
5 1093
 
8.4%
4 957
 
7.3%
1 866
 
6.6%
3 820
 
6.3%
. 307
 
2.3%
7 268
 
2.0%
Other values (8) 617
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9216
70.5%
Other Punctuation 2507
 
19.2%
Math Symbol 1336
 
10.2%
Open Punctuation 7
 
0.1%
Close Punctuation 7
 
0.1%
Other Letter 2
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3080
33.4%
2 1532
16.6%
5 1093
 
11.9%
4 957
 
10.4%
1 866
 
9.4%
3 820
 
8.9%
7 268
 
2.9%
6 238
 
2.6%
8 202
 
2.2%
9 160
 
1.7%
Other Punctuation
ValueCountFrequency (%)
/ 2200
87.8%
. 307
 
12.2%
Other Letter
ValueCountFrequency (%)
월 1
50.0%
일 1
50.0%
Math Symbol
ValueCountFrequency (%)
+ 1336
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13074
> 99.9%
Hangul 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3080
23.6%
/ 2200
16.8%
2 1532
11.7%
+ 1336
10.2%
5 1093
 
8.4%
4 957
 
7.3%
1 866
 
6.6%
3 820
 
6.3%
. 307
 
2.3%
7 268
 
2.0%
Other values (6) 615
 
4.7%
Hangul
ValueCountFrequency (%)
월 1
50.0%
일 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13074
> 99.9%
Hangul 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3080
23.6%
/ 2200
16.8%
2 1532
11.7%
+ 1336
10.2%
5 1093
 
8.4%
4 957
 
7.3%
1 866
 
6.6%
3 820
 
6.3%
. 307
 
2.3%
7 268
 
2.0%
Other values (6) 615
 
4.7%
Hangul
ValueCountFrequency (%)
월 1
50.0%
일 1
50.0%

설치일자
Date

Distinct318
Distinct (%)36.4%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
Minimum2013-01-01 00:00:00
Maximum2024-03-21 00:00:00
2024-05-11T10:34:10.586133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:34:11.128591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

고객센터전화번호
Categorical

Distinct37
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
1600-5136
282 
1666-0339
174 
1899-4711
105 
053-1600-5136
96 
02-1666-0339
36 
Other values (32)
181 

Length

Max length13
Median length9
Mean length9.8032037
Min length9

Unique

Unique14 ?
Unique (%)1.6%

Sample

1st row053-1600-5136
2nd row1666-0339
3rd row1666-0339
4th row1666-0339
5th row1599-2740

Common Values

ValueCountFrequency (%)
1600-5136 282
32.3%
1666-0339 174
19.9%
1899-4711 105
 
12.0%
053-1600-5136 96
 
11.0%
02-1666-0339 36
 
4.1%
1599-2740 30
 
3.4%
1666-2098 19
 
2.2%
1577-1545 16
 
1.8%
1688-1186 15
 
1.7%
02-857-2750 14
 
1.6%
Other values (27) 87
 
10.0%

Length

2024-05-11T10:34:11.620536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1600-5136 282
32.3%
1666-0339 174
19.9%
1899-4711 105
 
12.0%
053-1600-5136 96
 
11.0%
02-1666-0339 36
 
4.1%
1599-2740 30
 
3.4%
1666-2098 19
 
2.2%
1577-1545 16
 
1.8%
1688-1186 15
 
1.7%
02-857-2750 14
 
1.6%
Other values (27) 87
 
10.0%

관리기관명
Text

Distinct144
Distinct (%)16.5%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2024-05-11T10:34:12.308250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length17
Mean length11.130435
Min length3

Characters and Unicode

Total characters9728
Distinct characters192
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

Unique64 ?
Unique (%)7.3%

Sample

1st row대구광역시 동구청 안전총괄과
2nd row스마트큐브
3rd row스마트큐브
4th row스마트큐브
5th row광주광역시 북구청
ValueCountFrequency (%)
대구광역시 189
 
9.7%
여성가족과 144
 
7.4%
경기도 137
 
7.0%
안전총괄과 88
 
4.5%
서울특별시 79
 
4.1%
㈜스마트큐브 66
 
3.4%
인천광역시 65
 
3.3%
스마트큐브 52
 
2.7%
북구청 48
 
2.5%
서구청 47
 
2.4%
Other values (167) 1032
53.0%
2024-05-11T10:34:13.842878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1073
 
11.0%
시 674
 
6.9%
청 609
 
6.3%
구 587
 
6.0%
과 399
 
4.1%
광 363
 
3.7%
역 324
 
3.3%
도 277
 
2.8%
성 268
 
2.8%
대 226
 
2.3%
Other values (182) 4928
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8480
87.2%
Space Separator 1073
 
11.0%
Other Symbol 95
 
1.0%
Decimal Number 26
 
0.3%
Open Punctuation 22
 
0.2%
Close Punctuation 22
 
0.2%
Uppercase Letter 10
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 674
 
7.9%
청 609
 
7.2%
구 587
 
6.9%
과 399
 
4.7%
광 363
 
4.3%
역 324
 
3.8%
도 277
 
3.3%
성 268
 
3.2%
대 226
 
2.7%
전 202
 
2.4%
Other values (166) 4551
53.7%
Decimal Number
ValueCountFrequency (%)
1 9
34.6%
2 7
26.9%
3 3
 
11.5%
4 3
 
11.5%
6 2
 
7.7%
7 1
 
3.8%
5 1
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
C 3
30.0%
Y 2
20.0%
W 2
20.0%
A 2
20.0%
S 1
 
10.0%
Space Separator
ValueCountFrequency (%)
1073
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 95
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8575
88.1%
Common 1143
 
11.7%
Latin 10
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 674
 
7.9%
청 609
 
7.1%
구 587
 
6.8%
과 399
 
4.7%
광 363
 
4.2%
역 324
 
3.8%
도 277
 
3.2%
성 268
 
3.1%
대 226
 
2.6%
전 202
 
2.4%
Other values (167) 4646
54.2%
Common
ValueCountFrequency (%)
1073
93.9%
( 22
 
1.9%
) 22
 
1.9%
1 9
 
0.8%
2 7
 
0.6%
3 3
 
0.3%
4 3
 
0.3%
6 2
 
0.2%
7 1
 
0.1%
5 1
 
0.1%
Latin
ValueCountFrequency (%)
C 3
30.0%
Y 2
20.0%
W 2
20.0%
A 2
20.0%
S 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8480
87.2%
ASCII 1153
 
11.9%
None 95
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1073
93.1%
( 22
 
1.9%
) 22
 
1.9%
1 9
 
0.8%
2 7
 
0.6%
3 3
 
0.3%
C 3
 
0.3%
4 3
 
0.3%
6 2
 
0.2%
Y 2
 
0.2%
Other values (5) 7
 
0.6%
Hangul
ValueCountFrequency (%)
시 674
 
7.9%
청 609
 
7.2%
구 587
 
6.9%
과 399
 
4.7%
광 363
 
4.3%
역 324
 
3.8%
도 277
 
3.3%
성 268
 
3.2%
대 226
 
2.7%
전 202
 
2.4%
Other values (166) 4551
53.7%
None
ValueCountFrequency (%)
㈜ 95
100.0%

관리기관전화번호
Text

Distinct149
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2024-05-11T10:34:14.536207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.636156
Min length9

Characters and Unicode

Total characters10170
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

Unique66 ?
Unique (%)7.6%

Sample

1st row053-662-2948
2nd row1666-0339
3rd row1666-0339
4th row1666-0340
5th row062-410-6759
ValueCountFrequency (%)
1666-0339 63
 
7.2%
053-665-4314 40
 
4.6%
053-667-2894 39
 
4.5%
02-1666-0339 28
 
3.2%
031-8075-3336 25
 
2.9%
032-625-2921 25
 
2.9%
053-666-2961 19
 
2.2%
053-666-2964 19
 
2.2%
043-201-1753 16
 
1.8%
031-729-2315 16
 
1.8%
Other values (139) 584
66.8%
2024-05-11T10:34:15.931933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1647
16.2%
6 1269
12.5%
3 1265
12.4%
0 1257
12.4%
2 1154
11.3%
5 834
8.2%
1 792
7.8%
4 621
 
6.1%
9 519
 
5.1%
8 415
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8523
83.8%
Dash Punctuation 1647
 
16.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 1269
14.9%
3 1265
14.8%
0 1257
14.7%
2 1154
13.5%
5 834
9.8%
1 792
9.3%
4 621
7.3%
9 519
6.1%
8 415
 
4.9%
7 397
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 1647
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10170
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1647
16.2%
6 1269
12.5%
3 1265
12.4%
0 1257
12.4%
2 1154
11.3%
5 834
8.2%
1 792
7.8%
4 621
 
6.1%
9 519
 
5.1%
8 415
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10170
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1647
16.2%
6 1269
12.5%
3 1265
12.4%
0 1257
12.4%
2 1154
11.3%
5 834
8.2%
1 792
7.8%
4 621
 
6.1%
9 519
 
5.1%
8 415
 
4.1%

데이터기준일자
Date

Distinct79
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
Minimum2021-10-26 00:00:00
Maximum2024-04-11 00:00:00
2024-05-11T10:34:16.396085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:34:16.872624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

제공기관코드
Real number (ℝ)

Distinct95
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4107778.6
Minimum3000000
Maximum6500000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.8 KiB
2024-05-11T10:34:17.492202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3050000
Q13210000
median3560000
Q34810000
95-th percentile6270000
Maximum6500000
Range3500000
Interquartile range (IQR)1600000

Descriptive statistics

Standard deviation1146221.8
Coefficient of variation (CV)0.27903689
Kurtosis-0.42266511
Mean4107778.6
Median Absolute Deviation (MAD)390000
Skewness1.0647157
Sum3.5901985 × 109
Variance1.3138243 × 1012
MonotonicityNot monotonic
2024-05-11T10:34:17.958851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6270000 110
 
12.6%
3860000 25
 
2.9%
3940000 25
 
2.9%
3450000 20
 
2.3%
3470000 20
 
2.3%
3460000 19
 
2.2%
6430000 18
 
2.1%
3210000 17
 
1.9%
3780000 16
 
1.8%
3200000 16
 
1.8%
Other values (85) 588
67.3%
ValueCountFrequency (%)
3000000 5
 
0.6%
3010000 7
0.8%
3020000 8
0.9%
3030000 10
1.1%
3040000 13
1.5%
3050000 11
1.3%
3060000 6
0.7%
3070000 8
0.9%
3080000 9
1.0%
3100000 14
1.6%
ValueCountFrequency (%)
6500000 14
 
1.6%
6430000 18
 
2.1%
6270000 110
12.6%
5710000 8
 
0.9%
5680000 3
 
0.3%
5670000 7
 
0.8%
5590000 2
 
0.2%
5570000 1
 
0.1%
5530000 6
 
0.7%
5380000 5
 
0.6%

제공기관명
Text

Distinct95
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2024-05-11T10:34:18.658426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.8524027
Min length4

Characters and Unicode

Total characters6863
Distinct characters85
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 (%)0.9%

Sample

1st row대구광역시
2nd row서울특별시 중랑구
3rd row서울특별시 중랑구
4th row서울특별시 중랑구
5th row광주광역시 북구
ValueCountFrequency (%)
서울특별시 243
 
15.1%
대구광역시 212
 
13.2%
경기도 145
 
9.0%
인천광역시 74
 
4.6%
서구 37
 
2.3%
충청북도 36
 
2.2%
북구 28
 
1.7%
광주광역시 28
 
1.7%
남구 26
 
1.6%
고양시 25
 
1.6%
Other values (85) 752
46.8%
2024-05-11T10:34:19.649251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 832
 
12.1%
732
 
10.7%
구 716
 
10.4%
광 416
 
6.1%
역 359
 
5.2%
서 344
 
5.0%
도 272
 
4.0%
별 261
 
3.8%
특 261
 
3.8%
대 255
 
3.7%
Other values (75) 2415
35.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6131
89.3%
Space Separator 732
 
10.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 832
 
13.6%
구 716
 
11.7%
광 416
 
6.8%
역 359
 
5.9%
서 344
 
5.6%
도 272
 
4.4%
별 261
 
4.3%
특 261
 
4.3%
대 255
 
4.2%
울 249
 
4.1%
Other values (74) 2166
35.3%
Space Separator
ValueCountFrequency (%)
732
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6131
89.3%
Common 732
 
10.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 832
 
13.6%
구 716
 
11.7%
광 416
 
6.8%
역 359
 
5.9%
서 344
 
5.6%
도 272
 
4.4%
별 261
 
4.3%
특 261
 
4.3%
대 255
 
4.2%
울 249
 
4.1%
Other values (74) 2166
35.3%
Common
ValueCountFrequency (%)
732
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6131
89.3%
ASCII 732
 
10.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 832
 
13.6%
구 716
 
11.7%
광 416
 
6.8%
역 359
 
5.9%
서 344
 
5.6%
도 272
 
4.4%
별 261
 
4.3%
특 261
 
4.3%
대 255
 
4.2%
울 249
 
4.1%
Other values (74) 2166
35.3%
ASCII
ValueCountFrequency (%)
732
100.0%

Sample

시설명시도명시군구명시군구코드소재지도로명주소소재지지번주소위도경도평일운영시작시각평일운영종료시각토요일운영시작시각토요일운영종료시각공휴일운영시작시각공휴일운영종료시각무료이용시간연체료부과단위시간연체료제어방식구분코드사용방법설명택배함종류코드칸개수칸깊이칸너비칸높이설치일자고객센터전화번호관리기관명관리기관전화번호데이터기준일자제공기관코드제공기관명
0지저동 행정복지센터대구광역시동구27140대구광역시 동구 해동로3길 80대구광역시 동구 지저동 779-535.893392128.63828200:0023:5900:0023:5900:0023:5904810002물품배송시 휴대폰 문자로 전송되는 택배보관함 번호, 인증번호를 확인하여 해당 보관함에서 본인 휴대폰 번호와 전송받은 인증번호를 입력한 뒤 보관함을 열어 물품 수령대형/01+중형/02+중소형/03+소형/0401/01+02/04+03/03+04/1201/50+02/50+03/50+04/5001/52+02/44+03/52+04/4401/44+02/35+03/22+04/172017-12-18053-1600-5136대구광역시 동구청 안전총괄과053-662-29482023-01-196270000대구광역시
1상봉2동주민센터서울특별시중랑구11260서울특별시 중랑구 동일로114길 10서울특별시 중랑구 상봉동 12637.592892127.08089500:0023:5900:0023:5900:0023:59482410002물품 배송 시 휴대폰 문자로 전송되는 인증번호를 입력하여 물품 수령대형/01+중형/02+소형/0301/3+02/2+03/1401/53+02/53+03/5301/44+02/44+03/4401/51+02/37+03/182020-08-011666-0339스마트큐브1666-03392023-05-023060000서울특별시 중랑구
2중화1치안센터서울특별시중랑구11260서울특별시 중랑구 동일로 792서울특별시 중랑구 중화동 287-837.60116127.07981400:0023:5900:0023:5900:0023:59482410002물품 배송 시 휴대폰 문자로 전송되는 인증번호를 입력하여 물품 수령대형/01+중형/02+소형/0301/3+02/2+03/1401/53+02/53+03/5301/44+02/44+03/4401/51+02/37+03/182020-08-011666-0339스마트큐브1666-03392023-05-023060000서울특별시 중랑구
3상봉1동주민센터서울특별시중랑구11260서울특별시 중랑구 상봉중앙로1길 6서울특별시 중랑구 상봉동 204-137.599863127.08719400:0023:5900:0023:5900:0023:59482410002물품 배송 시 휴대폰 문자로 전송되는 인증번호를 입력하여 물품 수령대형/01+중형/02+소형/0301/3+02/2+03/1201/53+02/53+03/5301/44+02/44+03/4401/51+02/37+03/182023-02-131666-0339스마트큐브1666-03402023-05-023060000서울특별시 중랑구
4문흥동 청소년 수련관 별관광주광역시북구29170광주광역시 북구 대천로 86광주광역시 북구 문흥동 1009-135.184917126.91668600:0023:5900:0023:5900:0023:59482410001물품 배송 시 휴대폰 문자로 전송되는 택배보관함번호, 인증번호를 확인하여, 해당 보관함에서 본인 휴대폰 번호와 전송받은 인증번호를 입력한 뒤 보관함을 열어 물품 수령대형/01+중형/02+중소형/03+소형/0401/1+02/3+03/12+04/301/60+02/60+03/60+04/6001/50+02/50+03/50+04/5001/90+02/45+03/30+04/22.52019-06-271599-2740광주광역시 북구청062-410-67592023-11-233620000광주광역시 북구
5용봉동 용흥어린이공원광주광역시북구29170광주광역시 북구 우치로100번길 26광주광역시 북구 용봉동 158-635.176307126.91393800:0023:5900:0023:5900:0023:59482410001물품 배송 시 휴대폰 문자로 전송되는 택배보관함번호, 인증번호를 확인하여, 해당 보관함에서 본인 휴대폰 번호와 전송받은 인증번호를 입력한 뒤 보관함을 열어 물품 수령중형/02+소형/0302/2+03/802/60+03/6002/50+03/5002/45+03/22.52020-06-241600-5136광주광역시 북구청062-410-67592023-11-233620000광주광역시 북구
6용봉동 새봄어린이공원광주광역시북구29170광주광역시 북구 설죽로 214번길 60광주광역시 북구 용봉동 1251-135.177937126.90095600:0023:5900:0023:5900:0023:59482410001물품 배송 시 휴대폰 문자로 전송되는 택배보관함번호, 인증번호를 확인하여, 해당 보관함에서 본인 휴대폰 번호와 전송받은 인증번호를 입력한 뒤 보관함을 열어 물품 수령중형/02+소형/0302/3+03/802/60+03/6002/50+03/5002/45+03/22.52021-09-301600-5136광주광역시 북구청062-410-67592023-11-233620000광주광역시 북구
7중흥동 효죽공영주차장광주광역시북구29170광주광역시 북구 용봉로138번길 11광주광역시 북구 중흥동 358-335.173009126.9117200:0023:5900:0023:5900:0023:59482410001물품 배송 시 휴대폰 문자로 전송되는 택배보관함번호, 인증번호를 확인하여, 해당 보관함에서 본인 휴대폰 번호와 전송받은 인증번호를 입력한 뒤 보관함을 열어 물품 수령중형/02+소형/0302/2+03/802/60+03/6002/50+03/5002/45+03/22.52022-12-281600-5136광주광역시 북구청062-410-67592023-11-233620000광주광역시 북구
8중흥동 동부시장광주광역시북구29170광주광역시 북구 중문로9번길 39광주광역시 북구 중흥동 272-635.173886126.91633700:0023:5900:0023:5900:0023:59482410001물품 배송 시 휴대폰 문자로 전송되는 택배보관함번호, 인증번호를 확인하여, 해당 보관함에서 본인 휴대폰 번호와 전송받은 인증번호를 입력한 뒤 보관함을 열어 물품 수령중형/02+소형/0302/3+03/802/60+03/6002/50+03/5002/45+03/22.52023-02-021600-5136광주광역시 북구청062-410-67592023-11-233620000광주광역시 북구
9원고개 다락방대구광역시서구27170대구광역시 서구 북비산로59길 13대구광역시 서구 비산동 782-2635.880758128.5653600:0023:5900:0023:5900:0023:5904810002물품배송시 휴대폰 문자로 전송되는 택배보관함 번호, 인증번호를 확인하여 해당 보관함에서 본인 휴대폰 번호와 전송받은 인증번호를 입력한 뒤 보관함을 열어 물품 수령중형/02+소형/0402/03+04/0802/60+04/6002/45+04/2302/50+04/502021-08-01053-1600-5136대구광역시 서구청 건설안전과053-663-29132023-01-196270000대구광역시
시설명시도명시군구명시군구코드소재지도로명주소소재지지번주소위도경도평일운영시작시각평일운영종료시각토요일운영시작시각토요일운영종료시각공휴일운영시작시각공휴일운영종료시각무료이용시간연체료부과단위시간연체료제어방식구분코드사용방법설명택배함종류코드칸개수칸깊이칸너비칸높이설치일자고객센터전화번호관리기관명관리기관전화번호데이터기준일자제공기관코드제공기관명
864성동구립도서관서울특별시성동구11200서울특별시 성동구 고산자로10길 9서울특별시 성동구 행당동 142-437.559153127.03493900:0023:5900:0023:5900:0023:59482410001물품 배송 시 휴대폰 문자로 전송되는 택배보관함번호, 인증번호를 확인하여, 해당 보관함에서 본인 휴대폰 번호와 전송받은 인증번호를 입력한 뒤 보관함을 열어 물품 수령중소형/0304/26550450180/370/5102015-01-011666-0339㈜스마트큐브1666-03392023-07-143030000서울특별시 성동구
865성동구민종합체육센터서울특별시성동구11200서울특별시 성동구 왕십리로 89서울특별시 성동구 성수동1가 685-69737.545847127.04404900:0023:5900:0023:5900:0023:59482410001물품 배송 시 휴대폰 문자로 전송되는 택배보관함번호, 인증번호를 확인하여, 해당 보관함에서 본인 휴대폰 번호와 전송받은 인증번호를 입력한 뒤 보관함을 열어 물품 수령중소형/0303/19550450180/370/5102017-01-011666-0339㈜스마트큐브1666-03392023-07-143030000서울특별시 성동구
866사근동주민센터서울특별시성동구11200서울특별시 성동구 사근동길 37서울특별시 성동구 사근동 223-2237.5615127.04532700:0023:5900:0023:5900:0023:59482410001물품 배송 시 휴대폰 문자로 전송되는 택배보관함번호, 인증번호를 확인하여, 해당 보관함에서 본인 휴대폰 번호와 전송받은 인증번호를 입력한 뒤 보관함을 열어 물품 수령중소형/0302/12550450180/370/5102018-01-011666-0339㈜스마트큐브1666-03392023-07-143030000서울특별시 성동구
867열린금호교육문화관서울특별시성동구11200서울특별시 성동구 무수막길 69<NA>37.551898127.02075300:0023:5900:0023:5900:0023:59482410001물품 배송 시 휴대폰 문자로 전송되는 택배보관함번호, 인증번호를 확인하여, 해당 보관함에서 본인 휴대폰 번호와 전송받은 인증번호를 입력한 뒤 보관함을 열어 물품 수령중소형/0302/12550450180/370/5102019-06-011666-0339㈜스마트큐브1666-03392023-07-143030000서울특별시 성동구
868하왕십리역공영주차장서울특별시성동구11200서울특별시 성동구 무학봉길 48<NA>37.560286127.02792300:0023:5900:0023:5900:0023:59482410001물품 배송 시 휴대폰 문자로 전송되는 택배보관함번호, 인증번호를 확인하여, 해당 보관함에서 본인 휴대폰 번호와 전송받은 인증번호를 입력한 뒤 보관함을 열어 물품 수령중소형/0302/12550450180/370/5102020-07-011666-0339㈜스마트큐브1666-03392023-07-143030000서울특별시 성동구
869강변공영주차장서울특별시성동구11200서울특별시 성동구 둘레길 47-5<NA>37.536964127.04906700:0023:5900:0023:5900:0023:59482410001물품 배송 시 휴대폰 문자로 전송되는 택배보관함번호, 인증번호를 확인하여, 해당 보관함에서 본인 휴대폰 번호와 전송받은 인증번호를 입력한 뒤 보관함을 열어 물품 수령중소형/0303/19550450180/370/5102020-07-011666-0339㈜스마트큐브1666-03392023-07-143030000서울특별시 성동구
870용답건물서울특별시성동구11200서울특별시 성동구 용답29길 22<NA>37.564564127.05430700:0023:5900:0023:5900:0023:59482410001물품 배송 시 휴대폰 문자로 전송되는 택배보관함번호, 인증번호를 확인하여, 해당 보관함에서 본인 휴대폰 번호와 전송받은 인증번호를 입력한 뒤 보관함을 열어 물품 수령중소형/0302/12550450180/370/5102020-11-171666-0339㈜스마트큐브1666-03392023-07-143030000서울특별시 성동구
871성수2가3동공영주차장서울특별시성동구11200서울특별시 성동구 광나루로 4가길 23<NA>37.549124127.05517700:0023:5900:0023:5900:0023:59482410001물품 배송 시 휴대폰 문자로 전송되는 택배보관함번호, 인증번호를 확인하여, 해당 보관함에서 본인 휴대폰 번호와 전송받은 인증번호를 입력한 뒤 보관함을 열어 물품 수령중소형/0302/12550450180/370/5102020-11-171666-0339㈜스마트큐브1666-03392023-07-143030000서울특별시 성동구
872장안2동 공영주차장서울특별시동대문구11230서울특별시 동대문구 답십리로65길 124-5(장안동)서울특별시 동대문구 장안동 286-937.578264127.07060100:0023:5900:0023:5900:0023:59482410001물품 배송 시 휴대폰 문자로 전송되는 택배보관함번호,인증번호를 확인하여, 해당 보관함에서 본인휴대폰 번호와 전송받은 인증번호를 입력한 뒤, 보관함을 열어 물품 수령01/대형+02/중형+04/소형01/3+02/2+04/1401/550+02/550+04/55001/450+02/450+04/45001/510+02/370+04/1802020-03-061666-0339장안2동 공영주차장02-3295-14782024-01-093050000서울특별시 동대문구
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