Overview

Dataset statistics

Number of variables25
Number of observations219
Missing cells416
Missing cells (%)7.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory43.8 KiB
Average record size in memory204.6 B

Variable types

Text14
Categorical5
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/15021108/standard.do

Alerts

평일운영시작시각 is highly imbalanced (56.0%)Imbalance
소재지도로명주소 has 3 (1.4%) missing valuesMissing
소재지지번주소 has 18 (8.2%) missing valuesMissing
운영기관전화번호 has 12 (5.5%) missing valuesMissing
운영기관대표자명 has 27 (12.3%) missing valuesMissing
휴무일정보 has 21 (9.6%) missing valuesMissing
애프터서비스정보 has 171 (78.1%) missing valuesMissing
홈페이지주소 has 164 (74.9%) missing valuesMissing
차량보유대수 has 25 (11.4%) zerosZeros

Reproduction

Analysis started2024-05-11 07:47:59.119089
Analysis finished2024-05-11 07:48:01.232397
Duration2.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

재활용센터명
Text

Distinct190
Distinct (%)86.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-05-11T16:48:01.663106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length19
Mean length10.39726
Min length4

Characters and Unicode

Total characters2277
Distinct characters201
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

Unique162 ?
Unique (%)74.0%

Sample

1st row자월면 대이작 재활용 선별장
2nd row자월면 승봉 재활용 선별장
3rd row대청면 소청 재활용 선별장
4th row의정부시재활용센터
5th row곡성군 재활용품 선별장
ValueCountFrequency (%)
선별장 21
 
5.5%
재활용 21
 
5.5%
재활용센터 14
 
3.7%
재활용선별장 12
 
3.1%
재활용품 7
 
1.8%
생활자원회수센터 7
 
1.8%
재활용선별시설 5
 
1.3%
춘천시 4
 
1.0%
원주시 4
 
1.0%
재활용품선별장 4
 
1.0%
Other values (229) 282
74.0%
2024-05-11T16:48:02.525898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
활 174
 
7.6%
162
 
7.1%
용 159
 
7.0%
재 154
 
6.8%
센 120
 
5.3%
터 119
 
5.2%
시 92
 
4.0%
선 69
 
3.0%
별 67
 
2.9%
장 63
 
2.8%
Other values (191) 1098
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2079
91.3%
Space Separator 162
 
7.1%
Close Punctuation 13
 
0.6%
Open Punctuation 13
 
0.6%
Decimal Number 5
 
0.2%
Uppercase Letter 4
 
0.2%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
활 174
 
8.4%
용 159
 
7.6%
재 154
 
7.4%
센 120
 
5.8%
터 119
 
5.7%
시 92
 
4.4%
선 69
 
3.3%
별 67
 
3.2%
장 63
 
3.0%
구 53
 
2.5%
Other values (181) 1009
48.5%
Uppercase Letter
ValueCountFrequency (%)
A 1
25.0%
C 1
25.0%
W 1
25.0%
Y 1
25.0%
Decimal Number
ValueCountFrequency (%)
1 3
60.0%
2 2
40.0%
Space Separator
ValueCountFrequency (%)
162
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2079
91.3%
Common 194
 
8.5%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
활 174
 
8.4%
용 159
 
7.6%
재 154
 
7.4%
센 120
 
5.8%
터 119
 
5.7%
시 92
 
4.4%
선 69
 
3.3%
별 67
 
3.2%
장 63
 
3.0%
구 53
 
2.5%
Other values (181) 1009
48.5%
Common
ValueCountFrequency (%)
162
83.5%
) 13
 
6.7%
( 13
 
6.7%
1 3
 
1.5%
2 2
 
1.0%
· 1
 
0.5%
Latin
ValueCountFrequency (%)
A 1
25.0%
C 1
25.0%
W 1
25.0%
Y 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2079
91.3%
ASCII 197
 
8.7%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
활 174
 
8.4%
용 159
 
7.6%
재 154
 
7.4%
센 120
 
5.8%
터 119
 
5.7%
시 92
 
4.4%
선 69
 
3.3%
별 67
 
3.2%
장 63
 
3.0%
구 53
 
2.5%
Other values (181) 1009
48.5%
ASCII
ValueCountFrequency (%)
162
82.2%
) 13
 
6.6%
( 13
 
6.6%
1 3
 
1.5%
2 2
 
1.0%
A 1
 
0.5%
C 1
 
0.5%
W 1
 
0.5%
Y 1
 
0.5%
None
ValueCountFrequency (%)
· 1
100.0%

재활용센터운영구분
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
위탁
119 
직영
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row직영
2nd row직영
3rd row직영
4th row위탁
5th row직영

Common Values

ValueCountFrequency (%)
위탁 119
54.3%
직영 100
45.7%

Length

2024-05-11T16:48:02.910339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:48:03.205230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위탁 119
54.3%
직영 100
45.7%

소재지도로명주소
Text

MISSING 

Distinct206
Distinct (%)95.4%
Missing3
Missing (%)1.4%
Memory size1.8 KiB
2024-05-11T16:48:03.864209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length26
Mean length21.115741
Min length15

Characters and Unicode

Total characters4561
Distinct characters242
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

Unique196 ?
Unique (%)90.7%

Sample

1st row인천광역시 옹진군 자월면 대이작로 159번길 127
2nd row인천광역시 옹진군 자월면 승봉로29번길 100-13
3rd row인천광역시 옹진군 대청면 소청동로 159
4th row경기도 의정부시 장곡로 450(신곡동)
5th row전라남도 곡성군 곡성읍 곡고로 98-157
ValueCountFrequency (%)
부산광역시 23
 
2.4%
서울특별시 22
 
2.3%
강원도 20
 
2.0%
경기도 19
 
1.9%
인천광역시 18
 
1.8%
전라남도 17
 
1.7%
남구 15
 
1.5%
옹진군 14
 
1.4%
울산광역시 13
 
1.3%
전라북도 13
 
1.3%
Other values (577) 802
82.2%
2024-05-11T16:48:04.961797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
760
 
16.7%
1 172
 
3.8%
로 171
 
3.7%
시 168
 
3.7%
도 141
 
3.1%
2 106
 
2.3%
구 95
 
2.1%
길 87
 
1.9%
3 83
 
1.8%
군 81
 
1.8%
Other values (232) 2697
59.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2849
62.5%
Decimal Number 804
 
17.6%
Space Separator 760
 
16.7%
Dash Punctuation 62
 
1.4%
Open Punctuation 41
 
0.9%
Close Punctuation 41
 
0.9%
Other Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 171
 
6.0%
시 168
 
5.9%
도 141
 
4.9%
구 95
 
3.3%
길 87
 
3.1%
군 81
 
2.8%
산 79
 
2.8%
남 77
 
2.7%
광 77
 
2.7%
동 72
 
2.5%
Other values (217) 1801
63.2%
Decimal Number
ValueCountFrequency (%)
1 172
21.4%
2 106
13.2%
3 83
10.3%
6 71
8.8%
5 69
8.6%
0 68
 
8.5%
7 65
 
8.1%
8 64
 
8.0%
4 57
 
7.1%
9 49
 
6.1%
Space Separator
ValueCountFrequency (%)
760
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 62
100.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2849
62.5%
Common 1712
37.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 171
 
6.0%
시 168
 
5.9%
도 141
 
4.9%
구 95
 
3.3%
길 87
 
3.1%
군 81
 
2.8%
산 79
 
2.8%
남 77
 
2.7%
광 77
 
2.7%
동 72
 
2.5%
Other values (217) 1801
63.2%
Common
ValueCountFrequency (%)
760
44.4%
1 172
 
10.0%
2 106
 
6.2%
3 83
 
4.8%
6 71
 
4.1%
5 69
 
4.0%
0 68
 
4.0%
7 65
 
3.8%
8 64
 
3.7%
- 62
 
3.6%
Other values (5) 192
 
11.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2849
62.5%
ASCII 1712
37.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
760
44.4%
1 172
 
10.0%
2 106
 
6.2%
3 83
 
4.8%
6 71
 
4.1%
5 69
 
4.0%
0 68
 
4.0%
7 65
 
3.8%
8 64
 
3.7%
- 62
 
3.6%
Other values (5) 192
 
11.2%
Hangul
ValueCountFrequency (%)
로 171
 
6.0%
시 168
 
5.9%
도 141
 
4.9%
구 95
 
3.3%
길 87
 
3.1%
군 81
 
2.8%
산 79
 
2.8%
남 77
 
2.7%
광 77
 
2.7%
동 72
 
2.5%
Other values (217) 1801
63.2%

소재지지번주소
Text

MISSING 

Distinct191
Distinct (%)95.0%
Missing18
Missing (%)8.2%
Memory size1.8 KiB
2024-05-11T16:48:05.776079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length19.706468
Min length13

Characters and Unicode

Total characters3961
Distinct characters205
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique181 ?
Unique (%)90.0%

Sample

1st row인천광역시 옹진군 자월면 이작리 394-3
2nd row인천광역시 옹진군 자월면 승봉리 771-3
3rd row인천광역시 옹진군 대청면 소청리 58
4th row경기도 의정부시 신곡동 681
5th row서울특별시 강남구 개포동 1259-6
ValueCountFrequency (%)
서울특별시 22
 
2.4%
강원도 19
 
2.1%
인천광역시 19
 
2.1%
부산광역시 19
 
2.1%
경기도 16
 
1.8%
남구 15
 
1.7%
옹진군 15
 
1.7%
전라남도 14
 
1.6%
울산광역시 13
 
1.4%
전라북도 13
 
1.4%
Other values (534) 734
81.6%
2024-05-11T16:48:06.886582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
698
 
17.6%
시 156
 
3.9%
동 141
 
3.6%
1 140
 
3.5%
- 137
 
3.5%
도 131
 
3.3%
5 90
 
2.3%
3 88
 
2.2%
구 88
 
2.2%
리 85
 
2.1%
Other values (195) 2207
55.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2363
59.7%
Decimal Number 762
 
19.2%
Space Separator 698
 
17.6%
Dash Punctuation 137
 
3.5%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 156
 
6.6%
동 141
 
6.0%
도 131
 
5.5%
구 88
 
3.7%
리 85
 
3.6%
산 81
 
3.4%
군 75
 
3.2%
광 69
 
2.9%
남 62
 
2.6%
역 60
 
2.5%
Other values (182) 1415
59.9%
Decimal Number
ValueCountFrequency (%)
1 140
18.4%
5 90
11.8%
3 88
11.5%
2 84
11.0%
4 78
10.2%
9 62
8.1%
0 58
7.6%
7 58
7.6%
6 55
 
7.2%
8 49
 
6.4%
Space Separator
ValueCountFrequency (%)
698
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 137
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2363
59.7%
Common 1598
40.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 156
 
6.6%
동 141
 
6.0%
도 131
 
5.5%
구 88
 
3.7%
리 85
 
3.6%
산 81
 
3.4%
군 75
 
3.2%
광 69
 
2.9%
남 62
 
2.6%
역 60
 
2.5%
Other values (182) 1415
59.9%
Common
ValueCountFrequency (%)
698
43.7%
1 140
 
8.8%
- 137
 
8.6%
5 90
 
5.6%
3 88
 
5.5%
2 84
 
5.3%
4 78
 
4.9%
9 62
 
3.9%
0 58
 
3.6%
7 58
 
3.6%
Other values (3) 105
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2363
59.7%
ASCII 1598
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
698
43.7%
1 140
 
8.8%
- 137
 
8.6%
5 90
 
5.6%
3 88
 
5.5%
2 84
 
5.3%
4 78
 
4.9%
9 62
 
3.9%
0 58
 
3.6%
7 58
 
3.6%
Other values (3) 105
 
6.6%
Hangul
ValueCountFrequency (%)
시 156
 
6.6%
동 141
 
6.0%
도 131
 
5.5%
구 88
 
3.7%
리 85
 
3.6%
산 81
 
3.4%
군 75
 
3.2%
광 69
 
2.9%
남 62
 
2.6%
역 60
 
2.5%
Other values (182) 1415
59.9%

위도
Real number (ℝ)

Distinct196
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.453402
Minimum34.290004
Maximum38.363307
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-05-11T16:48:07.253053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.290004
5-th percentile34.881637
Q135.423056
median36.41328
Q337.510033
95-th percentile37.970682
Maximum38.363307
Range4.0733034
Interquartile range (IQR)2.0869775

Descriptive statistics

Standard deviation1.097508
Coefficient of variation (CV)0.03010715
Kurtosis-1.4719671
Mean36.453402
Median Absolute Deviation (MAD)1.0728432
Skewness-0.028984128
Sum7983.295
Variance1.2045239
MonotonicityNot monotonic
2024-05-11T16:48:07.595723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.30727229 2
 
0.9%
37.3557821 2
 
0.9%
37.1976912 2
 
0.9%
37.32612272 2
 
0.9%
37.69266797 2
 
0.9%
38.3633074449 2
 
0.9%
37.908602 2
 
0.9%
37.864773 2
 
0.9%
37.181318 2
 
0.9%
35.61423844 2
 
0.9%
Other values (186) 199
90.9%
ValueCountFrequency (%)
34.290004 1
0.5%
34.53069593 1
0.5%
34.56720876 1
0.5%
34.623583 1
0.5%
34.70880038 1
0.5%
34.78248754 1
0.5%
34.80677839 1
0.5%
34.82798253 1
0.5%
34.83982251 1
0.5%
34.84759436 1
0.5%
ValueCountFrequency (%)
38.3633074449 2
0.9%
38.22414087 2
0.9%
38.13766188 2
0.9%
38.0937569 2
0.9%
38.0707181246 1
0.5%
38.0702661636 1
0.5%
37.99813896 1
0.5%
37.967631 1
0.5%
37.95713929 1
0.5%
37.94229789 1
0.5%

경도
Real number (ℝ)

Distinct195
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.68868
Minimum124.69656
Maximum129.39012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-05-11T16:48:07.968802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum124.69656
5-th percentile126.29322
Q1126.91944
median127.46635
Q3128.67879
95-th percentile129.31911
Maximum129.39012
Range4.6935532
Interquartile range (IQR)1.7593519

Descriptive statistics

Standard deviation1.0519403
Coefficient of variation (CV)0.0082383205
Kurtosis-0.68354692
Mean127.68868
Median Absolute Deviation (MAD)0.74442252
Skewness-0.026774479
Sum27963.822
Variance1.1065784
MonotonicityNot monotonic
2024-05-11T16:48:08.363563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.6787899 2
 
0.9%
128.212133 2
 
0.9%
127.1700744 2
 
0.9%
129.003658 2
 
0.9%
127.9599504 2
 
0.9%
128.9879447 2
 
0.9%
128.4818995952 2
 
0.9%
127.751638 2
 
0.9%
127.749173 2
 
0.9%
127.735409 2
 
0.9%
Other values (185) 199
90.9%
ValueCountFrequency (%)
124.6965634 1
0.5%
124.7053035 1
0.5%
124.7609434 1
0.5%
125.6908597 1
0.5%
125.7203857 1
0.5%
125.9442335 1
0.5%
125.9966876 1
0.5%
126.1065875 1
0.5%
126.107333 1
0.5%
126.2622759 1
0.5%
ValueCountFrequency (%)
129.3901166 1
0.5%
129.389004 1
0.5%
129.354117 1
0.5%
129.353249 1
0.5%
129.3528164 1
0.5%
129.3378032 1
0.5%
129.3347502 1
0.5%
129.3287862 1
0.5%
129.3281284 1
0.5%
129.3209531 1
0.5%

면적
Real number (ℝ)

Distinct180
Distinct (%)82.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16441.492
Minimum15
Maximum2391000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-05-11T16:48:08.673321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile71.7
Q1263.5
median781
Q31989.46
95-th percentile31697
Maximum2391000
Range2390985
Interquartile range (IQR)1725.96

Descriptive statistics

Standard deviation162175.76
Coefficient of variation (CV)9.8638105
Kurtosis213.67413
Mean16441.492
Median Absolute Deviation (MAD)622
Skewness14.535811
Sum3600686.7
Variance2.6300977 × 1010
MonotonicityNot monotonic
2024-05-11T16:48:08.980412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
150.0 4
 
1.8%
100.0 4
 
1.8%
330.0 3
 
1.4%
198.0 3
 
1.4%
450.0 3
 
1.4%
23.0 2
 
0.9%
88072.0 2
 
0.9%
1696.0 2
 
0.9%
3245.0 2
 
0.9%
797.8 2
 
0.9%
Other values (170) 192
87.7%
ValueCountFrequency (%)
15.0 1
0.5%
23.0 2
0.9%
30.0 1
0.5%
33.0 1
0.5%
40.0 1
0.5%
46.704 1
0.5%
55.0 1
0.5%
59.5 1
0.5%
66.0 1
0.5%
69.0 1
0.5%
ValueCountFrequency (%)
2391000.0 1
0.5%
135188.0 1
0.5%
124491.0 1
0.5%
90444.0 1
0.5%
88072.0 2
0.9%
82332.0 1
0.5%
44160.0 2
0.9%
44134.0 1
0.5%
31697.0 2
0.9%
27086.0 1
0.5%

설립연월
Date

Distinct138
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum1990-08-01 00:00:00
Maximum2023-12-01 00:00:00
2024-05-11T16:48:09.274203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:48:09.637073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

차량보유대수
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9908676
Minimum0
Maximum112
Zeros25
Zeros (%)11.4%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-05-11T16:48:09.963202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q34
95-th percentile14.1
Maximum112
Range112
Interquartile range (IQR)3

Descriptive statistics

Standard deviation8.8582056
Coefficient of variation (CV)2.219619
Kurtosis102.6607
Mean3.9908676
Median Absolute Deviation (MAD)1
Skewness8.9104883
Sum874
Variance78.467806
MonotonicityNot monotonic
2024-05-11T16:48:10.229186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 73
33.3%
2 34
15.5%
3 30
13.7%
0 25
 
11.4%
4 14
 
6.4%
5 8
 
3.7%
10 5
 
2.3%
7 4
 
1.8%
6 4
 
1.8%
9 3
 
1.4%
Other values (14) 19
 
8.7%
ValueCountFrequency (%)
0 25
 
11.4%
1 73
33.3%
2 34
15.5%
3 30
13.7%
4 14
 
6.4%
5 8
 
3.7%
6 4
 
1.8%
7 4
 
1.8%
8 2
 
0.9%
9 3
 
1.4%
ValueCountFrequency (%)
112 1
0.5%
36 1
0.5%
29 1
0.5%
23 1
0.5%
20 2
0.9%
19 2
0.9%
18 1
0.5%
16 1
0.5%
15 1
0.5%
14 1
0.5%

주요취급품목정보
Text

Distinct143
Distinct (%)65.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-05-11T16:48:10.576053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length91
Median length38
Mean length15.374429
Min length2

Characters and Unicode

Total characters3367
Distinct characters177
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique106 ?
Unique (%)48.4%

Sample

1st row종이류+고철류+캔류+병류+플라스틱류+필름류+스티로폼류
2nd row종이류+고철류+캔류+병류+플라스틱류+필름류+스티로폼류
3rd row종이류+고철류+캔류+병류+플라스틱류+필름류+스티로폼류
4th row가전+가구 등
5th row플라스틱병+캔류
ValueCountFrequency (%)
등 69
 
18.0%
재활용품 19
 
5.0%
종이류+고철류+캔류+병류+플라스틱류+필름류+스티로폼류 16
 
4.2%
가전+가구 11
 
2.9%
선별 11
 
2.9%
가전 8
 
2.1%
외 6
 
1.6%
가구 6
 
1.6%
중고가전가구제품 6
 
1.6%
및 5
 
1.3%
Other values (167) 226
59.0%
2024-05-11T16:48:11.346069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
+ 513
 
15.2%
류 205
 
6.1%
164
 
4.9%
가 146
 
4.3%
스 129
 
3.8%
고 101
 
3.0%
병 85
 
2.5%
철 80
 
2.4%
전 79
 
2.3%
품 78
 
2.3%
Other values (167) 1787
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2532
75.2%
Math Symbol 513
 
15.2%
Space Separator 164
 
4.9%
Uppercase Letter 97
 
2.9%
Other Punctuation 30
 
0.9%
Decimal Number 13
 
0.4%
Open Punctuation 9
 
0.3%
Close Punctuation 9
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
류 205
 
8.1%
가 146
 
5.8%
스 129
 
5.1%
고 101
 
4.0%
병 85
 
3.4%
철 80
 
3.2%
전 79
 
3.1%
품 78
 
3.1%
등 73
 
2.9%
구 72
 
2.8%
Other values (148) 1484
58.6%
Decimal Number
ValueCountFrequency (%)
1 5
38.5%
9 4
30.8%
5 1
 
7.7%
6 1
 
7.7%
2 1
 
7.7%
8 1
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
P 44
45.4%
E 24
24.7%
T 20
20.6%
S 7
 
7.2%
V 2
 
2.1%
Other Punctuation
ValueCountFrequency (%)
, 25
83.3%
· 3
 
10.0%
/ 1
 
3.3%
. 1
 
3.3%
Math Symbol
ValueCountFrequency (%)
+ 513
100.0%
Space Separator
ValueCountFrequency (%)
164
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2532
75.2%
Common 738
 
21.9%
Latin 97
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
류 205
 
8.1%
가 146
 
5.8%
스 129
 
5.1%
고 101
 
4.0%
병 85
 
3.4%
철 80
 
3.2%
전 79
 
3.1%
품 78
 
3.1%
등 73
 
2.9%
구 72
 
2.8%
Other values (148) 1484
58.6%
Common
ValueCountFrequency (%)
+ 513
69.5%
164
 
22.2%
, 25
 
3.4%
( 9
 
1.2%
) 9
 
1.2%
1 5
 
0.7%
9 4
 
0.5%
· 3
 
0.4%
5 1
 
0.1%
/ 1
 
0.1%
Other values (4) 4
 
0.5%
Latin
ValueCountFrequency (%)
P 44
45.4%
E 24
24.7%
T 20
20.6%
S 7
 
7.2%
V 2
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2532
75.2%
ASCII 832
 
24.7%
None 3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
+ 513
61.7%
164
 
19.7%
P 44
 
5.3%
, 25
 
3.0%
E 24
 
2.9%
T 20
 
2.4%
( 9
 
1.1%
) 9
 
1.1%
S 7
 
0.8%
1 5
 
0.6%
Other values (8) 12
 
1.4%
Hangul
ValueCountFrequency (%)
류 205
 
8.1%
가 146
 
5.8%
스 129
 
5.1%
고 101
 
4.0%
병 85
 
3.4%
철 80
 
3.2%
전 79
 
3.1%
품 78
 
3.1%
등 73
 
2.9%
구 72
 
2.8%
Other values (148) 1484
58.6%
None
ValueCountFrequency (%)
· 3
100.0%

운영기관명
Text

Distinct184
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-05-11T16:48:11.761035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length18
Mean length8.8630137
Min length2

Characters and Unicode

Total characters1941
Distinct characters211
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique162 ?
Unique (%)74.0%

Sample

1st row인천광역시 옹진군 자월면
2nd row인천광역시 옹진군 자월면
3rd row인천광역시 옹진군 대청면
4th row(사)한국생활자원재활용협회 의정부지회
5th row전라남도 곡성군청
ValueCountFrequency (%)
인천광역시 16
 
4.5%
옹진군 15
 
4.2%
개인 10
 
2.8%
전라남도 9
 
2.5%
경상북도 8
 
2.2%
전라북도 8
 
2.2%
부산광역시 7
 
2.0%
강원도 7
 
2.0%
재활용 6
 
1.7%
충청북도 6
 
1.7%
Other values (205) 265
74.2%
2024-05-11T16:48:12.686167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
138
 
7.1%
시 82
 
4.2%
청 80
 
4.1%
도 76
 
3.9%
군 66
 
3.4%
활 62
 
3.2%
용 56
 
2.9%
재 51
 
2.6%
터 41
 
2.1%
센 41
 
2.1%
Other values (201) 1248
64.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1732
89.2%
Space Separator 138
 
7.1%
Other Symbol 19
 
1.0%
Close Punctuation 16
 
0.8%
Open Punctuation 16
 
0.8%
Uppercase Letter 14
 
0.7%
Decimal Number 4
 
0.2%
Math Symbol 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 82
 
4.7%
청 80
 
4.6%
도 76
 
4.4%
군 66
 
3.8%
활 62
 
3.6%
용 56
 
3.2%
재 51
 
2.9%
터 41
 
2.4%
센 41
 
2.4%
구 38
 
2.2%
Other values (186) 1139
65.8%
Uppercase Letter
ValueCountFrequency (%)
C 3
21.4%
A 3
21.4%
Y 3
21.4%
W 2
14.3%
M 1
 
7.1%
R 1
 
7.1%
S 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
9 2
50.0%
4 1
25.0%
8 1
25.0%
Space Separator
ValueCountFrequency (%)
138
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1751
90.2%
Common 176
 
9.1%
Latin 14
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 82
 
4.7%
청 80
 
4.6%
도 76
 
4.3%
군 66
 
3.8%
활 62
 
3.5%
용 56
 
3.2%
재 51
 
2.9%
터 41
 
2.3%
센 41
 
2.3%
구 38
 
2.2%
Other values (187) 1158
66.1%
Common
ValueCountFrequency (%)
138
78.4%
) 16
 
9.1%
( 16
 
9.1%
+ 2
 
1.1%
9 2
 
1.1%
4 1
 
0.6%
8 1
 
0.6%
Latin
ValueCountFrequency (%)
C 3
21.4%
A 3
21.4%
Y 3
21.4%
W 2
14.3%
M 1
 
7.1%
R 1
 
7.1%
S 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1732
89.2%
ASCII 190
 
9.8%
None 19
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
138
72.6%
) 16
 
8.4%
( 16
 
8.4%
C 3
 
1.6%
A 3
 
1.6%
Y 3
 
1.6%
W 2
 
1.1%
+ 2
 
1.1%
9 2
 
1.1%
M 1
 
0.5%
Other values (4) 4
 
2.1%
Hangul
ValueCountFrequency (%)
시 82
 
4.7%
청 80
 
4.6%
도 76
 
4.4%
군 66
 
3.8%
활 62
 
3.6%
용 56
 
3.2%
재 51
 
2.9%
터 41
 
2.4%
센 41
 
2.4%
구 38
 
2.2%
Other values (186) 1139
65.8%
None
ValueCountFrequency (%)
㈜ 19
100.0%

운영기관전화번호
Text

MISSING 

Distinct175
Distinct (%)84.5%
Missing12
Missing (%)5.5%
Memory size1.8 KiB
2024-05-11T16:48:13.315697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.927536
Min length11

Characters and Unicode

Total characters2469
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

Unique146 ?
Unique (%)70.5%

Sample

1st row032-899-3750
2nd row032-899-3750
3rd row032-899-3409
4th row031-844-7282
5th row061-360-8521
ValueCountFrequency (%)
032-899-3740 4
 
1.9%
032-899-3750 3
 
1.4%
033-345-7132 2
 
1.0%
033-743-0119 2
 
1.0%
063-560-2866 2
 
1.0%
033-735-7388 2
 
1.0%
063-454-3453 2
 
1.0%
063-620-6771 2
 
1.0%
033-450-5572 2
 
1.0%
033-262-0216 2
 
1.0%
Other values (165) 184
88.9%
2024-05-11T16:48:14.406298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 414
16.8%
0 364
14.7%
3 290
11.7%
2 254
10.3%
5 216
8.7%
8 172
7.0%
4 169
6.8%
6 161
 
6.5%
7 151
 
6.1%
1 145
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2055
83.2%
Dash Punctuation 414
 
16.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 364
17.7%
3 290
14.1%
2 254
12.4%
5 216
10.5%
8 172
8.4%
4 169
8.2%
6 161
7.8%
7 151
7.3%
1 145
 
7.1%
9 133
 
6.5%
Dash Punctuation
ValueCountFrequency (%)
- 414
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2469
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 414
16.8%
0 364
14.7%
3 290
11.7%
2 254
10.3%
5 216
8.7%
8 172
7.0%
4 169
6.8%
6 161
 
6.5%
7 151
 
6.1%
1 145
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2469
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 414
16.8%
0 364
14.7%
3 290
11.7%
2 254
10.3%
5 216
8.7%
8 172
7.0%
4 169
6.8%
6 161
 
6.5%
7 151
 
6.1%
1 145
 
5.9%

운영기관대표자명
Text

MISSING 

Distinct149
Distinct (%)77.6%
Missing27
Missing (%)12.3%
Memory size1.8 KiB
2024-05-11T16:48:15.053621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.2708333
Min length2

Characters and Unicode

Total characters628
Distinct characters134
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique122 ?
Unique (%)63.5%

Sample

1st row장정민
2nd row장정민
3rd row장정민
4th row이종철
5th row곡성군수
ValueCountFrequency (%)
장정민 15
 
7.8%
원덕자 4
 
2.1%
성기원 3
 
1.6%
이영란 2
 
1.0%
정선군수 2
 
1.0%
심덕섭 2
 
1.0%
이용현 2
 
1.0%
강임준 2
 
1.0%
강릉시장 2
 
1.0%
장호철 2
 
1.0%
Other values (139) 157
81.3%
2024-05-11T16:48:16.080352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 31
 
4.9%
장 30
 
4.8%
정 28
 
4.5%
이 26
 
4.1%
수 25
 
4.0%
원 19
 
3.0%
군 17
 
2.7%
민 16
 
2.5%
박 15
 
2.4%
영 13
 
2.1%
Other values (124) 408
65.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 622
99.0%
Close Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%
Math Symbol 1
 
0.2%
Space Separator 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 31
 
5.0%
장 30
 
4.8%
정 28
 
4.5%
이 26
 
4.2%
수 25
 
4.0%
원 19
 
3.1%
군 17
 
2.7%
민 16
 
2.6%
박 15
 
2.4%
영 13
 
2.1%
Other values (120) 402
64.6%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 622
99.0%
Common 6
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 31
 
5.0%
장 30
 
4.8%
정 28
 
4.5%
이 26
 
4.2%
수 25
 
4.0%
원 19
 
3.1%
군 17
 
2.7%
민 16
 
2.6%
박 15
 
2.4%
영 13
 
2.1%
Other values (120) 402
64.6%
Common
ValueCountFrequency (%)
) 2
33.3%
( 2
33.3%
+ 1
16.7%
1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 622
99.0%
ASCII 6
 
1.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 31
 
5.0%
장 30
 
4.8%
정 28
 
4.5%
이 26
 
4.2%
수 25
 
4.0%
원 19
 
3.1%
군 17
 
2.7%
민 16
 
2.6%
박 15
 
2.4%
영 13
 
2.1%
Other values (120) 402
64.6%
ASCII
ValueCountFrequency (%)
) 2
33.3%
( 2
33.3%
+ 1
16.7%
1
16.7%

평일운영시작시각
Categorical

IMBALANCE 

Distinct12
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
09:00
155 
08:00
34 
06:00
 
6
08:30
 
5
10:00
 
5
Other values (7)
 
14

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique4 ?
Unique (%)1.8%

Sample

1st row09:00
2nd row09:00
3rd row09:00
4th row09:00
5th row09:00

Common Values

ValueCountFrequency (%)
09:00 155
70.8%
08:00 34
 
15.5%
06:00 6
 
2.7%
08:30 5
 
2.3%
10:00 5
 
2.3%
07:00 4
 
1.8%
09:30 4
 
1.8%
05:30 2
 
0.9%
05:00 1
 
0.5%
13:00 1
 
0.5%
Other values (2) 2
 
0.9%

Length

2024-05-11T16:48:16.408421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
09:00 155
70.8%
08:00 34
 
15.5%
06:00 6
 
2.7%
08:30 5
 
2.3%
10:00 5
 
2.3%
07:00 4
 
1.8%
09:30 4
 
1.8%
05:30 2
 
0.9%
05:00 1
 
0.5%
13:00 1
 
0.5%
Other values (2) 2
 
0.9%

평일운영종료시각
Categorical

Distinct13
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
18:00
127 
17:00
37 
19:00
16 
16:00
 
11
17:30
 
6
Other values (8)
22 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique2 ?
Unique (%)0.9%

Sample

1st row18:00
2nd row18:00
3rd row18:00
4th row18:00
5th row18:00

Common Values

ValueCountFrequency (%)
18:00 127
58.0%
17:00 37
 
16.9%
19:00 16
 
7.3%
16:00 11
 
5.0%
17:30 6
 
2.7%
18:30 6
 
2.7%
20:00 4
 
1.8%
15:00 3
 
1.4%
16:30 3
 
1.4%
19:30 2
 
0.9%
Other values (3) 4
 
1.8%

Length

2024-05-11T16:48:16.655854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
18:00 127
58.0%
17:00 37
 
16.9%
19:00 16
 
7.3%
16:00 11
 
5.0%
17:30 6
 
2.7%
18:30 6
 
2.7%
20:00 4
 
1.8%
15:00 3
 
1.4%
16:30 3
 
1.4%
19:30 2
 
0.9%
Other values (3) 4
 
1.8%

공휴일운영시작시각
Categorical

Distinct12
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
00:00
120 
09:00
61 
08:00
15 
10:00
 
7
08:30
 
4
Other values (7)
 
12

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique3 ?
Unique (%)1.4%

Sample

1st row09:00
2nd row09:00
3rd row09:00
4th row00:00
5th row09:00

Common Values

ValueCountFrequency (%)
00:00 120
54.8%
09:00 61
27.9%
08:00 15
 
6.8%
10:00 7
 
3.2%
08:30 4
 
1.8%
06:00 3
 
1.4%
09:30 2
 
0.9%
07:00 2
 
0.9%
05:30 2
 
0.9%
23:59 1
 
0.5%
Other values (2) 2
 
0.9%

Length

2024-05-11T16:48:16.998348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
00:00 120
54.8%
09:00 61
27.9%
08:00 15
 
6.8%
10:00 7
 
3.2%
08:30 4
 
1.8%
06:00 3
 
1.4%
09:30 2
 
0.9%
07:00 2
 
0.9%
05:30 2
 
0.9%
23:59 1
 
0.5%
Other values (2) 2
 
0.9%

공휴일운영종료시각
Categorical

Distinct17
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
00:00
118 
18:00
21 
13:00
20 
17:00
15 
12:00
 
10
Other values (12)
35 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique3 ?
Unique (%)1.4%

Sample

1st row13:00
2nd row13:00
3rd row13:00
4th row00:00
5th row14:00

Common Values

ValueCountFrequency (%)
00:00 118
53.9%
18:00 21
 
9.6%
13:00 20
 
9.1%
17:00 15
 
6.8%
12:00 10
 
4.6%
19:00 9
 
4.1%
16:00 5
 
2.3%
17:30 4
 
1.8%
18:30 3
 
1.4%
23:59 3
 
1.4%
Other values (7) 11
 
5.0%

Length

2024-05-11T16:48:17.330321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
00:00 118
53.9%
18:00 21
 
9.6%
13:00 20
 
9.1%
17:00 15
 
6.8%
12:00 10
 
4.6%
19:00 9
 
4.1%
16:00 5
 
2.3%
17:30 4
 
1.8%
23:59 3
 
1.4%
18:30 3
 
1.4%
Other values (7) 11
 
5.0%

휴무일정보
Text

MISSING 

Distinct54
Distinct (%)27.3%
Missing21
Missing (%)9.6%
Memory size1.8 KiB
2024-05-11T16:48:18.022640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length20
Mean length6.9494949
Min length1

Characters and Unicode

Total characters1376
Distinct characters65
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

Unique29 ?
Unique (%)14.6%

Sample

1st row일요일
2nd row일요일
3rd row일요일
4th row토+일+공휴일
5th row일요일
ValueCountFrequency (%)
일요일 34
 
12.7%
공휴일 23
 
8.6%
토+일+공휴일 20
 
7.5%
일+공휴일 19
 
7.1%
일 14
 
5.2%
토+일+법정공휴일 10
 
3.7%
일+설 10
 
3.7%
연휴+추석 9
 
3.4%
일요일+공휴일 8
 
3.0%
연중무휴 8
 
3.0%
Other values (56) 112
41.9%
2024-05-11T16:48:19.434411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
일 368
26.7%
+ 178
12.9%
휴 156
11.3%
공 114
 
8.3%
요 86
 
6.2%
69
 
5.0%
토 61
 
4.4%
연 39
 
2.8%
석 21
 
1.5%
추 21
 
1.5%
Other values (55) 263
19.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1090
79.2%
Math Symbol 178
 
12.9%
Space Separator 69
 
5.0%
Other Punctuation 19
 
1.4%
Decimal Number 8
 
0.6%
Close Punctuation 6
 
0.4%
Open Punctuation 6
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 368
33.8%
휴 156
14.3%
공 114
 
10.5%
요 86
 
7.9%
토 61
 
5.6%
연 39
 
3.6%
석 21
 
1.9%
추 21
 
1.9%
설 21
 
1.9%
주 21
 
1.9%
Other values (46) 182
16.7%
Decimal Number
ValueCountFrequency (%)
1 4
50.0%
0 2
25.0%
2 2
25.0%
Other Punctuation
ValueCountFrequency (%)
, 18
94.7%
: 1
 
5.3%
Math Symbol
ValueCountFrequency (%)
+ 178
100.0%
Space Separator
ValueCountFrequency (%)
69
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1090
79.2%
Common 286
 
20.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
일 368
33.8%
휴 156
14.3%
공 114
 
10.5%
요 86
 
7.9%
토 61
 
5.6%
연 39
 
3.6%
석 21
 
1.9%
추 21
 
1.9%
설 21
 
1.9%
주 21
 
1.9%
Other values (46) 182
16.7%
Common
ValueCountFrequency (%)
+ 178
62.2%
69
 
24.1%
, 18
 
6.3%
) 6
 
2.1%
( 6
 
2.1%
1 4
 
1.4%
0 2
 
0.7%
2 2
 
0.7%
: 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1090
79.2%
ASCII 286
 
20.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
일 368
33.8%
휴 156
14.3%
공 114
 
10.5%
요 86
 
7.9%
토 61
 
5.6%
연 39
 
3.6%
석 21
 
1.9%
추 21
 
1.9%
설 21
 
1.9%
주 21
 
1.9%
Other values (46) 182
16.7%
ASCII
ValueCountFrequency (%)
+ 178
62.2%
69
 
24.1%
, 18
 
6.3%
) 6
 
2.1%
( 6
 
2.1%
1 4
 
1.4%
0 2
 
0.7%
2 2
 
0.7%
: 1
 
0.3%

애프터서비스정보
Text

MISSING 

Distinct27
Distinct (%)56.2%
Missing171
Missing (%)78.1%
Memory size1.8 KiB
2024-05-11T16:48:19.882732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length111
Median length21
Mean length12.9375
Min length1

Characters and Unicode

Total characters621
Distinct characters95
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

Unique22 ?
Unique (%)45.8%

Sample

1st row판매 또는 교환물품이 6개월이내에 하자 발생시 무상수리
2nd row해당없음
3rd row3개월
4th row6개월
5th row해당없음
ValueCountFrequency (%)
판매일로부터 18
 
12.2%
무상 12
 
8.1%
수리 11
 
7.4%
6개월이내 10
 
6.8%
없음 8
 
5.4%
6개월 8
 
5.4%
무상수리 7
 
4.7%
해당없음 6
 
4.1%
이내 4
 
2.7%
3개월 4
 
2.7%
Other values (53) 60
40.5%
2024-05-11T16:48:20.787602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
100
 
16.1%
개 32
 
5.2%
월 32
 
5.2%
6 23
 
3.7%
일 21
 
3.4%
무 21
 
3.4%
터 21
 
3.4%
이 20
 
3.2%
매 20
 
3.2%
부 20
 
3.2%
Other values (85) 311
50.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 455
73.3%
Space Separator 100
 
16.1%
Decimal Number 34
 
5.5%
Other Punctuation 10
 
1.6%
Uppercase Letter 9
 
1.4%
Open Punctuation 5
 
0.8%
Close Punctuation 5
 
0.8%
Math Symbol 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
개 32
 
7.0%
월 32
 
7.0%
일 21
 
4.6%
무 21
 
4.6%
터 21
 
4.6%
이 20
 
4.4%
매 20
 
4.4%
부 20
 
4.4%
내 19
 
4.2%
로 19
 
4.2%
Other values (67) 230
50.5%
Uppercase Letter
ValueCountFrequency (%)
A 3
33.3%
S 3
33.3%
T 1
 
11.1%
N 1
 
11.1%
V 1
 
11.1%
Decimal Number
ValueCountFrequency (%)
6 23
67.6%
3 8
 
23.5%
1 2
 
5.9%
7 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 7
70.0%
/ 3
30.0%
Open Punctuation
ValueCountFrequency (%)
( 3
60.0%
[ 2
40.0%
Close Punctuation
ValueCountFrequency (%)
) 3
60.0%
] 2
40.0%
Math Symbol
ValueCountFrequency (%)
~ 2
66.7%
+ 1
33.3%
Space Separator
ValueCountFrequency (%)
100
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 455
73.3%
Common 157
 
25.3%
Latin 9
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
개 32
 
7.0%
월 32
 
7.0%
일 21
 
4.6%
무 21
 
4.6%
터 21
 
4.6%
이 20
 
4.4%
매 20
 
4.4%
부 20
 
4.4%
내 19
 
4.2%
로 19
 
4.2%
Other values (67) 230
50.5%
Common
ValueCountFrequency (%)
100
63.7%
6 23
 
14.6%
3 8
 
5.1%
, 7
 
4.5%
( 3
 
1.9%
/ 3
 
1.9%
) 3
 
1.9%
[ 2
 
1.3%
1 2
 
1.3%
] 2
 
1.3%
Other values (3) 4
 
2.5%
Latin
ValueCountFrequency (%)
A 3
33.3%
S 3
33.3%
T 1
 
11.1%
N 1
 
11.1%
V 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 455
73.3%
ASCII 166
 
26.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
100
60.2%
6 23
 
13.9%
3 8
 
4.8%
, 7
 
4.2%
( 3
 
1.8%
A 3
 
1.8%
S 3
 
1.8%
/ 3
 
1.8%
) 3
 
1.8%
[ 2
 
1.2%
Other values (8) 11
 
6.6%
Hangul
ValueCountFrequency (%)
개 32
 
7.0%
월 32
 
7.0%
일 21
 
4.6%
무 21
 
4.6%
터 21
 
4.6%
이 20
 
4.4%
매 20
 
4.4%
부 20
 
4.4%
내 19
 
4.2%
로 19
 
4.2%
Other values (67) 230
50.5%

홈페이지주소
Text

MISSING 

Distinct42
Distinct (%)76.4%
Missing164
Missing (%)74.9%
Memory size1.8 KiB
2024-05-11T16:48:21.208450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length164
Median length38
Mean length22.563636
Min length2

Characters and Unicode

Total characters1241
Distinct characters66
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

Unique35 ?
Unique (%)63.6%

Sample

1st rowhttp://www.sacheon.go.kr
2nd rowwww.jangheung.go.kr
3rd rowhttp://gyeyangrc.co.kr
4th rowhttp://tyywca.or.kr
5th rowwww.gimje.go.kr
ValueCountFrequency (%)
없음 6
 
10.9%
wjrecycle.com 4
 
7.3%
www.cwg.go.kr 2
 
3.6%
www.iksan.go.kr 2
 
3.6%
wanju.go.kr 2
 
3.6%
www.gimje.go.kr 2
 
3.6%
http://www.recyclenw.co.kr 2
 
3.6%
www.yeogiro24.co.kr 1
 
1.8%
www.hygn.go.kr 1
 
1.8%
www.jungo7282.co.kr 1
 
1.8%
Other values (32) 32
58.2%
2024-05-11T16:48:22.134584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 133
 
10.7%
w 127
 
10.2%
r 77
 
6.2%
/ 74
 
6.0%
o 72
 
5.8%
e 64
 
5.2%
t 62
 
5.0%
c 57
 
4.6%
g 52
 
4.2%
k 48
 
3.9%
Other values (56) 475
38.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 890
71.7%
Other Punctuation 238
 
19.2%
Decimal Number 55
 
4.4%
Uppercase Letter 24
 
1.9%
Other Letter 22
 
1.8%
Math Symbol 8
 
0.6%
Connector Punctuation 3
 
0.2%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 127
14.3%
r 77
 
8.7%
o 72
 
8.1%
e 64
 
7.2%
t 62
 
7.0%
c 57
 
6.4%
g 52
 
5.8%
k 48
 
5.4%
n 44
 
4.9%
a 40
 
4.5%
Other values (14) 247
27.8%
Uppercase Letter
ValueCountFrequency (%)
I 5
20.8%
B 4
16.7%
W 2
 
8.3%
C 2
 
8.3%
S 2
 
8.3%
M 1
 
4.2%
J 1
 
4.2%
P 1
 
4.2%
D 1
 
4.2%
N 1
 
4.2%
Other values (4) 4
16.7%
Decimal Number
ValueCountFrequency (%)
0 23
41.8%
2 6
 
10.9%
4 5
 
9.1%
3 5
 
9.1%
8 4
 
7.3%
1 4
 
7.3%
7 2
 
3.6%
5 2
 
3.6%
9 2
 
3.6%
6 2
 
3.6%
Other Letter
ValueCountFrequency (%)
음 7
31.8%
없 7
31.8%
가 1
 
4.5%
고 1
 
4.5%
중 1
 
4.5%
산 1
 
4.5%
울 1
 
4.5%
해 1
 
4.5%
당 1
 
4.5%
전 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
. 133
55.9%
/ 74
31.1%
: 23
 
9.7%
& 6
 
2.5%
? 2
 
0.8%
Math Symbol
ValueCountFrequency (%)
= 8
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 914
73.7%
Common 305
 
24.6%
Hangul 22
 
1.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 127
13.9%
r 77
 
8.4%
o 72
 
7.9%
e 64
 
7.0%
t 62
 
6.8%
c 57
 
6.2%
g 52
 
5.7%
k 48
 
5.3%
n 44
 
4.8%
a 40
 
4.4%
Other values (28) 271
29.6%
Common
ValueCountFrequency (%)
. 133
43.6%
/ 74
24.3%
: 23
 
7.5%
0 23
 
7.5%
= 8
 
2.6%
& 6
 
2.0%
2 6
 
2.0%
4 5
 
1.6%
3 5
 
1.6%
8 4
 
1.3%
Other values (8) 18
 
5.9%
Hangul
ValueCountFrequency (%)
음 7
31.8%
없 7
31.8%
가 1
 
4.5%
고 1
 
4.5%
중 1
 
4.5%
산 1
 
4.5%
울 1
 
4.5%
해 1
 
4.5%
당 1
 
4.5%
전 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1219
98.2%
Hangul 22
 
1.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 133
 
10.9%
w 127
 
10.4%
r 77
 
6.3%
/ 74
 
6.1%
o 72
 
5.9%
e 64
 
5.3%
t 62
 
5.1%
c 57
 
4.7%
g 52
 
4.3%
k 48
 
3.9%
Other values (46) 453
37.2%
Hangul
ValueCountFrequency (%)
음 7
31.8%
없 7
31.8%
가 1
 
4.5%
고 1
 
4.5%
중 1
 
4.5%
산 1
 
4.5%
울 1
 
4.5%
해 1
 
4.5%
당 1
 
4.5%
전 1
 
4.5%

관리기관전화번호
Text

Distinct147
Distinct (%)67.1%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-05-11T16:48:22.799835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.981735
Min length11

Characters and Unicode

Total characters2624
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

Unique111 ?
Unique (%)50.7%

Sample

1st row032-899-2620
2nd row032-899-2620
3rd row032-899-2620
4th row031-828-2994
5th row061-360-8522
ValueCountFrequency (%)
032-899-2620 15
 
6.8%
052-226-4822 11
 
5.0%
033-250-3131 6
 
2.7%
051-309-4455 6
 
2.7%
051-610-4451 5
 
2.3%
033-737-3091 4
 
1.8%
02-2600-4242 3
 
1.4%
033-530-2155 2
 
0.9%
063-281-8452 2
 
0.9%
063-539-8173 2
 
0.9%
Other values (137) 163
74.4%
2024-05-11T16:48:23.721451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 438
16.7%
0 408
15.5%
3 323
12.3%
2 286
10.9%
5 235
9.0%
4 207
7.9%
6 197
7.5%
1 180
6.9%
8 129
 
4.9%
9 116
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2186
83.3%
Dash Punctuation 438
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 408
18.7%
3 323
14.8%
2 286
13.1%
5 235
10.8%
4 207
9.5%
6 197
9.0%
1 180
8.2%
8 129
 
5.9%
9 116
 
5.3%
7 105
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 438
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2624
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 438
16.7%
0 408
15.5%
3 323
12.3%
2 286
10.9%
5 235
9.0%
4 207
7.9%
6 197
7.5%
1 180
6.9%
8 129
 
4.9%
9 116
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2624
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 438
16.7%
0 408
15.5%
3 323
12.3%
2 286
10.9%
5 235
9.0%
4 207
7.9%
6 197
7.5%
1 180
6.9%
8 129
 
4.9%
9 116
 
4.4%

관리기관명
Text

Distinct156
Distinct (%)71.2%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-05-11T16:48:24.321131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length9.630137
Min length3

Characters and Unicode

Total characters2109
Distinct characters130
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique131 ?
Unique (%)59.8%

Sample

1st row인천광역시 옹진군
2nd row인천광역시 옹진군
3rd row인천광역시 옹진군
4th row경기도 의정부시청
5th row전라남도 곡성군청
ValueCountFrequency (%)
부산광역시 24
 
5.3%
서울특별시 23
 
5.1%
강원도 21
 
4.7%
인천광역시 19
 
4.2%
경기도 19
 
4.2%
옹진군 15
 
3.3%
전라남도 15
 
3.3%
울산광역시 13
 
2.9%
남구청 13
 
2.9%
전라북도 13
 
2.9%
Other values (148) 276
61.2%
2024-05-11T16:48:25.460704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
234
 
11.1%
청 207
 
9.8%
시 165
 
7.8%
도 127
 
6.0%
구 79
 
3.7%
군 76
 
3.6%
광 71
 
3.4%
역 65
 
3.1%
남 56
 
2.7%
원 55
 
2.6%
Other values (120) 974
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1874
88.9%
Space Separator 234
 
11.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 207
 
11.0%
시 165
 
8.8%
도 127
 
6.8%
구 79
 
4.2%
군 76
 
4.1%
광 71
 
3.8%
역 65
 
3.5%
남 56
 
3.0%
원 55
 
2.9%
산 53
 
2.8%
Other values (118) 920
49.1%
Space Separator
ValueCountFrequency (%)
234
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1875
88.9%
Common 234
 
11.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 207
 
11.0%
시 165
 
8.8%
도 127
 
6.8%
구 79
 
4.2%
군 76
 
4.1%
광 71
 
3.8%
역 65
 
3.5%
남 56
 
3.0%
원 55
 
2.9%
산 53
 
2.8%
Other values (119) 921
49.1%
Common
ValueCountFrequency (%)
234
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1874
88.9%
ASCII 234
 
11.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
234
100.0%
Hangul
ValueCountFrequency (%)
청 207
 
11.0%
시 165
 
8.8%
도 127
 
6.8%
구 79
 
4.2%
군 76
 
4.1%
광 71
 
3.8%
역 65
 
3.5%
남 56
 
3.0%
원 55
 
2.9%
산 53
 
2.8%
Other values (118) 920
49.1%
None
ValueCountFrequency (%)
㈜ 1
100.0%

데이터기준일자
Date

Distinct123
Distinct (%)56.2%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2018-05-15 00:00:00
Maximum2024-03-20 00:00:00
2024-05-11T16:48:25.896082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:48:26.212946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

제공기관코드
Text

Distinct166
Distinct (%)75.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-05-11T16:48:26.940797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters1533
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique147 ?
Unique (%)67.1%

Sample

1st row3580000
2nd row3580000
3rd row3580000
4th row3820000
5th row4860000
ValueCountFrequency (%)
3580000 15
 
6.8%
3700000 11
 
5.0%
3320000 6
 
2.7%
3380000 5
 
2.3%
4180000 4
 
1.8%
4181000 4
 
1.8%
3150000 3
 
1.4%
5380000 2
 
0.9%
5370000 2
 
0.9%
3100000 2
 
0.9%
Other values (156) 165
75.3%
2024-05-11T16:48:28.138213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 888
57.9%
3 146
 
9.5%
4 123
 
8.0%
5 82
 
5.3%
1 77
 
5.0%
8 51
 
3.3%
2 51
 
3.3%
7 44
 
2.9%
9 35
 
2.3%
6 33
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1530
99.8%
Uppercase Letter 3
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 888
58.0%
3 146
 
9.5%
4 123
 
8.0%
5 82
 
5.4%
1 77
 
5.0%
8 51
 
3.3%
2 51
 
3.3%
7 44
 
2.9%
9 35
 
2.3%
6 33
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
B 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1530
99.8%
Latin 3
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 888
58.0%
3 146
 
9.5%
4 123
 
8.0%
5 82
 
5.4%
1 77
 
5.0%
8 51
 
3.3%
2 51
 
3.3%
7 44
 
2.9%
9 35
 
2.3%
6 33
 
2.2%
Latin
ValueCountFrequency (%)
B 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1533
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 888
57.9%
3 146
 
9.5%
4 123
 
8.0%
5 82
 
5.3%
1 77
 
5.0%
8 51
 
3.3%
2 51
 
3.3%
7 44
 
2.9%
9 35
 
2.3%
6 33
 
2.2%

제공기관명
Text

Distinct166
Distinct (%)75.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-05-11T16:48:28.599294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length8.4520548
Min length6

Characters and Unicode

Total characters1851
Distinct characters113
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

Unique147 ?
Unique (%)67.1%

Sample

1st row인천광역시 옹진군
2nd row인천광역시 옹진군
3rd row인천광역시 옹진군
4th row경기도 의정부시
5th row전라남도 곡성군
ValueCountFrequency (%)
부산광역시 24
 
5.5%
서울특별시 23
 
5.3%
인천광역시 19
 
4.4%
전라남도 17
 
3.9%
강원도 16
 
3.7%
강원특별자치도 16
 
3.7%
경기도 16
 
3.7%
옹진군 15
 
3.4%
남구 13
 
3.0%
울산광역시 13
 
3.0%
Other values (139) 263
60.5%
2024-05-11T16:48:29.384011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
216
 
11.7%
시 165
 
8.9%
도 136
 
7.3%
구 79
 
4.3%
군 77
 
4.2%
광 71
 
3.8%
역 65
 
3.5%
남 59
 
3.2%
산 52
 
2.8%
특 48
 
2.6%
Other values (103) 883
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1635
88.3%
Space Separator 216
 
11.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 165
 
10.1%
도 136
 
8.3%
구 79
 
4.8%
군 77
 
4.7%
광 71
 
4.3%
역 65
 
4.0%
남 59
 
3.6%
산 52
 
3.2%
특 48
 
2.9%
북 48
 
2.9%
Other values (102) 835
51.1%
Space Separator
ValueCountFrequency (%)
216
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1635
88.3%
Common 216
 
11.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 165
 
10.1%
도 136
 
8.3%
구 79
 
4.8%
군 77
 
4.7%
광 71
 
4.3%
역 65
 
4.0%
남 59
 
3.6%
산 52
 
3.2%
특 48
 
2.9%
북 48
 
2.9%
Other values (102) 835
51.1%
Common
ValueCountFrequency (%)
216
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1635
88.3%
ASCII 216
 
11.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
216
100.0%
Hangul
ValueCountFrequency (%)
시 165
 
10.1%
도 136
 
8.3%
구 79
 
4.8%
군 77
 
4.7%
광 71
 
4.3%
역 65
 
4.0%
남 59
 
3.6%
산 52
 
3.2%
특 48
 
2.9%
북 48
 
2.9%
Other values (102) 835
51.1%

Sample

재활용센터명재활용센터운영구분소재지도로명주소소재지지번주소위도경도면적설립연월차량보유대수주요취급품목정보운영기관명운영기관전화번호운영기관대표자명평일운영시작시각평일운영종료시각공휴일운영시작시각공휴일운영종료시각휴무일정보애프터서비스정보홈페이지주소관리기관전화번호관리기관명데이터기준일자제공기관코드제공기관명
0자월면 대이작 재활용 선별장직영인천광역시 옹진군 자월면 대이작로 159번길 127인천광역시 옹진군 자월면 이작리 394-337.174685126.2648661351.02020-110종이류+고철류+캔류+병류+플라스틱류+필름류+스티로폼류인천광역시 옹진군 자월면032-899-3750장정민09:0018:0009:0013:00일요일<NA><NA>032-899-2620인천광역시 옹진군2021-11-163580000인천광역시 옹진군
1자월면 승봉 재활용 선별장직영인천광역시 옹진군 자월면 승봉로29번길 100-13인천광역시 옹진군 자월면 승봉리 771-337.172847126.296375128.52020-030종이류+고철류+캔류+병류+플라스틱류+필름류+스티로폼류인천광역시 옹진군 자월면032-899-3750장정민09:0018:0009:0013:00일요일<NA><NA>032-899-2620인천광역시 옹진군2021-11-163580000인천광역시 옹진군
2대청면 소청 재활용 선별장직영인천광역시 옹진군 대청면 소청동로 159인천광역시 옹진군 대청면 소청리 5837.771331124.760943115.92020-100종이류+고철류+캔류+병류+플라스틱류+필름류+스티로폼류인천광역시 옹진군 대청면032-899-3409장정민09:0018:0009:0013:00일요일<NA><NA>032-899-2620인천광역시 옹진군2021-11-163580000인천광역시 옹진군
3의정부시재활용센터위탁경기도 의정부시 장곡로 450(신곡동)경기도 의정부시 신곡동 68137.743517127.055199478.51998-061가전+가구 등(사)한국생활자원재활용협회 의정부지회031-844-7282이종철09:0018:0000:0000:00토+일+공휴일판매 또는 교환물품이 6개월이내에 하자 발생시 무상수리<NA>031-828-2994경기도 의정부시청2023-03-023820000경기도 의정부시
4곡성군 재활용품 선별장직영전라남도 곡성군 곡성읍 곡고로 98-157<NA>35.281813127.3252382066.02001-012플라스틱병+캔류전라남도 곡성군청061-360-8521곡성군수09:0018:0009:0014:00일요일해당없음<NA>061-360-8522전라남도 곡성군청2023-04-044860000전라남도 곡성군
5강남구재활용센터위탁서울특별시 강남구 개포로 247서울특별시 강남구 개포동 1259-637.479138127.049479660.02021-014가전가구류강남구재활용센터<NA><NA>09:0019:0009:0019:00<NA><NA><NA>02-3423-6008서울특별시 강남구청2023-03-273220000서울특별시 강남구
6리싸이클세상위탁서울특별시 강남구 논현로 115길 7서울특별시 강남구 논현동 191-637.508835127.032502781.02021-013가전가구류(주)리싸이클세상<NA><NA>09:0019:0009:0019:00<NA><NA><NA>02-3423-6008서울특별시 강남구청2023-03-273220000서울특별시 강남구
7사천시 재활용선별장직영경상남도 사천시 환경길 71경상남도 사천시 사등동 86-934.925223128.1138241234.02007-075잉코트 외 11개 품목경상남도 사천시청 환경사업소055-831-5606사천시장(박동식)08:0017:0000:0000:00토+일+공휴일<NA>http://www.sacheon.go.kr055-831-5606경상남도 사천시청2023-04-195340000경상남도 사천시
8장흥군그린환경센터위탁전라남도 장흥군 부산면 덕정길 206전라남도 장흥군 부산면 부춘리 9534.7088126.921073480.02011-042종이+필름+플라스틱+캔+병+발포합성수지류장흥지역자활센터061-862-8266위수미09:0018:0000:0000:00토+일+공휴일<NA>www.jangheung.go.kr061-860-7831전라남도 장흥군청2023-05-014910000전라남도 장흥군
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