Overview

Dataset statistics

Number of variables13
Number of observations36
Missing cells40
Missing cells (%)8.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 KiB
Average record size in memory111.7 B

Variable types

Text8
Numeric3
Categorical1
Unsupported1

Alerts

업무시간 has constant value ""Constant
우편번호 is highly overall correlated with WGS84위도High correlation
WGS84위도 is highly overall correlated with 우편번호High correlation
도로명주소 has 1 (2.8%) missing valuesMissing
우편번호 has 1 (2.8%) missing valuesMissing
참고사항 has 36 (100.0%) missing valuesMissing
WGS84위도 has 1 (2.8%) missing valuesMissing
WGS84경도 has 1 (2.8%) missing valuesMissing
시군명 has unique valuesUnique
지번주소 has unique valuesUnique
전화번호 has unique valuesUnique
팩스번호 has unique valuesUnique
참고사항 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 21:17:25.668467
Analysis finished2023-12-10 21:17:27.603134
Duration1.93 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-11T06:17:27.747463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length3
Mean length3.9166667
Min length3

Characters and Unicode

Total characters141
Distinct characters51
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st row군포시
2nd row성남시
3rd row김포시
4th row하남시
5th row오산시
ValueCountFrequency (%)
군포시 1
 
2.7%
안성시 1
 
2.7%
의왕시 1
 
2.7%
여주시 1
 
2.7%
부천시 1
 
2.7%
용인시 1
 
2.7%
시흥시 1
 
2.7%
동탄출장소(화성시 1
 
2.7%
양평군 1
 
2.7%
파주시 1
 
2.7%
Other values (27) 27
73.0%
2023-12-11T06:17:28.063987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 31
22.0%
양 7
 
5.0%
천 7
 
5.0%
주 5
 
3.5%
( 5
 
3.5%
) 5
 
3.5%
안 4
 
2.8%
동 4
 
2.8%
군 4
 
2.8%
성 4
 
2.8%
Other values (41) 65
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 130
92.2%
Open Punctuation 5
 
3.5%
Close Punctuation 5
 
3.5%
Space Separator 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 31
23.8%
양 7
 
5.4%
천 7
 
5.4%
주 5
 
3.8%
안 4
 
3.1%
동 4
 
3.1%
군 4
 
3.1%
성 4
 
3.1%
구 3
 
2.3%
부 3
 
2.3%
Other values (38) 58
44.6%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 130
92.2%
Common 11
 
7.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 31
23.8%
양 7
 
5.4%
천 7
 
5.4%
주 5
 
3.8%
안 4
 
3.1%
동 4
 
3.1%
군 4
 
3.1%
성 4
 
3.1%
구 3
 
2.3%
부 3
 
2.3%
Other values (38) 58
44.6%
Common
ValueCountFrequency (%)
( 5
45.5%
) 5
45.5%
1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 130
92.2%
ASCII 11
 
7.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 31
23.8%
양 7
 
5.4%
천 7
 
5.4%
주 5
 
3.8%
안 4
 
3.1%
동 4
 
3.1%
군 4
 
3.1%
성 4
 
3.1%
구 3
 
2.3%
부 3
 
2.3%
Other values (38) 58
44.6%
ASCII
ValueCountFrequency (%)
( 5
45.5%
) 5
45.5%
1
 
9.1%

기관명
Text

Distinct18
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-11T06:17:28.220925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.9444444
Min length3

Characters and Unicode

Total characters178
Distinct characters26
Distinct categories1 ?
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 (%)30.6%

Sample

1st row민원봉사과
2nd row민원여권과
3rd row민원여권과
4th row종합민원과
5th row민원토지과
ValueCountFrequency (%)
민원봉사과 8
22.2%
민원지적과 4
11.1%
민원여권과 4
11.1%
여권민원실 3
 
8.3%
민원토지과 2
 
5.6%
고객지원과 2
 
5.6%
시민봉사과 2
 
5.6%
민원담당관 1
 
2.8%
여권팀 1
 
2.8%
민원총무과 1
 
2.8%
Other values (8) 8
22.2%
2023-12-11T06:17:28.509436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
민 33
18.5%
원 33
18.5%
과 29
16.3%
봉 10
 
5.6%
사 10
 
5.6%
지 10
 
5.6%
여 9
 
5.1%
권 9
 
5.1%
적 4
 
2.2%
실 4
 
2.2%
Other values (16) 27
15.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 178
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
민 33
18.5%
원 33
18.5%
과 29
16.3%
봉 10
 
5.6%
사 10
 
5.6%
지 10
 
5.6%
여 9
 
5.1%
권 9
 
5.1%
적 4
 
2.2%
실 4
 
2.2%
Other values (16) 27
15.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 178
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
민 33
18.5%
원 33
18.5%
과 29
16.3%
봉 10
 
5.6%
사 10
 
5.6%
지 10
 
5.6%
여 9
 
5.1%
권 9
 
5.1%
적 4
 
2.2%
실 4
 
2.2%
Other values (16) 27
15.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 178
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
민 33
18.5%
원 33
18.5%
과 29
16.3%
봉 10
 
5.6%
사 10
 
5.6%
지 10
 
5.6%
여 9
 
5.1%
권 9
 
5.1%
적 4
 
2.2%
실 4
 
2.2%
Other values (16) 27
15.2%

도로명주소
Text

MISSING 

Distinct35
Distinct (%)100.0%
Missing1
Missing (%)2.8%
Memory size420.0 B
2023-12-11T06:17:28.761877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length16.485714
Min length13

Characters and Unicode

Total characters577
Distinct characters94
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)100.0%

Sample

1st row경기도 군포시 청백리길 6
2nd row경기도 성남시 중원구 성남대로 997
3rd row경기도 김포시 사우중로 1
4th row경기도 하남시 대청로 10
5th row경기도 오산시 성호대로 141
ValueCountFrequency (%)
경기도 35
 
23.0%
시청로 5
 
3.3%
1 4
 
2.6%
평택시 2
 
1.3%
화성시 2
 
1.3%
20 2
 
1.3%
부천시 2
 
1.3%
팔달구 2
 
1.3%
수원시 2
 
1.3%
50 2
 
1.3%
Other values (94) 94
61.8%
2023-12-11T06:17:29.122956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
117
20.3%
시 41
 
7.1%
경 37
 
6.4%
기 36
 
6.2%
도 35
 
6.1%
로 32
 
5.5%
1 23
 
4.0%
2 13
 
2.3%
5 11
 
1.9%
3 10
 
1.7%
Other values (84) 222
38.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 370
64.1%
Space Separator 117
 
20.3%
Decimal Number 89
 
15.4%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 41
 
11.1%
경 37
 
10.0%
기 36
 
9.7%
도 35
 
9.5%
로 32
 
8.6%
천 9
 
2.4%
청 9
 
2.4%
양 8
 
2.2%
구 8
 
2.2%
대 8
 
2.2%
Other values (72) 147
39.7%
Decimal Number
ValueCountFrequency (%)
1 23
25.8%
2 13
14.6%
5 11
12.4%
3 10
11.2%
0 9
 
10.1%
9 7
 
7.9%
4 5
 
5.6%
7 4
 
4.5%
6 4
 
4.5%
8 3
 
3.4%
Space Separator
ValueCountFrequency (%)
117
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 370
64.1%
Common 207
35.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 41
 
11.1%
경 37
 
10.0%
기 36
 
9.7%
도 35
 
9.5%
로 32
 
8.6%
천 9
 
2.4%
청 9
 
2.4%
양 8
 
2.2%
구 8
 
2.2%
대 8
 
2.2%
Other values (72) 147
39.7%
Common
ValueCountFrequency (%)
117
56.5%
1 23
 
11.1%
2 13
 
6.3%
5 11
 
5.3%
3 10
 
4.8%
0 9
 
4.3%
9 7
 
3.4%
4 5
 
2.4%
7 4
 
1.9%
6 4
 
1.9%
Other values (2) 4
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 370
64.1%
ASCII 207
35.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
117
56.5%
1 23
 
11.1%
2 13
 
6.3%
5 11
 
5.3%
3 10
 
4.8%
0 9
 
4.3%
9 7
 
3.4%
4 5
 
2.4%
7 4
 
1.9%
6 4
 
1.9%
Other values (2) 4
 
1.9%
Hangul
ValueCountFrequency (%)
시 41
 
11.1%
경 37
 
10.0%
기 36
 
9.7%
도 35
 
9.5%
로 32
 
8.6%
천 9
 
2.4%
청 9
 
2.4%
양 8
 
2.2%
구 8
 
2.2%
대 8
 
2.2%
Other values (72) 147
39.7%

지번주소
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-11T06:17:29.393585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length30
Mean length20.916667
Min length15

Characters and Unicode

Total characters753
Distinct characters109
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st row경기도 군포시 금정동 844번지
2nd row경기도 성남시 중원구 여수동 200번지
3rd row경기도 김포시 사우동 263-1번지
4th row경기도 하남시 신장동 520번지
5th row경기도 오산시 오산동 915번지
ValueCountFrequency (%)
경기도 36
 
21.3%
고양시 3
 
1.8%
평택시 2
 
1.2%
화성시 2
 
1.2%
수원시 2
 
1.2%
팔달구 2
 
1.2%
부천시 2
 
1.2%
오산동 2
 
1.2%
1-1번지 2
 
1.2%
홍문동 1
 
0.6%
Other values (115) 115
68.0%
2023-12-11T06:17:29.781836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
133
17.7%
경 38
 
5.0%
기 38
 
5.0%
지 37
 
4.9%
동 37
 
4.9%
도 36
 
4.8%
시 36
 
4.8%
번 35
 
4.6%
1 24
 
3.2%
2 18
 
2.4%
Other values (99) 321
42.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 480
63.7%
Space Separator 133
 
17.7%
Decimal Number 122
 
16.2%
Dash Punctuation 14
 
1.9%
Close Punctuation 2
 
0.3%
Open Punctuation 1
 
0.1%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 38
 
7.9%
기 38
 
7.9%
지 37
 
7.7%
동 37
 
7.7%
도 36
 
7.5%
시 36
 
7.5%
번 35
 
7.3%
양 13
 
2.7%
산 11
 
2.3%
구 11
 
2.3%
Other values (84) 188
39.2%
Decimal Number
ValueCountFrequency (%)
1 24
19.7%
2 18
14.8%
5 17
13.9%
0 14
11.5%
3 11
9.0%
4 9
 
7.4%
9 9
 
7.4%
6 7
 
5.7%
8 7
 
5.7%
7 6
 
4.9%
Space Separator
ValueCountFrequency (%)
133
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 480
63.7%
Common 272
36.1%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 38
 
7.9%
기 38
 
7.9%
지 37
 
7.7%
동 37
 
7.7%
도 36
 
7.5%
시 36
 
7.5%
번 35
 
7.3%
양 13
 
2.7%
산 11
 
2.3%
구 11
 
2.3%
Other values (84) 188
39.2%
Common
ValueCountFrequency (%)
133
48.9%
1 24
 
8.8%
2 18
 
6.6%
5 17
 
6.2%
- 14
 
5.1%
0 14
 
5.1%
3 11
 
4.0%
4 9
 
3.3%
9 9
 
3.3%
6 7
 
2.6%
Other values (4) 16
 
5.9%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 480
63.7%
ASCII 273
36.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
133
48.7%
1 24
 
8.8%
2 18
 
6.6%
5 17
 
6.2%
- 14
 
5.1%
0 14
 
5.1%
3 11
 
4.0%
4 9
 
3.3%
9 9
 
3.3%
6 7
 
2.6%
Other values (5) 17
 
6.2%
Hangul
ValueCountFrequency (%)
경 38
 
7.9%
기 38
 
7.9%
지 37
 
7.7%
동 37
 
7.7%
도 36
 
7.5%
시 36
 
7.5%
번 35
 
7.3%
양 13
 
2.7%
산 11
 
2.3%
구 11
 
2.3%
Other values (84) 188
39.2%

우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct35
Distinct (%)100.0%
Missing1
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean14218.943
Minimum10109
Maximum18478
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T06:17:29.912241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10109
5-th percentile10801.5
Q112119
median14053
Q316337
95-th percentile18174.6
Maximum18478
Range8369
Interquartile range (IQR)4218

Descriptive statistics

Standard deviation2592.2039
Coefficient of variation (CV)0.18230637
Kurtosis-1.2877955
Mean14218.943
Median Absolute Deviation (MAD)2177
Skewness0.18615974
Sum497663
Variance6719521.1
MonotonicityNot monotonic
2023-12-11T06:17:30.019204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
15829 1
 
2.8%
13437 1
 
2.8%
16075 1
 
2.8%
12619 1
 
2.8%
14547 1
 
2.8%
17019 1
 
2.8%
14998 1
 
2.8%
18478 1
 
2.8%
17379 1
 
2.8%
12554 1
 
2.8%
Other values (25) 25
69.4%
ValueCountFrequency (%)
10109 1
2.8%
10497 1
2.8%
10932 1
2.8%
11017 1
2.8%
11147 1
2.8%
11317 1
2.8%
11498 1
2.8%
11622 1
2.8%
11954 1
2.8%
12284 1
2.8%
ValueCountFrequency (%)
18478 1
2.8%
18274 1
2.8%
18132 1
2.8%
17901 1
2.8%
17816 1
2.8%
17586 1
2.8%
17379 1
2.8%
17019 1
2.8%
16444 1
2.8%
16230 1
2.8%

전화번호
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-11T06:17:30.242322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length24
Mean length15.444444
Min length9

Characters and Unicode

Total characters556
Distinct characters14
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

Unique36 ?
Unique (%)100.0%

Sample

1st row031-390-0137, 0139
2nd row1577-3100
3rd row031-980-2700
4th row031-790-5353
5th row031-8036-7282, 7288~7290
ValueCountFrequency (%)
031-390-0137 1
 
2.0%
031-8024-2821,2823 1
 
2.0%
031-8045-2536 1
 
2.0%
2602 1
 
2.0%
031-760-4613 1
 
2.0%
031-678-3284,2071 1
 
2.0%
031-644-2124 1
 
2.0%
031-345-2316 1
 
2.0%
2317 1
 
2.0%
031-887-2163,2160 1
 
2.0%
Other values (39) 39
79.6%
2023-12-11T06:17:30.672639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 78
14.0%
0 77
13.8%
- 71
12.8%
1 70
12.6%
2 56
10.1%
8 44
7.9%
7 28
 
5.0%
6 27
 
4.9%
5 26
 
4.7%
4 23
 
4.1%
Other values (4) 56
10.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 450
80.9%
Dash Punctuation 71
 
12.8%
Other Punctuation 18
 
3.2%
Space Separator 13
 
2.3%
Math Symbol 4
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 78
17.3%
0 77
17.1%
1 70
15.6%
2 56
12.4%
8 44
9.8%
7 28
 
6.2%
6 27
 
6.0%
5 26
 
5.8%
4 23
 
5.1%
9 21
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 71
100.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 78
14.0%
0 77
13.8%
- 71
12.8%
1 70
12.6%
2 56
10.1%
8 44
7.9%
7 28
 
5.0%
6 27
 
4.9%
5 26
 
4.7%
4 23
 
4.1%
Other values (4) 56
10.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 78
14.0%
0 77
13.8%
- 71
12.8%
1 70
12.6%
2 56
10.1%
8 44
7.9%
7 28
 
5.0%
6 27
 
4.9%
5 26
 
4.7%
4 23
 
4.1%
Other values (4) 56
10.1%

팩스번호
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-11T06:17:30.951144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length12.416667
Min length1

Characters and Unicode

Total characters447
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st row031-390-0661~2
2nd row031-729-4909
3rd row031-980-2900
4th row031-790-6139
5th row031-8036-8956
ValueCountFrequency (%)
031-390-0661~2 1
 
2.8%
031-729-4909 1
 
2.8%
031-631-2401,2458 1
 
2.8%
031-850-2249 1
 
2.8%
031-887-2137 1
 
2.8%
032-625-2458 1
 
2.8%
031-324-3350,2209 1
 
2.8%
031-310-2805 1
 
2.8%
031-5189-5656 1
 
2.8%
031-770-2802 1
 
2.8%
Other values (26) 26
72.2%
2023-12-11T06:17:31.322705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 76
17.0%
- 71
15.9%
1 52
11.6%
3 49
11.0%
8 46
10.3%
2 40
8.9%
9 29
 
6.5%
6 25
 
5.6%
5 23
 
5.1%
7 16
 
3.6%
Other values (3) 20
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 371
83.0%
Dash Punctuation 71
 
15.9%
Other Punctuation 3
 
0.7%
Math Symbol 2
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 76
20.5%
1 52
14.0%
3 49
13.2%
8 46
12.4%
2 40
10.8%
9 29
 
7.8%
6 25
 
6.7%
5 23
 
6.2%
7 16
 
4.3%
4 15
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 71
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 447
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 76
17.0%
- 71
15.9%
1 52
11.6%
3 49
11.0%
8 46
10.3%
2 40
8.9%
9 29
 
6.5%
6 25
 
5.6%
5 23
 
5.1%
7 16
 
3.6%
Other values (3) 20
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 447
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 76
17.0%
- 71
15.9%
1 52
11.6%
3 49
11.0%
8 46
10.3%
2 40
8.9%
9 29
 
6.5%
6 25
 
5.6%
5 23
 
5.1%
7 16
 
3.6%
Other values (3) 20
 
4.5%

홈페이지주소
Text

Distinct33
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-11T06:17:31.569682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length26
Mean length23.444444
Min length19

Characters and Unicode

Total characters844
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)83.3%

Sample

1st rowhttp://www.gunpo.go.kr
2nd rowhttp://www.seongnam.go.kr
3rd rowhttp://www.gimpo.go.kr
4th rowhttp://www.hanam.go.kr
5th rowhttp://www.osan.go.kr
ValueCountFrequency (%)
http://www.goyang.go.kr 2
 
5.6%
http://www.gg.go.kr 2
 
5.6%
http://www.hscity.go.kr 2
 
5.6%
http://www.gunpo.go.kr 1
 
2.8%
http://www.yeoju.go.kr 1
 
2.8%
http://www.bucheon.go.kr 1
 
2.8%
http://www.yongin.go.kr 1
 
2.8%
http://www.siheung.go.kr 1
 
2.8%
http://www.uiwang.go.kr 1
 
2.8%
http://www.yp21.go.kr 1
 
2.8%
Other values (23) 23
63.9%
2023-12-11T06:17:31.936694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 110
13.0%
. 107
12.7%
t 79
9.4%
/ 77
 
9.1%
g 61
 
7.2%
o 54
 
6.4%
h 45
 
5.3%
p 44
 
5.2%
k 37
 
4.4%
: 36
 
4.3%
Other values (22) 194
23.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 617
73.1%
Other Punctuation 220
 
26.1%
Decimal Number 6
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 110
17.8%
t 79
12.8%
g 61
9.9%
o 54
8.8%
h 45
7.3%
p 44
 
7.1%
k 37
 
6.0%
r 36
 
5.8%
n 32
 
5.2%
a 19
 
3.1%
Other values (13) 100
16.2%
Decimal Number
ValueCountFrequency (%)
1 2
33.3%
4 1
16.7%
0 1
16.7%
3 1
16.7%
2 1
16.7%
Other Punctuation
ValueCountFrequency (%)
. 107
48.6%
/ 77
35.0%
: 36
 
16.4%
Uppercase Letter
ValueCountFrequency (%)
O 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 618
73.2%
Common 226
 
26.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 110
17.8%
t 79
12.8%
g 61
9.9%
o 54
8.7%
h 45
7.3%
p 44
 
7.1%
k 37
 
6.0%
r 36
 
5.8%
n 32
 
5.2%
a 19
 
3.1%
Other values (14) 101
16.3%
Common
ValueCountFrequency (%)
. 107
47.3%
/ 77
34.1%
: 36
 
15.9%
1 2
 
0.9%
4 1
 
0.4%
0 1
 
0.4%
3 1
 
0.4%
2 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 844
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 110
13.0%
. 107
12.7%
t 79
9.4%
/ 77
 
9.1%
g 61
 
7.2%
o 54
 
6.4%
h 45
 
5.3%
p 44
 
5.2%
k 37
 
4.4%
: 36
 
4.3%
Other values (22) 194
23.0%

업무시간
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
월-금 9:00~18:00
36 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row월-금 9:00~18:00
2nd row월-금 9:00~18:00
3rd row월-금 9:00~18:00
4th row월-금 9:00~18:00
5th row월-금 9:00~18:00

Common Values

ValueCountFrequency (%)
월-금 9:00~18:00 36
100.0%

Length

2023-12-11T06:17:32.097639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:17:32.225342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
월-금 36
50.0%
9:00~18:00 36
50.0%

연장근무시간
Text

Distinct20
Distinct (%)55.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-11T06:17:32.368718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length59
Mean length21.861111
Min length1

Characters and Unicode

Total characters787
Distinct characters36
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

Unique13 ?
Unique (%)36.1%

Sample

1st row매주 화요일 18:00 ~ 21:00
2nd row매주 평일 18:00 ~ 21:00
3rd row매주 화,수,목요일 18:00 ~ 21:00
4th row-
5th row-
ValueCountFrequency (%)
43
22.5%
매주 35
18.3%
18:00 34
17.8%
21:00 19
9.9%
목요일 15
 
7.9%
평일 9
 
4.7%
20:00 7
 
3.7%
화요일 5
 
2.6%
수요일 3
 
1.6%
09:00 3
 
1.6%
Other values (16) 18
9.4%
2023-12-11T06:17:32.689171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 158
20.1%
158
20.1%
: 72
9.1%
1 64
8.1%
~ 38
 
4.8%
일 38
 
4.8%
8 35
 
4.4%
매 35
 
4.4%
주 35
 
4.4%
2 34
 
4.3%
Other values (26) 120
15.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 301
38.2%
Other Letter 193
24.5%
Space Separator 158
20.1%
Other Punctuation 85
 
10.8%
Math Symbol 38
 
4.8%
Close Punctuation 4
 
0.5%
Open Punctuation 4
 
0.5%
Dash Punctuation 4
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 38
19.7%
매 35
18.1%
주 35
18.1%
요 26
13.5%
목 16
8.3%
평 9
 
4.7%
화 8
 
4.1%
월 5
 
2.6%
휴 4
 
2.1%
수 4
 
2.1%
Other values (10) 13
 
6.7%
Decimal Number
ValueCountFrequency (%)
0 158
52.5%
1 64
21.3%
8 35
 
11.6%
2 34
 
11.3%
9 6
 
2.0%
3 3
 
1.0%
4 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
: 72
84.7%
, 7
 
8.2%
/ 3
 
3.5%
. 3
 
3.5%
Space Separator
ValueCountFrequency (%)
158
100.0%
Math Symbol
ValueCountFrequency (%)
~ 38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 594
75.5%
Hangul 193
 
24.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
일 38
19.7%
매 35
18.1%
주 35
18.1%
요 26
13.5%
목 16
8.3%
평 9
 
4.7%
화 8
 
4.1%
월 5
 
2.6%
휴 4
 
2.1%
수 4
 
2.1%
Other values (10) 13
 
6.7%
Common
ValueCountFrequency (%)
0 158
26.6%
158
26.6%
: 72
12.1%
1 64
10.8%
~ 38
 
6.4%
8 35
 
5.9%
2 34
 
5.7%
, 7
 
1.2%
9 6
 
1.0%
) 4
 
0.7%
Other values (6) 18
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 594
75.5%
Hangul 193
 
24.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 158
26.6%
158
26.6%
: 72
12.1%
1 64
10.8%
~ 38
 
6.4%
8 35
 
5.9%
2 34
 
5.7%
, 7
 
1.2%
9 6
 
1.0%
) 4
 
0.7%
Other values (6) 18
 
3.0%
Hangul
ValueCountFrequency (%)
일 38
19.7%
매 35
18.1%
주 35
18.1%
요 26
13.5%
목 16
8.3%
평 9
 
4.7%
화 8
 
4.1%
월 5
 
2.6%
휴 4
 
2.1%
수 4
 
2.1%
Other values (10) 13
 
6.7%

참고사항
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct35
Distinct (%)100.0%
Missing1
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean37.457386
Minimum36.989471
Maximum38.096517
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T06:17:32.844854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.989471
5-th percentile37.002839
Q137.28149
median37.42931
Q337.612564
95-th percentile37.897315
Maximum38.096517
Range1.1070452
Interquartile range (IQR)0.33107449

Descriptive statistics

Standard deviation0.26656559
Coefficient of variation (CV)0.0071165026
Kurtosis-0.14753886
Mean37.457386
Median Absolute Deviation (MAD)0.1651435
Skewness0.31906874
Sum1311.0085
Variance0.071057212
MonotonicityNot monotonic
2023-12-11T06:17:33.000507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
37.3623695182 1
 
2.8%
37.4201937973 1
 
2.8%
37.3452361445 1
 
2.8%
37.2982159296 1
 
2.8%
37.5035804617 1
 
2.8%
37.2406392886 1
 
2.8%
37.3804189876 1
 
2.8%
37.2031687037 1
 
2.8%
37.2724872049 1
 
2.8%
37.4919020854 1
 
2.8%
Other values (25) 25
69.4%
ValueCountFrequency (%)
36.9894714879 1
2.8%
36.992297194 1
2.8%
37.0073565913 1
2.8%
37.1490352115 1
2.8%
37.1999079098 1
2.8%
37.2031687037 1
2.8%
37.2406392886 1
2.8%
37.2724872049 1
2.8%
37.274663047 1
2.8%
37.2883165126 1
2.8%
ValueCountFrequency (%)
38.0965166652 1
2.8%
37.903420467 1
2.8%
37.8946984341 1
2.8%
37.8312936704 1
2.8%
37.78553628 1
2.8%
37.7592776144 1
2.8%
37.7384886928 1
2.8%
37.6374571807 1
2.8%
37.6148826054 1
2.8%
37.6102459421 1
2.8%

WGS84경도
Real number (ℝ)

MISSING 

Distinct35
Distinct (%)100.0%
Missing1
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean127.06166
Minimum126.71569
Maximum127.63663
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T06:17:33.140656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.71569
5-th percentile126.77552
Q1126.8918
median127.04667
Q3127.17558
95-th percentile127.49394
Maximum127.63663
Range0.92093335
Interquartile range (IQR)0.28378402

Descriptive statistics

Standard deviation0.22396115
Coefficient of variation (CV)0.0017626178
Kurtosis0.27438953
Mean127.06166
Median Absolute Deviation (MAD)0.13253521
Skewness0.71862745
Sum4447.1582
Variance0.050158596
MonotonicityNot monotonic
2023-12-11T06:17:33.259264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
126.9352272862 1
 
2.8%
127.1263063033 1
 
2.8%
126.9686952702 1
 
2.8%
127.6366282067 1
 
2.8%
126.7653515249 1
 
2.8%
127.1792040872 1
 
2.8%
126.8040662779 1
 
2.8%
127.0968738822 1
 
2.8%
127.4337338265 1
 
2.8%
127.4871719211 1
 
2.8%
Other values (25) 25
69.4%
ValueCountFrequency (%)
126.715694858 1
2.8%
126.7653515249 1
2.8%
126.7798816508 1
2.8%
126.7960281955 1
2.8%
126.8040662779 1
2.8%
126.830562363 1
2.8%
126.8309421906 1
2.8%
126.8322777968 1
2.8%
126.8643754325 1
2.8%
126.9192188039 1
2.8%
ValueCountFrequency (%)
127.6366282067 1
2.8%
127.5097161526 1
2.8%
127.4871719211 1
2.8%
127.4337338265 1
2.8%
127.280313201 1
2.8%
127.2550789677 1
2.8%
127.2145481557 1
2.8%
127.2003394909 1
2.8%
127.1792040872 1
2.8%
127.171958185 1
2.8%

Interactions

2023-12-11T06:17:26.974983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:26.210193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:26.445305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:27.070774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:26.281785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:26.524987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:27.150754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:26.358650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:17:26.877876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:17:33.356876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명기관명도로명주소지번주소우편번호전화번호팩스번호홈페이지주소연장근무시간WGS84위도WGS84경도
시군명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
기관명1.0001.0001.0001.0000.0001.0001.0000.0000.2980.3630.000
도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
우편번호1.0000.0001.0001.0001.0001.0001.0001.0000.6230.7950.846
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
팩스번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
홈페이지주소1.0000.0001.0001.0001.0001.0001.0001.0000.8901.0000.975
연장근무시간1.0000.2981.0001.0000.6231.0001.0000.8901.0000.0000.792
WGS84위도1.0000.3631.0001.0000.7951.0001.0001.0000.0001.0000.000
WGS84경도1.0000.0001.0001.0000.8461.0001.0000.9750.7920.0001.000
2023-12-11T06:17:33.476742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호WGS84위도WGS84경도
우편번호1.000-0.9200.001
WGS84위도-0.9201.000-0.055
WGS84경도0.001-0.0551.000

Missing values

2023-12-11T06:17:27.255284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:17:27.426013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-11T06:17:27.539057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시군명기관명도로명주소지번주소우편번호전화번호팩스번호홈페이지주소업무시간연장근무시간참고사항WGS84위도WGS84경도
0군포시민원봉사과경기도 군포시 청백리길 6경기도 군포시 금정동 844번지15829031-390-0137, 0139031-390-0661~2http://www.gunpo.go.kr월-금 9:00~18:00매주 화요일 18:00 ~ 21:00<NA>37.36237126.935227
1성남시민원여권과경기도 성남시 중원구 성남대로 997경기도 성남시 중원구 여수동 200번지134371577-3100031-729-4909http://www.seongnam.go.kr월-금 9:00~18:00매주 평일 18:00 ~ 21:00<NA>37.420194127.126306
2김포시민원여권과경기도 김포시 사우중로 1경기도 김포시 사우동 263-1번지10109031-980-2700031-980-2900http://www.gimpo.go.kr월-금 9:00~18:00매주 화,수,목요일 18:00 ~ 21:00<NA>37.614883126.715695
3하남시종합민원과경기도 하남시 대청로 10경기도 하남시 신장동 520번지12951031-790-5353031-790-6139http://www.hanam.go.kr월-금 9:00~18:00-<NA>37.539033127.214548
4오산시민원토지과경기도 오산시 성호대로 141경기도 오산시 오산동 915번지18132031-8036-7282, 7288~7290031-8036-8956http://www.osan.go.kr월-금 9:00~18:00-<NA>37.149035127.077658
5부천시(오정동)여권민원실경기도 부천시 성오로 172경기도 부천시 오정동 129번지 오정동행정복지센터 4층14434032-625-9700~4-http://www.bucheon.go.kr/site/mail/index130월-금 9:00~18:00-<NA>37.528347126.796028
6광명시민원토지과경기도 광명시 시청로 20경기도 광명시 철산동 222-1번지1423402-2680-618902-2680-6189http://www.gm.go.kr월-금 9:00~18:00매주 수요일 18:00 ~ 21:00<NA>37.478917126.864375
7화성시민원봉사과경기도 화성시 남양읍 시청로 159경기도 화성시 남양읍 남양리 2000번지18274031-369-3329,3535031-369-6311http://www.hscity.go.kr월-금 9:00~18:00매주 목요일 18:00 ~ 20:30<NA>37.199908126.830562
8과천시열린민원과경기도 과천시 관문로 69경기도 과천시 중앙동 1-3번지1380602-3677-2137, 214002-2150-1561http://www.gccity.go.kr월-금 9:00~18:00매주 목요일 18:00 ~ 21:00<NA>37.429513126.986659
9의정부시시민봉사과경기도 의정부시 시민로 1경기도 의정부시 의정부동 326-2번지11622031-828-2491031-828-2462http://www.ui4u.go.kr월-금 9:00~18:00매주 화, 목요일 18:00 ~ 21:00<NA>37.738489127.033143
시군명기관명도로명주소지번주소우편번호전화번호팩스번호홈페이지주소업무시간연장근무시간참고사항WGS84위도WGS84경도
26이천시민원봉사과경기도 이천시 부악로 40경기도 이천시 중리동 490번지17379031-644-2124031-631-2401,2458http://www.icheon.go.kr월-금 9:00~18:00매주 평일 18:00 ~ 20:00(11월~2월) 18:00 ~ 21:00(3월~10월)<NA>37.272487127.433734
27양평군고객지원과경기도 양평군 양평읍 군청앞길 2경기도 양평군 양평읍 양근리 448-8번지12554031-770-2042031-770-2802http://www.yp21.go.kr월-금 9:00~18:00매주 목요일 18:00 ~ 19:00<NA>37.491902127.487172
28가평군민원지적과경기도 가평군 가평읍 석봉로 181경기도 가평군 가평읍 읍내리 513번지12417031-580-2132031-580-2090http://www.gp.go.kr월-금 9:00~18:00매주 목요일 18:00 ~ 21:00<NA>37.831294127.509716
29고양시(일산 동구)여권팀<NA>경기도 고양시 일산서구 일산동 구) 경기 고양시 일산동구 중앙로 1256<NA>031-8075-2466031-8075-9896http://www.goyang.go.kr월-금 9:00~18:00매주 평일 18:00 ~ 20:00<NA><NA><NA>
30구리시민원봉사과경기도 구리시 아차산로 439경기도 구리시 교문동 390-1번지11954031-550-2308031-557-8282http://www.guri.go.kr월-금 9:00~18:00매주 화요일 18:00 ~ 21:00<NA>37.594454127.129095
31동두천시민원봉사과경기도 동두천시 방죽로 23경기도 동두천시 생연동 438번지11317031-860-2687031-860-2669http://www.ddc.go.kr월-금 9:00~18:00매주 목요일 18:00 ~ 20:00<NA>37.90342127.061542
32양주시민원봉사과경기도 양주시 부흥로 1533경기도 양주시 남방동 1-1번지11498031-8082-5318031-8082-5329http://www.yangju.go.kr월-금 9:00~18:00매주 목요일 18:00 ~ 20:00<NA>37.785536127.046669
33연천군고객지원과경기도 연천군 연천읍 연천로 220경기도 연천군 연천읍 차탄리 290-1번지11017031-839-2159031-839-2473http://www.yeoncheon.go.kr월-금 9:00~18:00-<NA>38.096517127.075228
34파주시민원봉사과경기도 파주시 시청로 50경기도 파주시 아동동 215-1번지10932031-940-5801031-940-5809http://www.paju.go.kr월-금 9:00~18:00매주 수요일 18:00 ~ 21:00<NA>37.759278126.779882
35포천시민원과경기도 포천시 중앙로 87경기도 포천시 신읍동 58-2번지11147031-538-3138031-538-2748http://www.pocheon.go.kr월-금 9:00~18:00매주 목요일 18:00 ~ 20:00<NA>37.894698127.200339