Overview

Dataset statistics

Number of variables26
Number of observations100
Missing cells279
Missing cells (%)10.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.5 KiB
Average record size in memory220.3 B

Variable types

Text9
Categorical7
Numeric8
Unsupported2

Alerts

lclas_nm has constant value ""Constant
updt_dt has constant value ""Constant
regist_dt has constant value ""Constant
legaldong_cd has 100 (100.0%) missing valuesMissing
buld_nm has 54 (54.0%) missing valuesMissing
tel_no has 8 (8.0%) missing valuesMissing
hmpg_url has 100 (100.0%) missing valuesMissing
adit_dc has 17 (17.0%) missing valuesMissing
esntl_id has unique valuesUnique
legaldong_cd is an unsupported type, check if it needs cleaning or further analysisUnsupported
hmpg_url is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 10:20:20.885022
Analysis finished2023-12-10 10:20:21.871335
Duration0.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

esntl_id
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:20:22.137021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters1900
Distinct characters16
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

Unique100 ?
Unique (%)100.0%

Sample

1st rowKCOCFPO20N000000595
2nd rowKCOCFPO20N000002724
3rd rowKCOCFPO20N000000597
4th rowKCOCFPO20N000000598
5th rowKCOCFPO20N000000599
ValueCountFrequency (%)
kcocfpo20n000000595 1
 
1.0%
kcocfpo20n000000657 1
 
1.0%
kcocfpo20n000000668 1
 
1.0%
kcocfpo20n000000667 1
 
1.0%
kcocfpo20n000000666 1
 
1.0%
kcocfpo20n000000665 1
 
1.0%
kcocfpo20n000000664 1
 
1.0%
kcocfpo20n000000663 1
 
1.0%
kcocfpo20n000000662 1
 
1.0%
kcocfpo20n000000661 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T19:20:22.762609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 716
37.7%
C 200
 
10.5%
O 200
 
10.5%
2 124
 
6.5%
6 112
 
5.9%
K 100
 
5.3%
F 100
 
5.3%
P 100
 
5.3%
N 100
 
5.3%
5 25
 
1.3%
Other values (6) 123
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1100
57.9%
Uppercase Letter 800
42.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 716
65.1%
2 124
 
11.3%
6 112
 
10.2%
5 25
 
2.3%
7 23
 
2.1%
4 21
 
1.9%
8 20
 
1.8%
1 20
 
1.8%
3 20
 
1.8%
9 19
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
C 200
25.0%
O 200
25.0%
K 100
12.5%
F 100
12.5%
P 100
12.5%
N 100
12.5%

Most occurring scripts

ValueCountFrequency (%)
Common 1100
57.9%
Latin 800
42.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 716
65.1%
2 124
 
11.3%
6 112
 
10.2%
5 25
 
2.3%
7 23
 
2.1%
4 21
 
1.9%
8 20
 
1.8%
1 20
 
1.8%
3 20
 
1.8%
9 19
 
1.7%
Latin
ValueCountFrequency (%)
C 200
25.0%
O 200
25.0%
K 100
12.5%
F 100
12.5%
P 100
12.5%
N 100
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 716
37.7%
C 200
 
10.5%
O 200
 
10.5%
2 124
 
6.5%
6 112
 
5.9%
K 100
 
5.3%
F 100
 
5.3%
P 100
 
5.3%
N 100
 
5.3%
5 25
 
1.3%
Other values (6) 123
 
6.5%

lclas_nm
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
문화시설
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
문화시설 100
100.0%

Length

2023-12-10T19:20:23.013566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:20:23.168077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문화시설 100
100.0%

mlsfc_nm
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
문화시설_사우나_할인_시니어
83 
문화시설_카페_시니어
17 

Length

Max length15
Median length15
Mean length14.32
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
문화시설_사우나_할인_시니어 83
83.0%
문화시설_카페_시니어 17
 
17.0%

Length

2023-12-10T19:20:23.345342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:20:23.554825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문화시설_사우나_할인_시니어 83
83.0%
문화시설_카페_시니어 17
 
17.0%

fclty_nm
Text

Distinct86
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:20:23.935656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length7.19
Min length3

Characters and Unicode

Total characters719
Distinct characters180
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

Unique75 ?
Unique (%)75.0%

Sample

1st row대송탕
2nd row그랜드사우나
3rd row세왕탕
4th row수어탕
5th row스파탕
ValueCountFrequency (%)
노노카페 4
 
3.3%
월드사우나 3
 
2.5%
강동시니어클럽 3
 
2.5%
상담카페 3
 
2.5%
그랜드사우나 3
 
2.5%
수어탕 2
 
1.6%
실버커피토마토 2
 
1.6%
화성시니어클럽 2
 
1.6%
문화목욕탕 2
 
1.6%
스파탕 2
 
1.6%
Other values (89) 96
78.7%
2023-12-10T19:20:24.603287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
우 42
 
5.8%
사 39
 
5.4%
나 37
 
5.1%
탕 33
 
4.6%
22
 
3.1%
스 20
 
2.8%
욕 17
 
2.4%
목 17
 
2.4%
어 16
 
2.2%
시 14
 
1.9%
Other values (170) 462
64.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 680
94.6%
Space Separator 22
 
3.1%
Decimal Number 7
 
1.0%
Uppercase Letter 6
 
0.8%
Other Punctuation 1
 
0.1%
Other Symbol 1
 
0.1%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
우 42
 
6.2%
사 39
 
5.7%
나 37
 
5.4%
탕 33
 
4.9%
스 20
 
2.9%
욕 17
 
2.5%
목 17
 
2.5%
어 16
 
2.4%
시 14
 
2.1%
수 13
 
1.9%
Other values (159) 432
63.5%
Decimal Number
ValueCountFrequency (%)
4 3
42.9%
2 3
42.9%
1 1
 
14.3%
Uppercase Letter
ValueCountFrequency (%)
E 2
33.3%
R 2
33.3%
X 2
33.3%
Space Separator
ValueCountFrequency (%)
22
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 681
94.7%
Common 32
 
4.5%
Latin 6
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
우 42
 
6.2%
사 39
 
5.7%
나 37
 
5.4%
탕 33
 
4.8%
스 20
 
2.9%
욕 17
 
2.5%
목 17
 
2.5%
어 16
 
2.3%
시 14
 
2.1%
수 13
 
1.9%
Other values (160) 433
63.6%
Common
ValueCountFrequency (%)
22
68.8%
4 3
 
9.4%
2 3
 
9.4%
1 1
 
3.1%
& 1
 
3.1%
) 1
 
3.1%
( 1
 
3.1%
Latin
ValueCountFrequency (%)
E 2
33.3%
R 2
33.3%
X 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 680
94.6%
ASCII 38
 
5.3%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
우 42
 
6.2%
사 39
 
5.7%
나 37
 
5.4%
탕 33
 
4.9%
스 20
 
2.9%
욕 17
 
2.5%
목 17
 
2.5%
어 16
 
2.4%
시 14
 
2.1%
수 13
 
1.9%
Other values (159) 432
63.5%
ASCII
ValueCountFrequency (%)
22
57.9%
4 3
 
7.9%
2 3
 
7.9%
E 2
 
5.3%
R 2
 
5.3%
X 2
 
5.3%
1 1
 
2.6%
& 1
 
2.6%
) 1
 
2.6%
( 1
 
2.6%
None
ValueCountFrequency (%)
㈜ 1
100.0%

ctprvn_cd
Real number (ℝ)

Distinct10
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.46
Minimum11
Maximum48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:20:24.853362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile11
Q128
median31
Q341
95-th percentile48
Maximum48
Range37
Interquartile range (IQR)13

Descriptive statistics

Standard deviation12.002037
Coefficient of variation (CV)0.36974852
Kurtosis-0.63429858
Mean32.46
Median Absolute Deviation (MAD)10
Skewness-0.6583186
Sum3246
Variance144.04889
MonotonicityNot monotonic
2023-12-10T19:20:25.029699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
41 30
30.0%
11 18
18.0%
31 15
15.0%
30 13
13.0%
48 12
 
12.0%
26 5
 
5.0%
28 2
 
2.0%
42 2
 
2.0%
45 2
 
2.0%
27 1
 
1.0%
ValueCountFrequency (%)
11 18
18.0%
26 5
 
5.0%
27 1
 
1.0%
28 2
 
2.0%
30 13
13.0%
31 15
15.0%
41 30
30.0%
42 2
 
2.0%
45 2
 
2.0%
48 12
 
12.0%
ValueCountFrequency (%)
48 12
 
12.0%
45 2
 
2.0%
42 2
 
2.0%
41 30
30.0%
31 15
15.0%
30 13
13.0%
28 2
 
2.0%
27 1
 
1.0%
26 5
 
5.0%
11 18
18.0%

ctprvn_nm
Categorical

Distinct10
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
경기도
30 
서울특별시
18 
울산광역시
15 
대전광역시
13 
경상남도
12 
Other values (5)
12 

Length

Max length5
Median length5
Mean length4.22
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row울산광역시
2nd row대전광역시
3rd row울산광역시
4th row울산광역시
5th row울산광역시

Common Values

ValueCountFrequency (%)
경기도 30
30.0%
서울특별시 18
18.0%
울산광역시 15
15.0%
대전광역시 13
13.0%
경상남도 12
 
12.0%
부산광역시 5
 
5.0%
인천광역시 2
 
2.0%
강원도 2
 
2.0%
전라북도 2
 
2.0%
대구광역시 1
 
1.0%

Length

2023-12-10T19:20:25.262732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:20:25.476930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 30
30.0%
서울특별시 18
18.0%
울산광역시 15
15.0%
대전광역시 13
13.0%
경상남도 12
 
12.0%
부산광역시 5
 
5.0%
인천광역시 2
 
2.0%
강원도 2
 
2.0%
전라북도 2
 
2.0%
대구광역시 1
 
1.0%

signgu_cd
Real number (ℝ)

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32721.13
Minimum11200
Maximum48250
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:20:25.693749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11200
5-th percentile11215
Q128200
median31170
Q341117
95-th percentile48250
Maximum48250
Range37050
Interquartile range (IQR)12917

Descriptive statistics

Standard deviation11970.096
Coefficient of variation (CV)0.36582161
Kurtosis-0.64062062
Mean32721.13
Median Absolute Deviation (MAD)9943
Skewness-0.6486554
Sum3272113
Variance1.4328321 × 108
MonotonicityNot monotonic
2023-12-10T19:20:25.906093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
31170 14
14.0%
30230 13
13.0%
48250 12
12.0%
41113 9
9.0%
11215 8
 
8.0%
41111 6
 
6.0%
41590 6
 
6.0%
41117 5
 
5.0%
11200 4
 
4.0%
11560 3
 
3.0%
Other values (12) 20
20.0%
ValueCountFrequency (%)
11200 4
4.0%
11215 8
8.0%
11560 3
 
3.0%
11740 3
 
3.0%
26170 1
 
1.0%
26350 1
 
1.0%
26470 2
 
2.0%
26530 1
 
1.0%
27260 1
 
1.0%
28200 2
 
2.0%
ValueCountFrequency (%)
48250 12
12.0%
45770 2
 
2.0%
42210 2
 
2.0%
41590 6
6.0%
41360 1
 
1.0%
41117 5
5.0%
41115 3
 
3.0%
41113 9
9.0%
41111 6
6.0%
31200 1
 
1.0%

signgu_nm
Categorical

Distinct21
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
동구
15 
대덕구
13 
김해시
12 
수원시 권선구
9 
광진구
8 
Other values (16)
43 

Length

Max length7
Median length3
Mean length3.81
Min length2

Unique

Unique5 ?
Unique (%)5.0%

Sample

1st row동구
2nd row대덕구
3rd row동구
4th row동구
5th row동구

Common Values

ValueCountFrequency (%)
동구 15
15.0%
대덕구 13
13.0%
김해시 12
12.0%
수원시 권선구 9
9.0%
광진구 8
8.0%
수원시 장안구 6
 
6.0%
화성시 6
 
6.0%
수원시 영통구 5
 
5.0%
성동구 4
 
4.0%
강동구 3
 
3.0%
Other values (11) 19
19.0%

Length

2023-12-10T19:20:26.165938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 23
18.7%
동구 15
12.2%
대덕구 13
10.6%
김해시 12
9.8%
권선구 9
 
7.3%
광진구 8
 
6.5%
장안구 6
 
4.9%
화성시 6
 
4.9%
영통구 5
 
4.1%
성동구 4
 
3.3%
Other values (12) 22
17.9%

legaldong_cd
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

legaldong_nm
Text

Distinct65
Distinct (%)65.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:20:26.556443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.4
Min length2

Characters and Unicode

Total characters340
Distinct characters84
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)43.0%

Sample

1st row화정동
2nd row송촌동
3rd row동부동
4th row화정동
5th row동부동
ValueCountFrequency (%)
동부동 5
 
4.6%
자양동 4
 
3.7%
송촌동 4
 
3.7%
화정동 4
 
3.7%
일산동 4
 
3.7%
상일동 3
 
2.8%
권선동 3
 
2.8%
삼계동 2
 
1.8%
봉담읍 2
 
1.8%
순창읍 2
 
1.8%
Other values (61) 76
69.7%
2023-12-10T19:20:27.239433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 98
28.8%
리 11
 
3.2%
양 9
 
2.6%
송 9
 
2.6%
화 9
 
2.6%
9
 
2.6%
읍 8
 
2.4%
영 8
 
2.4%
일 7
 
2.1%
정 7
 
2.1%
Other values (74) 165
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 327
96.2%
Space Separator 9
 
2.6%
Decimal Number 4
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 98
30.0%
리 11
 
3.4%
양 9
 
2.8%
송 9
 
2.8%
화 9
 
2.8%
읍 8
 
2.4%
영 8
 
2.4%
일 7
 
2.1%
정 7
 
2.1%
진 6
 
1.8%
Other values (70) 155
47.4%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
3 1
25.0%
4 1
25.0%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 327
96.2%
Common 13
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 98
30.0%
리 11
 
3.4%
양 9
 
2.8%
송 9
 
2.8%
화 9
 
2.8%
읍 8
 
2.4%
영 8
 
2.4%
일 7
 
2.1%
정 7
 
2.1%
진 6
 
1.8%
Other values (70) 155
47.4%
Common
ValueCountFrequency (%)
9
69.2%
1 2
 
15.4%
3 1
 
7.7%
4 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 327
96.2%
ASCII 13
 
3.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 98
30.0%
리 11
 
3.4%
양 9
 
2.8%
송 9
 
2.8%
화 9
 
2.8%
읍 8
 
2.4%
영 8
 
2.4%
일 7
 
2.1%
정 7
 
2.1%
진 6
 
1.8%
Other values (70) 155
47.4%
ASCII
ValueCountFrequency (%)
9
69.2%
1 2
 
15.4%
3 1
 
7.7%
4 1
 
7.7%

road_nm_cd
Real number (ℝ)

Distinct82
Distinct (%)82.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2721491 × 1011
Minimum1.1200301 × 1011
Maximum4.8250481 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:20:27.519326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1200301 × 1011
5-th percentile1.121531 × 1011
Q12.8200395 × 1011
median3.1170431 × 1011
Q34.1117318 × 1011
95-th percentile4.8250481 × 1011
Maximum4.8250481 × 1011
Range3.705018 × 1011
Interquartile range (IQR)1.2916923 × 1011

Descriptive statistics

Standard deviation1.1970111 × 1011
Coefficient of variation (CV)0.36581801
Kurtosis-0.64061912
Mean3.2721491 × 1011
Median Absolute Deviation (MAD)9.9430015 × 1010
Skewness-0.64865322
Sum3.2721491 × 1013
Variance1.4328355 × 1022
MonotonicityNot monotonic
2023-12-10T19:20:27.806632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
117403000034 3
 
3.0%
112003005014 2
 
2.0%
482504805282 2
 
2.0%
411113174005 2
 
2.0%
302302010003 2
 
2.0%
112153104010 2
 
2.0%
302304304005 2
 
2.0%
112153103010 2
 
2.0%
411133175012 2
 
2.0%
311702011001 2
 
2.0%
Other values (72) 79
79.0%
ValueCountFrequency (%)
112003005011 1
1.0%
112003005014 2
2.0%
112004109323 1
1.0%
112153005028 1
1.0%
112153103010 2
2.0%
112153104010 2
2.0%
112154112108 1
1.0%
112154112359 1
1.0%
112154112469 1
1.0%
115603118008 1
1.0%
ValueCountFrequency (%)
482504805729 1
1.0%
482504805629 1
1.0%
482504805401 1
1.0%
482504805282 2
2.0%
482504805224 1
1.0%
482504805086 1
1.0%
482503335068 1
1.0%
482503335054 1
1.0%
482503335032 1
1.0%
482503335013 1
1.0%

fclty_road_nm_addr
Text

Distinct88
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:20:28.425580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length24
Mean length19.34
Min length14

Characters and Unicode

Total characters1934
Distinct characters153
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

Unique77 ?
Unique (%)77.0%

Sample

1st row울산광역시 동구 대송2길 21
2nd row대전광역시 대덕구 동서대로 1755
3rd row울산광역시 동구 옥류로 68-1
4th row울산광역시 동구 대송1길 50
5th row울산광역시 동구 남목18길 8
ValueCountFrequency (%)
경기도 30
 
6.9%
수원시 23
 
5.3%
서울특별시 18
 
4.1%
울산광역시 15
 
3.4%
동구 15
 
3.4%
대전광역시 13
 
3.0%
대덕구 13
 
3.0%
경상남도 12
 
2.7%
김해시 12
 
2.7%
권선구 9
 
2.1%
Other values (185) 277
63.4%
2023-12-10T19:20:29.258604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
337
 
17.4%
시 101
 
5.2%
로 87
 
4.5%
구 78
 
4.0%
1 63
 
3.3%
2 50
 
2.6%
대 50
 
2.6%
도 48
 
2.5%
경 44
 
2.3%
동 44
 
2.3%
Other values (143) 1032
53.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1235
63.9%
Decimal Number 341
 
17.6%
Space Separator 337
 
17.4%
Dash Punctuation 12
 
0.6%
Close Punctuation 4
 
0.2%
Open Punctuation 4
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 101
 
8.2%
로 87
 
7.0%
구 78
 
6.3%
대 50
 
4.0%
도 48
 
3.9%
경 44
 
3.6%
동 44
 
3.6%
길 44
 
3.6%
광 44
 
3.6%
역 36
 
2.9%
Other values (128) 659
53.4%
Decimal Number
ValueCountFrequency (%)
1 63
18.5%
2 50
14.7%
3 40
11.7%
5 40
11.7%
8 33
9.7%
4 28
8.2%
6 25
 
7.3%
7 22
 
6.5%
9 20
 
5.9%
0 20
 
5.9%
Space Separator
ValueCountFrequency (%)
337
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1235
63.9%
Common 699
36.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 101
 
8.2%
로 87
 
7.0%
구 78
 
6.3%
대 50
 
4.0%
도 48
 
3.9%
경 44
 
3.6%
동 44
 
3.6%
길 44
 
3.6%
광 44
 
3.6%
역 36
 
2.9%
Other values (128) 659
53.4%
Common
ValueCountFrequency (%)
337
48.2%
1 63
 
9.0%
2 50
 
7.2%
3 40
 
5.7%
5 40
 
5.7%
8 33
 
4.7%
4 28
 
4.0%
6 25
 
3.6%
7 22
 
3.1%
9 20
 
2.9%
Other values (5) 41
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1235
63.9%
ASCII 699
36.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
337
48.2%
1 63
 
9.0%
2 50
 
7.2%
3 40
 
5.7%
5 40
 
5.7%
8 33
 
4.7%
4 28
 
4.0%
6 25
 
3.6%
7 22
 
3.1%
9 20
 
2.9%
Other values (5) 41
 
5.9%
Hangul
ValueCountFrequency (%)
시 101
 
8.2%
로 87
 
7.0%
구 78
 
6.3%
대 50
 
4.0%
도 48
 
3.9%
경 44
 
3.6%
동 44
 
3.6%
길 44
 
3.6%
광 44
 
3.6%
역 36
 
2.9%
Other values (128) 659
53.4%

lnm_addr
Text

Distinct88
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:20:29.914423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length20
Mean length17.38
Min length13

Characters and Unicode

Total characters1738
Distinct characters123
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)77.0%

Sample

1st row울산 동구 화정동 160-10
2nd row대전 대덕구 송촌동 295-10
3rd row울산 동구 동부동 395
4th row울산 동구 화정동 844-3
5th row울산 동구 동부동 303-3
ValueCountFrequency (%)
경기 30
 
6.9%
수원시 23
 
5.3%
서울 18
 
4.1%
울산 15
 
3.5%
동구 15
 
3.5%
대덕구 13
 
3.0%
대전 13
 
3.0%
경남 12
 
2.8%
김해시 12
 
2.8%
권선구 9
 
2.1%
Other values (184) 274
63.1%
2023-12-10T19:20:30.749395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
334
19.2%
동 122
 
7.0%
1 95
 
5.5%
구 79
 
4.5%
- 78
 
4.5%
4 50
 
2.9%
시 46
 
2.6%
5 46
 
2.6%
경 42
 
2.4%
2 41
 
2.4%
Other values (113) 805
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 902
51.9%
Decimal Number 422
24.3%
Space Separator 334
 
19.2%
Dash Punctuation 78
 
4.5%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 122
 
13.5%
구 79
 
8.8%
시 46
 
5.1%
경 42
 
4.7%
울 33
 
3.7%
대 30
 
3.3%
기 30
 
3.3%
수 28
 
3.1%
원 28
 
3.1%
산 25
 
2.8%
Other values (99) 439
48.7%
Decimal Number
ValueCountFrequency (%)
1 95
22.5%
4 50
11.8%
5 46
10.9%
2 41
9.7%
3 36
 
8.5%
0 36
 
8.5%
7 32
 
7.6%
6 30
 
7.1%
8 29
 
6.9%
9 27
 
6.4%
Space Separator
ValueCountFrequency (%)
334
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 78
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 902
51.9%
Common 836
48.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 122
 
13.5%
구 79
 
8.8%
시 46
 
5.1%
경 42
 
4.7%
울 33
 
3.7%
대 30
 
3.3%
기 30
 
3.3%
수 28
 
3.1%
원 28
 
3.1%
산 25
 
2.8%
Other values (99) 439
48.7%
Common
ValueCountFrequency (%)
334
40.0%
1 95
 
11.4%
- 78
 
9.3%
4 50
 
6.0%
5 46
 
5.5%
2 41
 
4.9%
3 36
 
4.3%
0 36
 
4.3%
7 32
 
3.8%
6 30
 
3.6%
Other values (4) 58
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 902
51.9%
ASCII 836
48.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
334
40.0%
1 95
 
11.4%
- 78
 
9.3%
4 50
 
6.0%
5 46
 
5.5%
2 41
 
4.9%
3 36
 
4.3%
0 36
 
4.3%
7 32
 
3.8%
6 30
 
3.6%
Other values (4) 58
 
6.9%
Hangul
ValueCountFrequency (%)
동 122
 
13.5%
구 79
 
8.8%
시 46
 
5.1%
경 42
 
4.7%
울 33
 
3.7%
대 30
 
3.3%
기 30
 
3.3%
수 28
 
3.1%
원 28
 
3.1%
산 25
 
2.8%
Other values (99) 439
48.7%

addr_eng_nm
Text

Distinct88
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:20:31.175073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length55
Mean length45.74
Min length29

Characters and Unicode

Total characters4574
Distinct characters50
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)77.0%

Sample

1st row21, Daesong 2-gil, Dong-gu, Ulsan
2nd row1755, Dongseo-daero, Daedeok-gu, Daejeon
3rd row68-1, Ongnyu-ro, Dong-gu, Ulsan
4th row50, Daesong 1-gil, Dong-gu, Ulsan
5th row8, Nammok 18-gil, Dong-gu, Ulsan
ValueCountFrequency (%)
gyeonggi-do 30
 
6.3%
suwon-si 23
 
4.8%
seoul 18
 
3.8%
dong-gu 15
 
3.1%
ulsan 15
 
3.1%
daedeok-gu 13
 
2.7%
daejeon 13
 
2.7%
gyeongsangnam-do 12
 
2.5%
gimhae-si 12
 
2.5%
gwonseon-gu 9
 
1.9%
Other values (212) 317
66.5%
2023-12-10T19:20:31.864164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 443
 
9.7%
n 399
 
8.7%
377
 
8.2%
g 371
 
8.1%
, 332
 
7.3%
- 321
 
7.0%
e 286
 
6.3%
a 237
 
5.2%
u 184
 
4.0%
i 160
 
3.5%
Other values (40) 1464
32.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2870
62.7%
Space Separator 377
 
8.2%
Decimal Number 341
 
7.5%
Uppercase Letter 333
 
7.3%
Other Punctuation 332
 
7.3%
Dash Punctuation 321
 
7.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 443
15.4%
n 399
13.9%
g 371
12.9%
e 286
10.0%
a 237
8.3%
u 184
 
6.4%
i 160
 
5.6%
s 118
 
4.1%
d 108
 
3.8%
l 99
 
3.4%
Other values (11) 465
16.2%
Uppercase Letter
ValueCountFrequency (%)
G 88
26.4%
S 70
21.0%
D 66
19.8%
J 26
 
7.8%
U 16
 
4.8%
B 15
 
4.5%
Y 13
 
3.9%
H 13
 
3.9%
N 9
 
2.7%
O 3
 
0.9%
Other values (6) 14
 
4.2%
Decimal Number
ValueCountFrequency (%)
1 63
18.5%
2 50
14.7%
5 40
11.7%
3 40
11.7%
8 33
9.7%
4 28
8.2%
6 25
 
7.3%
7 22
 
6.5%
9 20
 
5.9%
0 20
 
5.9%
Space Separator
ValueCountFrequency (%)
377
100.0%
Other Punctuation
ValueCountFrequency (%)
, 332
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 321
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3203
70.0%
Common 1371
30.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 443
13.8%
n 399
12.5%
g 371
11.6%
e 286
 
8.9%
a 237
 
7.4%
u 184
 
5.7%
i 160
 
5.0%
s 118
 
3.7%
d 108
 
3.4%
l 99
 
3.1%
Other values (27) 798
24.9%
Common
ValueCountFrequency (%)
377
27.5%
, 332
24.2%
- 321
23.4%
1 63
 
4.6%
2 50
 
3.6%
5 40
 
2.9%
3 40
 
2.9%
8 33
 
2.4%
4 28
 
2.0%
6 25
 
1.8%
Other values (3) 62
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4574
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 443
 
9.7%
n 399
 
8.7%
377
 
8.2%
g 371
 
8.1%
, 332
 
7.3%
- 321
 
7.0%
e 286
 
6.3%
a 237
 
5.2%
u 184
 
4.0%
i 160
 
3.5%
Other values (40) 1464
32.0%

adstrd_cd
Real number (ℝ)

Distinct65
Distinct (%)65.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2721258 × 109
Minimum1.1200112 × 109
Maximum4.825033 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:20:32.116068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1200112 × 109
5-th percentile1.1215101 × 109
Q12.8200102 × 109
median3.1170107 × 109
Q34.1117105 × 109
95-th percentile4.8250128 × 109
Maximum4.825033 × 109
Range3.7050218 × 109
Interquartile range (IQR)1.2917003 × 109

Descriptive statistics

Standard deviation1.1970114 × 109
Coefficient of variation (CV)0.36582073
Kurtosis-0.64062483
Mean3.2721258 × 109
Median Absolute Deviation (MAD)9.94303 × 108
Skewness-0.64865268
Sum3.2721258 × 1011
Variance1.4328364 × 1018
MonotonicityNot monotonic
2023-12-10T19:20:32.393102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3117010700 5
 
5.0%
3117010200 4
 
4.0%
1121510500 4
 
4.0%
3117010300 4
 
4.0%
3023010700 4
 
4.0%
1174010300 3
 
3.0%
4111313700 3
 
3.0%
4111313300 2
 
2.0%
4111113500 2
 
2.0%
4111312600 2
 
2.0%
Other values (55) 67
67.0%
ValueCountFrequency (%)
1120011200 1
 
1.0%
1120011300 1
 
1.0%
1120011400 2
2.0%
1121510100 2
2.0%
1121510300 1
 
1.0%
1121510400 1
 
1.0%
1121510500 4
4.0%
1156012100 1
 
1.0%
1156013200 1
 
1.0%
1156013300 1
 
1.0%
ValueCountFrequency (%)
4825033023 1
1.0%
4825025026 1
1.0%
4825013100 1
1.0%
4825013000 1
1.0%
4825012800 2
2.0%
4825012700 1
1.0%
4825011800 1
1.0%
4825010800 1
1.0%
4825010700 2
2.0%
4825010300 1
1.0%

buld_nm
Text

MISSING 

Distinct44
Distinct (%)95.7%
Missing54
Missing (%)54.0%
Memory size932.0 B
2023-12-10T19:20:32.804015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length6.3478261
Min length4

Characters and Unicode

Total characters292
Distinct characters143
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)91.3%

Sample

1st row남목시티프라자
2nd row성호아파트
3rd row영등포 SK 리더스뷰
4th row성수 그린빌
5th row노벨빌딩
ValueCountFrequency (%)
남목시티프라자 2
 
3.6%
sk 2
 
3.6%
홈플러스 2
 
3.6%
회덕농업협동조합 1
 
1.8%
봉담도서관 1
 
1.8%
골든리버 1
 
1.8%
삼성래미안아파트 1
 
1.8%
미영아파트 1
 
1.8%
강남커피숍 1
 
1.8%
수정아파트 1
 
1.8%
Other values (42) 42
76.4%
2023-12-10T19:20:33.494772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 12
 
4.1%
파 11
 
3.8%
트 11
 
3.8%
9
 
3.1%
아 9
 
3.1%
빌 8
 
2.7%
프 7
 
2.4%
라 7
 
2.4%
딩 6
 
2.1%
자 6
 
2.1%
Other values (133) 206
70.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 257
88.0%
Uppercase Letter 24
 
8.2%
Space Separator 9
 
3.1%
Close Punctuation 1
 
0.3%
Open Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 12
 
4.7%
파 11
 
4.3%
트 11
 
4.3%
아 9
 
3.5%
빌 8
 
3.1%
프 7
 
2.7%
라 7
 
2.7%
딩 6
 
2.3%
자 6
 
2.3%
성 6
 
2.3%
Other values (115) 174
67.7%
Uppercase Letter
ValueCountFrequency (%)
L 3
12.5%
E 2
 
8.3%
W 2
 
8.3%
A 2
 
8.3%
B 2
 
8.3%
S 2
 
8.3%
K 2
 
8.3%
U 2
 
8.3%
H 1
 
4.2%
N 1
 
4.2%
Other values (5) 5
20.8%
Space Separator
ValueCountFrequency (%)
9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 257
88.0%
Latin 24
 
8.2%
Common 11
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 12
 
4.7%
파 11
 
4.3%
트 11
 
4.3%
아 9
 
3.5%
빌 8
 
3.1%
프 7
 
2.7%
라 7
 
2.7%
딩 6
 
2.3%
자 6
 
2.3%
성 6
 
2.3%
Other values (115) 174
67.7%
Latin
ValueCountFrequency (%)
L 3
12.5%
E 2
 
8.3%
W 2
 
8.3%
A 2
 
8.3%
B 2
 
8.3%
S 2
 
8.3%
K 2
 
8.3%
U 2
 
8.3%
H 1
 
4.2%
N 1
 
4.2%
Other values (5) 5
20.8%
Common
ValueCountFrequency (%)
9
81.8%
) 1
 
9.1%
( 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 257
88.0%
ASCII 35
 
12.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 12
 
4.7%
파 11
 
4.3%
트 11
 
4.3%
아 9
 
3.5%
빌 8
 
3.1%
프 7
 
2.7%
라 7
 
2.7%
딩 6
 
2.3%
자 6
 
2.3%
성 6
 
2.3%
Other values (115) 174
67.7%
ASCII
ValueCountFrequency (%)
9
25.7%
L 3
 
8.6%
E 2
 
5.7%
W 2
 
5.7%
A 2
 
5.7%
B 2
 
5.7%
S 2
 
5.7%
K 2
 
5.7%
U 2
 
5.7%
H 1
 
2.9%
Other values (8) 8
22.9%

buld_manage_cd
Real number (ℝ)

Distinct88
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2721262 × 1024
Minimum1.1200112 × 1024
Maximum4.825033 × 1024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:20:33.764391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1200112 × 1024
5-th percentile1.1215101 × 1024
Q12.8200102 × 1024
median3.1170107 × 1024
Q34.1117105 × 1024
95-th percentile4.8250137 × 1024
Maximum4.825033 × 1024
Range3.7050218 × 1024
Interquartile range (IQR)1.2917003 × 1024

Descriptive statistics

Standard deviation1.197012 × 1024
Coefficient of variation (CV)0.36582087
Kurtosis-0.6406248
Mean3.2721262 × 1024
Median Absolute Deviation (MAD)9.94303 × 1023
Skewness-0.64865055
Sum3.2721262 × 1026
Variance1.4328378 × 1048
MonotonicityNot monotonic
2023-12-10T19:20:34.088880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.17401030010148e+24 3
 
3.0%
3.1170102001016e+24 2
 
2.0%
3.11701070010395e+24 2
 
2.0%
3.11701020010844e+24 2
 
2.0%
3.11701070010306e+24 2
 
2.0%
3.02301090010248e+24 2
 
2.0%
4.82503102610562e+24 2
 
2.0%
3.023011100102e+24 2
 
2.0%
3.11701030010464e+24 2
 
2.0%
3.11701030010577e+24 2
 
2.0%
Other values (78) 79
79.0%
ValueCountFrequency (%)
1.120011200108e+24 1
1.0%
1.12001130010559e+24 1
1.0%
1.12001140010659e+24 1
1.0%
1.12001140010685e+24 1
1.0%
1.12151010010074e+24 1
1.0%
1.12151010010169e+24 1
1.0%
1.12151030010252e+24 1
1.0%
1.12151040010114e+24 1
1.0%
1.1215105001052e+24 1
1.0%
1.1215105001055304e+24 1
1.0%
ValueCountFrequency (%)
4.8250330231043e+24 1
1.0%
4.82503102810282e+24 1
1.0%
4.82503102610562e+24 2
2.0%
4.82502502611614e+24 1
1.0%
4.8250131001133503e+24 1
1.0%
4.8250127001141694e+24 1
1.0%
4.8250118001035696e+24 1
1.0%
4.82501080011128e+24 1
1.0%
4.82501070011501e+24 1
1.0%
4.8250107001146094e+24 1
1.0%

tel_no
Text

MISSING 

Distinct80
Distinct (%)87.0%
Missing8
Missing (%)8.0%
Memory size932.0 B
2023-12-10T19:20:34.523409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.891304
Min length9

Characters and Unicode

Total characters1094
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

Unique69 ?
Unique (%)75.0%

Sample

1st row052-232-0062
2nd row042-639-7735
3rd row052-251-0187
4th row052-251-0943
5th row052-252-5060
ValueCountFrequency (%)
070-4603-6102 3
 
3.3%
042-639-7735 2
 
2.2%
042-631-8735 2
 
2.2%
052-232-0062 2
 
2.2%
052-233-6100 2
 
2.2%
051-851-2190 2
 
2.2%
042-931-5822 2
 
2.2%
052-251-0943 2
 
2.2%
055-330-9000 2
 
2.2%
052-251-0187 2
 
2.2%
Other values (70) 71
77.2%
2023-12-10T19:20:35.235636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 189
17.3%
- 182
16.6%
2 149
13.6%
3 125
11.4%
5 102
9.3%
1 81
7.4%
6 75
 
6.9%
4 61
 
5.6%
7 49
 
4.5%
8 42
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 912
83.4%
Dash Punctuation 182
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 189
20.7%
2 149
16.3%
3 125
13.7%
5 102
11.2%
1 81
8.9%
6 75
 
8.2%
4 61
 
6.7%
7 49
 
5.4%
8 42
 
4.6%
9 39
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 182
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1094
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 189
17.3%
- 182
16.6%
2 149
13.6%
3 125
11.4%
5 102
9.3%
1 81
7.4%
6 75
 
6.9%
4 61
 
5.6%
7 49
 
4.5%
8 42
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1094
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 189
17.3%
- 182
16.6%
2 149
13.6%
3 125
11.4%
5 102
9.3%
1 81
7.4%
6 75
 
6.9%
4 61
 
5.6%
7 49
 
4.5%
8 42
 
3.8%

zip_no
Real number (ℝ)

Distinct86
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28035.12
Minimum4734
Maximum56045
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:20:35.522308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4734
5-th percentile4944.8
Q116381
median23156.5
Q344062.75
95-th percentile51002.15
Maximum56045
Range51311
Interquartile range (IQR)27681.75

Descriptive statistics

Standard deviation16698.77
Coefficient of variation (CV)0.59563754
Kurtosis-1.4860006
Mean28035.12
Median Absolute Deviation (MAD)16869
Skewness0.086564316
Sum2803512
Variance2.7884891 × 108
MonotonicityNot monotonic
2023-12-10T19:20:35.801068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5278 3
 
3.0%
44006 3
 
3.0%
44061 2
 
2.0%
44053 2
 
2.0%
44068 2
 
2.0%
34425 2
 
2.0%
34428 2
 
2.0%
51002 2
 
2.0%
34305 2
 
2.0%
18274 2
 
2.0%
Other values (76) 78
78.0%
ValueCountFrequency (%)
4734 1
1.0%
4738 1
1.0%
4768 1
1.0%
4778 1
1.0%
4903 1
1.0%
4947 1
1.0%
4969 1
1.0%
5025 1
1.0%
5043 1
1.0%
5068 1
1.0%
ValueCountFrequency (%)
56045 1
1.0%
56038 1
1.0%
51019 1
1.0%
51011 1
1.0%
51005 1
1.0%
51002 2
2.0%
50948 1
1.0%
50921 1
1.0%
50902 1
1.0%
50901 1
1.0%

hmpg_url
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

fclty_la
Real number (ℝ)

Distinct88
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.56256
Minimum35.12822
Maximum38.219298
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:20:36.006339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.12822
5-th percentile35.17886
Q135.500631
median37.200153
Q337.300144
95-th percentile37.553086
Maximum38.219298
Range3.0910774
Interquartile range (IQR)1.7995123

Descriptive statistics

Standard deviation0.95720666
Coefficient of variation (CV)0.026179968
Kurtosis-1.5558744
Mean36.56256
Median Absolute Deviation (MAD)0.61075715
Skewness-0.29229262
Sum3656.256
Variance0.91624459
MonotonicityNot monotonic
2023-12-10T19:20:36.635212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5527694 3
 
3.0%
35.5006315 2
 
2.0%
35.5447725 2
 
2.0%
35.4992123 2
 
2.0%
35.5427778 2
 
2.0%
36.3570464 2
 
2.0%
35.1878529 2
 
2.0%
36.4513432 2
 
2.0%
35.5036112 2
 
2.0%
35.4989729 2
 
2.0%
Other values (78) 79
79.0%
ValueCountFrequency (%)
35.1282201 1
1.0%
35.1640895 1
1.0%
35.1688849 1
1.0%
35.1721431 1
1.0%
35.1778844 1
1.0%
35.1789112 1
1.0%
35.1817421 1
1.0%
35.1878529 2
2.0%
35.189405 1
1.0%
35.2317621 1
1.0%
ValueCountFrequency (%)
38.2192975 1
 
1.0%
38.1862403 1
 
1.0%
37.6728575 1
 
1.0%
37.5691287 1
 
1.0%
37.55911 1
 
1.0%
37.5527694 3
3.0%
37.550723 1
 
1.0%
37.5479278 1
 
1.0%
37.546644 1
 
1.0%
37.54543 1
 
1.0%

fclty_lo
Real number (ℝ)

Distinct88
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.80085
Minimum126.69615
Maximum129.44683
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:20:36.880012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.69615
5-th percentile126.90434
Q1127.02437
median127.15667
Q3128.83823
95-th percentile129.42753
Maximum129.44683
Range2.7506829
Interquartile range (IQR)1.8138543

Descriptive statistics

Standard deviation0.98623942
Coefficient of variation (CV)0.0077170021
Kurtosis-1.3445969
Mean127.80085
Median Absolute Deviation (MAD)0.2698264
Skewness0.67038655
Sum12780.085
Variance0.97266819
MonotonicityNot monotonic
2023-12-10T19:20:37.118027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1566715 3
 
3.0%
129.4188315 2
 
2.0%
129.4261457 2
 
2.0%
129.4211249 2
 
2.0%
129.4285507 2
 
2.0%
127.427565 2
 
2.0%
128.8072551 2
 
2.0%
127.4264979 2
 
2.0%
129.4287411 2
 
2.0%
129.4274731 2
 
2.0%
Other values (78) 79
79.0%
ValueCountFrequency (%)
126.6961469 1
1.0%
126.6981054 1
1.0%
126.8287351 1
1.0%
126.8314189 1
1.0%
126.900078 1
1.0%
126.90456 1
1.0%
126.914598 1
1.0%
126.9418526 1
1.0%
126.949007 1
1.0%
126.9688769 1
1.0%
ValueCountFrequency (%)
129.4468298 1
1.0%
129.4287411 2
2.0%
129.4285507 2
2.0%
129.4274731 2
2.0%
129.4269308 1
1.0%
129.4261457 2
2.0%
129.4255918 1
1.0%
129.4211249 2
2.0%
129.4188315 2
2.0%
129.1388167 1
1.0%

origin_nm
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
공공데이터
83 
문화정보원
17 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공데이터 83
83.0%
문화정보원 17
 
17.0%

Length

2023-12-10T19:20:37.374708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:20:37.545030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공데이터 83
83.0%
문화정보원 17
 
17.0%

adit_dc
Text

MISSING 

Distinct57
Distinct (%)68.7%
Missing17
Missing (%)17.0%
Memory size932.0 B
2023-12-10T19:20:37.769272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length250
Median length247
Mean length240.9759
Min length238

Characters and Unicode

Total characters20001
Distinct characters104
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

Unique40 ?
Unique (%)48.2%

Sample

1st row할인적용최소연령 : 66,할인율 : 10,할인금액 : ,할인대상서비스명 : ,할인부가정보 : ,평일운영시작시각 : 00:00,평일운영종료시각 : 00:00,토요일운영시작시각 : 00:00,토요일운영종료시각 : 00:00,공휴일운영시작시각 : 00:00,공휴일운영종료시각 : 00:00,경로우대업소지정일자 : 2014-03-01,경로우대업소해제일자 : ,관리기관명 : 울산광역시 동구청,관리기관전화번호 : 052-209-3436
2nd row할인적용최소연령 : 70,할인율 : 10,할인금액 : ,할인대상서비스명 : 목욕서비스,할인부가정보 : ,평일운영시작시각 : 23:59,평일운영종료시각 : 23:59,토요일운영시작시각 : 23:59,토요일운영종료시각 : 23:59,공휴일운영시작시각 : 23:59,공휴일운영종료시각 : 23:59,경로우대업소지정일자 : 2011-01-14,경로우대업소해제일자 : ,관리기관명 : 대전광역시 대덕구,관리기관전화번호 : 042-608-6883
3rd row할인적용최소연령 : 66,할인율 : 10,할인금액 : ,할인대상서비스명 : ,할인부가정보 : ,평일운영시작시각 : 00:00,평일운영종료시각 : 00:00,토요일운영시작시각 : 00:00,토요일운영종료시각 : 00:00,공휴일운영시작시각 : 00:00,공휴일운영종료시각 : 00:00,경로우대업소지정일자 : 2014-01-01,경로우대업소해제일자 : ,관리기관명 : 울산광역시 동구청,관리기관전화번호 : 052-209-3436
4th row할인적용최소연령 : 66,할인율 : 10,할인금액 : ,할인대상서비스명 : ,할인부가정보 : ,평일운영시작시각 : 00:00,평일운영종료시각 : 00:00,토요일운영시작시각 : 00:00,토요일운영종료시각 : 00:00,공휴일운영시작시각 : 00:00,공휴일운영종료시각 : 00:00,경로우대업소지정일자 : 2014-01-01,경로우대업소해제일자 : ,관리기관명 : 울산광역시 동구청,관리기관전화번호 : 052-209-3436
5th row할인적용최소연령 : 66,할인율 : 10,할인금액 : ,할인대상서비스명 : ,할인부가정보 : ,평일운영시작시각 : 00:00,평일운영종료시각 : 00:00,토요일운영시작시각 : 00:00,토요일운영종료시각 : 00:00,공휴일운영시작시각 : 00:00,공휴일운영종료시각 : 00:00,경로우대업소지정일자 : 2014-01-01,경로우대업소해제일자 : ,관리기관명 : 울산광역시 동구청,관리기관전화번호 : 052-209-3436
ValueCountFrequency (%)
1245
46.8%
할인적용최소연령 83
 
3.1%
관리기관명 83
 
3.1%
평일운영시작시각 81
 
3.0%
할인대상서비스명 54
 
2.0%
00:00,토요일운영종료시각 42
 
1.6%
00:00,경로우대업소지정일자 42
 
1.6%
00:00,공휴일운영종료시각 42
 
1.6%
00:00,공휴일운영시작시각 42
 
1.6%
00:00,토요일운영시작시각 42
 
1.6%
Other values (156) 905
34.0%
2023-12-10T19:20:38.236307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2578
 
12.9%
0 2109
 
10.5%
: 1743
 
8.7%
, 1165
 
5.8%
시 828
 
4.1%
일 665
 
3.3%
영 501
 
2.5%
운 498
 
2.5%
각 498
 
2.5%
1 452
 
2.3%
Other values (94) 8964
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10301
51.5%
Decimal Number 3875
 
19.4%
Other Punctuation 2912
 
14.6%
Space Separator 2578
 
12.9%
Dash Punctuation 332
 
1.7%
Math Symbol 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 828
 
8.0%
일 665
 
6.5%
영 501
 
4.9%
운 498
 
4.8%
각 498
 
4.8%
인 420
 
4.1%
할 418
 
4.1%
관 332
 
3.2%
대 275
 
2.7%
료 250
 
2.4%
Other values (76) 5616
54.5%
Decimal Number
ValueCountFrequency (%)
0 2109
54.4%
1 452
 
11.7%
2 368
 
9.5%
3 207
 
5.3%
6 181
 
4.7%
5 177
 
4.6%
4 121
 
3.1%
8 93
 
2.4%
9 89
 
2.3%
7 78
 
2.0%
Other Punctuation
ValueCountFrequency (%)
: 1743
59.9%
, 1165
40.0%
. 4
 
0.1%
Space Separator
ValueCountFrequency (%)
2578
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 332
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10301
51.5%
Common 9700
48.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 828
 
8.0%
일 665
 
6.5%
영 501
 
4.9%
운 498
 
4.8%
각 498
 
4.8%
인 420
 
4.1%
할 418
 
4.1%
관 332
 
3.2%
대 275
 
2.7%
료 250
 
2.4%
Other values (76) 5616
54.5%
Common
ValueCountFrequency (%)
2578
26.6%
0 2109
21.7%
: 1743
18.0%
, 1165
12.0%
1 452
 
4.7%
2 368
 
3.8%
- 332
 
3.4%
3 207
 
2.1%
6 181
 
1.9%
5 177
 
1.8%
Other values (8) 388
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10301
51.5%
ASCII 9700
48.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2578
26.6%
0 2109
21.7%
: 1743
18.0%
, 1165
12.0%
1 452
 
4.7%
2 368
 
3.8%
- 332
 
3.4%
3 207
 
2.1%
6 181
 
1.9%
5 177
 
1.8%
Other values (8) 388
 
4.0%
Hangul
ValueCountFrequency (%)
시 828
 
8.0%
일 665
 
6.5%
영 501
 
4.9%
운 498
 
4.8%
각 498
 
4.8%
인 420
 
4.1%
할 418
 
4.1%
관 332
 
3.2%
대 275
 
2.7%
료 250
 
2.4%
Other values (76) 5616
54.5%

updt_dt
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20201201120000
100 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20201201120000
2nd row20201201120000
3rd row20201201120000
4th row20201201120000
5th row20201201120000

Common Values

ValueCountFrequency (%)
20201201120000 100
100.0%

Length

2023-12-10T19:20:38.438678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:20:38.595856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20201201120000 100
100.0%

regist_dt
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20201201120000
100 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20201201120000
2nd row20201201120000
3rd row20201201120000
4th row20201201120000
5th row20201201120000

Common Values

ValueCountFrequency (%)
20201201120000 100
100.0%

Length

2023-12-10T19:20:38.754814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:20:39.091953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20201201120000 100
100.0%

Sample

esntl_idlclas_nmmlsfc_nmfclty_nmctprvn_cdctprvn_nmsigngu_cdsigngu_nmlegaldong_cdlegaldong_nmroad_nm_cdfclty_road_nm_addrlnm_addraddr_eng_nmadstrd_cdbuld_nmbuld_manage_cdtel_nozip_nohmpg_urlfclty_lafclty_loorigin_nmadit_dcupdt_dtregist_dt
0KCOCFPO20N000000595문화시설문화시설_사우나_할인_시니어대송탕31울산광역시31170동구<NA>화정동311704313061울산광역시 동구 대송2길 21울산 동구 화정동 160-1021, Daesong 2-gil, Dong-gu, Ulsan3117010200<NA>3117010200101600010002471052-232-006244061<NA>35.500631129.418832공공데이터할인적용최소연령 : 66,할인율 : 10,할인금액 : ,할인대상서비스명 : ,할인부가정보 : ,평일운영시작시각 : 00:00,평일운영종료시각 : 00:00,토요일운영시작시각 : 00:00,토요일운영종료시각 : 00:00,공휴일운영시작시각 : 00:00,공휴일운영종료시각 : 00:00,경로우대업소지정일자 : 2014-03-01,경로우대업소해제일자 : ,관리기관명 : 울산광역시 동구청,관리기관전화번호 : 052-209-34362020120112000020201201120000
1KCOCFPO20N000002724문화시설문화시설_사우나_할인_시니어그랜드사우나30대전광역시30230대덕구<NA>송촌동302302010003대전광역시 대덕구 동서대로 1755대전 대덕구 송촌동 295-101755, Dongseo-daero, Daedeok-gu, Daejeon3023010700<NA>3023010700102950010018918042-639-773534425<NA>36.35289127.441967공공데이터할인적용최소연령 : 70,할인율 : 10,할인금액 : ,할인대상서비스명 : 목욕서비스,할인부가정보 : ,평일운영시작시각 : 23:59,평일운영종료시각 : 23:59,토요일운영시작시각 : 23:59,토요일운영종료시각 : 23:59,공휴일운영시작시각 : 23:59,공휴일운영종료시각 : 23:59,경로우대업소지정일자 : 2011-01-14,경로우대업소해제일자 : ,관리기관명 : 대전광역시 대덕구,관리기관전화번호 : 042-608-68832020120112000020201201120000
2KCOCFPO20N000000597문화시설문화시설_사우나_할인_시니어세왕탕31울산광역시31170동구<NA>동부동311703171014울산광역시 동구 옥류로 68-1울산 동구 동부동 39568-1, Ongnyu-ro, Dong-gu, Ulsan3117010700<NA>3117010700103950000003804052-251-018744004<NA>35.544773129.426146공공데이터할인적용최소연령 : 66,할인율 : 10,할인금액 : ,할인대상서비스명 : ,할인부가정보 : ,평일운영시작시각 : 00:00,평일운영종료시각 : 00:00,토요일운영시작시각 : 00:00,토요일운영종료시각 : 00:00,공휴일운영시작시각 : 00:00,공휴일운영종료시각 : 00:00,경로우대업소지정일자 : 2014-01-01,경로우대업소해제일자 : ,관리기관명 : 울산광역시 동구청,관리기관전화번호 : 052-209-34362020120112000020201201120000
3KCOCFPO20N000000598문화시설문화시설_사우나_할인_시니어수어탕31울산광역시31170동구<NA>화정동311704313060울산광역시 동구 대송1길 50울산 동구 화정동 844-350, Daesong 1-gil, Dong-gu, Ulsan3117010200<NA>3117010200108440003002798052-251-094344070<NA>35.499212129.421125공공데이터할인적용최소연령 : 66,할인율 : 10,할인금액 : ,할인대상서비스명 : ,할인부가정보 : ,평일운영시작시각 : 00:00,평일운영종료시각 : 00:00,토요일운영시작시각 : 00:00,토요일운영종료시각 : 00:00,공휴일운영시작시각 : 00:00,공휴일운영종료시각 : 00:00,경로우대업소지정일자 : 2014-01-01,경로우대업소해제일자 : ,관리기관명 : 울산광역시 동구청,관리기관전화번호 : 052-209-34362020120112000020201201120000
4KCOCFPO20N000000599문화시설문화시설_사우나_할인_시니어스파탕31울산광역시31170동구<NA>동부동311704313019울산광역시 동구 남목18길 8울산 동구 동부동 303-38, Nammok 18-gil, Dong-gu, Ulsan3117010700남목시티프라자3117010700103060004004542052-252-506044006<NA>35.542778129.428551공공데이터할인적용최소연령 : 66,할인율 : 10,할인금액 : ,할인대상서비스명 : ,할인부가정보 : ,평일운영시작시각 : 00:00,평일운영종료시각 : 00:00,토요일운영시작시각 : 00:00,토요일운영종료시각 : 00:00,공휴일운영시작시각 : 00:00,공휴일운영종료시각 : 00:00,경로우대업소지정일자 : 2014-01-01,경로우대업소해제일자 : ,관리기관명 : 울산광역시 동구청,관리기관전화번호 : 052-209-34362020120112000020201201120000
5KCOCFPO20N000000600문화시설문화시설_사우나_할인_시니어24시천연해수사우나28인천광역시28200남동구<NA>간석동282004259461인천광역시 남동구 석정로565번길 20-4인천 남동구 간석동 611-820-4, Seokjeong-ro 565beon-gil, Namdong-gu, Incheon2820010200성호아파트2820010200106110008005779032-421-128121503<NA>37.467393126.698105공공데이터할인적용최소연령 : 65,할인율 : 20,할인금액 : ,할인대상서비스명 : ,할인부가정보 : ,평일운영시작시각 : 11:00,평일운영종료시각 : 23:00,토요일운영시작시각 : 11:00,토요일운영종료시각 : 23:00,공휴일운영시작시각 : 11:00,공휴일운영종료시각 : 23:00,경로우대업소지정일자 : 2016-11-18,경로우대업소해제일자 : ,관리기관명 : 인천광역시 남동구,관리기관전화번호 : 032-453-58532020120112000020201201120000
6KCOCFPO20N000000601문화시설문화시설_사우나_할인_시니어피부미인28인천광역시28200남동구<NA>간석동282003008014인천광역시 남동구 주안로 234인천 남동구 간석동 935234, Juan-ro, Namdong-gu, Incheon2820010200<NA>2820010200109350000006336032-423-030821505<NA>37.463078126.696147공공데이터할인적용최소연령 : 65,할인율 : 20+30,할인금액 : ,할인대상서비스명 : ,할인부가정보 : ,평일운영시작시각 : 10:00,평일운영종료시각 : 22:00,토요일운영시작시각 : 10:00,토요일운영종료시각 : 22:00,공휴일운영시작시각 : 10:00,공휴일운영종료시각 : 22:00,경로우대업소지정일자 : 2017-12-12,경로우대업소해제일자 : ,관리기관명 : 인천광역시 남동구,관리기관전화번호 : 032-453-58532020120112000020201201120000
7KCOCFPO20N000002725문화시설문화시설_사우나_할인_시니어등마루목욕탕30대전광역시30230대덕구<NA>석봉동302304304059대전광역시 대덕구 대덕대로1605번길 16-3대전 대덕구 석봉동 200-716-3, Daedeok-daero 1605beon-gil, Daedeok-gu, Daejeon3023011100<NA>3023011100102000007000768042-931-582234305<NA>36.451343127.426498공공데이터할인적용최소연령 : 70,할인율 : 10,할인금액 : ,할인대상서비스명 : 목욕서비스,할인부가정보 : ,평일운영시작시각 : 05:00,평일운영종료시각 : 16:00,토요일운영시작시각 : 05:00,토요일운영종료시각 : 16:00,공휴일운영시작시각 : 05:00,공휴일운영종료시각 : 16:00,경로우대업소지정일자 : 2010-01-01,경로우대업소해제일자 : ,관리기관명 : 대전광역시 대덕구,관리기관전화번호 : 042-608-68832020120112000020201201120000
8KCOCFPO20N000000603문화시설문화시설_사우나_할인_시니어일산탕31울산광역시31170동구<NA>일산동311704313117울산광역시 동구 번덕1길 12-6울산 동구 일산동 464-712-6, Beondeok 1-gil, Dong-gu, Ulsan3117010300<NA>3117010300104640008004645000-0000-000044053<NA>35.503611129.428741공공데이터할인적용최소연령 : 66,할인율 : 목욕10,할인금액 : ,할인대상서비스명 : ,할인부가정보 : ,평일운영시작시각 : 00:00,평일운영종료시각 : 00:00,토요일운영시작시각 : 00:00,토요일운영종료시각 : 00:00,공휴일운영시작시각 : 00:00,공휴일운영종료시각 : 00:00,경로우대업소지정일자 : 2014-10-06,경로우대업소해제일자 : ,관리기관명 : 울산광역시 동구청,관리기관전화번호 : 052-209-34362020120112000020201201120000
9KCOCFPO20N000000604문화시설문화시설_사우나_할인_시니어석정여자사우나11서울특별시11560영등포구<NA>대림동115604154480서울특별시 영등포구 시흥대로175길 5서울 영등포구 대림동 993-725, Siheung-daero 175-gil, Yeongdeungpo-gu, Seoul1156013300<NA>115601330010993007200382702-843-59597445<NA>37.487919126.90456공공데이터할인적용최소연령 : 65,할인율 : ,할인금액 : 1000,할인대상서비스명 : ,할인부가정보 : ,평일운영시작시각 : 10:00,평일운영종료시각 : 22:00,토요일운영시작시각 : 10:00,토요일운영종료시각 : 22:00,공휴일운영시작시각 : 10:00,공휴일운영종료시각 : 21:00,경로우대업소지정일자 : 2018-12-01,경로우대업소해제일자 : ,관리기관명 : 서울특별시 영등포구,관리기관전화번호 : 02-2670-33902020120112000020201201120000
esntl_idlclas_nmmlsfc_nmfclty_nmctprvn_cdctprvn_nmsigngu_cdsigngu_nmlegaldong_cdlegaldong_nmroad_nm_cdfclty_road_nm_addrlnm_addraddr_eng_nmadstrd_cdbuld_nmbuld_manage_cdtel_nozip_nohmpg_urlfclty_lafclty_loorigin_nmadit_dcupdt_dtregist_dt
90KCOCFPO20N000000685문화시설문화시설_카페_시니어연제시니어클럽다방 거제점26부산광역시26470연제구<NA>거제동264704211415부산광역시 연제구 해맞이로89번길 52부산 연제구 거제동 1446-152, Haemaji-ro 89beon-gil, Yeonje-gu, Busan2647010100<NA>2647010100114460001015730051-851-219047534<NA>35.181742129.066404문화정보원<NA>2020120112000020201201120000
91KCOCFPO20N000000686문화시설문화시설_카페_시니어커피토마토 사상점26부산광역시26530사상구<NA>괘법동265304217208부산광역시 사상구 사상로212번길 8부산 사상구 괘법동 535-18, Sasang-ro 212beon-gil, Sasang-gu, Busan2653010400강남커피숍2653010400105350001019443070-7730-360546968<NA>35.16409128.984328문화정보원<NA>2020120112000020201201120000
92KCOCFPO20N000000687문화시설문화시설_카페_시니어니어앤디어31울산광역시31200북구<NA>정자동312004316275울산광역시 북구 정자2길 19울산 북구 정자동 425-319, Jeongja 2-gil, Buk-gu, Ulsan3120011300<NA>3120011300104250003008749052-933-070744233<NA>35.621075129.44683문화정보원<NA>2020120112000020201201120000
93KCOCFPO20N000000688문화시설문화시설_카페_시니어화성시니어클럽 노노카페 동탄1호공원점41경기도41590화성시<NA>영천동415904852386경기도 화성시 동탄순환대로29길 38경기 화성시 영천동 670-238, Dongtansunhwan-daero 29-gil, Hwaseong-si, Gyeonggi-do4159013100<NA>4159013100105820001000001<NA>18472<NA>37.205916127.106967문화정보원<NA>2020120112000020201201120000
94KCOCFPO20N000000689문화시설문화시설_카페_시니어화성시니어클럽커피앤 한국농수산대학교점41경기도41590화성시<NA>봉담읍 동화리415903012007경기도 화성시 봉담읍 효행로 212경기 화성시 봉담읍 동화리 11-1212, Hyohaeng-ro, Bongdam-eup, Hwaseong-si, Gyeonggi-do4159025324<NA>4159025324100110001026042<NA>18299<NA>37.228743126.968877문화정보원<NA>2020120112000020201201120000
95KCOCFPO20N000000690문화시설문화시설_카페_시니어노노카페 봉담도서관점41경기도41590화성시<NA>봉담읍 상리415904430668경기도 화성시 봉담읍 샘마을1길 8-4경기 화성시 봉담읍 상리 27-498-4, Saemmaeul 1-gil, Bongdam-eup, Hwaseong-si, Gyeonggi-do4159025321봉담도서관4159025321100270049000001<NA>18316<NA>37.219338126.949007문화정보원<NA>2020120112000020201201120000
96KCOCFPO20N000000691문화시설문화시설_카페_시니어행복일번지분식카페41경기도41360남양주시<NA>진건읍 송능리413603197050경기도 남양주시 진건읍 진건오남로 379경기 남양주시 진건읍 송능리 115-22379, Jingeononam-ro, Jingeon-eup, Namyangju-si, Gyeonggi-do4136025926<NA>4136025926101150022007877031-529-801012129<NA>37.672857127.199104문화정보원<NA>2020120112000020201201120000
97KCOCFPO20N000000692문화시설문화시설_카페_시니어노노카페 본점41경기도41590화성시<NA>반송동415903210025경기도 화성시 노작로 134경기 화성시 반송동 108134, Nojak-ro, Hwaseong-si, Gyeonggi-do4159012700<NA>4159012700101080000000001<NA>18459<NA>37.200826127.074988문화정보원<NA>2020120112000020201201120000
98KCOCFPO20N000000693문화시설문화시설_카페_시니어노노카페 모두누림센터점41경기도41590화성시<NA>남양읍 남양리415903210146경기도 화성시 남양읍 시청로 155경기 화성시 남양읍 남양리 2147155, Sicheong-ro, Namyang-eup, Hwaseong-si, Gyeonggi-do4159026221화성서부복합문화센터4159026221121470000000001031-8059-434918274<NA>37.198787126.828735문화정보원<NA>2020120112000020201201120000
99KCOCFPO20N000000694문화시설문화시설_카페_시니어화성시니어클럽 커피앤 시청점41경기도41590화성시<NA>남양읍 남양리415903210146경기도 화성시 남양읍 시청로 159경기 화성시 남양읍 남양리 2000159, Sicheong-ro, Namyang-eup, Hwaseong-si, Gyeonggi-do4159026221<NA>4159010100120000000305449<NA>18274<NA>37.19948126.831419문화정보원<NA>2020120112000020201201120000