Overview

Dataset statistics

Number of variables27
Number of observations100
Missing cells361
Missing cells (%)13.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.3 KiB
Average record size in memory228.3 B

Variable types

Text10
Categorical6
Numeric8
Unsupported2
Boolean1

Alerts

lclas_nm has constant value ""Constant
origin_nm has constant value ""Constant
updt_dt has constant value ""Constant
regist_dt has constant value ""Constant
mlsfc_nm is highly imbalanced (80.6%)Imbalance
water_ply_fclty_at is highly imbalanced (85.9%)Imbalance
legaldong_cd has 100 (100.0%) missing valuesMissing
buld_nm has 46 (46.0%) missing valuesMissing
tel_no has 18 (18.0%) missing valuesMissing
hmpg_url has 100 (100.0%) missing valuesMissing
adit_dc has 97 (97.0%) 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 09:46:54.281965
Analysis finished2023-12-10 09:46:55.792749
Duration1.51 second
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
2023-12-10T18:46:56.032464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters1900
Distinct characters17
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 rowKCIPFPO20N000000001
2nd rowKCIPFPO20N000048481
3rd rowKCIPFPO20N000000003
4th rowKCIPFPO20N000000004
5th rowKCIPFPO20N000000005
ValueCountFrequency (%)
kcipfpo20n000000001 1
 
1.0%
kcipfpo20n000000063 1
 
1.0%
kcipfpo20n000000074 1
 
1.0%
kcipfpo20n000000073 1
 
1.0%
kcipfpo20n000000072 1
 
1.0%
kcipfpo20n000000071 1
 
1.0%
kcipfpo20n000000070 1
 
1.0%
kcipfpo20n000000069 1
 
1.0%
kcipfpo20n000000068 1
 
1.0%
kcipfpo20n000000067 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T18:46:56.691680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 808
42.5%
P 200
 
10.5%
2 119
 
6.3%
K 100
 
5.3%
C 100
 
5.3%
N 100
 
5.3%
O 100
 
5.3%
F 100
 
5.3%
I 100
 
5.3%
4 26
 
1.4%
Other values (7) 147
 
7.7%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 808
73.5%
2 119
 
10.8%
4 26
 
2.4%
8 25
 
2.3%
1 22
 
2.0%
3 20
 
1.8%
5 20
 
1.8%
6 20
 
1.8%
7 20
 
1.8%
9 20
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
P 200
25.0%
K 100
12.5%
C 100
12.5%
N 100
12.5%
O 100
12.5%
F 100
12.5%
I 100
12.5%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 808
73.5%
2 119
 
10.8%
4 26
 
2.4%
8 25
 
2.3%
1 22
 
2.0%
3 20
 
1.8%
5 20
 
1.8%
6 20
 
1.8%
7 20
 
1.8%
9 20
 
1.8%
Latin
ValueCountFrequency (%)
P 200
25.0%
K 100
12.5%
C 100
12.5%
N 100
12.5%
O 100
12.5%
F 100
12.5%
I 100
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 808
42.5%
P 200
 
10.5%
2 119
 
6.3%
K 100
 
5.3%
C 100
 
5.3%
N 100
 
5.3%
O 100
 
5.3%
F 100
 
5.3%
I 100
 
5.3%
4 26
 
1.4%
Other values (7) 147
 
7.7%

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

2023-12-10T18:46:56.969675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:46:57.168766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문화시설 100
100.0%

mlsfc_nm
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
문화시설_유원시설_어린이
97 
문화시설_놀이터_실내
 
3

Length

Max length13
Median length13
Mean length12.94
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row문화시설_유원시설_어린이
2nd row문화시설_놀이터_실내
3rd row문화시설_유원시설_어린이
4th row문화시설_유원시설_어린이
5th row문화시설_유원시설_어린이

Common Values

ValueCountFrequency (%)
문화시설_유원시설_어린이 97
97.0%
문화시설_놀이터_실내 3
 
3.0%

Length

2023-12-10T18:46:57.380856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:46:57.579738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문화시설_유원시설_어린이 97
97.0%
문화시설_놀이터_실내 3
 
3.0%
Distinct96
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:46:58.046101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length15
Mean length10.38
Min length4

Characters and Unicode

Total characters1038
Distinct characters211
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique92 ?
Unique (%)92.0%

Sample

1st row어린이대공원
2nd row두산판교어린이집 실외놀이터
3rd row화성시 어린이문화센터
4th row경천대 어린이랜드
5th row어린이비전센터 라바파크
ValueCountFrequency (%)
키즈카페 13
 
7.3%
타요키즈카페 8
 
4.5%
점프노리키즈카페 4
 
2.3%
커뮤니티센터키즈룸 2
 
1.1%
키즈다쿵 2
 
1.1%
키즈파크 2
 
1.1%
로프 2
 
1.1%
키즈까페 2
 
1.1%
목포 2
 
1.1%
키즈방방 2
 
1.1%
Other values (133) 138
78.0%
2023-12-10T18:46:59.098920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
89
 
8.6%
89
 
8.6%
77
 
7.4%
52
 
5.0%
51
 
4.9%
36
 
3.5%
27
 
2.6%
18
 
1.7%
16
 
1.5%
( 16
 
1.5%
Other values (201) 567
54.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 922
88.8%
Space Separator 77
 
7.4%
Open Punctuation 16
 
1.5%
Close Punctuation 16
 
1.5%
Decimal Number 4
 
0.4%
Dash Punctuation 2
 
0.2%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
89
 
9.7%
89
 
9.7%
52
 
5.6%
51
 
5.5%
36
 
3.9%
27
 
2.9%
18
 
2.0%
16
 
1.7%
14
 
1.5%
14
 
1.5%
Other values (193) 516
56.0%
Decimal Number
ValueCountFrequency (%)
6 2
50.0%
4 1
25.0%
2 1
25.0%
Space Separator
ValueCountFrequency (%)
77
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 923
88.9%
Common 115
 
11.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
89
 
9.6%
89
 
9.6%
52
 
5.6%
51
 
5.5%
36
 
3.9%
27
 
2.9%
18
 
2.0%
16
 
1.7%
14
 
1.5%
14
 
1.5%
Other values (194) 517
56.0%
Common
ValueCountFrequency (%)
77
67.0%
( 16
 
13.9%
) 16
 
13.9%
6 2
 
1.7%
- 2
 
1.7%
4 1
 
0.9%
2 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 922
88.8%
ASCII 115
 
11.1%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
89
 
9.7%
89
 
9.7%
52
 
5.6%
51
 
5.5%
36
 
3.9%
27
 
2.9%
18
 
2.0%
16
 
1.7%
14
 
1.5%
14
 
1.5%
Other values (193) 516
56.0%
ASCII
ValueCountFrequency (%)
77
67.0%
( 16
 
13.9%
) 16
 
13.9%
6 2
 
1.7%
- 2
 
1.7%
4 1
 
0.9%
2 1
 
0.9%
None
ValueCountFrequency (%)
1
100.0%

ctprvn_cd
Real number (ℝ)

Distinct16
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.13
Minimum11
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:46:59.369912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile11
Q128
median41
Q344
95-th percentile48
Maximum50
Range39
Interquartile range (IQR)16

Descriptive statistics

Standard deviation11.225562
Coefficient of variation (CV)0.31069919
Kurtosis0.22434759
Mean36.13
Median Absolute Deviation (MAD)5
Skewness-1.0964073
Sum3613
Variance126.01323
MonotonicityNot monotonic
2023-12-10T18:46:59.633062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
41 34
34.0%
11 11
 
11.0%
28 7
 
7.0%
47 6
 
6.0%
27 5
 
5.0%
44 5
 
5.0%
50 4
 
4.0%
45 4
 
4.0%
26 4
 
4.0%
46 4
 
4.0%
Other values (6) 16
16.0%
ValueCountFrequency (%)
11 11
 
11.0%
26 4
 
4.0%
27 5
 
5.0%
28 7
 
7.0%
29 3
 
3.0%
30 2
 
2.0%
31 3
 
3.0%
41 34
34.0%
42 2
 
2.0%
43 3
 
3.0%
ValueCountFrequency (%)
50 4
 
4.0%
48 3
 
3.0%
47 6
 
6.0%
46 4
 
4.0%
45 4
 
4.0%
44 5
 
5.0%
43 3
 
3.0%
42 2
 
2.0%
41 34
34.0%
31 3
 
3.0%

ctprvn_nm
Categorical

Distinct16
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
경기도
34 
서울특별시
11 
인천광역시
경상북도
충청남도
Other values (11)
37 

Length

Max length7
Median length5
Mean length4.11
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시
2nd row경기도
3rd row경기도
4th row경상북도
5th row경기도

Common Values

ValueCountFrequency (%)
경기도 34
34.0%
서울특별시 11
 
11.0%
인천광역시 7
 
7.0%
경상북도 6
 
6.0%
충청남도 5
 
5.0%
대구광역시 5
 
5.0%
제주특별자치도 4
 
4.0%
전라북도 4
 
4.0%
부산광역시 4
 
4.0%
전라남도 4
 
4.0%
Other values (6) 16
16.0%

Length

2023-12-10T18:47:00.076604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 34
34.0%
서울특별시 11
 
11.0%
인천광역시 7
 
7.0%
경상북도 6
 
6.0%
충청남도 5
 
5.0%
대구광역시 5
 
5.0%
제주특별자치도 4
 
4.0%
전라북도 4
 
4.0%
부산광역시 4
 
4.0%
전라남도 4
 
4.0%
Other values (6) 16
16.0%

signgu_cd
Real number (ℝ)

Distinct67
Distinct (%)67.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36411.36
Minimum11200
Maximum50130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:47:00.508018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11200
5-th percentile11345.5
Q128243
median41245.5
Q344133
95-th percentile48300.5
Maximum50130
Range38930
Interquartile range (IQR)15890

Descriptive statistics

Standard deviation11193.854
Coefficient of variation (CV)0.30742751
Kurtosis0.21079214
Mean36411.36
Median Absolute Deviation (MAD)4884.5
Skewness-1.0939265
Sum3641136
Variance1.2530236 × 108
MonotonicityNot monotonic
2023-12-10T18:47:00.861564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41360 5
 
5.0%
41173 4
 
4.0%
41190 3
 
3.0%
41135 3
 
3.0%
44200 3
 
3.0%
11530 2
 
2.0%
27290 2
 
2.0%
41271 2
 
2.0%
29170 2
 
2.0%
41410 2
 
2.0%
Other values (57) 72
72.0%
ValueCountFrequency (%)
11200 1
1.0%
11215 1
1.0%
11230 1
1.0%
11260 2
2.0%
11350 1
1.0%
11380 1
1.0%
11500 1
1.0%
11530 2
2.0%
11740 1
1.0%
26290 1
1.0%
ValueCountFrequency (%)
50130 2
2.0%
50110 2
2.0%
48880 1
1.0%
48270 1
1.0%
48170 1
1.0%
47290 1
1.0%
47250 1
1.0%
47190 2
2.0%
47130 2
2.0%
46890 1
1.0%
Distinct63
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:47:01.369747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.98
Min length2

Characters and Unicode

Total characters398
Distinct characters70
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

Unique38 ?
Unique (%)38.0%

Sample

1st row광진구
2nd row성남시 분당구
3rd row화성시
4th row상주시
5th row남양주시
ValueCountFrequency (%)
북구 6
 
4.8%
성남시 6
 
4.8%
남양주시 5
 
4.0%
안양시 5
 
4.0%
동안구 4
 
3.2%
용인시 3
 
2.4%
전주시 3
 
2.4%
안산시 3
 
2.4%
부천시 3
 
2.4%
아산시 3
 
2.4%
Other values (61) 84
67.2%
2023-12-10T18:47:02.231574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
63
15.8%
62
 
15.6%
25
 
6.3%
18
 
4.5%
15
 
3.8%
15
 
3.8%
13
 
3.3%
11
 
2.8%
10
 
2.5%
10
 
2.5%
Other values (60) 156
39.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 373
93.7%
Space Separator 25
 
6.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
63
16.9%
62
16.6%
18
 
4.8%
15
 
4.0%
15
 
4.0%
13
 
3.5%
11
 
2.9%
10
 
2.7%
10
 
2.7%
9
 
2.4%
Other values (59) 147
39.4%
Space Separator
ValueCountFrequency (%)
25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 373
93.7%
Common 25
 
6.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
63
16.9%
62
16.6%
18
 
4.8%
15
 
4.0%
15
 
4.0%
13
 
3.5%
11
 
2.9%
10
 
2.7%
10
 
2.7%
9
 
2.4%
Other values (59) 147
39.4%
Common
ValueCountFrequency (%)
25
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 373
93.7%
ASCII 25
 
6.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
63
16.9%
62
16.6%
18
 
4.8%
15
 
4.0%
15
 
4.0%
13
 
3.5%
11
 
2.9%
10
 
2.7%
10
 
2.7%
9
 
2.4%
Other values (59) 147
39.4%
ASCII
ValueCountFrequency (%)
25
100.0%

legaldong_cd
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB
Distinct90
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:47:02.946522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.51
Min length2

Characters and Unicode

Total characters351
Distinct characters122
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

Unique83 ?
Unique (%)83.0%

Sample

1st row능동
2nd row정자동
3rd row봉담읍
4th row사벌국면 삼덕리
5th row진접읍
ValueCountFrequency (%)
진접읍 4
 
3.6%
상동 3
 
2.7%
창곡동 2
 
1.8%
비산동 2
 
1.8%
성복동 2
 
1.8%
신내동 2
 
1.8%
둔포면 2
 
1.8%
능동 1
 
0.9%
신안동 1
 
0.9%
신용동 1
 
0.9%
Other values (92) 92
82.1%
2023-12-10T18:47:03.855197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
79
22.5%
15
 
4.3%
13
 
3.7%
12
 
3.4%
8
 
2.3%
7
 
2.0%
6
 
1.7%
6
 
1.7%
6
 
1.7%
6
 
1.7%
Other values (112) 193
55.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 336
95.7%
Space Separator 12
 
3.4%
Decimal Number 3
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
79
23.5%
15
 
4.5%
13
 
3.9%
8
 
2.4%
7
 
2.1%
6
 
1.8%
6
 
1.8%
6
 
1.8%
6
 
1.8%
5
 
1.5%
Other values (108) 185
55.1%
Decimal Number
ValueCountFrequency (%)
3 1
33.3%
2 1
33.3%
1 1
33.3%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 336
95.7%
Common 15
 
4.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
79
23.5%
15
 
4.5%
13
 
3.9%
8
 
2.4%
7
 
2.1%
6
 
1.8%
6
 
1.8%
6
 
1.8%
6
 
1.8%
5
 
1.5%
Other values (108) 185
55.1%
Common
ValueCountFrequency (%)
12
80.0%
3 1
 
6.7%
2 1
 
6.7%
1 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 336
95.7%
ASCII 15
 
4.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
79
23.5%
15
 
4.5%
13
 
3.9%
8
 
2.4%
7
 
2.1%
6
 
1.8%
6
 
1.8%
6
 
1.8%
6
 
1.8%
5
 
1.5%
Other values (108) 185
55.1%
ASCII
ValueCountFrequency (%)
12
80.0%
3 1
 
6.7%
2 1
 
6.7%
1 1
 
6.7%

road_nm_cd
Real number (ℝ)

Distinct95
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.6411709 × 1011
Minimum1.1200301 × 1011
Maximum5.0130485 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:47:04.162599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1200301 × 1011
5-th percentile1.1345908 × 1011
Q12.8243426 × 1011
median4.1245819 × 1011
Q34.4133325 × 1011
95-th percentile4.8300834 × 1011
Maximum5.0130485 × 1011
Range3.8930185 × 1011
Interquartile range (IQR)1.5889899 × 1011

Descriptive statistics

Standard deviation1.1193863 × 1011
Coefficient of variation (CV)0.30742482
Kurtosis0.21079412
Mean3.6411709 × 1011
Median Absolute Deviation (MAD)4.8845777 × 1010
Skewness-1.0939262
Sum3.6411709 × 1013
Variance1.2530257 × 1022
MonotonicityNot monotonic
2023-12-10T18:47:04.485992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
413603197065 4
 
4.0%
414653205010 2
 
2.0%
442003253057 2
 
2.0%
112153104007 1
 
1.0%
113504130198 1
 
1.0%
263202132001 1
 
1.0%
451113266087 1
 
1.0%
292003163033 1
 
1.0%
112303005032 1
 
1.0%
411734349275 1
 
1.0%
Other values (85) 85
85.0%
ValueCountFrequency (%)
112003005011 1
1.0%
112153104007 1
1.0%
112303005032 1
1.0%
112603106003 1
1.0%
112603106013 1
1.0%
113504130198 1
1.0%
113803000008 1
1.0%
115003115002 1
1.0%
115303000019 1
1.0%
115303116004 1
1.0%
ValueCountFrequency (%)
501304850209 1
1.0%
501303349238 1
1.0%
501104848994 1
1.0%
501103349160 1
1.0%
488803347018 1
1.0%
482703336062 1
1.0%
481703332065 1
1.0%
472904721501 1
1.0%
472503311003 1
1.0%
471904724268 1
1.0%
Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:47:05.005797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length28
Mean length20.12
Min length13

Characters and Unicode

Total characters2012
Distinct characters198
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

Unique95 ?
Unique (%)95.0%

Sample

1st row서울 광진구 능동로 216
2nd row경기 성남시 분당구 정자일로 155
3rd row경기도 화성시 봉담읍 동화길 146
4th row경상북도 상주시 사벌국면 경천로 652-18
5th row경기도 남양주시 진접읍 해밀예당1로 96
ValueCountFrequency (%)
경기도 32
 
6.7%
서울 11
 
2.3%
인천 7
 
1.5%
성남시 6
 
1.3%
북구 6
 
1.3%
충청남도 5
 
1.0%
대구 5
 
1.0%
남양주시 5
 
1.0%
안양시 5
 
1.0%
해밀예당1로 4
 
0.8%
Other values (305) 393
82.0%
2023-12-10T18:47:05.903817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
379
 
18.8%
86
 
4.3%
70
 
3.5%
67
 
3.3%
1 66
 
3.3%
51
 
2.5%
50
 
2.5%
50
 
2.5%
2 39
 
1.9%
36
 
1.8%
Other values (188) 1118
55.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1244
61.8%
Space Separator 379
 
18.8%
Decimal Number 315
 
15.7%
Close Punctuation 30
 
1.5%
Open Punctuation 30
 
1.5%
Dash Punctuation 13
 
0.6%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
86
 
6.9%
70
 
5.6%
67
 
5.4%
51
 
4.1%
50
 
4.0%
50
 
4.0%
36
 
2.9%
31
 
2.5%
30
 
2.4%
29
 
2.3%
Other values (173) 744
59.8%
Decimal Number
ValueCountFrequency (%)
1 66
21.0%
2 39
12.4%
6 35
11.1%
4 31
9.8%
3 29
9.2%
9 23
 
7.3%
5 23
 
7.3%
8 23
 
7.3%
7 23
 
7.3%
0 23
 
7.3%
Space Separator
ValueCountFrequency (%)
379
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1244
61.8%
Common 768
38.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
86
 
6.9%
70
 
5.6%
67
 
5.4%
51
 
4.1%
50
 
4.0%
50
 
4.0%
36
 
2.9%
31
 
2.5%
30
 
2.4%
29
 
2.3%
Other values (173) 744
59.8%
Common
ValueCountFrequency (%)
379
49.3%
1 66
 
8.6%
2 39
 
5.1%
6 35
 
4.6%
4 31
 
4.0%
) 30
 
3.9%
( 30
 
3.9%
3 29
 
3.8%
9 23
 
3.0%
5 23
 
3.0%
Other values (5) 83
 
10.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1244
61.8%
ASCII 768
38.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
379
49.3%
1 66
 
8.6%
2 39
 
5.1%
6 35
 
4.6%
4 31
 
4.0%
) 30
 
3.9%
( 30
 
3.9%
3 29
 
3.8%
9 23
 
3.0%
5 23
 
3.0%
Other values (5) 83
 
10.8%
Hangul
ValueCountFrequency (%)
86
 
6.9%
70
 
5.6%
67
 
5.4%
51
 
4.1%
50
 
4.0%
50
 
4.0%
36
 
2.9%
31
 
2.5%
30
 
2.4%
29
 
2.3%
Other values (173) 744
59.8%
Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:47:06.697905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length29
Mean length20.16
Min length12

Characters and Unicode

Total characters2016
Distinct characters202
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

Unique95 ?
Unique (%)95.0%

Sample

1st row서울 광진구 능동 18
2nd row경기 성남시 분당구 정자동 161-1
3rd row경기도 화성시 봉담읍 동화리 590
4th row경북 상주시 사벌국면 삼덕리 3-2
5th row경기도 남양주시 진접읍 금곡리 1077
ValueCountFrequency (%)
경기도 32
 
6.7%
서울 11
 
2.3%
인천 7
 
1.5%
성남시 6
 
1.3%
경북 6
 
1.3%
북구 6
 
1.3%
대구 5
 
1.0%
남양주시 5
 
1.0%
안양시 5
 
1.0%
충청남도 5
 
1.0%
Other values (312) 391
81.6%
2023-12-10T18:47:07.684810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
379
 
18.8%
94
 
4.7%
1 83
 
4.1%
69
 
3.4%
- 66
 
3.3%
64
 
3.2%
49
 
2.4%
2 48
 
2.4%
47
 
2.3%
6 40
 
2.0%
Other values (192) 1077
53.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1176
58.3%
Decimal Number 392
 
19.4%
Space Separator 379
 
18.8%
Dash Punctuation 66
 
3.3%
Uppercase Letter 1
 
< 0.1%
Lowercase Letter 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
94
 
8.0%
69
 
5.9%
64
 
5.4%
49
 
4.2%
47
 
4.0%
36
 
3.1%
29
 
2.5%
28
 
2.4%
26
 
2.2%
25
 
2.1%
Other values (177) 709
60.3%
Decimal Number
ValueCountFrequency (%)
1 83
21.2%
2 48
12.2%
6 40
10.2%
9 40
10.2%
5 36
9.2%
7 36
9.2%
4 30
 
7.7%
3 29
 
7.4%
8 26
 
6.6%
0 24
 
6.1%
Space Separator
ValueCountFrequency (%)
379
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 66
100.0%
Uppercase Letter
ValueCountFrequency (%)
W 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1176
58.3%
Common 838
41.6%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
94
 
8.0%
69
 
5.9%
64
 
5.4%
49
 
4.2%
47
 
4.0%
36
 
3.1%
29
 
2.5%
28
 
2.4%
26
 
2.2%
25
 
2.1%
Other values (177) 709
60.3%
Common
ValueCountFrequency (%)
379
45.2%
1 83
 
9.9%
- 66
 
7.9%
2 48
 
5.7%
6 40
 
4.8%
9 40
 
4.8%
5 36
 
4.3%
7 36
 
4.3%
4 30
 
3.6%
3 29
 
3.5%
Other values (3) 51
 
6.1%
Latin
ValueCountFrequency (%)
W 1
50.0%
e 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1176
58.3%
ASCII 840
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
379
45.1%
1 83
 
9.9%
- 66
 
7.9%
2 48
 
5.7%
6 40
 
4.8%
9 40
 
4.8%
5 36
 
4.3%
7 36
 
4.3%
4 30
 
3.6%
3 29
 
3.5%
Other values (5) 53
 
6.3%
Hangul
ValueCountFrequency (%)
94
 
8.0%
69
 
5.9%
64
 
5.4%
49
 
4.2%
47
 
4.0%
36
 
3.1%
29
 
2.5%
28
 
2.4%
26
 
2.2%
25
 
2.1%
Other values (177) 709
60.3%
Distinct96
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:47:08.196190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length78
Median length60
Mean length48.26
Min length28

Characters and Unicode

Total characters4826
Distinct characters55
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

Unique93 ?
Unique (%)93.0%

Sample

1st row216, Neungdong-ro, Gwangjin-gu, Seoul
2nd row155, Jeongjail-ro, Bundang-gu, Seongnam-si, Gyeonggi-do
3rd row146, Donghwa-gil, Bongdam-eup, Hwaseong-si, Gyeonggi-do
4th row652-18, Gyeongcheon-ro, Sabeolgung-myeon, Sangju-si, Gyeongsangbuk-do
5th row96, Haemiryedang 1-ro, Jinjeop-eup, Namyangju-si, Gyeonggi-do
ValueCountFrequency (%)
gyeonggi-do 34
 
7.1%
seoul 11
 
2.3%
incheon 7
 
1.5%
seongnam-si 6
 
1.2%
buk-gu 6
 
1.2%
gyeongsangbuk-do 6
 
1.2%
daegu 5
 
1.0%
anyang-si 5
 
1.0%
1-ro 5
 
1.0%
namyangju-si 5
 
1.0%
Other values (295) 391
81.3%
2023-12-10T18:47:09.068435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 454
 
9.4%
n 439
 
9.1%
g 397
 
8.2%
381
 
7.9%
, 348
 
7.2%
- 343
 
7.1%
e 280
 
5.8%
a 229
 
4.7%
u 225
 
4.7%
i 179
 
3.7%
Other values (45) 1551
32.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3089
64.0%
Space Separator 381
 
7.9%
Uppercase Letter 351
 
7.3%
Other Punctuation 348
 
7.2%
Dash Punctuation 343
 
7.1%
Decimal Number 314
 
6.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 454
14.7%
n 439
14.2%
g 397
12.9%
e 280
9.1%
a 229
7.4%
u 225
7.3%
i 179
 
5.8%
s 111
 
3.6%
y 107
 
3.5%
d 107
 
3.5%
Other values (13) 561
18.2%
Uppercase Letter
ValueCountFrequency (%)
G 88
25.1%
S 48
13.7%
J 40
11.4%
D 26
 
7.4%
B 25
 
7.1%
C 19
 
5.4%
H 18
 
5.1%
N 15
 
4.3%
A 14
 
4.0%
I 9
 
2.6%
Other values (9) 49
14.0%
Decimal Number
ValueCountFrequency (%)
1 68
21.7%
2 40
12.7%
4 32
10.2%
6 32
10.2%
3 29
9.2%
7 23
 
7.3%
5 23
 
7.3%
9 23
 
7.3%
0 22
 
7.0%
8 22
 
7.0%
Space Separator
ValueCountFrequency (%)
381
100.0%
Other Punctuation
ValueCountFrequency (%)
, 348
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 343
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3440
71.3%
Common 1386
28.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 454
13.2%
n 439
12.8%
g 397
11.5%
e 280
 
8.1%
a 229
 
6.7%
u 225
 
6.5%
i 179
 
5.2%
s 111
 
3.2%
y 107
 
3.1%
d 107
 
3.1%
Other values (32) 912
26.5%
Common
ValueCountFrequency (%)
381
27.5%
, 348
25.1%
- 343
24.7%
1 68
 
4.9%
2 40
 
2.9%
4 32
 
2.3%
6 32
 
2.3%
3 29
 
2.1%
7 23
 
1.7%
5 23
 
1.7%
Other values (3) 67
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4826
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 454
 
9.4%
n 439
 
9.1%
g 397
 
8.2%
381
 
7.9%
, 348
 
7.2%
- 343
 
7.1%
e 280
 
5.8%
a 229
 
4.7%
u 225
 
4.7%
i 179
 
3.7%
Other values (45) 1551
32.1%

adstrd_cd
Real number (ℝ)

Distinct91
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.6411513 × 109
Minimum1.1200102 × 109
Maximum5.0130106 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:47:09.386441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1200102 × 109
5-th percentile1.1345606 × 109
Q12.8243105 × 109
median4.1245677 × 109
Q34.4133105 × 109
95-th percentile4.8300864 × 109
Maximum5.0130106 × 109
Range3.8930004 × 109
Interquartile range (IQR)1.589 × 109

Descriptive statistics

Standard deviation1.1193881 × 109
Coefficient of variation (CV)0.30742696
Kurtosis0.21078643
Mean3.6411513 × 109
Median Absolute Deviation (MAD)4.8845605 × 108
Skewness-1.0939239
Sum3.6411513 × 1011
Variance1.2530296 × 1018
MonotonicityNot monotonic
2023-12-10T18:47:09.882684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4136025328 4
 
4.0%
4119010900 2
 
2.0%
4113110800 2
 
2.0%
1126010600 2
 
2.0%
4117310100 2
 
2.0%
4146510600 2
 
2.0%
4420036032 2
 
2.0%
1121510200 1
 
1.0%
4117110300 1
 
1.0%
2629010600 1
 
1.0%
Other values (81) 81
81.0%
ValueCountFrequency (%)
1120010200 1
1.0%
1121510200 1
1.0%
1123010900 1
1.0%
1126010600 2
2.0%
1135010600 1
1.0%
1138011400 1
1.0%
1150010900 1
1.0%
1153010200 1
1.0%
1153011000 1
1.0%
1174010800 1
1.0%
ValueCountFrequency (%)
5013010600 1
1.0%
5013010500 1
1.0%
5011025024 1
1.0%
5011012300 1
1.0%
4888025021 1
1.0%
4827037024 1
1.0%
4817012900 1
1.0%
4729025325 1
1.0%
4725032535 1
1.0%
4719025331 1
1.0%

buld_nm
Text

MISSING 

Distinct52
Distinct (%)96.3%
Missing46
Missing (%)46.0%
Memory size932.0 B
2023-12-10T18:47:10.893278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length11
Mean length6.962963
Min length2

Characters and Unicode

Total characters376
Distinct characters161
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

Unique50 ?
Unique (%)92.6%

Sample

1st row어린이대공원
2nd row청주랜드
3rd row중앙타워
4th row창의체험관
5th row펜타포트
ValueCountFrequency (%)
롯데몰성복점 2
 
2.9%
오피스텔 2
 
2.9%
아산테크노밸리이지더원6단지아파트 2
 
2.9%
롯데캐슬골드타운 2
 
2.9%
현대백화점 2
 
2.9%
중동점 1
 
1.4%
신내우디안프라자 1
 
1.4%
신아타운 1
 
1.4%
한우리교육문화센타 1
 
1.4%
김포운양헤리움타운 1
 
1.4%
Other values (55) 55
78.6%
2023-12-10T18:47:11.864994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16
 
4.3%
12
 
3.2%
10
 
2.7%
9
 
2.4%
9
 
2.4%
8
 
2.1%
8
 
2.1%
8
 
2.1%
8
 
2.1%
8
 
2.1%
Other values (151) 280
74.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 343
91.2%
Space Separator 16
 
4.3%
Uppercase Letter 9
 
2.4%
Decimal Number 4
 
1.1%
Other Punctuation 2
 
0.5%
Dash Punctuation 1
 
0.3%
Lowercase Letter 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12
 
3.5%
10
 
2.9%
9
 
2.6%
9
 
2.6%
8
 
2.3%
8
 
2.3%
8
 
2.3%
8
 
2.3%
8
 
2.3%
7
 
2.0%
Other values (137) 256
74.6%
Uppercase Letter
ValueCountFrequency (%)
W 2
22.2%
C 2
22.2%
J 1
11.1%
N 1
11.1%
M 1
11.1%
B 1
11.1%
K 1
11.1%
Decimal Number
ValueCountFrequency (%)
6 2
50.0%
1 1
25.0%
2 1
25.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 343
91.2%
Common 23
 
6.1%
Latin 10
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12
 
3.5%
10
 
2.9%
9
 
2.6%
9
 
2.6%
8
 
2.3%
8
 
2.3%
8
 
2.3%
8
 
2.3%
8
 
2.3%
7
 
2.0%
Other values (137) 256
74.6%
Latin
ValueCountFrequency (%)
W 2
20.0%
C 2
20.0%
J 1
10.0%
N 1
10.0%
e 1
10.0%
M 1
10.0%
B 1
10.0%
K 1
10.0%
Common
ValueCountFrequency (%)
16
69.6%
, 2
 
8.7%
6 2
 
8.7%
1 1
 
4.3%
- 1
 
4.3%
2 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 343
91.2%
ASCII 33
 
8.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16
48.5%
W 2
 
6.1%
C 2
 
6.1%
, 2
 
6.1%
6 2
 
6.1%
J 1
 
3.0%
N 1
 
3.0%
1 1
 
3.0%
- 1
 
3.0%
e 1
 
3.0%
Other values (4) 4
 
12.1%
Hangul
ValueCountFrequency (%)
12
 
3.5%
10
 
2.9%
9
 
2.6%
9
 
2.6%
8
 
2.3%
8
 
2.3%
8
 
2.3%
8
 
2.3%
8
 
2.3%
7
 
2.0%
Other values (137) 256
74.6%

buld_manage_cd
Real number (ℝ)

Distinct96
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.6411662 × 1024
Minimum1.1200102 × 1024
Maximum5.0130106 × 1024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:47:12.149897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1200102 × 1024
5-th percentile1.1345606 × 1024
Q12.8243105 × 1024
median4.1245677 × 1024
Q34.4133105 × 1024
95-th percentile4.8300864 × 1024
Maximum5.0130106 × 1024
Range3.8930004 × 1024
Interquartile range (IQR)1.589 × 1024

Descriptive statistics

Standard deviation1.1193945 × 1024
Coefficient of variation (CV)0.30742747
Kurtosis0.2107754
Mean3.6411662 × 1024
Median Absolute Deviation (MAD)4.8845605 × 1023
Skewness-1.0939384
Sum3.6411662 × 1026
Variance1.2530441 × 1048
MonotonicityNot monotonic
2023-12-10T18:47:12.429549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.1360253281107694e+24 3
 
3.0%
4.4200360321179295e+24 2
 
2.0%
4.1465106001002305e+24 2
 
2.0%
1.12151020010018e+24 1
 
1.0%
1.13501060010509e+24 1
 
1.0%
2.63201010011874e+24 1
 
1.0%
4.51111420011693e+24 1
 
1.0%
2.92001230010082e+24 1
 
1.0%
1.12301090010269e+24 1
 
1.0%
4.1173102001101903e+24 1
 
1.0%
Other values (86) 86
86.0%
ValueCountFrequency (%)
1.12001020010842e+24 1
1.0%
1.12151020010018e+24 1
1.0%
1.12301090010269e+24 1
1.0%
1.12601060010255e+24 1
1.0%
1.12601060010666e+24 1
1.0%
1.13501060010509e+24 1
1.0%
1.13801140010061e+24 1
1.0%
1.15001090010829e+24 1
1.0%
1.15301020010552e+24 1
1.0%
1.15301100010011e+24 1
1.0%
ValueCountFrequency (%)
5.01301060010259e+24 1
1.0%
5.01301050010498e+24 1
1.0%
5.011025024012e+24 1
1.0%
5.01101230010445e+24 1
1.0%
4.88802502110064e+24 1
1.0%
4.8270370241024496e+24 1
1.0%
4.81701290010097e+24 1
1.0%
4.7290253251011e+24 1
1.0%
4.7250320351000305e+24 1
1.0%
4.71902533110448e+24 1
1.0%

tel_no
Text

MISSING 

Distinct79
Distinct (%)96.3%
Missing18
Missing (%)18.0%
Memory size932.0 B
2023-12-10T18:47:12.899245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.146341
Min length11

Characters and Unicode

Total characters996
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

Unique76 ?
Unique (%)92.7%

Sample

1st row02-450-9311
2nd row031-5183-3200
3rd row054-536-3686
4th row031-528-4124
5th row064-763-3655
ValueCountFrequency (%)
031-8049-2095 2
 
2.4%
031-5174-4327 2
 
2.4%
041-547-9031 2
 
2.4%
061-802-2010 1
 
1.2%
031-342-8585 1
 
1.2%
032-437-8005 1
 
1.2%
051-625-1561 1
 
1.2%
051-363-9087 1
 
1.2%
063-225-6793 1
 
1.2%
062-956-6677 1
 
1.2%
Other values (69) 69
84.1%
2023-12-10T18:47:13.703705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 164
16.5%
0 150
15.1%
3 103
10.3%
2 92
9.2%
1 90
9.0%
7 85
8.5%
5 81
8.1%
6 66
6.6%
4 62
 
6.2%
9 55
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 832
83.5%
Dash Punctuation 164
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 150
18.0%
3 103
12.4%
2 92
11.1%
1 90
10.8%
7 85
10.2%
5 81
9.7%
6 66
7.9%
4 62
7.5%
9 55
 
6.6%
8 48
 
5.8%
Dash Punctuation
ValueCountFrequency (%)
- 164
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 996
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 164
16.5%
0 150
15.1%
3 103
10.3%
2 92
9.2%
1 90
9.0%
7 85
8.5%
5 81
8.1%
6 66
6.6%
4 62
 
6.2%
9 55
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 996
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 164
16.5%
0 150
15.1%
3 103
10.3%
2 92
9.2%
1 90
9.0%
7 85
8.5%
5 81
8.1%
6 66
6.6%
4 62
 
6.2%
9 55
 
5.5%

zip_no
Real number (ℝ)

Distinct96
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28562.13
Minimum1783
Maximum63587
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:47:13.999826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1783
5-th percentile4631.25
Q113866.25
median22029
Q343124.75
95-th percentile61301.6
Maximum63587
Range61804
Interquartile range (IQR)29258.5

Descriptive statistics

Standard deviation18459.23
Coefficient of variation (CV)0.64628337
Kurtosis-1.0732852
Mean28562.13
Median Absolute Deviation (MAD)11866.5
Skewness0.47168999
Sum2856213
Variance3.4074316 × 108
MonotonicityNot monotonic
2023-12-10T18:47:14.307201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12057 3
 
3.0%
31406 2
 
2.0%
16847 2
 
2.0%
4991 1
 
1.0%
1783 1
 
1.0%
46519 1
 
1.0%
54963 1
 
1.0%
62244 1
 
1.0%
2496 1
 
1.0%
14055 1
 
1.0%
Other values (86) 86
86.0%
ValueCountFrequency (%)
1783 1
1.0%
2055 1
1.0%
2076 1
1.0%
2496 1
1.0%
3306 1
1.0%
4701 1
1.0%
4991 1
1.0%
5386 1
1.0%
7510 1
1.0%
8260 1
1.0%
ValueCountFrequency (%)
63587 1
1.0%
63578 1
1.0%
63069 1
1.0%
63032 1
1.0%
62244 1
1.0%
61252 1
1.0%
61087 1
1.0%
59118 1
1.0%
58676 1
1.0%
58662 1
1.0%

hmpg_url
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

fclty_la
Real number (ℝ)

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.614804
Minimum33.255157
Maximum37.811445
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:47:14.659572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.255157
5-th percentile34.782885
Q135.839965
median37.302146
Q337.494813
95-th percentile37.71732
Maximum37.811445
Range4.5562879
Interquartile range (IQR)1.6548478

Descriptive statistics

Standard deviation1.1437651
Coefficient of variation (CV)0.031237777
Kurtosis0.62301783
Mean36.614804
Median Absolute Deviation (MAD)0.37590675
Skewness-1.1388938
Sum3661.4804
Variance1.3081986
MonotonicityNot monotonic
2023-12-10T18:47:14.924451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.7173205 3
 
3.0%
36.9262396 2
 
2.0%
37.5495607 1
 
1.0%
37.6192555 1
 
1.0%
35.8194305 1
 
1.0%
35.2037472 1
 
1.0%
37.5895826 1
 
1.0%
37.3966413 1
 
1.0%
37.3990458 1
 
1.0%
35.2065551 1
 
1.0%
Other values (87) 87
87.0%
ValueCountFrequency (%)
33.255157 1
1.0%
33.2645917 1
1.0%
33.4125735 1
1.0%
33.4905329 1
1.0%
34.3189026 1
1.0%
34.8073046 1
1.0%
34.8109068 1
1.0%
34.9347215 1
1.0%
35.0993751 1
1.0%
35.1380513 1
1.0%
ValueCountFrequency (%)
37.8114449 1
 
1.0%
37.7198288 1
 
1.0%
37.7189825 1
 
1.0%
37.7173205 3
3.0%
37.6542595 1
 
1.0%
37.6466419 1
 
1.0%
37.6459292 1
 
1.0%
37.6399187 1
 
1.0%
37.6391556 1
 
1.0%
37.6192555 1
 
1.0%

fclty_lo
Real number (ℝ)

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.35948
Minimum126.2644
Maximum129.3624
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:47:15.185572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.2644
5-th percentile126.55404
Q1126.84754
median127.1018
Q3127.51621
95-th percentile129.11644
Maximum129.3624
Range3.0979987
Interquartile range (IQR)0.66866597

Descriptive statistics

Standard deviation0.78896534
Coefficient of variation (CV)0.0061947907
Kurtosis0.49299373
Mean127.35948
Median Absolute Deviation (MAD)0.2881556
Skewness1.2755959
Sum12735.948
Variance0.62246631
MonotonicityNot monotonic
2023-12-10T18:47:15.464248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1934865 3
 
3.0%
127.0553813 2
 
2.0%
127.0810294 1
 
1.0%
127.106544 1
 
1.0%
127.1025575 1
 
1.0%
126.8143844 1
 
1.0%
127.0613504 1
 
1.0%
126.9669997 1
 
1.0%
126.9015123 1
 
1.0%
126.8625018 1
 
1.0%
Other values (87) 87
87.0%
ValueCountFrequency (%)
126.2643986 1
1.0%
126.425831 1
1.0%
126.4306891 1
1.0%
126.4450082 1
1.0%
126.4864246 1
1.0%
126.5575958 1
1.0%
126.5736139 1
1.0%
126.6520433 1
1.0%
126.6848617 1
1.0%
126.7026244 1
1.0%
ValueCountFrequency (%)
129.3623973 1
1.0%
129.3205123 1
1.0%
129.2896083 1
1.0%
129.2163609 1
1.0%
129.2019361 1
1.0%
129.1119449 1
1.0%
129.1070815 1
1.0%
129.0112569 1
1.0%
128.9571736 1
1.0%
128.8261032 1
1.0%

origin_nm
Categorical

CONSTANT 

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

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
문화정보원 100
100.0%

Length

2023-12-10T18:47:15.732977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:47:16.006899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문화정보원 100
100.0%

water_ply_fclty_at
Boolean

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
False
98 
True
 
2
ValueCountFrequency (%)
False 98
98.0%
True 2
 
2.0%
2023-12-10T18:47:16.154038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

adit_dc
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing97
Missing (%)97.0%
Memory size932.0 B
2023-12-10T18:47:16.475820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length96
Median length95
Mean length94.666667
Min length93

Characters and Unicode

Total characters284
Distinct characters62
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

Unique3 ?
Unique (%)100.0%

Sample

1st row설치일자: 2020-11-06,시설분류: 어린이집,안전검사: 검사완료,안전교육: 미이수,보험가입: 미가입,놀이기구: 흔들놀이기구 1개,충격흡수용표면재(포설도포바닥재) 1개
2nd row설치일자: 2020-11-01,시설분류: 식품접객업소,안전검사: 검사완료,안전교육: 미이수,보험가입: 미가입,놀이기구: 폐쇄형놀이기구 1개,충격흡수용표면재(기타바닥재) 1개
3rd row설치일자: 2020-10-26,시설분류: 어린이집,안전검사: 검사완료,안전교육: 미이수,보험가입: 미가입,놀이기구: 흔들놀이기구 1개,충격흡수용표면재(기타바닥재) 1개
ValueCountFrequency (%)
설치일자 3
11.1%
검사완료,안전교육 3
11.1%
미이수,보험가입 3
11.1%
미가입,놀이기구 3
11.1%
1개 3
11.1%
어린이집,안전검사 2
7.4%
흔들놀이기구 2
7.4%
1개,충격흡수용표면재(기타바닥재 2
7.4%
2020-11-06,시설분류 1
 
3.7%
1개,충격흡수용표면재(포설도포바닥재 1
 
3.7%
Other values (4) 4
14.8%
2023-12-10T18:47:17.143622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24
 
8.5%
, 18
 
6.3%
: 18
 
6.3%
1 12
 
4.2%
11
 
3.9%
0 9
 
3.2%
8
 
2.8%
7
 
2.5%
2 7
 
2.5%
6
 
2.1%
Other values (52) 164
57.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 182
64.1%
Other Punctuation 36
 
12.7%
Decimal Number 30
 
10.6%
Space Separator 24
 
8.5%
Dash Punctuation 6
 
2.1%
Close Punctuation 3
 
1.1%
Open Punctuation 3
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11
 
6.0%
8
 
4.4%
7
 
3.8%
6
 
3.3%
6
 
3.3%
6
 
3.3%
6
 
3.3%
6
 
3.3%
6
 
3.3%
6
 
3.3%
Other values (42) 114
62.6%
Decimal Number
ValueCountFrequency (%)
1 12
40.0%
0 9
30.0%
2 7
23.3%
6 2
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 18
50.0%
: 18
50.0%
Space Separator
ValueCountFrequency (%)
24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 182
64.1%
Common 102
35.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11
 
6.0%
8
 
4.4%
7
 
3.8%
6
 
3.3%
6
 
3.3%
6
 
3.3%
6
 
3.3%
6
 
3.3%
6
 
3.3%
6
 
3.3%
Other values (42) 114
62.6%
Common
ValueCountFrequency (%)
24
23.5%
, 18
17.6%
: 18
17.6%
1 12
11.8%
0 9
 
8.8%
2 7
 
6.9%
- 6
 
5.9%
) 3
 
2.9%
( 3
 
2.9%
6 2
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 182
64.1%
ASCII 102
35.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24
23.5%
, 18
17.6%
: 18
17.6%
1 12
11.8%
0 9
 
8.8%
2 7
 
6.9%
- 6
 
5.9%
) 3
 
2.9%
( 3
 
2.9%
6 2
 
2.0%
Hangul
ValueCountFrequency (%)
11
 
6.0%
8
 
4.4%
7
 
3.8%
6
 
3.3%
6
 
3.3%
6
 
3.3%
6
 
3.3%
6
 
3.3%
6
 
3.3%
6
 
3.3%
Other values (42) 114
62.6%

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

2023-12-10T18:47:17.404173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:47:17.656641image/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

2023-12-10T18:47:17.839351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:47:18.047032image/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_nmwater_ply_fclty_atadit_dcupdt_dtregist_dt
0KCIPFPO20N000000001문화시설문화시설_유원시설_어린이어린이대공원11서울특별시11215광진구<NA>능동112153104007서울 광진구 능동로 216서울 광진구 능동 18216, Neungdong-ro, Gwangjin-gu, Seoul1121510200어린이대공원112151020010018000000562502-450-93114991<NA>37.549561127.081029문화정보원N<NA>2020120112000020201201120000
1KCIPFPO20N000048481문화시설문화시설_놀이터_실내두산판교어린이집 실외놀이터41경기도41135성남시 분당구<NA>정자동411353180021경기 성남시 분당구 정자일로 155경기 성남시 분당구 정자동 161-1155, Jeongjail-ro, Bundang-gu, Seongnam-si, Gyeonggi-do4113510300<NA>4113510300101610000000001<NA>13557<NA>37.364562127.105687문화정보원N설치일자: 2020-11-06,시설분류: 어린이집,안전검사: 검사완료,안전교육: 미이수,보험가입: 미가입,놀이기구: 흔들놀이기구 1개,충격흡수용표면재(포설도포바닥재) 1개2020120112000020201201120000
2KCIPFPO20N000000003문화시설문화시설_유원시설_어린이화성시 어린이문화센터41경기도41590화성시<NA>봉담읍415904430329경기도 화성시 봉담읍 동화길 146경기도 화성시 봉담읍 동화리 590146, Donghwa-gil, Bongdam-eup, Hwaseong-si, Gyeonggi-do4159025324<NA>4159025324105900000000001031-5183-320018316<NA>37.212371126.960715문화정보원N<NA>2020120112000020201201120000
3KCIPFPO20N000000004문화시설문화시설_유원시설_어린이경천대 어린이랜드47경상북도47250상주시<NA>사벌국면 삼덕리472503311003경상북도 상주시 사벌국면 경천로 652-18경북 상주시 사벌국면 삼덕리 3-2652-18, Gyeongcheon-ro, Sabeolgung-myeon, Sangju-si, Gyeongsangbuk-do4725032535<NA>4725032035100030002016504054-536-368637128<NA>36.455462128.243677문화정보원N<NA>2020120112000020201201120000
4KCIPFPO20N000000005문화시설문화시설_유원시설_어린이어린이비전센터 라바파크41경기도41360남양주시<NA>진접읍413603197065경기도 남양주시 진접읍 해밀예당1로 96경기도 남양주시 진접읍 금곡리 107796, Haemiryedang 1-ro, Jinjeop-eup, Namyangju-si, Gyeonggi-do4136025328<NA>4136025328110770000000001031-528-412412057<NA>37.71732127.193487문화정보원N<NA>2020120112000020201201120000
5KCIPFPO20N000000006문화시설문화시설_유원시설_어린이어린이회관회전목마43충청북도43111청주시 상당구<NA>명암동431113236016충청북도 청주시 상당구 명암로 171충북 청주시 상당구 명암동 70171, Myeongam-ro, Sangdang-gu, Cheongju-si, Chungcheongbuk-do4311112200청주랜드4311112200100700000050392<NA>28311<NA>36.651109127.51652문화정보원N<NA>2020120112000020201201120000
6KCIPFPO20N000000007문화시설문화시설_유원시설_어린이어린이나라방방50제주특별자치도50130서귀포시<NA>동홍동501304850209제주특별자치도 서귀포시 일주동로 8560제주특별자치도 서귀포시 동홍동 498-114-1, Donghongjungang-ro 52beon-gil, Seogwipo-si, Jeju-do5013010500<NA>5013010500104980001001703064-763-365563587<NA>33.255157126.573614문화정보원N<NA>2020120112000020201201120000
7KCIPFPO20N000048482문화시설문화시설_놀이터_실내한사리 위례점 실내놀이시설41경기도41131성남시 수정구<NA>창곡동411313000238경기도 성남시 수정구 위례광장로 300 (창곡동)경기도 성남시 수정구 창곡동 509 중앙타워300, Wiryegwangjang-ro, Sujeong-gu, Seongnam-si, Gyeonggi-do4113110800중앙타워4113110800104980021000001<NA>13640<NA>37.473472127.142736문화정보원N설치일자: 2020-11-01,시설분류: 식품접객업소,안전검사: 검사완료,안전교육: 미이수,보험가입: 미가입,놀이기구: 폐쇄형놀이기구 1개,충격흡수용표면재(기타바닥재) 1개2020120112000020201201120000
8KCIPFPO20N000000009문화시설문화시설_유원시설_어린이어린이비전센터 야외물놀이장41경기도41360남양주시<NA>진접읍413603197065경기도 남양주시 진접읍 해밀예당1로 96경기도 남양주시 진접읍 금곡리 107796, Haemiryedang 1-ro, Jinjeop-eup, Namyangju-si, Gyeonggi-do4136025328<NA>4136025328110770000000001031-560-151212057<NA>37.71732127.193487문화정보원Y<NA>2020120112000020201201120000
9KCIPFPO20N000000010문화시설문화시설_유원시설_어린이남양주도시공사 어린이비젼센터41경기도41360남양주시<NA>진접읍413603197065경기도 남양주시 진접읍 해밀예당1로 96경기도 남양주시 진접읍 금곡리 107796, Haemiryedang 1-ro, Jinjeop-eup, Namyangju-si, Gyeonggi-do4136025328<NA>4136025328110770000000001<NA>12057<NA>37.71732127.193487문화정보원N<NA>2020120112000020201201120000
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_nmwater_ply_fclty_atadit_dcupdt_dtregist_dt
90KCIPFPO20N000000091문화시설문화시설_유원시설_어린이키즈까페 어린왕자 목포46전라남도46110목포시<NA>상동461103281056전남 목포시 옥암로 95전남 목포시 상동 860-195, Ogam-ro, Mokpo-si, Jeollanam-do4611015800쇼핑천국포르모4611015800108600001026030061-802-201058662<NA>34.807305126.425831문화정보원N<NA>2020120112000020201201120000
91KCIPFPO20N000000092문화시설문화시설_유원시설_어린이러블리베베 키즈카페 목포46전라남도46110목포시<NA>옥암동461102281005전남 목포시 후광대로 110전남 목포시 옥암동 1225-1110, Hugwang-daero, Mokpo-si, Jeollanam-do4611016400디 타워4611016400112250001000001061-282-787958676<NA>34.810907126.445008문화정보원N<NA>2020120112000020201201120000
92KCIPFPO20N000000093문화시설문화시설_유원시설_어린이키즈다쿵 순천46전라남도46150순천시<NA>해룡면 신대리461504650212전남 순천시 해룡면 신대4길 4-57전남 순천시 해룡면 신대리 19834-57, Sindae 4-gil, Haeryong-myeon, Suncheon-si, Jeollanam-do4615031022<NA>4615031022119830000000001061-723-717958011<NA>34.934722127.551986문화정보원N<NA>2020120112000020201201120000
93KCIPFPO20N000000094문화시설문화시설_유원시설_어린이타요키즈카페 원주단계점42강원도42130원주시<NA>단계동421304517934강원도 원주시 바우골길 5 (단계동)강원도 원주시 단계동 1186-45, Baugol-gil, Wonju-si, Gangwon-do4213011000<NA>4213011000111860004000001033-735-197726379<NA>37.355816127.918509문화정보원N<NA>2020120112000020201201120000
94KCIPFPO20N000000095문화시설문화시설_유원시설_어린이아이점프키즈카페 진량점47경상북도47290경산시<NA>진량읍 북리472904721501경북 경산시 진량읍 봉황길 75경북 경산시 진량읍 북리 11075, Bonghwang-gil, Jillyang-eup, Gyeongsan-si, Gyeongsangbuk-do4729025325<NA>4729025325101100000000001053-856-127738450<NA>35.883692128.826103문화정보원N<NA>2020120112000020201201120000
95KCIPFPO20N000000096문화시설문화시설_유원시설_어린이아이편키즈카페27대구광역시27290달서구<NA>이곡동272903147034대구 달서구 이곡동로 11대구 달서구 이곡동 1246-611, Igokdong-ro, Dalseo-gu, Daegu2729010800<NA>2729010800112460006000001<NA>42620<NA>35.854282128.508717문화정보원N<NA>2020120112000020201201120000
96KCIPFPO20N000000097문화시설문화시설_유원시설_어린이소풍키즈카페 서귀포50제주특별자치도50130서귀포시<NA>서홍동501303349238제주특별자치도 서귀포시 중산간동로 8044-4제주특별자치도 서귀포시 서홍동 259-198044-4, Jungsangandong-ro, Seogwipo-si, Jeju-do5013010600<NA>5013010600102590019023417064-762-002063578<NA>33.264592126.557596문화정보원N<NA>2020120112000020201201120000
97KCIPFPO20N000000098문화시설문화시설_유원시설_어린이비쥬베베 키즈카페50제주특별자치도50110제주시<NA>외도일동501103349160제주특별자치도 제주시 우정로 26제주특별자치도 제주시 외도일동 445-726, Ujeong-ro, Jeju-si, Jeju-do5011012300<NA>5011012300104450007000001064-712-838563069<NA>33.490533126.430689문화정보원N<NA>2020120112000020201201120000
98KCIPFPO20N000000099문화시설문화시설_유원시설_어린이어린왕자(키즈파크)43충청북도43750진천군<NA>광혜원면 광혜원리437504535026충북 진천군 광혜원면 광혜원산단길 141충북 진천군 광혜원면 광혜원리 560141, Gwanghyewonsandan-gil, Gwanghyewon-myeon, Jincheon-gun, Chungcheongbuk-do4375037027JK빌딩4375037027105600000000001043-532-623327804<NA>36.990156127.437824문화정보원N<NA>2020120112000020201201120000
99KCIPFPO20N000000100문화시설문화시설_유원시설_어린이요미요미 키즈카페 제주50제주특별자치도50110제주시<NA>한림읍 한림리501104848994제주특별자치도 제주시 한림읍 한림남2길 4제주특별자치도 제주시 한림읍 한림리 1200-124, Hallimnam 2-gil, Hallim-eup, Jeju-si, Jeju-do5011025024<NA>5011025024012000012006522064-796-646463032<NA>33.412574126.264399문화정보원N<NA>2020120112000020201201120000