Overview

Dataset statistics

Number of variables36
Number of observations100
Missing cells6
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.4 KiB
Average record size in memory301.3 B

Variable types

Text6
Categorical17
Numeric10
DateTime1
Boolean2

Alerts

lclas has constant value ""Constant
mlsfc has constant value ""Constant
lst_updt_dt has constant value ""Constant
data_orgn has constant value ""Constant
FILE_NAME has constant value ""Constant
base_ymd has constant value ""Constant
repr_bnch_instl_yn is highly imbalanced (71.4%)Imbalance
frnsh_cnt has 5 (5.0%) missing valuesMissing
id has unique valuesUnique
frnsh_cnt has 3 (3.0%) zerosZeros

Reproduction

Analysis started2023-12-10 10:06:48.827209
Analysis finished2023-12-10 10:06:50.106394
Duration1.28 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

id
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:06:50.396804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length16
Min length16

Characters and Unicode

Total characters1600
Distinct characters14
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 rowKC487PC19N000001
2nd rowKC487PC19N000002
3rd rowKC487PC19N000003
4th rowKC487PC19N000004
5th rowKC487PC19N000005
ValueCountFrequency (%)
kc487pc19n000001 1
 
1.0%
kc487pc19n000063 1
 
1.0%
kc487pc19n000074 1
 
1.0%
kc487pc19n000073 1
 
1.0%
kc487pc19n000072 1
 
1.0%
kc487pc19n000071 1
 
1.0%
kc487pc19n000070 1
 
1.0%
kc487pc19n000069 1
 
1.0%
kc487pc19n000068 1
 
1.0%
kc487pc19n000067 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T19:06:51.106539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 419
26.2%
C 200
12.5%
1 123
 
7.7%
4 120
 
7.5%
7 120
 
7.5%
8 119
 
7.4%
9 119
 
7.4%
K 100
 
6.2%
P 100
 
6.2%
N 100
 
6.2%
Other values (4) 80
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1100
68.8%
Uppercase Letter 500
31.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 419
38.1%
1 123
 
11.2%
4 120
 
10.9%
7 120
 
10.9%
8 119
 
10.8%
9 119
 
10.8%
3 20
 
1.8%
5 20
 
1.8%
6 20
 
1.8%
2 20
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
C 200
40.0%
K 100
20.0%
P 100
20.0%
N 100
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1100
68.8%
Latin 500
31.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 419
38.1%
1 123
 
11.2%
4 120
 
10.9%
7 120
 
10.9%
8 119
 
10.8%
9 119
 
10.8%
3 20
 
1.8%
5 20
 
1.8%
6 20
 
1.8%
2 20
 
1.8%
Latin
ValueCountFrequency (%)
C 200
40.0%
K 100
20.0%
P 100
20.0%
N 100
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1600
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 419
26.2%
C 200
12.5%
1 123
 
7.7%
4 120
 
7.5%
7 120
 
7.5%
8 119
 
7.4%
9 119
 
7.4%
K 100
 
6.2%
P 100
 
6.2%
N 100
 
6.2%
Other values (4) 80
 
5.0%

lclas
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
레포츠 100
100.0%

Length

2023-12-10T19:06:51.342930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:06:51.493923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
레포츠 100
100.0%

mlsfc
Categorical

CONSTANT 

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

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row체육시설(공공)
2nd row체육시설(공공)
3rd row체육시설(공공)
4th row체육시설(공공)
5th row체육시설(공공)

Common Values

ValueCountFrequency (%)
체육시설(공공) 100
100.0%

Length

2023-12-10T19:06:51.664000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:06:51.819958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
체육시설(공공 100
100.0%

fclt_name
Text

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:06:52.616347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length17
Mean length9.5
Min length3

Characters and Unicode

Total characters950
Distinct characters178
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

Unique98 ?
Unique (%)98.0%

Sample

1st row무심천 청남교 옆 하천둔치
2nd row두바퀴쉼터
3rd row금강신관공원 유인대여소
4th row공산성
5th row공주시청
ValueCountFrequency (%)
무인대여소 9
 
4.8%
대여소 7
 
3.8%
입구 5
 
2.7%
영주시 5
 
2.7%
앞 4
 
2.2%
자전거 4
 
2.2%
공공자전거무인대여소 4
 
2.2%
주차장 4
 
2.2%
옆 2
 
1.1%
금강신관공원 2
 
1.1%
Other values (132) 140
75.3%
2023-12-10T19:06:53.407414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
86
 
9.1%
대 51
 
5.4%
여 47
 
4.9%
소 46
 
4.8%
공 37
 
3.9%
무 33
 
3.5%
인 27
 
2.8%
거 26
 
2.7%
동 26
 
2.7%
주 21
 
2.2%
Other values (168) 550
57.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 857
90.2%
Space Separator 86
 
9.1%
Decimal Number 4
 
0.4%
Uppercase Letter 2
 
0.2%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 51
 
6.0%
여 47
 
5.5%
소 46
 
5.4%
공 37
 
4.3%
무 33
 
3.9%
인 27
 
3.2%
거 26
 
3.0%
동 26
 
3.0%
주 21
 
2.5%
원 21
 
2.5%
Other values (162) 522
60.9%
Decimal Number
ValueCountFrequency (%)
2 3
75.0%
1 1
 
25.0%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
G 1
50.0%
Space Separator
ValueCountFrequency (%)
86
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 857
90.2%
Common 91
 
9.6%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 51
 
6.0%
여 47
 
5.5%
소 46
 
5.4%
공 37
 
4.3%
무 33
 
3.9%
인 27
 
3.2%
거 26
 
3.0%
동 26
 
3.0%
주 21
 
2.5%
원 21
 
2.5%
Other values (162) 522
60.9%
Common
ValueCountFrequency (%)
86
94.5%
2 3
 
3.3%
1 1
 
1.1%
) 1
 
1.1%
Latin
ValueCountFrequency (%)
S 1
50.0%
G 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 857
90.2%
ASCII 93
 
9.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
86
92.5%
2 3
 
3.2%
1 1
 
1.1%
) 1
 
1.1%
S 1
 
1.1%
G 1
 
1.1%
Hangul
ValueCountFrequency (%)
대 51
 
6.0%
여 47
 
5.5%
소 46
 
5.4%
공 37
 
4.3%
무 33
 
3.9%
인 27
 
3.2%
거 26
 
3.0%
동 26
 
3.0%
주 21
 
2.5%
원 21
 
2.5%
Other values (162) 522
60.9%

ctprvn_nm
Categorical

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
전라남도
31 
충청남도
21 
경상남도
16 
경상북도
7 
부산광역시
5 
Other values (7)
20 

Length

Max length7
Median length4
Mean length4.19
Min length3

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row충청북도
2nd row서울특별시
3rd row충청남도
4th row충청남도
5th row충청남도

Common Values

ValueCountFrequency (%)
전라남도 31
31.0%
충청남도 21
21.0%
경상남도 16
16.0%
경상북도 7
 
7.0%
부산광역시 5
 
5.0%
강원도 5
 
5.0%
제주특별자치도 5
 
5.0%
서울특별시 4
 
4.0%
경기도 2
 
2.0%
광주광역시 2
 
2.0%
Other values (2) 2
 
2.0%

Length

2023-12-10T19:06:53.666195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전라남도 31
31.0%
충청남도 21
21.0%
경상남도 16
16.0%
경상북도 7
 
7.0%
부산광역시 5
 
5.0%
강원도 5
 
5.0%
제주특별자치도 5
 
5.0%
서울특별시 4
 
4.0%
경기도 2
 
2.0%
광주광역시 2
 
2.0%
Other values (2) 2
 
2.0%

sgnr_nm
Categorical

Distinct23
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
여수시
31 
공주시
21 
거창군
13 
제주시
5 
영주시
5 
Other values (18)
25 

Length

Max length7
Median length3
Mean length3.08
Min length2

Unique

Unique12 ?
Unique (%)12.0%

Sample

1st row청주시 서원구
2nd row서대문구
3rd row공주시
4th row공주시
5th row공주시

Common Values

ValueCountFrequency (%)
여수시 31
31.0%
공주시 21
21.0%
거창군 13
13.0%
제주시 5
 
5.0%
영주시 5
 
5.0%
사천시 3
 
3.0%
고성군 2
 
2.0%
북구 2
 
2.0%
영도구 2
 
2.0%
서대문구 2
 
2.0%
Other values (13) 14
14.0%

Length

2023-12-10T19:06:53.893358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
여수시 31
30.4%
공주시 21
20.6%
거창군 13
12.7%
제주시 5
 
4.9%
영주시 5
 
4.9%
사천시 3
 
2.9%
서대문구 2
 
2.0%
춘천시 2
 
2.0%
영도구 2
 
2.0%
북구 2
 
2.0%
Other values (15) 16
15.7%

legaldong_cd
Real number (ℝ)

Distinct70
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3377989 × 109
Minimum1.1410117 × 109
Maximum5.0110137 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:06:54.159375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1410117 × 109
5-th percentile2.6200121 × 109
Q14.4150107 × 109
median4.613012 × 109
Q34.7210102 × 109
95-th percentile4.8941743 × 109
Maximum5.0110137 × 109
Range3.870002 × 109
Interquartile range (IQR)3.059995 × 108

Descriptive statistics

Standard deviation8.3901797 × 108
Coefficient of variation (CV)0.19342021
Kurtosis6.9467977
Mean4.3377989 × 109
Median Absolute Deviation (MAD)1.980011 × 108
Skewness-2.6962277
Sum4.3377989 × 1011
Variance7.0395115 × 1017
MonotonicityNot monotonic
2023-12-10T19:06:54.473567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4415012000 8
 
8.0%
4613012800 6
 
6.0%
4888025023 4
 
4.0%
4613012100 3
 
3.0%
4415010700 3
 
3.0%
4888025024 2
 
2.0%
4613010200 2
 
2.0%
1141011700 2
 
2.0%
4613013100 2
 
2.0%
4613013500 2
 
2.0%
Other values (60) 66
66.0%
ValueCountFrequency (%)
1141011700 2
2.0%
1168010500 1
1.0%
1174010200 1
1.0%
2620012100 2
2.0%
2626010900 1
1.0%
2635010400 1
1.0%
2641010900 1
1.0%
2917010700 1
1.0%
2917010800 1
1.0%
4141010600 1
1.0%
ValueCountFrequency (%)
5011013700 2
2.0%
5011012200 1
 
1.0%
5011012000 1
 
1.0%
5011010500 1
 
1.0%
4888025032 1
 
1.0%
4888025031 1
 
1.0%
4888025026 1
 
1.0%
4888025025 1
 
1.0%
4888025024 2
2.0%
4888025023 4
4.0%

legalemd_nm
Text

Distinct61
Distinct (%)61.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:06:54.884018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9
Min length2

Characters and Unicode

Total characters290
Distinct characters83
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)46.0%

Sample

1st row모충동
2nd row연희동
3rd row신관동
4th row금성동
5th row봉황동
ValueCountFrequency (%)
거창읍 13
 
13.0%
신관동 8
 
8.0%
학동 6
 
6.0%
웅진동 3
 
3.0%
오림동 3
 
3.0%
축동면 3
 
3.0%
연동 2
 
2.0%
선원동 2
 
2.0%
소호동 2
 
2.0%
국동 2
 
2.0%
Other values (51) 56
56.0%
2023-12-10T19:06:55.553416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 81
27.9%
읍 15
 
5.2%
거 13
 
4.5%
창 13
 
4.5%
신 10
 
3.4%
면 10
 
3.4%
관 8
 
2.8%
학 7
 
2.4%
정 5
 
1.7%
삼 4
 
1.4%
Other values (73) 124
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 290
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 81
27.9%
읍 15
 
5.2%
거 13
 
4.5%
창 13
 
4.5%
신 10
 
3.4%
면 10
 
3.4%
관 8
 
2.8%
학 7
 
2.4%
정 5
 
1.7%
삼 4
 
1.4%
Other values (73) 124
42.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 290
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 81
27.9%
읍 15
 
5.2%
거 13
 
4.5%
창 13
 
4.5%
신 10
 
3.4%
면 10
 
3.4%
관 8
 
2.8%
학 7
 
2.4%
정 5
 
1.7%
삼 4
 
1.4%
Other values (73) 124
42.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 290
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 81
27.9%
읍 15
 
5.2%
거 13
 
4.5%
창 13
 
4.5%
신 10
 
3.4%
면 10
 
3.4%
관 8
 
2.8%
학 7
 
2.4%
정 5
 
1.7%
삼 4
 
1.4%
Other values (73) 124
42.8%

adstrd_cd
Real number (ℝ)

Distinct52
Distinct (%)52.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3378376 × 109
Minimum1.1410615 × 109
Maximum5.011066 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:06:55.824086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1410615 × 109
5-th percentile2.620067 × 109
Q14.415054 × 109
median4.6130625 × 109
Q34.721034 × 109
95-th percentile4.8941765 × 109
Maximum5.011066 × 109
Range3.8700045 × 109
Interquartile range (IQR)3.0598 × 108

Descriptive statistics

Standard deviation8.3901252 × 108
Coefficient of variation (CV)0.19341723
Kurtosis6.946909
Mean4.3378376 × 109
Median Absolute Deviation (MAD)1.980065 × 108
Skewness-2.696254
Sum4.3378376 × 1011
Variance7.0394201 × 1017
MonotonicityNot monotonic
2023-12-10T19:06:56.092657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4888025000 13
 
13.0%
4613078000 8
 
8.0%
4415057000 7
 
7.0%
4415054000 5
 
5.0%
4415051000 3
 
3.0%
4613080000 3
 
3.0%
4415059000 3
 
3.0%
4824034000 3
 
3.0%
4613062500 3
 
3.0%
4613079000 2
 
2.0%
Other values (42) 50
50.0%
ValueCountFrequency (%)
1141061500 2
2.0%
1168059000 1
1.0%
1174056000 1
1.0%
2620067000 2
2.0%
2626060000 1
1.0%
2635065000 1
1.0%
2641057000 1
1.0%
2917059000 1
1.0%
2917061500 1
1.0%
4141061000 1
1.0%
ValueCountFrequency (%)
5011066000 1
 
1.0%
5011065000 2
 
2.0%
5011064000 1
 
1.0%
5011055000 1
 
1.0%
4888025000 13
13.0%
4824034000 3
 
3.0%
4721063000 1
 
1.0%
4721062000 1
 
1.0%
4721056000 1
 
1.0%
4721037000 1
 
1.0%

adstrd_nm
Text

Distinct52
Distinct (%)52.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:06:56.437613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.19
Min length2

Characters and Unicode

Total characters319
Distinct characters86
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

Unique34 ?
Unique (%)34.0%

Sample

1st row모충동
2nd row연희동
3rd row신관동
4th row웅진동
5th row중학동
ValueCountFrequency (%)
거창읍 13
 
13.0%
쌍봉동 8
 
8.0%
신관동 7
 
7.0%
웅진동 5
 
5.0%
여천동 3
 
3.0%
중학동 3
 
3.0%
월송동 3
 
3.0%
광림동 3
 
3.0%
축동면 3
 
3.0%
옥룡동 2
 
2.0%
Other values (42) 50
50.0%
2023-12-10T19:06:57.016219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 81
25.4%
읍 15
 
4.7%
거 13
 
4.1%
창 13
 
4.1%
면 10
 
3.1%
봉 9
 
2.8%
신 8
 
2.5%
쌍 8
 
2.5%
관 7
 
2.2%
제 6
 
1.9%
Other values (76) 149
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 308
96.6%
Decimal Number 11
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 81
26.3%
읍 15
 
4.9%
거 13
 
4.2%
창 13
 
4.2%
면 10
 
3.2%
봉 9
 
2.9%
신 8
 
2.6%
쌍 8
 
2.6%
관 7
 
2.3%
제 6
 
1.9%
Other values (73) 138
44.8%
Decimal Number
ValueCountFrequency (%)
1 4
36.4%
2 4
36.4%
3 3
27.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 308
96.6%
Common 11
 
3.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 81
26.3%
읍 15
 
4.9%
거 13
 
4.2%
창 13
 
4.2%
면 10
 
3.2%
봉 9
 
2.9%
신 8
 
2.6%
쌍 8
 
2.6%
관 7
 
2.3%
제 6
 
1.9%
Other values (73) 138
44.8%
Common
ValueCountFrequency (%)
1 4
36.4%
2 4
36.4%
3 3
27.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 308
96.6%
ASCII 11
 
3.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 81
26.3%
읍 15
 
4.9%
거 13
 
4.2%
창 13
 
4.2%
면 10
 
3.2%
봉 9
 
2.9%
신 8
 
2.6%
쌍 8
 
2.6%
관 7
 
2.3%
제 6
 
1.9%
Other values (73) 138
44.8%
ASCII
ValueCountFrequency (%)
1 4
36.4%
2 4
36.4%
3 3
27.3%

rdnmaddr_cd
Real number (ℝ)

Distinct90
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3378211 × 1011
Minimum1.1410414 × 1011
Maximum5.0110485 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:06:57.303719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1410414 × 1011
5-th percentile2.6200413 × 1011
Q14.4150325 × 1011
median4.6130328 × 1011
Q34.7210331 × 1011
95-th percentile4.8941977 × 1011
Maximum5.0110485 × 1011
Range3.8700071 × 1011
Interquartile range (IQR)3.0600058 × 1010

Descriptive statistics

Standard deviation8.3901713 × 1010
Coefficient of variation (CV)0.19341903
Kurtosis6.9468031
Mean4.3378211 × 1011
Median Absolute Deviation (MAD)1.9800031 × 1010
Skewness-2.6962298
Sum4.3378211 × 1013
Variance7.0394975 × 1021
MonotonicityNot monotonic
2023-12-10T19:06:57.728888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
441503251030 3
 
3.0%
461303282043 2
 
2.0%
441503251015 2
 
2.0%
114104136457 2
 
2.0%
461303282016 2
 
2.0%
461303282025 2
 
2.0%
421103013022 2
 
2.0%
461303282059 2
 
2.0%
441503251008 2
 
2.0%
501103349090 1
 
1.0%
Other values (80) 80
80.0%
ValueCountFrequency (%)
114104136457 2
2.0%
116803122011 1
1.0%
117403000034 1
1.0%
262003128015 1
1.0%
262004184389 1
1.0%
262602000010 1
1.0%
263503133020 1
1.0%
264104205339 1
1.0%
291703162056 1
1.0%
291704286300 1
1.0%
ValueCountFrequency (%)
501104847953 1
1.0%
501104847251 1
1.0%
501103349178 1
1.0%
501103349144 1
1.0%
501103349090 1
1.0%
488804841459 1
1.0%
488804841384 1
1.0%
488804841372 1
1.0%
488804841348 1
1.0%
488804841197 1
1.0%

rdnm_addr
Text

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:06:58.320428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length31
Mean length23.48
Min length18

Characters and Unicode

Total characters2348
Distinct characters176
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

Unique96 ?
Unique (%)96.0%

Sample

1st row충청북도 청주시 서원구 청남로 2156 (모충동)
2nd row서울특별시 서대문구 홍제천로6길 29 (연희동)
3rd row충청남도 공주시 금벽로 368 (신관동)
4th row충청남도 공주시 웅진로 280 (금성동)
5th row충청남도 공주시 봉황로 10 (봉황동)
ValueCountFrequency (%)
전라남도 31
 
6.0%
여수시 31
 
6.0%
충청남도 21
 
4.1%
공주시 21
 
4.1%
경상남도 16
 
3.1%
거창군 13
 
2.5%
거창읍 13
 
2.5%
신관동 8
 
1.6%
경상북도 7
 
1.4%
학동 6
 
1.2%
Other values (279) 346
67.4%
2023-12-10T19:06:59.083539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
413
 
17.6%
도 96
 
4.1%
동 96
 
4.1%
시 89
 
3.8%
( 79
 
3.4%
남 79
 
3.4%
) 79
 
3.4%
로 69
 
2.9%
2 63
 
2.7%
1 59
 
2.5%
Other values (166) 1226
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1429
60.9%
Space Separator 413
 
17.6%
Decimal Number 316
 
13.5%
Open Punctuation 79
 
3.4%
Close Punctuation 79
 
3.4%
Dash Punctuation 27
 
1.1%
Other Punctuation 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 96
 
6.7%
동 96
 
6.7%
시 89
 
6.2%
남 79
 
5.5%
로 69
 
4.8%
주 44
 
3.1%
길 42
 
2.9%
수 39
 
2.7%
여 35
 
2.4%
라 35
 
2.4%
Other values (151) 805
56.3%
Decimal Number
ValueCountFrequency (%)
2 63
19.9%
1 59
18.7%
4 33
10.4%
3 31
9.8%
9 28
8.9%
5 26
8.2%
6 23
 
7.3%
0 20
 
6.3%
8 17
 
5.4%
7 16
 
5.1%
Space Separator
ValueCountFrequency (%)
413
100.0%
Open Punctuation
ValueCountFrequency (%)
( 79
100.0%
Close Punctuation
ValueCountFrequency (%)
) 79
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1429
60.9%
Common 919
39.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 96
 
6.7%
동 96
 
6.7%
시 89
 
6.2%
남 79
 
5.5%
로 69
 
4.8%
주 44
 
3.1%
길 42
 
2.9%
수 39
 
2.7%
여 35
 
2.4%
라 35
 
2.4%
Other values (151) 805
56.3%
Common
ValueCountFrequency (%)
413
44.9%
( 79
 
8.6%
) 79
 
8.6%
2 63
 
6.9%
1 59
 
6.4%
4 33
 
3.6%
3 31
 
3.4%
9 28
 
3.0%
- 27
 
2.9%
5 26
 
2.8%
Other values (5) 81
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1429
60.9%
ASCII 919
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
413
44.9%
( 79
 
8.6%
) 79
 
8.6%
2 63
 
6.9%
1 59
 
6.4%
4 33
 
3.6%
3 31
 
3.4%
9 28
 
3.0%
- 27
 
2.9%
5 26
 
2.8%
Other values (5) 81
 
8.8%
Hangul
ValueCountFrequency (%)
도 96
 
6.7%
동 96
 
6.7%
시 89
 
6.2%
남 79
 
5.5%
로 69
 
4.8%
주 44
 
3.1%
길 42
 
2.9%
수 39
 
2.7%
여 35
 
2.4%
라 35
 
2.4%
Other values (151) 805
56.3%

zip_cd
Real number (ℝ)

Distinct89
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45326.84
Minimum3700
Maximum63185
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:06:59.296921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3700
5-th percentile15647.45
Q132573
median50133.5
Q359677.75
95-th percentile61356.2
Maximum63185
Range59485
Interquartile range (IQR)27104.75

Descriptive statistics

Standard deviation15600.524
Coefficient of variation (CV)0.3441785
Kurtosis-0.076721691
Mean45326.84
Median Absolute Deviation (MAD)9617
Skewness-0.81262727
Sum4532684
Variance2.4337635 × 108
MonotonicityNot monotonic
2023-12-10T19:06:59.522702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
32573 3
 
3.0%
59715 3
 
3.0%
59735 2
 
2.0%
59723 2
 
2.0%
52510 2
 
2.0%
59671 2
 
2.0%
50130 2
 
2.0%
32535 2
 
2.0%
3700 2
 
2.0%
59638 1
 
1.0%
Other values (79) 79
79.0%
ValueCountFrequency (%)
3700 2
2.0%
5225 1
1.0%
6090 1
1.0%
11001 1
1.0%
15892 1
1.0%
24244 1
1.0%
24368 1
1.0%
24706 1
1.0%
24747 1
1.0%
25925 1
1.0%
ValueCountFrequency (%)
63185 1
1.0%
63147 1
1.0%
63139 1
1.0%
63134 1
1.0%
63089 1
1.0%
61265 1
1.0%
61187 1
1.0%
59767 1
1.0%
59765 1
1.0%
59757 1
1.0%

grid_cd
Text

Distinct97
Distinct (%)98.0%
Missing1
Missing (%)1.0%
Memory size932.0 B
2023-12-10T19:06:59.948318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters792
Distinct characters17
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

Unique95 ?
Unique (%)96.0%

Sample

1st row다바990474
2nd row다사492529
3rd row다바665302
4th row다바662297
5th row다바659277
ValueCountFrequency (%)
다사492529 2
 
2.0%
다바665302 2
 
2.0%
라마374434 1
 
1.0%
라라198404 1
 
1.0%
라라222420 1
 
1.0%
라라200406 1
 
1.0%
라라186415 1
 
1.0%
라라205373 1
 
1.0%
라라190401 1
 
1.0%
라라120407 1
 
1.0%
Other values (87) 87
87.9%
2023-12-10T19:07:00.462077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
라 95
12.0%
4 76
9.6%
3 74
9.3%
6 70
8.8%
2 68
8.6%
8 60
7.6%
9 56
7.1%
0 55
 
6.9%
7 51
 
6.4%
1 49
 
6.2%
Other values (7) 138
17.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 594
75.0%
Other Letter 198
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 76
12.8%
3 74
12.5%
6 70
11.8%
2 68
11.4%
8 60
10.1%
9 56
9.4%
0 55
9.3%
7 51
8.6%
1 49
8.2%
5 35
5.9%
Other Letter
ValueCountFrequency (%)
라 95
48.0%
다 37
 
18.7%
바 27
 
13.6%
마 24
 
12.1%
사 8
 
4.0%
나 4
 
2.0%
아 3
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
Common 594
75.0%
Hangul 198
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 76
12.8%
3 74
12.5%
6 70
11.8%
2 68
11.4%
8 60
10.1%
9 56
9.4%
0 55
9.3%
7 51
8.6%
1 49
8.2%
5 35
5.9%
Hangul
ValueCountFrequency (%)
라 95
48.0%
다 37
 
18.7%
바 27
 
13.6%
마 24
 
12.1%
사 8
 
4.0%
나 4
 
2.0%
아 3
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 594
75.0%
Hangul 198
 
25.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
라 95
48.0%
다 37
 
18.7%
바 27
 
13.6%
마 24
 
12.1%
사 8
 
4.0%
나 4
 
2.0%
아 3
 
1.5%
ASCII
ValueCountFrequency (%)
4 76
12.8%
3 74
12.5%
6 70
11.8%
2 68
11.4%
8 60
10.1%
9 56
9.4%
0 55
9.3%
7 51
8.6%
1 49
8.2%
5 35
5.9%

x_cd
Real number (ℝ)

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.695923
Minimum33.475464
Maximum38.282514
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:07:00.665988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.475464
5-th percentile34.667221
Q134.76069
median35.68405
Q336.468919
95-th percentile37.589291
Maximum38.282514
Range4.8070504
Interquartile range (IQR)1.7082285

Descriptive statistics

Standard deviation1.1155411
Coefficient of variation (CV)0.031251219
Kurtosis-0.35663894
Mean35.695923
Median Absolute Deviation (MAD)0.9102616
Skewness0.30270315
Sum3569.5923
Variance1.244432
MonotonicityNot monotonic
2023-12-10T19:07:00.841881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.57477 2
 
2.0%
36.4689189906 2
 
2.0%
34.774463 1
 
1.0%
34.777494 1
 
1.0%
34.768369 1
 
1.0%
34.773113 1
 
1.0%
34.760557 1
 
1.0%
34.768341 1
 
1.0%
34.730011 1
 
1.0%
34.755789 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
33.4754636 1
1.0%
33.4779003 1
1.0%
33.47867251 1
1.0%
33.4844207 1
1.0%
33.49915844 1
1.0%
34.728698 1
1.0%
34.730011 1
1.0%
34.731874 1
1.0%
34.738452 1
1.0%
34.739287 1
1.0%
ValueCountFrequency (%)
38.282514 1
1.0%
38.2128035139 1
1.0%
38.201015 1
1.0%
37.885526 1
1.0%
37.865198 1
1.0%
37.57477 2
2.0%
37.5556702109 1
1.0%
37.5175282 1
1.0%
37.432163 1
1.0%
37.32478354 1
1.0%

y_cd
Real number (ℝ)

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.67037
Minimum126.47682
Maximum129.56606
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:07:00.984029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.47682
5-th percentile126.84373
Q1127.1344
median127.68905
Q3127.91301
95-th percentile129.07873
Maximum129.56606
Range3.0892343
Interquartile range (IQR)0.77860563

Descriptive statistics

Standard deviation0.64966178
Coefficient of variation (CV)0.005088587
Kurtosis0.62155112
Mean127.67037
Median Absolute Deviation (MAD)0.3736207
Skewness0.71594437
Sum12767.037
Variance0.42206043
MonotonicityNot monotonic
2023-12-10T19:07:01.156708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.925607 2
 
2.0%
127.127104525 2
 
2.0%
127.6994546 1
 
1.0%
127.651525 1
 
1.0%
127.661156 1
 
1.0%
127.743487 1
 
1.0%
127.718817 1
 
1.0%
127.703489 1
 
1.0%
127.724219 1
 
1.0%
127.708258 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
126.4768245 1
1.0%
126.490582 1
1.0%
126.500595 1
1.0%
126.5156482 1
1.0%
126.5161719 1
1.0%
126.8609652144 1
1.0%
126.8905197 1
1.0%
126.9121085578 1
1.0%
126.925607 2
2.0%
127.0474699 1
1.0%
ValueCountFrequency (%)
129.5660588 1
1.0%
129.223891 1
1.0%
129.185515 1
1.0%
129.121651 1
1.0%
129.088057 1
1.0%
129.078243 1
1.0%
129.076 1
1.0%
129.066 1
1.0%
128.6218982 1
1.0%
128.6160493 1
1.0%

bycc_lend_div
Categorical

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
무인대여소
73 
유인대여소
26 
무인·유인대여소
 
1

Length

Max length8
Median length5
Mean length5.03
Min length5

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row유인대여소
2nd row유인대여소
3rd row유인대여소
4th row무인대여소
5th row무인대여소

Common Values

ValueCountFrequency (%)
무인대여소 73
73.0%
유인대여소 26
 
26.0%
무인·유인대여소 1
 
1.0%

Length

2023-12-10T19:07:01.326608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:07:01.516500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무인대여소 73
73.0%
유인대여소 26
 
26.0%
무인·유인대여소 1
 
1.0%

opn_tm
Date

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2023-12-10 00:00:00
Maximum2023-12-10 10:00:00
2023-12-10T19:07:01.635776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:07:01.758922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)

cls_tm
Categorical

Distinct10
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
23:59
45 
22:00
20 
18:00
14 
17:00
7 
21:00
6 
Other values (5)
8 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique3 ?
Unique (%)3.0%

Sample

1st row17:00
2nd row17:00
3rd row19:00
4th row22:00
5th row22:00

Common Values

ValueCountFrequency (%)
23:59 45
45.0%
22:00 20
20.0%
18:00 14
 
14.0%
17:00 7
 
7.0%
21:00 6
 
6.0%
19:00 3
 
3.0%
17:30 2
 
2.0%
18:30 1
 
1.0%
24:00 1
 
1.0%
16:00 1
 
1.0%

Length

2023-12-10T19:07:01.930246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:07:02.127615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
23:59 45
45.0%
22:00 20
20.0%
18:00 14
 
14.0%
17:00 7
 
7.0%
21:00 6
 
6.0%
19:00 3
 
3.0%
17:30 2
 
2.0%
18:30 1
 
1.0%
24:00 1
 
1.0%
16:00 1
 
1.0%

rstde
Categorical

Distinct19
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
연중무휴
53 
-
20 
없음
 
5
매주 월요일
 
4
11월~3월 휴무
 
2
Other values (14)
16 

Length

Max length23
Median length4
Mean length4.03
Min length1

Unique

Unique12 ?
Unique (%)12.0%

Sample

1st row매주 월요일 휴무
2nd row매주 월요일
3rd row동절기
4th row-
5th row-

Common Values

ValueCountFrequency (%)
연중무휴 53
53.0%
- 20
 
20.0%
없음 5
 
5.0%
매주 월요일 4
 
4.0%
11월~3월 휴무 2
 
2.0%
설,추석 연휴 2
 
2.0%
명절, 선거일 2
 
2.0%
공휴일, 토요일, 일요일 1
 
1.0%
4~11월 1
 
1.0%
월, 화 1
 
1.0%
Other values (9) 9
 
9.0%

Length

2023-12-10T19:07:02.369402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연중무휴 53
43.8%
20
 
16.5%
월요일 6
 
5.0%
없음 5
 
4.1%
매주 5
 
4.1%
휴무 4
 
3.3%
선거일 2
 
1.7%
일요일 2
 
1.7%
명절 2
 
1.7%
연휴 2
 
1.7%
Other values (18) 20
 
16.5%

fee_div
Categorical

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
유료
50 
무료
49 
혼합
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
유료 50
50.0%
무료 49
49.0%
혼합 1
 
1.0%

Length

2023-12-10T19:07:02.591437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:07:02.781278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유료 50
50.0%
무료 49
49.0%
혼합 1
 
1.0%

bycc_use_fee
Categorical

Distinct13
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
정기권 1년 3만원,정기권6개월 1만8천원,정기권 1개월 5천원,일일권 1천원
31 
무료
30 
<NA>
13 
일일이용 1천원+정기권 1개월 3천원+정기권 1년 2만원
13 
0원
5 
Other values (8)
8 

Length

Max length52
Median length43
Mean length20.12
Min length1

Unique

Unique8 ?
Unique (%)8.0%

Sample

1st row<NA>
2nd row무료
3rd row무료
4th row무료
5th row무료

Common Values

ValueCountFrequency (%)
정기권 1년 3만원,정기권6개월 1만8천원,정기권 1개월 5천원,일일권 1천원 31
31.0%
무료 30
30.0%
<NA> 13
13.0%
일일이용 1천원+정기권 1개월 3천원+정기권 1년 2만원 13
13.0%
0원 5
 
5.0%
0 1
 
1.0%
1일권 4천원+정기권 1
 
1.0%
1시간 3000원 +추가 1시간 2000원 + 종일원 12000원 1
 
1.0%
종일권 10000원 1
 
1.0%
보증금 1만원 월 1,000원 1
 
1.0%
Other values (3) 3
 
3.0%

Length

2023-12-10T19:07:02.969594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1년 44
11.8%
1개월 44
11.8%
1천원 31
8.3%
5천원,일일권 31
8.3%
정기권 31
8.3%
1만8천원,정기권 31
8.3%
3만원,정기권6개월 31
8.3%
무료 30
 
8.0%
na 13
 
3.5%
일일이용 13
 
3.5%
Other values (34) 75
20.1%

bycc_pos_cnt
Real number (ℝ)

Distinct31
Distinct (%)31.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.56
Minimum3
Maximum533
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:07:03.361450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4
Q17
median12
Q321.25
95-th percentile167.25
Maximum533
Range530
Interquartile range (IQR)14.25

Descriptive statistics

Standard deviation69.750395
Coefficient of variation (CV)2.0182406
Kurtosis28.684464
Mean34.56
Median Absolute Deviation (MAD)7
Skewness4.8244904
Sum3456
Variance4865.1176
MonotonicityNot monotonic
2023-12-10T19:07:03.626100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
5 14
14.0%
20 11
11.0%
12 10
 
10.0%
7 8
 
8.0%
10 7
 
7.0%
15 7
 
7.0%
4 6
 
6.0%
8 5
 
5.0%
70 3
 
3.0%
35 3
 
3.0%
Other values (21) 26
26.0%
ValueCountFrequency (%)
3 1
 
1.0%
4 6
6.0%
5 14
14.0%
6 1
 
1.0%
7 8
8.0%
8 5
 
5.0%
10 7
7.0%
12 10
10.0%
14 1
 
1.0%
15 7
7.0%
ValueCountFrequency (%)
533 1
1.0%
320 1
1.0%
180 1
1.0%
172 2
2.0%
167 1
1.0%
151 1
1.0%
96 1
1.0%
89 1
1.0%
80 1
1.0%
75 2
2.0%

frnsh_cnt
Real number (ℝ)

MISSING  ZEROS 

Distinct25
Distinct (%)26.3%
Missing5
Missing (%)5.0%
Infinite0
Infinite (%)0.0%
Mean15.252632
Minimum0
Maximum167
Zeros3
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:07:04.309780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q110
median14
Q315.5
95-th percentile29.8
Maximum167
Range167
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation18.012388
Coefficient of variation (CV)1.1809364
Kurtosis54.399813
Mean15.252632
Median Absolute Deviation (MAD)4
Skewness6.5930848
Sum1449
Variance324.44614
MonotonicityNot monotonic
2023-12-10T19:07:04.515291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
15 16
16.0%
12 13
13.0%
20 11
11.0%
14 10
10.0%
2 10
10.0%
10 9
9.0%
1 3
 
3.0%
0 3
 
3.0%
13 2
 
2.0%
11 2
 
2.0%
Other values (15) 16
16.0%
(Missing) 5
 
5.0%
ValueCountFrequency (%)
0 3
 
3.0%
1 3
 
3.0%
2 10
10.0%
6 1
 
1.0%
8 1
 
1.0%
9 1
 
1.0%
10 9
9.0%
11 2
 
2.0%
12 13
13.0%
13 2
 
2.0%
ValueCountFrequency (%)
167 1
 
1.0%
50 1
 
1.0%
47 1
 
1.0%
37 1
 
1.0%
34 1
 
1.0%
28 1
 
1.0%
26 1
 
1.0%
25 2
 
2.0%
20 11
11.0%
19 1
 
1.0%

air_suply_frnsh_yn
Boolean

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
False
53 
True
47 
ValueCountFrequency (%)
False 53
53.0%
True 47
47.0%
2023-12-10T19:07:04.717256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

air_suply_typ
Categorical

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
44 
기계식
28 
수동식
27 
태양광식
 
1

Length

Max length4
Median length3
Mean length3.45
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row수동식
2nd row기계식
3rd row기계식
4th row기계식
5th row기계식

Common Values

ValueCountFrequency (%)
<NA> 44
44.0%
기계식 28
28.0%
수동식 27
27.0%
태양광식 1
 
1.0%

Length

2023-12-10T19:07:04.936215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:07:05.314140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 44
44.0%
기계식 28
28.0%
수동식 27
27.0%
태양광식 1
 
1.0%

repr_bnch_instl_yn
Boolean

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
False
95 
True
 
5
ValueCountFrequency (%)
False 95
95.0%
True 5
 
5.0%
2023-12-10T19:07:05.525686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

minstt_telno
Categorical

Distinct23
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
061-659-4567
31 
041-840-8507
21 
055-940-3596
13 
064-728-3554
5 
054-639-3813
5 
Other values (18)
25 

Length

Max length13
Median length12
Mean length12.01
Min length11

Unique

Unique12 ?
Unique (%)12.0%

Sample

1st row043-201-2736
2nd row02-330-1655
3rd row041-840-8507
4th row041-840-8507
5th row041-840-8507

Common Values

ValueCountFrequency (%)
061-659-4567 31
31.0%
041-840-8507 21
21.0%
055-940-3596 13
13.0%
064-728-3554 5
 
5.0%
054-639-3813 5
 
5.0%
055-749-8659 3
 
3.0%
062-410-6775 2
 
2.0%
033-680-3047 2
 
2.0%
070-7204-7948 2
 
2.0%
051-610-4555 2
 
2.0%
Other values (13) 14
14.0%

Length

2023-12-10T19:07:05.822600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
061-659-4567 31
31.0%
041-840-8507 21
21.0%
055-940-3596 13
13.0%
064-728-3554 5
 
5.0%
054-639-3813 5
 
5.0%
055-749-8659 3
 
3.0%
062-410-6775 2
 
2.0%
033-680-3047 2
 
2.0%
070-7204-7948 2
 
2.0%
051-610-4555 2
 
2.0%
Other values (13) 14
14.0%

minstt_nm
Categorical

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
전라남도 여수시청
31 
공주시청
21 
거창군청 도시건축과
13 
제주특별자치도 제주시청
5 
경상북도 영주시청
5 
Other values (17)
25 

Length

Max length12
Median length11
Mean length8.07
Min length2

Unique

Unique10 ?
Unique (%)10.0%

Sample

1st row충청북도 청주시청
2nd row서대문구청 교통행정과
3rd row공주시청
4th row공주시청
5th row공주시청

Common Values

ValueCountFrequency (%)
전라남도 여수시청 31
31.0%
공주시청 21
21.0%
거창군청 도시건축과 13
13.0%
제주특별자치도 제주시청 5
 
5.0%
경상북도 영주시청 5
 
5.0%
경상남도 진주시청 3
 
3.0%
부산광역시 수영구청 2
 
2.0%
서대문구청 교통행정과 2
 
2.0%
개인 2
 
2.0%
경북포항지역자활센터 2
 
2.0%
Other values (12) 14
14.0%

Length

2023-12-10T19:07:06.102954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전라남도 31
18.1%
여수시청 31
18.1%
공주시청 21
12.3%
거창군청 13
 
7.6%
도시건축과 13
 
7.6%
부산광역시 5
 
2.9%
제주특별자치도 5
 
2.9%
제주시청 5
 
2.9%
경상북도 5
 
2.9%
영주시청 5
 
2.9%
Other values (24) 37
21.6%

data_stdde
Real number (ℝ)

Distinct21
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20189915
Minimum20180101
Maximum20191017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:07:06.394698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20180101
5-th percentile20180902
Q120190315
median20190527
Q320190925
95-th percentile20190925
Maximum20191017
Range10916
Interquartile range (IQR)610

Descriptive statistics

Standard deviation2575.6363
Coefficient of variation (CV)0.00012757043
Kurtosis9.6734888
Mean20189915
Median Absolute Deviation (MAD)296
Skewness-3.3576024
Sum2.0189915 × 109
Variance6633902.1
MonotonicityNot monotonic
2023-12-10T19:07:06.596856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
20190315 31
31.0%
20190925 23
23.0%
20190823 13
13.0%
20190527 5
 
5.0%
20190101 5
 
5.0%
20191017 3
 
3.0%
20190816 2
 
2.0%
20180906 2
 
2.0%
20190820 2
 
2.0%
20180101 2
 
2.0%
Other values (11) 12
 
12.0%
ValueCountFrequency (%)
20180101 2
 
2.0%
20180801 1
 
1.0%
20180813 1
 
1.0%
20180831 1
 
1.0%
20180906 2
 
2.0%
20190101 5
 
5.0%
20190304 1
 
1.0%
20190315 31
31.0%
20190501 1
 
1.0%
20190510 1
 
1.0%
ValueCountFrequency (%)
20191017 3
 
3.0%
20190925 23
23.0%
20190924 1
 
1.0%
20190910 1
 
1.0%
20190831 2
 
2.0%
20190823 13
13.0%
20190820 2
 
2.0%
20190816 2
 
2.0%
20190528 1
 
1.0%
20190527 5
 
5.0%

prvd_agnc_cd
Real number (ℝ)

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4752200
Minimum3120000
Maximum6510000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:07:06.807240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3120000
5-th percentile3328500
Q14500000
median4810000
Q35090000
95-th percentile5750000
Maximum6510000
Range3390000
Interquartile range (IQR)590000

Descriptive statistics

Standard deviation715710.54
Coefficient of variation (CV)0.15060615
Kurtosis1.0365448
Mean4752200
Median Absolute Deviation (MAD)310000
Skewness-0.014759748
Sum4.7522 × 108
Variance5.1224158 × 1011
MonotonicityNot monotonic
2023-12-10T19:07:07.250693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
4810000 31
31.0%
4500000 21
21.0%
5470000 13
13.0%
6510000 5
 
5.0%
5090000 5
 
5.0%
5310000 3
 
3.0%
3620000 2
 
2.0%
4340000 2
 
2.0%
5020000 2
 
2.0%
3380000 2
 
2.0%
Other values (12) 14
14.0%
ValueCountFrequency (%)
3120000 2
2.0%
3220000 1
1.0%
3240000 1
1.0%
3300000 1
1.0%
3330000 1
1.0%
3350000 1
1.0%
3380000 2
2.0%
3620000 2
2.0%
4020000 1
1.0%
4140000 1
1.0%
ValueCountFrequency (%)
6510000 5
 
5.0%
5710000 1
 
1.0%
5470000 13
13.0%
5310000 3
 
3.0%
5090000 5
 
5.0%
5020000 2
 
2.0%
4810000 31
31.0%
4700000 1
 
1.0%
4500000 21
21.0%
4340000 2
 
2.0%

prvd_agnc_nm
Categorical

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
전라남도 여수시
31 
충청남도 공주시
21 
경상남도 거창군
13 
제주특별자치도 제주시
5 
경상북도 영주시
5 
Other values (17)
25 

Length

Max length11
Median length8
Mean length8.2
Min length7

Unique

Unique10 ?
Unique (%)10.0%

Sample

1st row충청북도 청주시
2nd row서울특별시 서대문구
3rd row충청남도 공주시
4th row충청남도 공주시
5th row충청남도 공주시

Common Values

ValueCountFrequency (%)
전라남도 여수시 31
31.0%
충청남도 공주시 21
21.0%
경상남도 거창군 13
13.0%
제주특별자치도 제주시 5
 
5.0%
경상북도 영주시 5
 
5.0%
경상남도 진주시 3
 
3.0%
부산광역시 수영구 2
 
2.0%
서울특별시 서대문구 2
 
2.0%
강원도 춘천시 2
 
2.0%
경상북도 포항시 2
 
2.0%
Other values (12) 14
14.0%

Length

2023-12-10T19:07:07.704985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전라남도 31
15.5%
여수시 31
15.5%
충청남도 21
10.5%
공주시 21
10.5%
경상남도 16
 
8.0%
거창군 13
 
6.5%
경상북도 7
 
3.5%
제주특별자치도 5
 
2.5%
제주시 5
 
2.5%
부산광역시 5
 
2.5%
Other values (24) 45
22.5%

lst_updt_dt
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20191117
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20191117
2nd row20191117
3rd row20191117
4th row20191117
5th row20191117

Common Values

ValueCountFrequency (%)
20191117 100
100.0%

Length

2023-12-10T19:07:07.941549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:07:08.111555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20191117 100
100.0%

data_orgn
Categorical

CONSTANT 

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

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공데이터포털 100
100.0%

Length

2023-12-10T19:07:08.351830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:07:08.525307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공데이터포털 100
100.0%

FILE_NAME
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
KC_487_WNTY_BIKELENT_2019
100 

Length

Max length25
Median length25
Mean length25
Min length25

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKC_487_WNTY_BIKELENT_2019
2nd rowKC_487_WNTY_BIKELENT_2019
3rd rowKC_487_WNTY_BIKELENT_2019
4th rowKC_487_WNTY_BIKELENT_2019
5th rowKC_487_WNTY_BIKELENT_2019

Common Values

ValueCountFrequency (%)
KC_487_WNTY_BIKELENT_2019 100
100.0%

Length

2023-12-10T19:07:08.720702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:07:08.884753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kc_487_wnty_bikelent_2019 100
100.0%

base_ymd
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20191125
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20191125
2nd row20191125
3rd row20191125
4th row20191125
5th row20191125

Common Values

ValueCountFrequency (%)
20191125 100
100.0%

Length

2023-12-10T19:07:09.097628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:07:09.283506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20191125 100
100.0%

Sample

idlclasmlsfcfclt_namectprvn_nmsgnr_nmlegaldong_cdlegalemd_nmadstrd_cdadstrd_nmrdnmaddr_cdrdnm_addrzip_cdgrid_cdx_cdy_cdbycc_lend_divopn_tmcls_tmrstdefee_divbycc_use_feebycc_pos_cntfrnsh_cntair_suply_frnsh_ynair_suply_typrepr_bnch_instl_ynminstt_telnominstt_nmdata_stddeprvd_agnc_cdprvd_agnc_nmlst_updt_dtdata_orgnFILE_NAMEbase_ymd
0KC487PC19N000001레포츠체육시설(공공)무심천 청남교 옆 하천둔치충청북도청주시 서원구4311210300모충동4311254000모충동431123236067충청북도 청주시 서원구 청남로 2156 (모충동)28702다바99047436.624534127.489418유인대여소10:0017:00매주 월요일 휴무무료<NA>35<NA>Y수동식N043-201-2736충청북도 청주시청201808135710000충청북도 청주시20191117공공데이터포털KC_487_WNTY_BIKELENT_201920191125
1KC487PC19N000002레포츠체육시설(공공)두바퀴쉼터서울특별시서대문구1141011700연희동1141061500연희동114104136457서울특별시 서대문구 홍제천로6길 29 (연희동)3700다사49252937.57477126.925607유인대여소09:0017:00매주 월요일무료무료17215Y기계식N02-330-1655서대문구청 교통행정과201808013120000서울특별시 서대문구20191117공공데이터포털KC_487_WNTY_BIKELENT_201920191125
2KC487PC19N000003레포츠체육시설(공공)금강신관공원 유인대여소충청남도공주시4415012000신관동4415057000신관동441503251008충청남도 공주시 금벽로 368 (신관동)32573다바66530236.468919127.127105유인대여소10:0019:00동절기무료무료167167Y기계식N041-840-8507공주시청201909254500000충청남도 공주시20191117공공데이터포털KC_487_WNTY_BIKELENT_201920191125
3KC487PC19N000004레포츠체육시설(공공)공산성충청남도공주시4415010800금성동4415054000웅진동441503251030충청남도 공주시 웅진로 280 (금성동)32555다바66229736.4646127.12363무인대여소07:0022:00-무료무료514Y기계식N041-840-8507공주시청201909254500000충청남도 공주시20191117공공데이터포털KC_487_WNTY_BIKELENT_201920191125
4KC487PC19N000005레포츠체육시설(공공)공주시청충청남도공주시4415010200봉황동4415051000중학동441503251019충청남도 공주시 봉황로 10 (봉황동)32551다바65927736.446836127.120341무인대여소07:0022:00-무료무료412Y기계식N041-840-8507공주시청201909254500000충청남도 공주시20191117공공데이터포털KC_487_WNTY_BIKELENT_201920191125
5KC487PC19N000006레포츠체육시설(공공)무령왕릉충청남도공주시4415010700웅진동4415054000웅진동441503251026충청남도 공주시 왕릉로 35 (웅진동)32535다바65229336.4611127.11258무인대여소07:0022:00-무료무료411Y기계식N041-840-8507공주시청201909254500000충청남도 공주시20191117공공데이터포털KC_487_WNTY_BIKELENT_201920191125
6KC487PC19N000007레포츠체육시설(공공)옥룡GS마켓충청남도공주시4415010900옥룡동4415056000옥룡동441504553455충청남도 공주시 버드나무1길 15 (옥룡동)32556다바67028836.456418127.132094무인대여소07:0022:00-무료무료514Y기계식N041-840-8507공주시청201909254500000충청남도 공주시20191117공공데이터포털KC_487_WNTY_BIKELENT_201920191125
7KC487PC19N000008레포츠체육시설(공공)한옥마을충청남도공주시4415010700웅진동4415054000웅진동441504553091충청남도 공주시 관광단지길 12 (웅진동)32535다바64929736.464524127.109148무인대여소07:0022:00-무료무료514Y기계식N041-840-8507공주시청201909254500000충청남도 공주시20191117공공데이터포털KC_487_WNTY_BIKELENT_201920191125
8KC487PC19N000009레포츠체육시설(공공)경찰서앞교차로충청남도공주시4415010700웅진동4415054000웅진동441504553497충청남도 공주시 봉황산1길 55 (웅진동)32544다바65628136.450719127.11663무인대여소07:0022:00-무료무료514N수동식N041-840-8507공주시청201909254500000충청남도 공주시20191117공공데이터포털KC_487_WNTY_BIKELENT_201920191125
9KC487PC19N000010레포츠체육시설(공공)시내버스터미널충청남도공주시4415010500산성동4415054000웅진동441503251030충청남도 공주시 웅진로 223 (산성동, 산성빌딩)32539다바66329236.46044127.12431무인대여소07:0022:00-무료무료411N수동식N041-840-8507공주시청201909254500000충청남도 공주시20191117공공데이터포털KC_487_WNTY_BIKELENT_201920191125
idlclasmlsfcfclt_namectprvn_nmsgnr_nmlegaldong_cdlegalemd_nmadstrd_cdadstrd_nmrdnmaddr_cdrdnm_addrzip_cdgrid_cdx_cdy_cdbycc_lend_divopn_tmcls_tmrstdefee_divbycc_use_feebycc_pos_cntfrnsh_cntair_suply_frnsh_ynair_suply_typrepr_bnch_instl_ynminstt_telnominstt_nmdata_stddeprvd_agnc_cdprvd_agnc_nmlst_updt_dtdata_orgnFILE_NAMEbase_ymd
90KC487PC19N000092레포츠체육시설(공공)장미공원자전거대여소강원도삼척시4223012500정상동4223054000정라동422304472170강원도 삼척시 삼척항1길 4-19 (정상동)25925마사49138337.432163129.185515유인대여소10:0018:00연중무휴유료5000751Y기계식N033-570-3551강원도 삼척시청201808314240000강원도 삼척시20191117공공데이터포털KC_487_WNTY_BIKELENT_201920191125
91KC487PC19N000093레포츠체육시설(공공)대야동 시민자전거 대여소경기도군포시4141010600둔대동4141061000대야동414103200028경기도 군포시 호수로 99 (둔대동)15892다사46025237.324784126.89052유인대여소10:0018:00평일유료1인용 3,000원 2인용 6,000원, 가족 4인용 12,000원, 가족6인용 14,000원35<NA>Y기계식Y031-396-4135군포시새마을회201905284020000경기도 군포시20191117공공데이터포털KC_487_WNTY_BIKELENT_201920191125
92KC487PC19N000094레포츠체육시설(공공)신탄리 자전거 대여소경기도연천군4180036021신서면4180036000신서면418004445003경기도 연천군 신서면 고대산길 411001다아68323638.212804127.138975유인대여소10:0017:30월, 화유료시간당 3,000원/하루 대여 10,000원3434Y기계식N000-0000-0000신탄리 자전거 대여소201909244140000경기도 연천군20191117공공데이터포털KC_487_WNTY_BIKELENT_201920191125
93KC487PC19N000095레포츠체육시설(공공)북구청 구내식당 앞광주광역시북구2917010700용봉동2917059000용봉동291703162056광주광역시 북구 우치로 77 (용봉동)61187다라46486735.174289126.912109유인대여소00:0023:59연중무휴무료무료162Y수동식N062-410-6775광주광역시북구청201909253620000광주광역시 북구20191117공공데이터포털KC_487_WNTY_BIKELENT_201920191125
94KC487PC19N000096레포츠체육시설(공공)동림동 산동교 하부광주광역시북구2917010800동림동2917061500동림동291704286300광주광역시 북구 북문대로249번길 34 (동림동)61265다라41888235.188281126.860965유인대여소10:0018:004~11월무료무료558Y수동식Y062-410-6775광주광역시북구청201909253620000광주광역시 북구20191117공공데이터포털KC_487_WNTY_BIKELENT_201920191125
95KC487PC19N000097레포츠체육시설(공공)삼도1동 오라지구대 뒤제주특별자치도제주시5011010500삼도일동5011055000삼도1동501103349090제주특별자치도 제주시 서광로 182-6 (삼도일동)63185다다08601233.499158126.516172무인대여소06:0021:00없음무료<NA>82Y수동식N064-728-3554제주특별자치도 제주시청201905276510000제주특별자치도 제주시20191117공공데이터포털KC_487_WNTY_BIKELENT_201920191125
96KC487PC19N000098레포츠체육시설(공공)노형동 탐라도서관 주차장 내제주특별자치도제주시5011012200노형동5011066000노형동501103349178제주특별자치도 제주시 정원로 47 (노형동)63089다나04998933.4779126.476825무인대여소06:0021:00없음무료<NA>82Y수동식N064-728-3554제주특별자치도 제주시청201905276510000제주특별자치도 제주시20191117공공데이터포털KC_487_WNTY_BIKELENT_201920191125
97KC487PC19N000099레포츠체육시설(공공)연동 대림아파트 동측 주차장내제주특별자치도제주시5011013700연동5011065000연동501104847251제주특별자치도 제주시 국기로2길 2-13 (연동)63139다나06298933.478673126.490582무인대여소06:0021:00없음무료<NA>82Y수동식N064-728-3554제주특별자치도 제주시청201905276510000제주특별자치도 제주시20191117공공데이터포털KC_487_WNTY_BIKELENT_201920191125
98KC487PC19N000100레포츠체육시설(공공)오라2동 제주아트센터 주차장 내제주특별자치도제주시5011012000오라이동5011064000오라동501103349144제주특별자치도 제주시 오남로 231 (오라이동)63147다나08598633.475464126.515648무인대여소06:0021:00없음무료<NA>82Y수동식N064-728-3554제주특별자치도 제주시청201905276510000제주특별자치도 제주시20191117공공데이터포털KC_487_WNTY_BIKELENT_201920191125
99KC487PC19N000101레포츠체육시설(공공)연동 설문대여성문화센터 주차장내제주특별자치도제주시5011013700연동5011065000연동501104847953제주특별자치도 제주시 선덕로8길 12 (연동)63134다나07199633.484421126.500595무인대여소06:0021:00없음무료<NA>82Y수동식N064-728-3554제주특별자치도 제주시청201905276510000제주특별자치도 제주시20191117공공데이터포털KC_487_WNTY_BIKELENT_201920191125