Overview

Dataset statistics

Number of variables27
Number of observations100
Missing cells300
Missing cells (%)11.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.6 KiB
Average record size in memory231.3 B

Variable types

Text3
Categorical10
Numeric11
Unsupported3

Alerts

lclas_nm has constant value ""Constant
mlsfc_nm has constant value ""Constant
ctprvn_nm has constant value ""Constant
cl_nm is highly imbalanced (60.2%)Imbalance
bhf_nm has 100 (100.0%) missing valuesMissing
asstn_nm has 100 (100.0%) missing valuesMissing
trrsrt_li_nm has 100 (100.0%) missing valuesMissing
esntl_id has unique valuesUnique
bhf_nm is an unsupported type, check if it needs cleaning or further analysisUnsupported
asstn_nm is an unsupported type, check if it needs cleaning or further analysisUnsupported
trrsrt_li_nm is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 09:53:35.003053
Analysis finished2023-12-10 09:53:35.785872
Duration0.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

esntl_id
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:53:36.097141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters1900
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st rowKCUPCPO21N000000001
2nd rowKCUPCPO21N000011012
3rd rowKCUPCPO21N000000003
4th rowKCUPCPO21N000000004
5th rowKCUPCPO21N000000005
ValueCountFrequency (%)
kcupcpo21n000000001 1
 
1.0%
kcupcpo21n000000063 1
 
1.0%
kcupcpo21n000000074 1
 
1.0%
kcupcpo21n000000073 1
 
1.0%
kcupcpo21n000000072 1
 
1.0%
kcupcpo21n000000071 1
 
1.0%
kcupcpo21n000000070 1
 
1.0%
kcupcpo21n000000069 1
 
1.0%
kcupcpo21n000000068 1
 
1.0%
kcupcpo21n000000067 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T18:53:37.009790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 711
37.4%
C 200
 
10.5%
P 200
 
10.5%
1 130
 
6.8%
2 119
 
6.3%
K 100
 
5.3%
U 100
 
5.3%
O 100
 
5.3%
N 100
 
5.3%
4 21
 
1.1%
Other values (6) 119
 
6.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 711
64.6%
1 130
 
11.8%
2 119
 
10.8%
4 21
 
1.9%
3 20
 
1.8%
5 20
 
1.8%
6 20
 
1.8%
7 20
 
1.8%
9 20
 
1.8%
8 19
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
C 200
25.0%
P 200
25.0%
K 100
12.5%
U 100
12.5%
O 100
12.5%
N 100
12.5%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 711
64.6%
1 130
 
11.8%
2 119
 
10.8%
4 21
 
1.9%
3 20
 
1.8%
5 20
 
1.8%
6 20
 
1.8%
7 20
 
1.8%
9 20
 
1.8%
8 19
 
1.7%
Latin
ValueCountFrequency (%)
C 200
25.0%
P 200
25.0%
K 100
12.5%
U 100
12.5%
O 100
12.5%
N 100
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 711
37.4%
C 200
 
10.5%
P 200
 
10.5%
1 130
 
6.8%
2 119
 
6.3%
K 100
 
5.3%
U 100
 
5.3%
O 100
 
5.3%
N 100
 
5.3%
4 21
 
1.1%
Other values (6) 119
 
6.3%

lclas_nm
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
장소 100
100.0%

Length

2023-12-10T18:53:37.278187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:53:37.441400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
장소 100
100.0%

mlsfc_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

2023-12-10T18:53:37.636212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:53:37.880155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문화시설 100
100.0%

poi_id
Real number (ℝ)

Distinct25
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10233140
Minimum9650921
Maximum10253269
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:53:38.099640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9650921
5-th percentile10213333
Q110253191
median10253192
Q310253209
95-th percentile10253267
Maximum10253269
Range602348
Interquartile range (IQR)18.25

Descriptive statistics

Standard deviation103275.97
Coefficient of variation (CV)0.010092305
Kurtosis29.429041
Mean10233140
Median Absolute Deviation (MAD)17
Skewness-5.5335724
Sum1.023314 × 109
Variance1.0665927 × 1010
MonotonicityNot monotonic
2023-12-10T18:53:38.319026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
10253192 14
14.0%
10253191 12
12.0%
10253149 10
 
10.0%
10253267 7
 
7.0%
10253263 6
 
6.0%
10253209 5
 
5.0%
10253193 5
 
5.0%
10253207 4
 
4.0%
10253197 4
 
4.0%
10253203 4
 
4.0%
Other values (15) 29
29.0%
ValueCountFrequency (%)
9650921 3
 
3.0%
10213333 3
 
3.0%
10213335 1
 
1.0%
10213354 1
 
1.0%
10253144 3
 
3.0%
10253146 3
 
3.0%
10253149 10
10.0%
10253190 1
 
1.0%
10253191 12
12.0%
10253192 14
14.0%
ValueCountFrequency (%)
10253269 1
 
1.0%
10253267 7
7.0%
10253264 1
 
1.0%
10253263 6
6.0%
10253262 3
3.0%
10253214 2
 
2.0%
10253212 2
 
2.0%
10253209 5
5.0%
10253207 4
4.0%
10253206 1
 
1.0%

poi_nm
Categorical

Distinct25
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
아트센터나비
14 
신문박물관
12 
한국잡지박물관
10 
백송화랑
7 
서울시립대학교박물관
6 
Other values (20)
51 

Length

Max length10
Median length8
Mean length5.95
Min length3

Unique

Unique7 ?
Unique (%)7.0%

Sample

1st row강북문화예술회관
2nd row아르코미술관
3rd row강북문화예술회관
4th row강북문화예술회관
5th row갤러리S.P

Common Values

ValueCountFrequency (%)
아트센터나비 14
14.0%
신문박물관 12
12.0%
한국잡지박물관 10
 
10.0%
백송화랑 7
 
7.0%
서울시립대학교박물관 6
 
6.0%
한국자수박물관 5
 
5.0%
원앤제이갤러리 5
 
5.0%
학고재 4
 
4.0%
축구전시관 4
 
4.0%
한상수박물관 4
 
4.0%
Other values (15) 29
29.0%

Length

2023-12-10T18:53:38.568361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
아트센터나비 14
14.0%
신문박물관 12
12.0%
한국잡지박물관 10
 
10.0%
백송화랑 7
 
7.0%
서울시립대학교박물관 6
 
6.0%
한국자수박물관 5
 
5.0%
원앤제이갤러리 5
 
5.0%
학고재 4
 
4.0%
축구전시관 4
 
4.0%
한상수박물관 4
 
4.0%
Other values (15) 29
29.0%

bhf_nm
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

asstn_nm
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

cl_nm
Categorical

IMBALANCE 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
기타전시/박물관
83 
소형갤러리
10 
대형예술센터
 
3
미술관
 
3
구민/시민회관
 
1

Length

Max length8
Median length8
Mean length7.48
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row대형예술센터
2nd row미술관
3rd row대형예술센터
4th row대형예술센터
5th row소형갤러리

Common Values

ValueCountFrequency (%)
기타전시/박물관 83
83.0%
소형갤러리 10
 
10.0%
대형예술센터 3
 
3.0%
미술관 3
 
3.0%
구민/시민회관 1
 
1.0%

Length

2023-12-10T18:53:38.794214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:53:38.970986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타전시/박물관 83
83.0%
소형갤러리 10
 
10.0%
대형예술센터 3
 
3.0%
미술관 3
 
3.0%
구민/시민회관 1
 
1.0%

pnu
Real number (ℝ)

Distinct25
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1247972 × 1018
Minimum1.1110106 × 1018
Maximum1.1680108 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:53:39.162000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110106 × 1018
5-th percentile1.1110119 × 1018
Q11.1110123 × 1018
median1.1110146 × 1018
Q31.1350105 × 1018
95-th percentile1.1680107 × 1018
Maximum1.1680108 × 1018
Range5.70002 × 1016
Interquartile range (IQR)2.3998175 × 1016

Descriptive statistics

Standard deviation2.0571126 × 1016
Coefficient of variation (CV)0.018288741
Kurtosis-0.41611031
Mean1.1247972 × 1018
Median Absolute Deviation (MAD)2.6999987 × 1012
Skewness1.1148947
Sum1.7992596 × 1018
Variance4.2317122 × 1032
MonotonicityNot monotonic
2023-12-10T18:53:39.404993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1111012300100990000 14
14.0%
1111011900101390000 12
12.0%
1156011000100440031 10
 
10.0%
1111012800101970009 7
 
7.0%
1123010400106940000 6
 
6.0%
1168010800100890004 5
 
5.0%
1111014600100110009 5
 
5.0%
1111014200100700000 4
 
4.0%
1111014600100110032 4
 
4.0%
1111012100100010131 4
 
4.0%
Other values (15) 29
29.0%
ValueCountFrequency (%)
1111010600100070038 3
 
3.0%
1111011900101390000 12
12.0%
1111012100100010131 4
 
4.0%
1111012300100990000 14
14.0%
1111012800101970009 7
7.0%
1111014200100700000 4
 
4.0%
1111014200101440002 3
 
3.0%
1111014600100110009 5
 
5.0%
1111014600100110032 4
 
4.0%
1111014900100090004 1
 
1.0%
ValueCountFrequency (%)
1168010800100890004 5
5.0%
1168010700105240036 1
 
1.0%
1168010600105090002 1
 
1.0%
1168010400101180017 1
 
1.0%
1162010200117070000 2
 
2.0%
1156011000100440031 10
10.0%
1153010800101500015 1
 
1.0%
1144011400100050129 1
 
1.0%
1144010400100370000 3
 
3.0%
1132010500104970015 3
 
3.0%

ctprvn_nm
Categorical

CONSTANT 

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

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 100
100.0%

Length

2023-12-10T18:53:39.724679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:53:39.928367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 100
100.0%

signgu_nm
Categorical

Distinct10
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
종로구
62 
영등포구
10 
강남구
8 
동대문구
 
6
마포구
 
4
Other values (5)
10 

Length

Max length4
Median length3
Mean length3.15
Min length2

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row강북구
2nd row종로구
3rd row강북구
4th row강북구
5th row강남구

Common Values

ValueCountFrequency (%)
종로구 62
62.0%
영등포구 10
 
10.0%
강남구 8
 
8.0%
동대문구 6
 
6.0%
마포구 4
 
4.0%
강북구 3
 
3.0%
도봉구 3
 
3.0%
관악구 2
 
2.0%
중구 1
 
1.0%
구로구 1
 
1.0%

Length

2023-12-10T18:53:40.122364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:53:40.543800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종로구 62
62.0%
영등포구 10
 
10.0%
강남구 8
 
8.0%
동대문구 6
 
6.0%
마포구 4
 
4.0%
강북구 3
 
3.0%
도봉구 3
 
3.0%
관악구 2
 
2.0%
중구 1
 
1.0%
구로구 1
 
1.0%

legaldong_nm
Categorical

Distinct23
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서린동
14 
세종로
12 
여의도동
10 
가회동
9 
관훈동
7 
Other values (18)
48 

Length

Max length5
Median length3
Mean length3.2
Min length3

Unique

Unique7 ?
Unique (%)7.0%

Sample

1st row수유동
2nd row동숭동
3rd row수유동
4th row수유동
5th row신사동

Common Values

ValueCountFrequency (%)
서린동 14
14.0%
세종로 12
12.0%
여의도동 10
10.0%
가회동 9
 
9.0%
관훈동 7
 
7.0%
소격동 7
 
7.0%
전농동 6
 
6.0%
논현동 5
 
5.0%
신문로2가 4
 
4.0%
도화동 3
 
3.0%
Other values (13) 23
23.0%

Length

2023-12-10T18:53:41.439672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서린동 14
14.0%
세종로 12
12.0%
여의도동 10
10.0%
가회동 9
 
9.0%
관훈동 7
 
7.0%
소격동 7
 
7.0%
전농동 6
 
6.0%
논현동 5
 
5.0%
신문로2가 4
 
4.0%
쌍문동 3
 
3.0%
Other values (13) 23
23.0%

trrsrt_li_nm
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

lnbr_no
Real number (ℝ)

Distinct23
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean183.64
Minimum1
Maximum1707
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:53:41.718746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q144
median99
Q3161.75
95-th percentile694
Maximum1707
Range1706
Interquartile range (IQR)117.75

Descriptive statistics

Standard deviation284.06268
Coefficient of variation (CV)1.5468454
Kurtosis15.469931
Mean183.64
Median Absolute Deviation (MAD)55
Skewness3.5423665
Sum18364
Variance80691.606
MonotonicityNot monotonic
2023-12-10T18:53:41.978015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
99 14
14.0%
139 12
12.0%
44 10
10.0%
11 9
 
9.0%
1 7
 
7.0%
197 7
 
7.0%
694 6
 
6.0%
89 5
 
5.0%
70 4
 
4.0%
360 3
 
3.0%
Other values (13) 23
23.0%
ValueCountFrequency (%)
1 7
7.0%
5 1
 
1.0%
7 3
 
3.0%
9 1
 
1.0%
11 9
9.0%
37 3
 
3.0%
44 10
10.0%
70 4
 
4.0%
86 1
 
1.0%
89 5
5.0%
ValueCountFrequency (%)
1707 2
 
2.0%
694 6
6.0%
524 1
 
1.0%
509 1
 
1.0%
497 3
3.0%
360 3
3.0%
273 2
 
2.0%
197 7
7.0%
150 1
 
1.0%
144 3
3.0%

legaldong_cd
Real number (ℝ)

Distinct23
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1247972 × 109
Minimum1.1110106 × 109
Maximum1.1680108 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:53:42.236192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110106 × 109
5-th percentile1.1110119 × 109
Q11.1110123 × 109
median1.1110146 × 109
Q31.1350105 × 109
95-th percentile1.1680107 × 109
Maximum1.1680108 × 109
Range57000200
Interquartile range (IQR)23998175

Descriptive statistics

Standard deviation20571126
Coefficient of variation (CV)0.018288741
Kurtosis-0.41611031
Mean1.1247972 × 109
Median Absolute Deviation (MAD)2700
Skewness1.1148947
Sum1.1247972 × 1011
Variance4.2317122 × 1014
MonotonicityNot monotonic
2023-12-10T18:53:42.496304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1111012300 14
14.0%
1111011900 12
12.0%
1156011000 10
10.0%
1111014600 9
 
9.0%
1111012800 7
 
7.0%
1111014200 7
 
7.0%
1123010400 6
 
6.0%
1168010800 5
 
5.0%
1111012100 4
 
4.0%
1130510300 3
 
3.0%
Other values (13) 23
23.0%
ValueCountFrequency (%)
1111010600 3
 
3.0%
1111011900 12
12.0%
1111012100 4
 
4.0%
1111012300 14
14.0%
1111012800 7
7.0%
1111014200 7
7.0%
1111014600 9
9.0%
1111014900 1
 
1.0%
1111016800 3
 
3.0%
1111018300 2
 
2.0%
ValueCountFrequency (%)
1168010800 5
5.0%
1168010700 1
 
1.0%
1168010600 1
 
1.0%
1168010400 1
 
1.0%
1162010200 2
 
2.0%
1156011000 10
10.0%
1153010800 1
 
1.0%
1144011400 1
 
1.0%
1144010400 3
 
3.0%
1132010500 3
 
3.0%

adstrd_cd
Real number (ℝ)

Distinct19
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1248442 × 109
Minimum1.111053 × 109
Maximum1.168061 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:53:42.750712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111053 × 109
5-th percentile1.111053 × 109
Q11.11106 × 109
median1.1110615 × 109
Q31.1350641 × 109
95-th percentile1.1680531 × 109
Maximum1.168061 × 109
Range57008000
Interquartile range (IQR)24004125

Descriptive statistics

Standard deviation20571534
Coefficient of variation (CV)0.01828834
Kurtosis-0.4165024
Mean1.1248442 × 109
Median Absolute Deviation (MAD)7500
Skewness1.1147447
Sum1.1248442 × 1011
Variance4.23188 × 1014
MonotonicityNot monotonic
2023-12-10T18:53:43.074979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
1111061500 33
33.0%
1156054000 10
 
10.0%
1111060000 10
 
10.0%
1111054000 7
 
7.0%
1111053000 7
 
7.0%
1123057000 6
 
6.0%
1168053100 5
 
5.0%
1130566000 3
 
3.0%
1144058500 3
 
3.0%
1111064000 3
 
3.0%
Other values (9) 13
 
13.0%
ValueCountFrequency (%)
1111053000 7
 
7.0%
1111054000 7
 
7.0%
1111056000 2
 
2.0%
1111060000 10
 
10.0%
1111061500 33
33.0%
1111064000 3
 
3.0%
1114054000 1
 
1.0%
1123057000 6
 
6.0%
1130566000 3
 
3.0%
1132066000 3
 
3.0%
ValueCountFrequency (%)
1168061000 1
 
1.0%
1168056500 1
 
1.0%
1168053100 5
5.0%
1168051000 1
 
1.0%
1162076500 2
 
2.0%
1156054000 10
10.0%
1153078000 1
 
1.0%
1144065500 1
 
1.0%
1144058500 3
 
3.0%
1132066000 3
 
3.0%

road_nm_cd
Real number (ℝ)

Distinct24
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.124821 × 1011
Minimum1.111031 × 1011
Maximum1.1680417 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:53:43.313487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111031 × 1011
5-th percentile1.111031 × 1011
Q11.111031 × 1011
median1.111041 × 1011
Q31.1350362 × 1011
95-th percentile1.1680417 × 1011
Maximum1.1680417 × 1011
Range5.7010665 × 109
Interquartile range (IQR)2.4005237 × 109

Descriptive statistics

Standard deviation2.0573633 × 109
Coefficient of variation (CV)0.018290583
Kurtosis-0.41599754
Mean1.124821 × 1011
Median Absolute Deviation (MAD)1000223
Skewness1.1149586
Sum1.124821 × 1013
Variance4.2327437 × 1018
MonotonicityNot monotonic
2023-12-10T18:53:43.560827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
111103100013 14
14.0%
111103100021 12
12.0%
115604154686 10
 
10.0%
111104100106 9
 
9.0%
111104100259 7
 
7.0%
112303105004 6
 
6.0%
116804166130 5
 
5.0%
111103100007 4
 
4.0%
111104100010 4
 
4.0%
113053108001 3
 
3.0%
Other values (14) 26
26.0%
ValueCountFrequency (%)
111103100007 4
 
4.0%
111103100013 14
14.0%
111103100017 3
 
3.0%
111103100021 12
12.0%
111104100010 4
 
4.0%
111104100075 3
 
3.0%
111104100106 9
9.0%
111104100236 3
 
3.0%
111104100259 7
7.0%
111104100426 1
 
1.0%
ValueCountFrequency (%)
116804166526 1
 
1.0%
116804166130 5
5.0%
116803122007 1
 
1.0%
116803122005 1
 
1.0%
116204160194 2
 
2.0%
115604154686 10
10.0%
115304148425 1
 
1.0%
114404139472 1
 
1.0%
114402113001 3
 
3.0%
113204127235 3
 
3.0%

road_nm
Categorical

Distinct25
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
종로
14 
세종대로
12 
여의대방로67길
10 
인사동길
7 
서울시립대로
6 
Other values (20)
51 

Length

Max length9
Median length7
Mean length4.6
Min length2

Unique

Unique7 ?
Unique (%)7.0%

Sample

1st row삼각산로
2nd row동숭길
3rd row삼각산로
4th row삼각산로
5th row압구정로4길

Common Values

ValueCountFrequency (%)
종로 14
14.0%
세종대로 12
12.0%
여의대방로67길 10
 
10.0%
인사동길 7
 
7.0%
서울시립대로 6
 
6.0%
논현로132길 5
 
5.0%
북촌로 5
 
5.0%
삼청로 4
 
4.0%
경희궁길 4
 
4.0%
북촌로12길 4
 
4.0%
Other values (15) 29
29.0%

Length

2023-12-10T18:53:43.855705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
종로 14
14.0%
세종대로 12
12.0%
여의대방로67길 10
 
10.0%
인사동길 7
 
7.0%
서울시립대로 6
 
6.0%
논현로132길 5
 
5.0%
북촌로 5
 
5.0%
삼청로 4
 
4.0%
경희궁길 4
 
4.0%
북촌로12길 4
 
4.0%
Other values (15) 29
29.0%

buld_no
Real number (ℝ)

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61.16
Minimum3
Maximum461
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:53:44.063820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile10.6
Q126
median34
Q385
95-th percentile163
Maximum461
Range458
Interquartile range (IQR)59

Descriptive statistics

Standard deviation65.460871
Coefficient of variation (CV)1.0703216
Kurtosis12.849402
Mean61.16
Median Absolute Deviation (MAD)16.5
Skewness2.801858
Sum6116
Variance4285.1257
MonotonicityNot monotonic
2023-12-10T18:53:44.301402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
26 14
14.0%
152 12
12.0%
11 10
 
10.0%
31 7
 
7.0%
163 6
 
6.0%
34 5
 
5.0%
56 5
 
5.0%
3 5
 
5.0%
29 4
 
4.0%
46 4
 
4.0%
Other values (12) 28
28.0%
ValueCountFrequency (%)
3 5
 
5.0%
11 10
10.0%
13 1
 
1.0%
18 1
 
1.0%
22 4
 
4.0%
25 3
 
3.0%
26 14
14.0%
29 4
 
4.0%
31 7
7.0%
34 5
 
5.0%
ValueCountFrequency (%)
461 1
 
1.0%
163 6
6.0%
154 1
 
1.0%
152 12
12.0%
87 3
 
3.0%
85 3
 
3.0%
56 5
5.0%
53 2
 
2.0%
51 1
 
1.0%
50 4
 
4.0%

fclty_la
Real number (ℝ)

Distinct25
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.565815
Minimum37.480884
Maximum37.654535
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:53:44.519349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.480884
5-th percentile37.5154
Q137.558045
median37.569934
Q337.580528
95-th percentile37.640899
Maximum37.654535
Range0.17365072
Interquartile range (IQR)0.022482658

Descriptive statistics

Standard deviation0.03428726
Coefficient of variation (CV)0.00091272506
Kurtosis1.0469428
Mean37.565815
Median Absolute Deviation (MAD)0.010593159
Skewness-0.05617269
Sum3756.5815
Variance0.0011756162
MonotonicityNot monotonic
2023-12-10T18:53:44.763945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
37.5698161294514 14
14.0%
37.5699343799262 12
12.0%
37.5197427168593 10
 
10.0%
37.5733027256519 7
 
7.0%
37.583172357095 6
 
6.0%
37.5154003365572 5
 
5.0%
37.5817274632398 5
 
5.0%
37.5803676023138 4
 
4.0%
37.5827783868919 4
 
4.0%
37.5735050353397 4
 
4.0%
Other values (15) 29
29.0%
ValueCountFrequency (%)
37.4808842091443 2
 
2.0%
37.4919744367079 1
 
1.0%
37.4939058830142 1
 
1.0%
37.5154003365572 5
5.0%
37.5197427168593 10
10.0%
37.5223547096329 1
 
1.0%
37.5252498120057 1
 
1.0%
37.5399681953471 3
 
3.0%
37.5539225586113 1
 
1.0%
37.5594189881234 1
 
1.0%
ValueCountFrequency (%)
37.6545349328794 3
3.0%
37.640899242035 3
3.0%
37.604688465649 2
 
2.0%
37.5837549591081 1
 
1.0%
37.583172357095 6
6.0%
37.5827783868919 4
4.0%
37.5817274632398 5
5.0%
37.5805275390665 3
3.0%
37.5803676023138 4
4.0%
37.5794978149528 3
3.0%

fclty_lo
Real number (ℝ)

Distinct25
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.98278
Minimum126.84406
Maximum127.06428
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:53:45.041438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.84406
5-th percentile126.93026
Q1126.97368
median126.98029
Q3126.98564
95-th percentile127.05691
Maximum127.06428
Range0.22021625
Interquartile range (IQR)0.011959199

Descriptive statistics

Standard deviation0.036119289
Coefficient of variation (CV)0.00028444241
Kurtosis1.8137167
Mean126.98278
Median Absolute Deviation (MAD)0.0059795997
Skewness-0.1746514
Sum12698.278
Variance0.0013046031
MonotonicityNot monotonic
2023-12-10T18:53:45.259549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
126.980286763081 14
14.0%
126.97767124462 12
12.0%
126.930259606917 10
 
10.0%
126.985287984346 7
 
7.0%
127.056911551003 6
 
6.0%
127.033346654041 5
 
5.0%
126.985297716405 5
 
5.0%
126.980298367847 4
 
4.0%
126.985639091829 4
 
4.0%
126.969098253912 4
 
4.0%
Other values (15) 29
29.0%
ValueCountFrequency (%)
126.844061599284 1
 
1.0%
126.918215760664 2
 
2.0%
126.929651812291 1
 
1.0%
126.930259606917 10
10.0%
126.947094324244 3
 
3.0%
126.965907779054 2
 
2.0%
126.969098253912 4
 
4.0%
126.973679892447 3
 
3.0%
126.97767124462 12
12.0%
126.980286763081 14
14.0%
ValueCountFrequency (%)
127.064277849948 1
 
1.0%
127.056911551003 6
6.0%
127.047217239636 1
 
1.0%
127.033346654041 5
5.0%
127.021666090458 1
 
1.0%
127.014748703613 3
3.0%
127.013476224682 3
3.0%
127.003230580869 3
3.0%
126.988618367966 1
 
1.0%
126.985639091829 4
4.0%

gid_cd
Categorical

Distinct25
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
다사541523
14 
다사538524
12 
다사496468
10 
다사545527
7 
다사608538
6 
Other values (20)
51 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique7 ?
Unique (%)7.0%

Sample

1st row다사570602
2nd row다사561535
3rd row다사570602
4th row다사570602
5th row다사577471

Common Values

ValueCountFrequency (%)
다사541523 14
14.0%
다사538524 12
12.0%
다사496468 10
 
10.0%
다사545527 7
 
7.0%
다사608538 6
 
6.0%
다사587463 5
 
5.0%
다사545537 5
 
5.0%
다사541535 4
 
4.0%
다사531528 4
 
4.0%
다사545538 4
 
4.0%
Other values (15) 29
29.0%

Length

2023-12-10T18:53:45.475151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
다사541523 14
14.0%
다사538524 12
12.0%
다사496468 10
 
10.0%
다사545527 7
 
7.0%
다사608538 6
 
6.0%
다사587463 5
 
5.0%
다사545537 5
 
5.0%
다사541535 4
 
4.0%
다사531528 4
 
4.0%
다사545538 4
 
4.0%
Other values (15) 29
29.0%

lend_fclty_gugun_nm
Categorical

Distinct10
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
종로구
55 
영등포구
10 
중구
9 
강남구
8 
강북구
 
5
Other values (5)
13 

Length

Max length4
Median length3
Mean length3.06
Min length2

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row강북구
2nd row종로구
3rd row강북구
4th row강북구
5th row강남구

Common Values

ValueCountFrequency (%)
종로구 55
55.0%
영등포구 10
 
10.0%
중구 9
 
9.0%
강남구 8
 
8.0%
강북구 5
 
5.0%
동대문구 5
 
5.0%
마포구 4
 
4.0%
관악구 2
 
2.0%
도봉구 1
 
1.0%
구로구 1
 
1.0%

Length

2023-12-10T18:53:45.719871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:53:45.964519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종로구 55
55.0%
영등포구 10
 
10.0%
중구 9
 
9.0%
강남구 8
 
8.0%
강북구 5
 
5.0%
동대문구 5
 
5.0%
마포구 4
 
4.0%
관악구 2
 
2.0%
도봉구 1
 
1.0%
구로구 1
 
1.0%

lend_fclty_nm
Text

Distinct75
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:53:46.401040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length13.56
Min length5

Characters and Unicode

Total characters1356
Distinct characters192
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)57.0%

Sample

1st row1506. 강북문화예술회관
2nd row355. 서울사대부속초교 앞
3rd row1518. SK telecom(수유직영점) 앞
4th row1540. 가오리역
5th row2301. 현대고등학교 건너편
ValueCountFrequency (%)
앞 42
 
13.8%
옆 10
 
3.3%
광화문역 9
 
3.0%
삼거리 7
 
2.3%
종각역 6
 
2.0%
1번출구 6
 
2.0%
5번출구 6
 
2.0%
2번출구 5
 
1.6%
353 4
 
1.3%
재동초교 4
 
1.3%
Other values (152) 205
67.4%
2023-12-10T18:53:47.257265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
204
 
15.0%
. 88
 
6.5%
3 70
 
5.2%
1 47
 
3.5%
2 45
 
3.3%
앞 44
 
3.2%
5 38
 
2.8%
구 35
 
2.6%
역 32
 
2.4%
0 27
 
2.0%
Other values (182) 726
53.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 715
52.7%
Decimal Number 309
22.8%
Space Separator 204
 
15.0%
Other Punctuation 88
 
6.5%
Uppercase Letter 23
 
1.7%
Lowercase Letter 7
 
0.5%
Open Punctuation 5
 
0.4%
Close Punctuation 5
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 44
 
6.2%
구 35
 
4.9%
역 32
 
4.5%
출 26
 
3.6%
번 26
 
3.6%
대 18
 
2.5%
동 17
 
2.4%
광 16
 
2.2%
서 15
 
2.1%
거 15
 
2.1%
Other values (149) 471
65.9%
Uppercase Letter
ValueCountFrequency (%)
A 4
17.4%
S 4
17.4%
K 4
17.4%
L 2
8.7%
O 1
 
4.3%
Y 1
 
4.3%
P 1
 
4.3%
C 1
 
4.3%
E 1
 
4.3%
R 1
 
4.3%
Other values (3) 3
13.0%
Decimal Number
ValueCountFrequency (%)
3 70
22.7%
1 47
15.2%
2 45
14.6%
5 38
12.3%
0 27
 
8.7%
4 26
 
8.4%
6 19
 
6.1%
8 17
 
5.5%
7 14
 
4.5%
9 6
 
1.9%
Lowercase Letter
ValueCountFrequency (%)
e 2
28.6%
m 1
14.3%
o 1
14.3%
c 1
14.3%
l 1
14.3%
t 1
14.3%
Space Separator
ValueCountFrequency (%)
204
100.0%
Other Punctuation
ValueCountFrequency (%)
. 88
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 715
52.7%
Common 611
45.1%
Latin 30
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 44
 
6.2%
구 35
 
4.9%
역 32
 
4.5%
출 26
 
3.6%
번 26
 
3.6%
대 18
 
2.5%
동 17
 
2.4%
광 16
 
2.2%
서 15
 
2.1%
거 15
 
2.1%
Other values (149) 471
65.9%
Latin
ValueCountFrequency (%)
A 4
13.3%
S 4
13.3%
K 4
13.3%
L 2
 
6.7%
e 2
 
6.7%
O 1
 
3.3%
Y 1
 
3.3%
P 1
 
3.3%
C 1
 
3.3%
E 1
 
3.3%
Other values (9) 9
30.0%
Common
ValueCountFrequency (%)
204
33.4%
. 88
14.4%
3 70
 
11.5%
1 47
 
7.7%
2 45
 
7.4%
5 38
 
6.2%
0 27
 
4.4%
4 26
 
4.3%
6 19
 
3.1%
8 17
 
2.8%
Other values (4) 30
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 715
52.7%
ASCII 641
47.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
204
31.8%
. 88
13.7%
3 70
 
10.9%
1 47
 
7.3%
2 45
 
7.0%
5 38
 
5.9%
0 27
 
4.2%
4 26
 
4.1%
6 19
 
3.0%
8 17
 
2.7%
Other values (23) 60
 
9.4%
Hangul
ValueCountFrequency (%)
앞 44
 
6.2%
구 35
 
4.9%
역 32
 
4.5%
출 26
 
3.6%
번 26
 
3.6%
대 18
 
2.5%
동 17
 
2.4%
광 16
 
2.2%
서 15
 
2.1%
거 15
 
2.1%
Other values (149) 471
65.9%

lend_fclty_addr
Text

Distinct69
Distinct (%)69.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:53:47.801423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20.5
Mean length17.42
Min length10

Characters and Unicode

Total characters1742
Distinct characters98
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)50.0%

Sample

1st row서울특별시 강북구 삼각산로 85
2nd row서울특별시 종로구 연건동 178-3
3rd row서울특별시 강북구 삼양로 439
4th row서울특별시 강북구 삼양로 426
5th row서울특별시 강남구 압구정로 134
ValueCountFrequency (%)
서울특별시 89
22.8%
종로구 54
 
13.8%
세종대로 10
 
2.6%
영등포구 10
 
2.6%
중구 9
 
2.3%
강남구 8
 
2.0%
지하172 6
 
1.5%
동대문구 6
 
1.5%
30 5
 
1.3%
서린동 5
 
1.3%
Other values (118) 189
48.3%
2023-12-10T18:53:48.654360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
291
16.7%
로 130
 
7.5%
구 102
 
5.9%
서 98
 
5.6%
울 92
 
5.3%
시 92
 
5.3%
별 89
 
5.1%
특 89
 
5.1%
종 71
 
4.1%
1 66
 
3.8%
Other values (88) 622
35.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1144
65.7%
Space Separator 291
 
16.7%
Decimal Number 286
 
16.4%
Dash Punctuation 21
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 130
 
11.4%
구 102
 
8.9%
서 98
 
8.6%
울 92
 
8.0%
시 92
 
8.0%
별 89
 
7.8%
특 89
 
7.8%
종 71
 
6.2%
대 29
 
2.5%
동 24
 
2.1%
Other values (76) 328
28.7%
Decimal Number
ValueCountFrequency (%)
1 66
23.1%
3 36
12.6%
2 33
11.5%
6 32
11.2%
9 23
 
8.0%
7 23
 
8.0%
5 22
 
7.7%
4 22
 
7.7%
0 15
 
5.2%
8 14
 
4.9%
Space Separator
ValueCountFrequency (%)
291
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1144
65.7%
Common 598
34.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 130
 
11.4%
구 102
 
8.9%
서 98
 
8.6%
울 92
 
8.0%
시 92
 
8.0%
별 89
 
7.8%
특 89
 
7.8%
종 71
 
6.2%
대 29
 
2.5%
동 24
 
2.1%
Other values (76) 328
28.7%
Common
ValueCountFrequency (%)
291
48.7%
1 66
 
11.0%
3 36
 
6.0%
2 33
 
5.5%
6 32
 
5.4%
9 23
 
3.8%
7 23
 
3.8%
5 22
 
3.7%
4 22
 
3.7%
- 21
 
3.5%
Other values (2) 29
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1144
65.7%
ASCII 598
34.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
291
48.7%
1 66
 
11.0%
3 36
 
6.0%
2 33
 
5.5%
6 32
 
5.4%
9 23
 
3.8%
7 23
 
3.8%
5 22
 
3.7%
4 22
 
3.7%
- 21
 
3.5%
Other values (2) 29
 
4.8%
Hangul
ValueCountFrequency (%)
로 130
 
11.4%
구 102
 
8.9%
서 98
 
8.6%
울 92
 
8.0%
시 92
 
8.0%
별 89
 
7.8%
특 89
 
7.8%
종 71
 
6.2%
대 29
 
2.5%
동 24
 
2.1%
Other values (76) 328
28.7%

lend_fclty_la
Real number (ℝ)

Distinct74
Distinct (%)74.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.565747
Minimum37.477776
Maximum37.656158
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:53:48.934438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.477776
5-th percentile37.513879
Q137.559244
median37.570602
Q337.579708
95-th percentile37.640394
Maximum37.656158
Range0.178382
Interquartile range (IQR)0.020464

Descriptive statistics

Standard deviation0.034208054
Coefficient of variation (CV)0.00091061824
Kurtosis1.1423076
Mean37.565747
Median Absolute Deviation (MAD)0.009106
Skewness-0.036485648
Sum3756.5747
Variance0.001170191
MonotonicityNot monotonic
2023-12-10T18:53:49.222089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.579388 4
 
4.0%
37.570396 4
 
4.0%
37.569836 3
 
3.0%
37.58419037 3
 
3.0%
37.583416 3
 
3.0%
37.579708 3
 
3.0%
37.569939 2
 
2.0%
37.572582 2
 
2.0%
37.570808 2
 
2.0%
37.569889 2
 
2.0%
Other values (64) 72
72.0%
ValueCountFrequency (%)
37.477776 1
1.0%
37.480251 1
1.0%
37.493938 1
1.0%
37.494499 1
1.0%
37.512527 1
1.0%
37.51395 1
1.0%
37.514748 1
1.0%
37.517368 1
1.0%
37.51759 1
1.0%
37.517765 1
1.0%
ValueCountFrequency (%)
37.656158 1
 
1.0%
37.654472 1
 
1.0%
37.653179 1
 
1.0%
37.643085 1
 
1.0%
37.64167 1
 
1.0%
37.640327 1
 
1.0%
37.603992 1
 
1.0%
37.603512 1
 
1.0%
37.585197 1
 
1.0%
37.58419037 3
3.0%

lend_fclty_lo
Real number (ℝ)

Distinct74
Distinct (%)74.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.98262
Minimum126.84405
Maximum127.0638
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:53:49.651869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.84405
5-th percentile126.92705
Q1126.97355
median126.9817
Q3126.98838
95-th percentile127.05442
Maximum127.0638
Range0.219742
Interquartile range (IQR)0.0148375

Descriptive statistics

Standard deviation0.036572912
Coefficient of variation (CV)0.0002880151
Kurtosis1.7154686
Mean126.98262
Median Absolute Deviation (MAD)0.00745
Skewness-0.15442732
Sum12698.262
Variance0.0013375779
MonotonicityNot monotonic
2023-12-10T18:53:49.938604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.984947 4
 
4.0%
126.982658 3
 
3.0%
126.9816971 3
 
3.0%
126.985237 3
 
3.0%
126.980858 3
 
3.0%
126.97747 3
 
3.0%
126.981789 3
 
3.0%
126.971451 2
 
2.0%
126.978355 2
 
2.0%
126.976433 2
 
2.0%
Other values (64) 72
72.0%
ValueCountFrequency (%)
126.844055 1
1.0%
126.914604 1
1.0%
126.916756 1
1.0%
126.925835 1
1.0%
126.926048 1
1.0%
126.927101 1
1.0%
126.928413 1
1.0%
126.929237 1
1.0%
126.929253 1
1.0%
126.930367 1
1.0%
ValueCountFrequency (%)
127.063797 1
1.0%
127.060974 1
1.0%
127.060951 1
1.0%
127.0579376 1
1.0%
127.055344 1
1.0%
127.054367 1
1.0%
127.053856 1
1.0%
127.052467 1
1.0%
127.035835 1
1.0%
127.0354 1
1.0%

Sample

esntl_idlclas_nmmlsfc_nmpoi_idpoi_nmbhf_nmasstn_nmcl_nmpnuctprvn_nmsigngu_nmlegaldong_nmtrrsrt_li_nmlnbr_nolegaldong_cdadstrd_cdroad_nm_cdroad_nmbuld_nofclty_lafclty_logid_cdlend_fclty_gugun_nmlend_fclty_nmlend_fclty_addrlend_fclty_lalend_fclty_lo
0KCUPCPO21N000000001장소문화시설10213333강북문화예술회관<NA><NA>대형예술센터1130510300103600010서울특별시강북구수유동<NA>36011305103001130566000113053108001삼각산로8537.640899127.013476다사570602강북구1506. 강북문화예술회관서울특별시 강북구 삼각산로 8537.640327127.013359
1KCUPCPO21N000011012장소문화시설9650921아르코미술관<NA><NA>미술관1111016800100010130서울특별시종로구동숭동<NA>111110168001111064000111104100075동숭길337.580528127.003231다사561535종로구355. 서울사대부속초교 앞서울특별시 종로구 연건동 178-337.576508127.002457
2KCUPCPO21N000000003장소문화시설10213333강북문화예술회관<NA><NA>대형예술센터1130510300103600010서울특별시강북구수유동<NA>36011305103001130566000113053108001삼각산로8537.640899127.013476다사570602강북구1518. SK telecom(수유직영점) 앞서울특별시 강북구 삼양로 43937.643085127.016167
3KCUPCPO21N000000004장소문화시설10213333강북문화예술회관<NA><NA>대형예술센터1130510300103600010서울특별시강북구수유동<NA>36011305103001130566000113053108001삼각산로8537.640899127.013476다사570602강북구1540. 가오리역서울특별시 강북구 삼양로 42637.64167127.016884
4KCUPCPO21N000000005장소문화시설10213335갤러리S.P<NA><NA>소형갤러리1168010700105240036서울특별시강남구신사동<NA>52411680107001168051000116804166526압구정로4길1337.522355127.021666다사577471강남구2301. 현대고등학교 건너편서울특별시 강남구 압구정로 13437.524071127.02179
5KCUPCPO21N000000006장소문화시설10213354강남구민회관<NA><NA>구민/시민회관1168010600105090002서울특별시강남구대치동<NA>50911680106001168061000116803122005삼성로15437.493906127.064278다사614439강남구2372. 대치역 사거리서울특별시 강남구 삼성로 15637.494499127.063797
6KCUPCPO21N000000007장소문화시설10253144아트선재센터<NA><NA>기타전시/박물관1111014200101440002서울특별시종로구소격동<NA>14411110142001111054000111104100236율곡로3길8737.579498126.98188다사542534종로구314. 국립현대미술관서울특별시 종로구 삼청로 3037.579708126.980858
7KCUPCPO21N000011013장소문화시설9650921아르코미술관<NA><NA>미술관1111016800100010130서울특별시종로구동숭동<NA>111110168001111064000111104100075동숭길337.580528127.003231다사561535종로구356. KT혜화지사 앞서울특별시 종로구 대학로 6537.577145127.00206
8KCUPCPO21N000000009장소문화시설10253144아트선재센터<NA><NA>기타전시/박물관1111014200101440002서울특별시종로구소격동<NA>14411110142001111054000111104100236율곡로3길8737.579498126.98188다사542534종로구353. 재동초교 앞 삼거리서울특별시 종로구 재동 1937.579388126.984947
9KCUPCPO21N000000010장소문화시설10253144아트선재센터<NA><NA>기타전시/박물관1111014200101440002서울특별시종로구소격동<NA>14411110142001111054000111104100236율곡로3길8737.579498126.98188다사542534종로구451. 청와대앞길서울특별시 종로구 청와대로 7337.583515126.979668
esntl_idlclas_nmmlsfc_nmpoi_idpoi_nmbhf_nmasstn_nmcl_nmpnuctprvn_nmsigngu_nmlegaldong_nmtrrsrt_li_nmlnbr_nolegaldong_cdadstrd_cdroad_nm_cdroad_nmbuld_nofclty_lafclty_logid_cdlend_fclty_gugun_nmlend_fclty_nmlend_fclty_addrlend_fclty_lalend_fclty_lo
90KCUPCPO21N000000091장소문화시설10253263서울시립대학교박물관<NA><NA>기타전시/박물관1123010400106940000서울특별시동대문구전농동<NA>69411230104001123057000112303105004서울시립대로16337.583172127.056912다사608538종로구서울시립대 대학본부동대문구 서울시립대로 163 서울시립대학교37.584129127.057938
91KCUPCPO21N000000092장소문화시설10253264디자인박물관<NA><NA>기타전시/박물관1111014900100090004서울특별시종로구원서동<NA>911110149001111060000111104100426창덕궁5길2237.583755126.988618다사548539종로구352. 중앙고입구 삼거리서울특별시 종로구 창덕궁길 19137.583416126.985237
92KCUPCPO21N000000093장소문화시설10253267백송화랑<NA><NA>기타전시/박물관1111012800101970009서울특별시종로구관훈동<NA>19711110128001111061500111104100259인사동길3137.573303126.985288다사545527종로구315. 신한은행 안국역지점 옆서울특별시 종로구 율곡로 3337.57597126.983063
93KCUPCPO21N000000094장소문화시설10253267백송화랑<NA><NA>기타전시/박물관1111012800101970009서울특별시종로구관훈동<NA>19711110128001111061500111104100259인사동길3137.573303126.985288다사545527종로구316. 종각역 1번출구 앞서울특별시 종로구 종로 4737.570396126.981789
94KCUPCPO21N000000095장소문화시설10253267백송화랑<NA><NA>기타전시/박물관1111012800101970009서울특별시종로구관훈동<NA>19711110128001111061500111104100259인사동길3137.573303126.985288다사545527종로구326. 안국역 5번출구 앞서울특별시 종로구 율곡로 지하6237.576241126.98616
95KCUPCPO21N000000096장소문화시설10253267백송화랑<NA><NA>기타전시/박물관1111012800101970009서울특별시종로구관훈동<NA>19711110128001111061500111104100259인사동길3137.573303126.985288다사545527종로구327. 낙원상가 옆서울특별시 종로구 삼일대로 42837.573357126.987465
96KCUPCPO21N000000097장소문화시설10253267백송화랑<NA><NA>기타전시/박물관1111012800101970009서울특별시종로구관훈동<NA>19711110128001111061500111104100259인사동길3137.573303126.985288다사545527종로구328. 탑골공원 앞서울특별시 종로구 종로 9937.570396126.98819
97KCUPCPO21N000000098장소문화시설10253267백송화랑<NA><NA>기타전시/박물관1111012800101970009서울특별시종로구관훈동<NA>19711110128001111061500111104100259인사동길3137.573303126.985288다사545527종로구385. 종각역 5번출구서울특별시 종로구 서린동 26-137.569836126.982658
98KCUPCPO21N000000099장소문화시설10253267백송화랑<NA><NA>기타전시/박물관1111012800101970009서울특별시종로구관훈동<NA>19711110128001111061500111104100259인사동길3137.573303126.985288다사545527종로구종로2가 버스정류장(종각방향)종로구 종로 79-137.570358126.986382
99KCUPCPO21N000000100장소문화시설10253269박여숙화랑<NA><NA>기타전시/박물관1168010400101180017서울특별시강남구청담동<NA>11811680104001168056500116803122007압구정로46137.52525127.047217다사599474강남구2313. 금원빌딩 앞서울특별시 강남구 도산대로 53937.525116127.052467