Overview

Dataset statistics

Number of variables27
Number of observations100
Missing cells139
Missing cells (%)5.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.2 KiB
Average record size in memory227.3 B

Variable types

Text9
Categorical10
Numeric8

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
ri_nm has 73 (73.0%) missing valuesMissing
rd_cd has 22 (22.0%) missing valuesMissing
rd_nm has 22 (22.0%) missing valuesMissing
bld_num has 22 (22.0%) missing valuesMissing
id has unique valuesUnique
id_poi has unique valuesUnique
x has unique valuesUnique
y has unique valuesUnique

Reproduction

Analysis started2023-12-10 09:39:47.136466
Analysis finished2023-12-10 09:39:47.988404
Duration0.85 seconds
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
2023-12-10T18:39:48.238261image/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 rowKCLPPPO21N000038441
2nd rowKCLPPPO21N000096058
3rd rowKCLPPPO21N000038443
4th rowKCLPPPO21N000038444
5th rowKCLPPPO21N000038445
ValueCountFrequency (%)
kclpppo21n000038441 1
 
1.0%
kclpppo21n000038503 1
 
1.0%
kclpppo21n000038514 1
 
1.0%
kclpppo21n000038513 1
 
1.0%
kclpppo21n000038512 1
 
1.0%
kclpppo21n000038511 1
 
1.0%
kclpppo21n000038510 1
 
1.0%
kclpppo21n000038509 1
 
1.0%
kclpppo21n000038508 1
 
1.0%
kclpppo21n000038507 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T18:39:48.792575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 424
22.3%
P 300
15.8%
1 120
 
6.3%
2 118
 
6.2%
3 117
 
6.2%
8 117
 
6.2%
K 100
 
5.3%
C 100
 
5.3%
L 100
 
5.3%
O 100
 
5.3%
Other values (6) 304
16.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 424
38.5%
1 120
 
10.9%
2 118
 
10.7%
3 117
 
10.6%
8 117
 
10.6%
4 74
 
6.7%
5 63
 
5.7%
6 24
 
2.2%
9 24
 
2.2%
7 19
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
P 300
37.5%
K 100
 
12.5%
C 100
 
12.5%
L 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 (%)
0 424
38.5%
1 120
 
10.9%
2 118
 
10.7%
3 117
 
10.6%
8 117
 
10.6%
4 74
 
6.7%
5 63
 
5.7%
6 24
 
2.2%
9 24
 
2.2%
7 19
 
1.7%
Latin
ValueCountFrequency (%)
P 300
37.5%
K 100
 
12.5%
C 100
 
12.5%
L 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 (%)
0 424
22.3%
P 300
15.8%
1 120
 
6.3%
2 118
 
6.2%
3 117
 
6.2%
8 117
 
6.2%
K 100
 
5.3%
C 100
 
5.3%
L 100
 
5.3%
O 100
 
5.3%
Other values (6) 304
16.0%

lclas
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

2023-12-10T18:39:49.026440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:39:49.179247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
장소 100
100.0%

mlsfc
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
교통 100
100.0%

Length

2023-12-10T18:39:49.323817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:39:49.476315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교통 100
100.0%

id_poi
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10058915
Minimum223454
Maximum20935217
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:39:49.647486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum223454
5-th percentile660349.6
Q17235133
median7236966
Q314806274
95-th percentile16603499
Maximum20935217
Range20711763
Interquartile range (IQR)7571141.2

Descriptive statistics

Standard deviation4967008
Coefficient of variation (CV)0.49379161
Kurtosis-0.66573506
Mean10058915
Median Absolute Deviation (MAD)2414067
Skewness0.21762896
Sum1.0058915 × 109
Variance2.4671169 × 1013
MonotonicityNot monotonic
2023-12-10T18:39:49.857703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
223454 1
 
1.0%
11177006 1
 
1.0%
14118745 1
 
1.0%
13933992 1
 
1.0%
13825615 1
 
1.0%
13732999 1
 
1.0%
13728075 1
 
1.0%
11397572 1
 
1.0%
11294173 1
 
1.0%
11294078 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
223454 1
1.0%
549306 1
1.0%
549653 1
1.0%
659889 1
1.0%
660266 1
1.0%
660354 1
1.0%
1247015 1
1.0%
4989939 1
1.0%
5499602 1
1.0%
5540457 1
1.0%
ValueCountFrequency (%)
20935217 1
1.0%
20661412 1
1.0%
20545282 1
1.0%
16608627 1
1.0%
16603864 1
1.0%
16603480 1
1.0%
16597032 1
1.0%
16593131 1
1.0%
16590696 1
1.0%
16589978 1
1.0%

poi_nm
Text

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:39:50.227187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length5.42
Min length3

Characters and Unicode

Total characters542
Distinct characters148
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

Unique96 ?
Unique (%)96.0%

Sample

1st row삼화택시
2nd row목원대학교입구버스정류장
3rd row산성역
4th row문곡역
5th row금강휴게소
ValueCountFrequency (%)
계명대역 2
 
2.0%
오리역 2
 
2.0%
고미당휴게소 1
 
1.0%
한일택시 1
 
1.0%
삼화택시 1
 
1.0%
군산공항여객청사 1
 
1.0%
칠성택시 1
 
1.0%
광명역 1
 
1.0%
오금역 1
 
1.0%
동송정역 1
 
1.0%
Other values (88) 88
88.0%
2023-12-10T18:39:50.837867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
역 55
 
10.1%
장 19
 
3.5%
정 17
 
3.1%
버 16
 
3.0%
스 16
 
3.0%
터 14
 
2.6%
미 13
 
2.4%
대 12
 
2.2%
류 12
 
2.2%
게 11
 
2.0%
Other values (138) 357
65.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 538
99.3%
Decimal Number 4
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
역 55
 
10.2%
장 19
 
3.5%
정 17
 
3.2%
버 16
 
3.0%
스 16
 
3.0%
터 14
 
2.6%
미 13
 
2.4%
대 12
 
2.2%
류 12
 
2.2%
게 11
 
2.0%
Other values (136) 353
65.6%
Decimal Number
ValueCountFrequency (%)
3 3
75.0%
2 1
 
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 538
99.3%
Common 4
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
역 55
 
10.2%
장 19
 
3.5%
정 17
 
3.2%
버 16
 
3.0%
스 16
 
3.0%
터 14
 
2.6%
미 13
 
2.4%
대 12
 
2.2%
류 12
 
2.2%
게 11
 
2.0%
Other values (136) 353
65.6%
Common
ValueCountFrequency (%)
3 3
75.0%
2 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 538
99.3%
ASCII 4
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
역 55
 
10.2%
장 19
 
3.5%
정 17
 
3.2%
버 16
 
3.0%
스 16
 
3.0%
터 14
 
2.6%
미 13
 
2.4%
대 12
 
2.2%
류 12
 
2.2%
게 11
 
2.0%
Other values (136) 353
65.6%
ASCII
ValueCountFrequency (%)
3 3
75.0%
2 1
 
25.0%

branch_nm
Categorical

Distinct29
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
41 
서울1호선
7 
서울5호선
6 
서울2호선
5 
인천1호선
5 
Other values (24)
36 

Length

Max length7
Median length6
Mean length4.71
Min length3

Unique

Unique18 ?
Unique (%)18.0%

Sample

1st row<NA>
2nd row34-900
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 41
41.0%
서울1호선 7
 
7.0%
서울5호선 6
 
6.0%
서울2호선 5
 
5.0%
인천1호선 5
 
5.0%
대구2호선 5
 
5.0%
서울4호선 4
 
4.0%
부산1호선 3
 
3.0%
수인분당선 2
 
2.0%
대전1호선 2
 
2.0%
Other values (19) 20
20.0%

Length

2023-12-10T18:39:51.099016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 41
41.0%
서울1호선 7
 
7.0%
서울5호선 6
 
6.0%
서울2호선 5
 
5.0%
인천1호선 5
 
5.0%
대구2호선 5
 
5.0%
서울4호선 4
 
4.0%
부산1호선 3
 
3.0%
대구1호선 2
 
2.0%
대전1호선 2
 
2.0%
Other values (19) 20
20.0%

sub_nm
Categorical

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
59 
3번출구
7 
2번출구
6 
4번출구
6 
6번출구
6 
Other values (7)
16 

Length

Max length5
Median length4
Mean length4.03
Min length4

Unique

Unique3 ?
Unique (%)3.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 59
59.0%
3번출구 7
 
7.0%
2번출구 6
 
6.0%
4번출구 6
 
6.0%
6번출구 6
 
6.0%
8번출구 4
 
4.0%
7번출구 3
 
3.0%
5번출구 3
 
3.0%
1번출구 3
 
3.0%
12번출구 1
 
1.0%
Other values (2) 2
 
2.0%

Length

2023-12-10T18:39:51.324993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 59
59.0%
3번출구 7
 
7.0%
2번출구 6
 
6.0%
4번출구 6
 
6.0%
6번출구 6
 
6.0%
8번출구 4
 
4.0%
7번출구 3
 
3.0%
5번출구 3
 
3.0%
1번출구 3
 
3.0%
12번출구 1
 
1.0%
Other values (2) 2
 
2.0%

mcate_cd
Real number (ℝ)

Distinct30
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean149194.11
Minimum140401
Maximum150619
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:39:51.599509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum140401
5-th percentile140401
Q1150387
median150505
Q3150604
95-th percentile150617
Maximum150619
Range10218
Interquartile range (IQR)217

Descriptive statistics

Standard deviation3418.4681
Coefficient of variation (CV)0.022912889
Kurtosis3.036097
Mean149194.11
Median Absolute Deviation (MAD)99
Skewness-2.227996
Sum14919411
Variance11685924
MonotonicityNot monotonic
2023-12-10T18:39:52.152251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
140401 13
13.0%
150504 11
 
11.0%
150506 9
 
9.0%
150601 7
 
7.0%
150605 5
 
5.0%
150203 5
 
5.0%
150612 5
 
5.0%
150617 5
 
5.0%
150602 5
 
5.0%
150502 4
 
4.0%
Other values (20) 31
31.0%
ValueCountFrequency (%)
140401 13
13.0%
150101 1
 
1.0%
150103 1
 
1.0%
150104 1
 
1.0%
150203 5
 
5.0%
150302 1
 
1.0%
150303 3
 
3.0%
150415 1
 
1.0%
150416 1
 
1.0%
150421 1
 
1.0%
ValueCountFrequency (%)
150619 2
 
2.0%
150617 5
5.0%
150613 3
3.0%
150612 5
5.0%
150610 2
 
2.0%
150608 1
 
1.0%
150607 1
 
1.0%
150605 5
5.0%
150604 4
4.0%
150603 1
 
1.0%

mcate_nm
Categorical

Distinct29
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
국도/지방도휴게소
13 
시내버스정류장명
11 
버스/택시/화물차고지
9 
서울1호선
7 
서울5호선
6 
Other values (24)
54 

Length

Max length11
Median length9
Mean length6.68
Min length3

Unique

Unique12 ?
Unique (%)12.0%

Sample

1st row버스/택시/화물차고지
2nd row시내버스정류장명
3rd row기타철도역명
4th row기타철도역명
5th row국도/지방도휴게소

Common Values

ValueCountFrequency (%)
국도/지방도휴게소 13
13.0%
시내버스정류장명 11
 
11.0%
버스/택시/화물차고지 9
 
9.0%
서울1호선 7
 
7.0%
서울5호선 6
 
6.0%
일반페리터미널 5
 
5.0%
인천1호선 5
 
5.0%
대구2호선 5
 
5.0%
서울2호선 5
 
5.0%
서울4호선 4
 
4.0%
Other values (19) 30
30.0%

Length

2023-12-10T18:39:52.393022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
국도/지방도휴게소 13
13.0%
시내버스정류장명 11
 
11.0%
버스/택시/화물차고지 9
 
9.0%
서울1호선 7
 
7.0%
서울5호선 6
 
6.0%
일반페리터미널 5
 
5.0%
인천1호선 5
 
5.0%
대구2호선 5
 
5.0%
서울2호선 5
 
5.0%
서울4호선 4
 
4.0%
Other values (19) 30
30.0%

pnu
Real number (ℝ)

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9522932 × 1018
Minimum1.1110132 × 1018
Maximum5.0110111 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:39:52.630979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110132 × 1018
5-th percentile1.1138628 × 1018
Q11.1601352 × 1018
median2.8237103 × 1018
Q34.3111905 × 1018
95-th percentile4.726483 × 1018
Maximum5.0110111 × 1018
Range3.8999979 × 1018
Interquartile range (IQR)3.1510553 × 1018

Descriptive statistics

Standard deviation1.4223667 × 1018
Coefficient of variation (CV)0.48178369
Kurtosis-1.5786748
Mean2.9522932 × 1018
Median Absolute Deviation (MAD)1.6511995 × 1018
Skewness-0.17281035
Sum8.1416807 × 1016
Variance2.023127 × 1036
MonotonicityNot monotonic
2023-12-10T18:39:52.890887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2729010700110340004 2
 
2.0%
4113511400101970001 2
 
2.0%
1132010800106250144 1
 
1.0%
4311425022101650005 1
 
1.0%
5011011100121650002 1
 
1.0%
4376034021102210001 1
 
1.0%
4121010600102760001 1
 
1.0%
1171010700100020011 1
 
1.0%
2920010900101780026 1
 
1.0%
2729010200112900001 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
1111013200100980007 1
1.0%
1111013500100070005 1
1.0%
1111015600100100005 1
1.0%
1111016400100940011 1
1.0%
1111017700102220000 1
1.0%
1114012500101090002 1
1.0%
1114014900101120003 1
1.0%
1114015500103470003 1
1.0%
1120011100115830000 1
1.0%
1121510300102450024 1
1.0%
ValueCountFrequency (%)
5011011100121650002 1
1.0%
4822037021102080003 1
1.0%
4817036025108900000 1
1.0%
4792037027100480000 1
1.0%
4792033024105530001 1
1.0%
4723033033104970000 1
1.0%
4713025331111260002 1
1.0%
4713010700101600002 1
1.0%
4683031028100760015 1
1.0%
4677033024103340034 1
1.0%

sido_nm
Categorical

Distinct15
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울특별시
32 
경기도
13 
인천광역시
8 
전라북도
7 
충청북도
7 
Other values (10)
33 

Length

Max length7
Median length5
Mean length4.43
Min length3

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row서울특별시
2nd row대전광역시
3rd row전라북도
4th row강원도
5th row전라남도

Common Values

ValueCountFrequency (%)
서울특별시 32
32.0%
경기도 13
13.0%
인천광역시 8
 
8.0%
전라북도 7
 
7.0%
충청북도 7
 
7.0%
대구광역시 7
 
7.0%
부산광역시 6
 
6.0%
경상북도 5
 
5.0%
강원도 4
 
4.0%
대전광역시 3
 
3.0%
Other values (5) 8
 
8.0%

Length

2023-12-10T18:39:53.128943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 32
32.0%
경기도 13
13.0%
인천광역시 8
 
8.0%
전라북도 7
 
7.0%
충청북도 7
 
7.0%
대구광역시 7
 
7.0%
부산광역시 6
 
6.0%
경상북도 5
 
5.0%
강원도 4
 
4.0%
대전광역시 3
 
3.0%
Other values (5) 8
 
8.0%

sgg_nm
Text

Distinct64
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:39:53.509266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.18
Min length2

Characters and Unicode

Total characters318
Distinct characters73
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

Unique40 ?
Unique (%)40.0%

Sample

1st row도봉구
2nd row서구
3rd row남원시
4th row태백시
5th row영암군
ValueCountFrequency (%)
중구 6
 
5.7%
종로구 5
 
4.8%
달서구 4
 
3.8%
도봉구 3
 
2.9%
남동구 3
 
2.9%
송파구 3
 
2.9%
성남시 3
 
2.9%
노원구 2
 
1.9%
청주시 2
 
1.9%
중랑구 2
 
1.9%
Other values (56) 72
68.6%
2023-12-10T18:39:54.103965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 60
 
18.9%
시 31
 
9.7%
군 17
 
5.3%
성 10
 
3.1%
서 9
 
2.8%
중 9
 
2.8%
동 8
 
2.5%
주 8
 
2.5%
남 7
 
2.2%
강 6
 
1.9%
Other values (63) 153
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 313
98.4%
Space Separator 5
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 60
19.2%
시 31
 
9.9%
군 17
 
5.4%
성 10
 
3.2%
서 9
 
2.9%
중 9
 
2.9%
동 8
 
2.6%
주 8
 
2.6%
남 7
 
2.2%
강 6
 
1.9%
Other values (62) 148
47.3%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 313
98.4%
Common 5
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 60
19.2%
시 31
 
9.9%
군 17
 
5.4%
성 10
 
3.2%
서 9
 
2.9%
중 9
 
2.9%
동 8
 
2.6%
주 8
 
2.6%
남 7
 
2.2%
강 6
 
1.9%
Other values (62) 148
47.3%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 313
98.4%
ASCII 5
 
1.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 60
19.2%
시 31
 
9.9%
군 17
 
5.4%
성 10
 
3.2%
서 9
 
2.9%
중 9
 
2.9%
동 8
 
2.6%
주 8
 
2.6%
남 7
 
2.2%
강 6
 
1.9%
Other values (62) 148
47.3%
ASCII
ValueCountFrequency (%)
5
100.0%

bemd_nm
Text

Distinct93
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:39:54.572608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.19
Min length2

Characters and Unicode

Total characters319
Distinct characters114
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

Unique86 ?
Unique (%)86.0%

Sample

1st row도봉동
2nd row도안동
3rd row내척동
4th row황지동
5th row덕진면
ValueCountFrequency (%)
신당동 2
 
2.0%
상계동 2
 
2.0%
방학동 2
 
2.0%
망우동 2
 
2.0%
간석동 2
 
2.0%
구미동 2
 
2.0%
수유동 2
 
2.0%
위도면 1
 
1.0%
우동 1
 
1.0%
우산동 1
 
1.0%
Other values (83) 83
83.0%
2023-12-10T18:39:55.355545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 69
 
21.6%
면 21
 
6.6%
가 11
 
3.4%
산 8
 
2.5%
화 6
 
1.9%
성 6
 
1.9%
로 6
 
1.9%
읍 6
 
1.9%
지 5
 
1.6%
구 4
 
1.3%
Other values (104) 177
55.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 309
96.9%
Decimal Number 10
 
3.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 69
22.3%
면 21
 
6.8%
가 11
 
3.6%
산 8
 
2.6%
화 6
 
1.9%
성 6
 
1.9%
로 6
 
1.9%
읍 6
 
1.9%
지 5
 
1.6%
구 4
 
1.3%
Other values (99) 167
54.0%
Decimal Number
ValueCountFrequency (%)
3 3
30.0%
2 2
20.0%
7 2
20.0%
1 2
20.0%
6 1
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 309
96.9%
Common 10
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 69
22.3%
면 21
 
6.8%
가 11
 
3.6%
산 8
 
2.6%
화 6
 
1.9%
성 6
 
1.9%
로 6
 
1.9%
읍 6
 
1.9%
지 5
 
1.6%
구 4
 
1.3%
Other values (99) 167
54.0%
Common
ValueCountFrequency (%)
3 3
30.0%
2 2
20.0%
7 2
20.0%
1 2
20.0%
6 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 309
96.9%
ASCII 10
 
3.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 69
22.3%
면 21
 
6.8%
가 11
 
3.6%
산 8
 
2.6%
화 6
 
1.9%
성 6
 
1.9%
로 6
 
1.9%
읍 6
 
1.9%
지 5
 
1.6%
구 4
 
1.3%
Other values (99) 167
54.0%
ASCII
ValueCountFrequency (%)
3 3
30.0%
2 2
20.0%
7 2
20.0%
1 2
20.0%
6 1
 
10.0%

ri_nm
Text

MISSING 

Distinct27
Distinct (%)100.0%
Missing73
Missing (%)73.0%
Memory size932.0 B
2023-12-10T18:39:55.717392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.962963
Min length2

Characters and Unicode

Total characters80
Distinct characters38
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

Unique27 ?
Unique (%)100.0%

Sample

1st row금강리
2nd row북곡리
3rd row강교리
4th row유현리
5th row비산리
ValueCountFrequency (%)
금강리 1
 
3.7%
유성리 1
 
3.7%
운천리 1
 
3.7%
신촌리 1
 
3.7%
지월리 1
 
3.7%
소천리 1
 
3.7%
전호리 1
 
3.7%
대치리 1
 
3.7%
산성리 1
 
3.7%
금평리 1
 
3.7%
Other values (17) 17
63.0%
2023-12-10T18:39:56.369968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 27
33.8%
산 4
 
5.0%
성 4
 
5.0%
금 2
 
2.5%
신 2
 
2.5%
유 2
 
2.5%
현 2
 
2.5%
천 2
 
2.5%
덕 2
 
2.5%
강 2
 
2.5%
Other values (28) 31
38.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 80
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 27
33.8%
산 4
 
5.0%
성 4
 
5.0%
금 2
 
2.5%
신 2
 
2.5%
유 2
 
2.5%
현 2
 
2.5%
천 2
 
2.5%
덕 2
 
2.5%
강 2
 
2.5%
Other values (28) 31
38.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 80
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 27
33.8%
산 4
 
5.0%
성 4
 
5.0%
금 2
 
2.5%
신 2
 
2.5%
유 2
 
2.5%
현 2
 
2.5%
천 2
 
2.5%
덕 2
 
2.5%
강 2
 
2.5%
Other values (28) 31
38.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 80
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 27
33.8%
산 4
 
5.0%
성 4
 
5.0%
금 2
 
2.5%
신 2
 
2.5%
유 2
 
2.5%
현 2
 
2.5%
천 2
 
2.5%
덕 2
 
2.5%
강 2
 
2.5%
Other values (28) 31
38.8%

beonji
Text

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:39:56.828050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.69
Min length2

Characters and Unicode

Total characters469
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

Unique94 ?
Unique (%)94.0%

Sample

1st row625-144
2nd row1493-1
3rd row294-44
4th row180-81
5th row76-15
ValueCountFrequency (%)
1034-4 2
 
2.0%
197-1 2
 
2.0%
222 2
 
2.0%
7-5 1
 
1.0%
165-5 1
 
1.0%
385 1
 
1.0%
276-1 1
 
1.0%
2-11 1
 
1.0%
178-26 1
 
1.0%
1290-1 1
 
1.0%
Other values (87) 87
87.0%
2023-12-10T18:39:57.471186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 91
19.4%
- 75
16.0%
2 53
11.3%
4 45
9.6%
3 40
8.5%
5 32
 
6.8%
7 30
 
6.4%
8 30
 
6.4%
6 26
 
5.5%
0 24
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 394
84.0%
Dash Punctuation 75
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 91
23.1%
2 53
13.5%
4 45
11.4%
3 40
10.2%
5 32
 
8.1%
7 30
 
7.6%
8 30
 
7.6%
6 26
 
6.6%
0 24
 
6.1%
9 23
 
5.8%
Dash Punctuation
ValueCountFrequency (%)
- 75
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 469
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 91
19.4%
- 75
16.0%
2 53
11.3%
4 45
9.6%
3 40
8.5%
5 32
 
6.8%
7 30
 
6.4%
8 30
 
6.4%
6 26
 
5.5%
0 24
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 469
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 91
19.4%
- 75
16.0%
2 53
11.3%
4 45
9.6%
3 40
8.5%
5 32
 
6.8%
7 30
 
6.4%
8 30
 
6.4%
6 26
 
5.5%
0 24
 
5.1%

badm_cd
Real number (ℝ)

Distinct93
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9522262 × 109
Minimum1.1110132 × 109
Maximum5.0110111 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:39:57.742570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110132 × 109
5-th percentile1.1138609 × 109
Q11.1601352 × 109
median2.8218603 × 109
Q34.3111905 × 109
95-th percentile4.726483 × 109
Maximum5.0110111 × 109
Range3.8999979 × 109
Interquartile range (IQR)3.1510553 × 109

Descriptive statistics

Standard deviation1.4224082 × 109
Coefficient of variation (CV)0.48180869
Kurtosis-1.578706
Mean2.9522262 × 109
Median Absolute Deviation (MAD)1.6493495 × 109
Skewness-0.17275458
Sum2.9522262 × 1011
Variance2.0232452 × 1018
MonotonicityNot monotonic
2023-12-10T18:39:58.035351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1135010500 2
 
2.0%
1130510300 2
 
2.0%
4113511400 2
 
2.0%
1126010500 2
 
2.0%
1132010600 2
 
2.0%
2820010200 2
 
2.0%
2729010700 2
 
2.0%
4275025022 1
 
1.0%
4121010100 1
 
1.0%
4376034021 1
 
1.0%
Other values (83) 83
83.0%
ValueCountFrequency (%)
1111013200 1
1.0%
1111013500 1
1.0%
1111015600 1
1.0%
1111016400 1
1.0%
1111017700 1
1.0%
1114010500 1
1.0%
1114012400 1
1.0%
1114014900 1
1.0%
1120011100 1
1.0%
1121510500 1
1.0%
ValueCountFrequency (%)
5011011100 1
1.0%
4822037021 1
1.0%
4817036025 1
1.0%
4792037027 1
1.0%
4792033024 1
1.0%
4723033033 1
1.0%
4713025331 1
1.0%
4713010700 1
1.0%
4683031028 1
1.0%
4677033024 1
1.0%

hadm_cd
Real number (ℝ)

Distinct94
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9522622 × 109
Minimum1.111058 × 109
Maximum5.01106 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:39:58.324039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111058 × 109
5-th percentile1.1139054 × 109
Q11.1601854 × 109
median2.8219072 × 109
Q34.311233 × 109
95-th percentile4.726483 × 109
Maximum5.01106 × 109
Range3.900002 × 109
Interquartile range (IQR)3.1510476 × 109

Descriptive statistics

Standard deviation1.422394 × 109
Coefficient of variation (CV)0.48179798
Kurtosis-1.5787064
Mean2.9522622 × 109
Median Absolute Deviation (MAD)1.6493408 × 109
Skewness-0.17276168
Sum2.9522622 × 1011
Variance2.0232047 × 1018
MonotonicityNot monotonic
2023-12-10T18:39:58.629125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1111061500 3
 
3.0%
2729058500 2
 
2.0%
4113567000 2
 
2.0%
1126065500 2
 
2.0%
1132071000 2
 
2.0%
4513040000 1
 
1.0%
4121065000 1
 
1.0%
1171062000 1
 
1.0%
2920055000 1
 
1.0%
2729055000 1
 
1.0%
Other values (84) 84
84.0%
ValueCountFrequency (%)
1111058000 1
 
1.0%
1111061500 3
3.0%
1111063000 1
 
1.0%
1114055000 1
 
1.0%
1114059000 1
 
1.0%
1114060500 1
 
1.0%
1120061500 1
 
1.0%
1121583000 1
 
1.0%
1123065000 1
 
1.0%
1123070500 1
 
1.0%
ValueCountFrequency (%)
5011060000 1
1.0%
4822037000 1
1.0%
4817038000 1
1.0%
4792037000 1
1.0%
4792033000 1
1.0%
4723033000 1
1.0%
4713051500 1
1.0%
4713025300 1
1.0%
4683031000 1
1.0%
4677033000 1
1.0%

rd_cd
Real number (ℝ)

MISSING 

Distinct74
Distinct (%)94.9%
Missing22
Missing (%)22.0%
Infinite0
Infinite (%)0.0%
Mean2.9852084 × 1011
Minimum1.11103 × 1011
Maximum5.0110485 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:39:58.907495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.11103 × 1011
5-th percentile1.1135825 × 1011
Q11.1492712 × 1011
median2.823725 × 1011
Q34.3126244 × 1011
95-th percentile4.7333853 × 1011
Maximum5.0110485 × 1011
Range3.9000185 × 1011
Interquartile range (IQR)3.1633532 × 1011

Descriptive statistics

Standard deviation1.419766 × 1011
Coefficient of variation (CV)0.47560029
Kurtosis-1.5516493
Mean2.9852084 × 1011
Median Absolute Deviation (MAD)1.603 × 1011
Skewness-0.20624284
Sum2.3284626 × 1013
Variance2.0157354 × 1022
MonotonicityNot monotonic
2023-12-10T18:39:59.170365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
272902007002 3
 
3.0%
411352000005 2
 
2.0%
111403101006 2
 
2.0%
472303309054 1
 
1.0%
292004289271 1
 
1.0%
112604118485 1
 
1.0%
113203109002 1
 
1.0%
113053005041 1
 
1.0%
431143014017 1
 
1.0%
451304604441 1
 
1.0%
Other values (64) 64
64.0%
(Missing) 22
 
22.0%
ValueCountFrequency (%)
111103000008 1
1.0%
111103100010 1
1.0%
111103100013 1
1.0%
111104100140 1
1.0%
111403101006 2
2.0%
111403101011 1
1.0%
112153000002 1
1.0%
112302000008 1
1.0%
112303105008 1
1.0%
112603106013 1
1.0%
ValueCountFrequency (%)
501104847960 1
1.0%
482204799430 1
1.0%
481703019017 1
1.0%
479204772346 1
1.0%
472303309054 1
1.0%
471303305004 1
1.0%
471303018037 1
1.0%
468303284049 1
1.0%
458004640283 1
1.0%
457203274045 1
1.0%

rd_nm
Text

MISSING 

Distinct67
Distinct (%)85.9%
Missing22
Missing (%)22.0%
Memory size932.0 B
2023-12-10T18:39:59.623757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length4
Min length2

Characters and Unicode

Total characters312
Distinct characters106
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

Unique60 ?
Unique (%)76.9%

Sample

1st row도봉로152가길
2nd row예향로
3rd row청량산길
4th row호국로
5th row양촌역길
ValueCountFrequency (%)
달구벌대로 5
 
6.4%
중앙로 3
 
3.8%
중앙대로 2
 
2.6%
예술로 2
 
2.6%
성남대로 2
 
2.6%
을지로 2
 
2.6%
경인로 2
 
2.6%
하슬라로 1
 
1.3%
산동길 1
 
1.3%
장수로 1
 
1.3%
Other values (57) 57
73.1%
2023-12-10T18:40:00.241996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 69
22.1%
대 22
 
7.1%
길 18
 
5.8%
1 9
 
2.9%
중 7
 
2.2%
구 6
 
1.9%
앙 6
 
1.9%
산 6
 
1.9%
달 5
 
1.6%
벌 5
 
1.6%
Other values (96) 159
51.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 287
92.0%
Decimal Number 25
 
8.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 69
24.0%
대 22
 
7.7%
길 18
 
6.3%
중 7
 
2.4%
구 6
 
2.1%
앙 6
 
2.1%
산 6
 
2.1%
달 5
 
1.7%
벌 5
 
1.7%
성 4
 
1.4%
Other values (88) 139
48.4%
Decimal Number
ValueCountFrequency (%)
1 9
36.0%
2 4
16.0%
4 4
16.0%
7 3
 
12.0%
3 2
 
8.0%
9 1
 
4.0%
0 1
 
4.0%
5 1
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 287
92.0%
Common 25
 
8.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 69
24.0%
대 22
 
7.7%
길 18
 
6.3%
중 7
 
2.4%
구 6
 
2.1%
앙 6
 
2.1%
산 6
 
2.1%
달 5
 
1.7%
벌 5
 
1.7%
성 4
 
1.4%
Other values (88) 139
48.4%
Common
ValueCountFrequency (%)
1 9
36.0%
2 4
16.0%
4 4
16.0%
7 3
 
12.0%
3 2
 
8.0%
9 1
 
4.0%
0 1
 
4.0%
5 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 287
92.0%
ASCII 25
 
8.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 69
24.0%
대 22
 
7.7%
길 18
 
6.3%
중 7
 
2.4%
구 6
 
2.1%
앙 6
 
2.1%
산 6
 
2.1%
달 5
 
1.7%
벌 5
 
1.7%
성 4
 
1.4%
Other values (88) 139
48.4%
ASCII
ValueCountFrequency (%)
1 9
36.0%
2 4
16.0%
4 4
16.0%
7 3
 
12.0%
3 2
 
8.0%
9 1
 
4.0%
0 1
 
4.0%
5 1
 
4.0%

bld_num
Text

MISSING 

Distinct71
Distinct (%)91.0%
Missing22
Missing (%)22.0%
Memory size932.0 B
2023-12-10T18:40:00.609061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.974359
Min length1

Characters and Unicode

Total characters232
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

Unique65 ?
Unique (%)83.3%

Sample

1st row114
2nd row1860-8
3rd row326
4th row1960
5th row107
ValueCountFrequency (%)
2 3
 
3.8%
23 2
 
2.6%
55 2
 
2.6%
9 2
 
2.6%
1 2
 
2.6%
1140 2
 
2.6%
184 1
 
1.3%
149-39 1
 
1.3%
363 1
 
1.3%
728 1
 
1.3%
Other values (61) 61
78.2%
2023-12-10T18:40:01.127641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 47
20.3%
2 35
15.1%
0 23
9.9%
3 21
9.1%
8 20
8.6%
7 19
8.2%
6 15
 
6.5%
9 14
 
6.0%
4 13
 
5.6%
5 13
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 220
94.8%
Dash Punctuation 12
 
5.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 47
21.4%
2 35
15.9%
0 23
10.5%
3 21
9.5%
8 20
9.1%
7 19
8.6%
6 15
 
6.8%
9 14
 
6.4%
4 13
 
5.9%
5 13
 
5.9%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 232
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 47
20.3%
2 35
15.1%
0 23
9.9%
3 21
9.1%
8 20
8.6%
7 19
8.2%
6 15
 
6.5%
9 14
 
6.0%
4 13
 
5.6%
5 13
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 232
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 47
20.3%
2 35
15.1%
0 23
9.9%
3 21
9.1%
8 20
8.6%
7 19
8.2%
6 15
 
6.5%
9 14
 
6.0%
4 13
 
5.6%
5 13
 
5.6%

x
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.44853
Minimum126.26231
Maximum129.20246
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:40:01.520478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.26231
5-th percentile126.61543
Q1126.9378
median127.05908
Q3127.98253
95-th percentile129.0381
Maximum129.20246
Range2.9401508
Interquartile range (IQR)1.0447302

Descriptive statistics

Standard deviation0.8233569
Coefficient of variation (CV)0.0064603092
Kurtosis-0.54100768
Mean127.44853
Median Absolute Deviation (MAD)0.2828812
Skewness0.95046641
Sum12744.853
Variance0.67791658
MonotonicityNot monotonic
2023-12-10T18:40:01.799490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.045150517503 1
 
1.0%
126.615464136341 1
 
1.0%
126.568779271213 1
 
1.0%
127.864200833288 1
 
1.0%
126.883712322247 1
 
1.0%
127.127285867284 1
 
1.0%
126.816814187889 1
 
1.0%
128.554495949274 1
 
1.0%
127.098753625618 1
 
1.0%
127.027205927116 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
126.262307936046 1
1.0%
126.291114789218 1
1.0%
126.490385981702 1
1.0%
126.568779271213 1
1.0%
126.614786926865 1
1.0%
126.615464136341 1
1.0%
126.668545710723 1
1.0%
126.695708384224 1
1.0%
126.699531360887 1
1.0%
126.701571250144 1
1.0%
ValueCountFrequency (%)
129.20245869774 1
1.0%
129.148245048431 1
1.0%
129.129193706892 1
1.0%
129.092792346414 1
1.0%
129.080242770152 1
1.0%
129.035880661031 1
1.0%
129.026268796578 1
1.0%
129.021925220234 1
1.0%
128.989592603022 1
1.0%
128.937656351391 1
1.0%

y
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.80815
Minimum33.513325
Maximum38.05978
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:40:02.044001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.513325
5-th percentile35.101207
Q135.923525
median37.384916
Q337.561226
95-th percentile37.681888
Maximum38.05978
Range4.5464549
Interquartile range (IQR)1.6377003

Descriptive statistics

Standard deviation0.97773523
Coefficient of variation (CV)0.02656301
Kurtosis0.11866528
Mean36.80815
Median Absolute Deviation (MAD)0.29184757
Skewness-1.0181761
Sum3680.815
Variance0.95596619
MonotonicityNot monotonic
2023-12-10T18:40:02.329687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.6746876871633 1
 
1.0%
35.9260125974759 1
 
1.0%
33.5133249250704 1
 
1.0%
36.7877245055927 1
 
1.0%
37.4162269092032 1
 
1.0%
37.5023910161355 1
 
1.0%
35.145174564755 1
 
1.0%
35.8565462296674 1
 
1.0%
37.6000215289287 1
 
1.0%
37.6649547397381 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
33.5133249250704 1
1.0%
34.4900858418859 1
1.0%
34.8305568301716 1
1.0%
34.8440952588905 1
1.0%
35.0978119154002 1
1.0%
35.1013856890994 1
1.0%
35.145174564755 1
1.0%
35.1614871261 1
1.0%
35.1747464745645 1
1.0%
35.2128874616478 1
1.0%
ValueCountFrequency (%)
38.0597798556631 1
1.0%
37.7630495160377 1
1.0%
37.7546396160384 1
1.0%
37.7426998923851 1
1.0%
37.7397983183727 1
1.0%
37.6788399832658 1
1.0%
37.6746876871633 1
1.0%
37.6649547397381 1
1.0%
37.6634401692926 1
1.0%
37.6566037582616 1
1.0%

grid_cd
Text

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:40:02.878767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters800
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

Unique98 ?
Unique (%)98.0%

Sample

1st row다사598640
2nd row다바863149
3rd row다마874160
4th row마사322069
5th row다라264487
ValueCountFrequency (%)
다사653267 2
 
2.0%
라라662501 1
 
1.0%
다마202702 1
 
1.0%
라바324655 1
 
1.0%
다사454354 1
 
1.0%
다사670448 1
 
1.0%
다라377835 1
 
1.0%
라마952627 1
 
1.0%
다사645556 1
 
1.0%
다사583629 1
 
1.0%
Other values (89) 89
89.0%
2023-12-10T18:40:03.604803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 91
11.4%
6 73
9.1%
다 68
8.5%
4 68
8.5%
1 59
 
7.4%
3 58
 
7.2%
2 58
 
7.2%
8 55
 
6.9%
사 55
 
6.9%
7 51
 
6.4%
Other values (7) 164
20.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 600
75.0%
Other Letter 200
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 91
15.2%
6 73
12.2%
4 68
11.3%
1 59
9.8%
3 58
9.7%
2 58
9.7%
8 55
9.2%
7 51
8.5%
9 47
7.8%
0 40
6.7%
Other Letter
ValueCountFrequency (%)
다 68
34.0%
사 55
27.5%
마 33
16.5%
라 26
 
13.0%
바 15
 
7.5%
나 2
 
1.0%
아 1
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 600
75.0%
Hangul 200
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 91
15.2%
6 73
12.2%
4 68
11.3%
1 59
9.8%
3 58
9.7%
2 58
9.7%
8 55
9.2%
7 51
8.5%
9 47
7.8%
0 40
6.7%
Hangul
ValueCountFrequency (%)
다 68
34.0%
사 55
27.5%
마 33
16.5%
라 26
 
13.0%
바 15
 
7.5%
나 2
 
1.0%
아 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 600
75.0%
Hangul 200
 
25.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 91
15.2%
6 73
12.2%
4 68
11.3%
1 59
9.8%
3 58
9.7%
2 58
9.7%
8 55
9.2%
7 51
8.5%
9 47
7.8%
0 40
6.7%
Hangul
ValueCountFrequency (%)
다 68
34.0%
사 55
27.5%
마 33
16.5%
라 26
 
13.0%
바 15
 
7.5%
나 2
 
1.0%
아 1
 
0.5%

lst_updt_dt
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20210916170801
100 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210916170801
2nd row20210916170801
3rd row20210916170801
4th row20210916170801
5th row20210916170801

Common Values

ValueCountFrequency (%)
20210916170801 100
100.0%

Length

2023-12-10T18:40:03.858201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:40:04.026948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210916170801 100
100.0%

data_orgn
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
KT 100
100.0%

Length

2023-12-10T18:40:04.202030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:40:04.355370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kt 100
100.0%

file_name
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
KC_496_LLR_PPLTEQP_2021
100 

Length

Max length23
Median length23
Mean length23
Min length23

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKC_496_LLR_PPLTEQP_2021
2nd rowKC_496_LLR_PPLTEQP_2021
3rd rowKC_496_LLR_PPLTEQP_2021
4th rowKC_496_LLR_PPLTEQP_2021
5th rowKC_496_LLR_PPLTEQP_2021

Common Values

ValueCountFrequency (%)
KC_496_LLR_PPLTEQP_2021 100
100.0%

Length

2023-12-10T18:40:04.515477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:40:04.723386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kc_496_llr_pplteqp_2021 100
100.0%

base_ymd
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20210916
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210916
2nd row20210916
3rd row20210916
4th row20210916
5th row20210916

Common Values

ValueCountFrequency (%)
20210916 100
100.0%

Length

2023-12-10T18:40:04.966479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:40:05.198953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210916 100
100.0%

Sample

idlclasmlsfcid_poipoi_nmbranch_nmsub_nmmcate_cdmcate_nmpnusido_nmsgg_nmbemd_nmri_nmbeonjibadm_cdhadm_cdrd_cdrd_nmbld_numxygrid_cdlst_updt_dtdata_orgnfile_namebase_ymd
0KCLPPPO21N000038441장소교통223454삼화택시<NA><NA>150506버스/택시/화물차고지1132010800106250144서울특별시도봉구도봉동<NA>625-14411320108001132052200113204127150도봉로152가길114127.04515137.674688다사59864020210916170801KTKC_496_LLR_PPLTEQP_202120210916
1KCLPPPO21N000096058장소교통20545282목원대학교입구버스정류장34-900<NA>150504시내버스정류장명3017011500114930001대전광역시서구도안동<NA>1493-130170115003017059000<NA><NA><NA>127.34804136.331655다바86314920210916170801KTKC_496_LLR_PPLTEQP_202120210916
2KCLPPPO21N000038443장소교통549306산성역<NA><NA>150303기타철도역명4519011400102940044전라북도남원시내척동<NA>294-4445190114004519057000<NA><NA><NA>127.36212835.440594다마87416020210916170801KTKC_496_LLR_PPLTEQP_202120210916
3KCLPPPO21N000038444장소교통549653문곡역<NA><NA>150303기타철도역명4219010100101800081강원도태백시황지동<NA>180-8142190101004219054000<NA><NA><NA>128.98959337.151719마사32206920210916170801KTKC_496_LLR_PPLTEQP_202120210916
4KCLPPPO21N000038445장소교통659889금강휴게소<NA><NA>140401국도/지방도휴게소4683031028100760015전라남도영암군덕진면금강리76-1546830310284683031000468303284049예향로1860-8126.69570834.830557다라26448720210916170801KTKC_496_LLR_PPLTEQP_202120210916
5KCLPPPO21N000038446장소교통660266청량산휴게소<NA><NA>140401국도/지방도휴게소4792037027100480000경상북도봉화군명호면북곡리4847920370274792037000479204772346청량산길326128.92852436.779892마바27465520210916170801KTKC_496_LLR_PPLTEQP_202120210916
6KCLPPPO21N000038447장소교통660354강교휴게소<NA><NA>140401국도/지방도휴게소4713025331111260002경상북도경주시안강읍강교리1126-247130253314713025300471303018037호국로1960129.12919435.980236마마46877120210916170801KTKC_496_LLR_PPLTEQP_202120210916
7KCLPPPO21N000096059장소교통20661412양촌역김포도시철도<NA>150493김포도시철도4157025627102750007경기도김포시양촌읍유현리275-741570256274157025600415704856047양촌역길107126.61478737.641633다사21960620210916170801KTKC_496_LLR_PPLTEQP_202120210916
8KCLPPPO21N000038449장소교통1247015민속광장휴게소<NA><NA>140401국도/지방도휴게소4377031029110140000충청북도음성군소이면비산리101443770310294377031000437702014003충청대로1754127.72476636.942344라바20082620210916170801KTKC_496_LLR_PPLTEQP_202120210916
9KCLPPPO21N000038450장소교통4989939금강호휴게소<NA><NA>140401국도/지방도휴게소4513037021104370001전라북도군산시성산면성덕리437-145130370214513037000451303016006철새로25126.75859636.013593다마33179820210916170801KTKC_496_LLR_PPLTEQP_202120210916
idlclasmlsfcid_poipoi_nmbranch_nmsub_nmmcate_cdmcate_nmpnusido_nmsgg_nmbemd_nmri_nmbeonjibadm_cdhadm_cdrd_cdrd_nmbld_numxygrid_cdlst_updt_dtdata_orgnfile_namebase_ymd
90KCLPPPO21N000038531장소교통16519525홍대입구역경의중앙선<NA>150421경의중앙선1144012100101760033서울특별시마포구동교동<NA>176-3311440121001144066000<NA><NA><NA>126.92728437.557374다사49451020210916170801KTKC_496_LLR_PPLTEQP_202120210916
91KCLPPPO21N000038532장소교통16597032시흥유통센터버스정류장18-013<NA>150504시내버스정류장명1154510300110010022서울특별시금천구시흥동<NA>1001-2211545103001154569000<NA><NA><NA>126.90339637.440321다사47238020210916170801KTKC_496_LLR_PPLTEQP_202120210916
92KCLPPPO21N000038533장소교통16603480흥아농장입구버스정류장<NA><NA>150504시내버스정류장명2632010200101740008부산광역시북구화명동<NA>174-826320102002632054200<NA><NA><NA>129.02626935.242832마라38895220210916170801KTKC_496_LLR_PPLTEQP_202120210916
93KCLPPPO21N000038534장소교통16603864동백역버스정류장09-255<NA>150504시내버스정류장명2635010500109910001부산광역시해운대구우동<NA>991-126350105002635051000<NA><NA><NA>129.14824535.161487마라50186320210916170801KTKC_496_LLR_PPLTEQP_202120210916
94KCLPPPO21N000038535장소교통16570099파장금여객터미널<NA><NA>150203일반페리터미널4580042024103210001전라북도부안군위도면대리321-145800420244580042000458004640283살막금길16-1126.26230835.57156나마87831320210916170801KTKC_496_LLR_PPLTEQP_202120210916
95KCLPPPO21N000038536장소교통16608627성남동성당버스정류장06-244<NA>150504시내버스정류장명4113310900100180000경기도성남시 중원구하대원동<NA>1841133109004113366000<NA><NA><NA>127.13203637.428052다사67436620210916170801KTKC_496_LLR_PPLTEQP_202120210916
96KCLPPPO21N000038537장소교통16589978창덕궁버스정류장01-781<NA>150504시내버스정류장명1111013200100980007서울특별시종로구운니동<NA>98-711110132001111061500<NA><NA><NA>126.98883337.577525다사54853220210916170801KTKC_496_LLR_PPLTEQP_202120210916
97KCLPPPO21N000038538장소교통16589752종로2가버스정류장01-185<NA>150504시내버스정류장명1111013500100070005서울특별시종로구관철동<NA>7-511110135001111061500111104100140삼일대로17길8126.98746237.569274다사54752320210916170801KTKC_496_LLR_PPLTEQP_202120210916
98KCLPPPO21N000038539장소교통16589779동대문버스정류장01-214<NA>150504시내버스정류장명1111016400100940011서울특별시종로구종로6가<NA>94-1111110164001111063000111103100010율곡로288127.00841137.571769다사56552620210916170801KTKC_496_LLR_PPLTEQP_202120210916
99KCLPPPO21N000038540장소교통16589840서대문3번출구버스정류장01-505<NA>150504시내버스정류장명1111017700102220000서울특별시종로구평동<NA>22211110177001111058000111103000008통일로134126.96626237.56648다사52852020210916170801KTKC_496_LLR_PPLTEQP_202120210916