Overview

Dataset statistics

Number of variables27
Number of observations100
Missing cells370
Missing cells (%)13.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.4 KiB
Average record size in memory229.3 B

Variable types

Text9
Categorical8
Numeric8
Unsupported2

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
branch_nm has 100 (100.0%) missing valuesMissing
sub_nm has 100 (100.0%) missing valuesMissing
ri_nm has 30 (30.0%) missing valuesMissing
rd_cd has 46 (46.0%) missing valuesMissing
rd_nm has 46 (46.0%) missing valuesMissing
bld_num has 46 (46.0%) missing valuesMissing
id has unique valuesUnique
id_poi has unique valuesUnique
poi_nm has unique valuesUnique
x has unique valuesUnique
y has unique valuesUnique
grid_cd has unique valuesUnique
branch_nm is an unsupported type, check if it needs cleaning or further analysisUnsupported
sub_nm is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 09:48:55.037323
Analysis finished2023-12-10 09:48:55.958625
Duration0.92 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
2023-12-10T18:48:56.214544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters1900
Distinct characters18
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 rowKCLHTPO21N000000001
2nd rowKCLHTPO21N000007617
3rd rowKCLHTPO21N000000003
4th rowKCLHTPO21N000000004
5th rowKCLHTPO21N000000005
ValueCountFrequency (%)
kclhtpo21n000000001 1
 
1.0%
kclhtpo21n000000063 1
 
1.0%
kclhtpo21n000000074 1
 
1.0%
kclhtpo21n000000073 1
 
1.0%
kclhtpo21n000000072 1
 
1.0%
kclhtpo21n000000071 1
 
1.0%
kclhtpo21n000000070 1
 
1.0%
kclhtpo21n000000069 1
 
1.0%
kclhtpo21n000000068 1
 
1.0%
kclhtpo21n000000067 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T18:48:56.917610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 711
37.4%
1 124
 
6.5%
2 118
 
6.2%
K 100
 
5.3%
O 100
 
5.3%
C 100
 
5.3%
N 100
 
5.3%
P 100
 
5.3%
T 100
 
5.3%
H 100
 
5.3%
Other values (8) 247
 
13.0%

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%
1 124
 
11.3%
2 118
 
10.7%
7 24
 
2.2%
6 23
 
2.1%
9 21
 
1.9%
4 20
 
1.8%
5 20
 
1.8%
8 20
 
1.8%
3 19
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
K 100
12.5%
O 100
12.5%
C 100
12.5%
N 100
12.5%
P 100
12.5%
T 100
12.5%
H 100
12.5%
L 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%
1 124
 
11.3%
2 118
 
10.7%
7 24
 
2.2%
6 23
 
2.1%
9 21
 
1.9%
4 20
 
1.8%
5 20
 
1.8%
8 20
 
1.8%
3 19
 
1.7%
Latin
ValueCountFrequency (%)
K 100
12.5%
O 100
12.5%
C 100
12.5%
N 100
12.5%
P 100
12.5%
T 100
12.5%
H 100
12.5%
L 100
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 711
37.4%
1 124
 
6.5%
2 118
 
6.2%
K 100
 
5.3%
O 100
 
5.3%
C 100
 
5.3%
N 100
 
5.3%
P 100
 
5.3%
T 100
 
5.3%
H 100
 
5.3%
Other values (8) 247
 
13.0%

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

2023-12-10T18:48:57.192739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:48:57.397956image/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
관광지
100 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관광지 100
100.0%

Length

2023-12-10T18:48:57.574437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:48:57.758595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관광지 100
100.0%

id_poi
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10729267
Minimum142444
Maximum21239259
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:48:57.988846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum142444
5-th percentile706770.9
Q18269950.2
median11324858
Q313658177
95-th percentile17092842
Maximum21239259
Range21096815
Interquartile range (IQR)5388226.5

Descriptive statistics

Standard deviation4698031.4
Coefficient of variation (CV)0.43787068
Kurtosis0.47378632
Mean10729267
Median Absolute Deviation (MAD)2858728.5
Skewness-0.41533433
Sum1.0729267 × 109
Variance2.2071499 × 1013
MonotonicityNot monotonic
2023-12-10T18:48:58.262109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
142444 1
 
1.0%
11398931 1
 
1.0%
13641812 1
 
1.0%
11410060 1
 
1.0%
11409967 1
 
1.0%
11409920 1
 
1.0%
11409762 1
 
1.0%
11409459 1
 
1.0%
11402693 1
 
1.0%
11399179 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
142444 1
1.0%
157800 1
1.0%
214928 1
1.0%
228110 1
1.0%
248527 1
1.0%
730889 1
1.0%
744924 1
1.0%
746581 1
1.0%
747724 1
1.0%
4978754 1
1.0%
ValueCountFrequency (%)
21239259 1
1.0%
21144478 1
1.0%
20637214 1
1.0%
18936048 1
1.0%
17701549 1
1.0%
17060805 1
1.0%
17043673 1
1.0%
17005015 1
1.0%
16933825 1
1.0%
16695634 1
1.0%

poi_nm
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:48:58.815199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9
Mean length5.09
Min length2

Characters and Unicode

Total characters509
Distinct characters193
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

Unique100 ?
Unique (%)100.0%

Sample

1st row사자암
2nd row송광사향로전
3rd row백천암
4th row금강암
5th row심오암
ValueCountFrequency (%)
사자암 1
 
1.0%
세성산성 1
 
1.0%
송도조개더미 1
 
1.0%
발포만호성 1
 
1.0%
존심당과아문 1
 
1.0%
위봉환가옥 1
 
1.0%
해남단군전 1
 
1.0%
중대봉 1
 
1.0%
흥학당 1
 
1.0%
정인지묘 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T18:48:59.575881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 21
 
4.1%
지 17
 
3.3%
암 16
 
3.1%
산 15
 
2.9%
석 11
 
2.2%
비 10
 
2.0%
대 9
 
1.8%
묘 8
 
1.6%
적 8
 
1.6%
리 8
 
1.6%
Other values (183) 386
75.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 508
99.8%
Decimal Number 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 21
 
4.1%
지 17
 
3.3%
암 16
 
3.1%
산 15
 
3.0%
석 11
 
2.2%
비 10
 
2.0%
대 9
 
1.8%
묘 8
 
1.6%
적 8
 
1.6%
리 8
 
1.6%
Other values (182) 385
75.8%
Decimal Number
ValueCountFrequency (%)
3 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 508
99.8%
Common 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 21
 
4.1%
지 17
 
3.3%
암 16
 
3.1%
산 15
 
3.0%
석 11
 
2.2%
비 10
 
2.0%
대 9
 
1.8%
묘 8
 
1.6%
적 8
 
1.6%
리 8
 
1.6%
Other values (182) 385
75.8%
Common
ValueCountFrequency (%)
3 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 508
99.8%
ASCII 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 21
 
4.1%
지 17
 
3.3%
암 16
 
3.1%
산 15
 
3.0%
석 11
 
2.2%
비 10
 
2.0%
대 9
 
1.8%
묘 8
 
1.6%
적 8
 
1.6%
리 8
 
1.6%
Other values (182) 385
75.8%
ASCII
ValueCountFrequency (%)
3 1
100.0%

branch_nm
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

sub_nm
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

mcate_cd
Real number (ℝ)

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83226.87
Minimum60602
Maximum180303
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:48:59.787837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum60602
5-th percentile60603
Q160603
median60606
Q360608.5
95-th percentile180303
Maximum180303
Range119701
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation44412.215
Coefficient of variation (CV)0.53362833
Kurtosis0.89238447
Mean83226.87
Median Absolute Deviation (MAD)3
Skewness1.6334641
Sum8322687
Variance1.9724449 × 109
MonotonicityNot monotonic
2023-12-10T18:48:59.984147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
60603 39
39.0%
60606 18
18.0%
180303 16
16.0%
60608 11
 
11.0%
110204 4
 
4.0%
60607 2
 
2.0%
60602 2
 
2.0%
60605 2
 
2.0%
60610 2
 
2.0%
110121 2
 
2.0%
Other values (2) 2
 
2.0%
ValueCountFrequency (%)
60602 2
 
2.0%
60603 39
39.0%
60604 1
 
1.0%
60605 2
 
2.0%
60606 18
18.0%
60607 2
 
2.0%
60608 11
 
11.0%
60610 2
 
2.0%
110121 2
 
2.0%
110204 4
 
4.0%
ValueCountFrequency (%)
180303 16
16.0%
110216 1
 
1.0%
110204 4
 
4.0%
110121 2
 
2.0%
60610 2
 
2.0%
60608 11
11.0%
60607 2
 
2.0%
60606 18
18.0%
60605 2
 
2.0%
60604 1
 
1.0%

mcate_nm
Categorical

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
유명사적/유적지
39 
비/탑/문/각
18 
암자
16 
고택/생가/민속마을
11 
봉우리/고지
4 
Other values (7)
12 

Length

Max length10
Median length8
Mean length6.44
Min length2

Unique

Unique2 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
유명사적/유적지 39
39.0%
비/탑/문/각 18
18.0%
암자 16
16.0%
고택/생가/민속마을 11
 
11.0%
봉우리/고지 4
 
4.0%
천연기념물 2
 
2.0%
왕릉/고분 2
 
2.0%
보물 2
 
2.0%
성/성터 2
 
2.0%
바위 2
 
2.0%
Other values (2) 2
 
2.0%

Length

2023-12-10T18:49:00.217379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
유명사적/유적지 39
39.0%
비/탑/문/각 18
18.0%
암자 16
16.0%
고택/생가/민속마을 11
 
11.0%
봉우리/고지 4
 
4.0%
천연기념물 2
 
2.0%
왕릉/고분 2
 
2.0%
보물 2
 
2.0%
성/성터 2
 
2.0%
바위 2
 
2.0%
Other values (2) 2
 
2.0%

pnu
Real number (ℝ)

Distinct98
Distinct (%)99.0%
Missing1
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean4.4001265 × 1018
Minimum1.1530108 × 1018
Maximum5.011031 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:49:00.507679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1530108 × 1018
5-th percentile2.8562237 × 1018
Q14.219012 × 1018
median4.615035 × 1018
Q34.7720355 × 1018
95-th percentile5.0110113 × 1018
Maximum5.011031 × 1018
Range3.8580202 × 1018
Interquartile range (IQR)5.5302353 × 1017

Descriptive statistics

Standard deviation6.4385402 × 1017
Coefficient of variation (CV)0.14632625
Kurtosis7.3190694
Mean4.4001265 × 1018
Median Absolute Deviation (MAD)2.0997538 × 1017
Skewness-2.4738607
Sum-7.1093343 × 1018
Variance4.14548 × 1035
MonotonicityNot monotonic
2023-12-10T18:49:00.821512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4579032036200990208 2
 
2.0%
4215010900103320064 1
 
1.0%
4873034026113380352 1
 
1.0%
4613025021113650176 1
 
1.0%
4677034031106270208 1
 
1.0%
4677025027102000128 1
 
1.0%
4680025328104609792 1
 
1.0%
4682025036103459840 1
 
1.0%
4376036051200249856 1
 
1.0%
4374034021104520192 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
1153010800101560064 1
1.0%
2632010300108100096 1
1.0%
2632010500106999808 1
1.0%
2714014200111600128 1
1.0%
2723011800105999872 1
1.0%
2871025029109470208 1
1.0%
3017010200102499840 1
1.0%
3114010400108980224 1
1.0%
3171034025202070016 1
1.0%
3171036021100700160 1
1.0%
ValueCountFrequency (%)
5011031023136270336 1
1.0%
5011025929200619520 1
1.0%
5011025924109400064 1
1.0%
5011013900103549952 1
1.0%
5011011600200779776 1
1.0%
5011011300106959872 1
1.0%
4886040021106289664 1
1.0%
4885039025200329728 1
1.0%
4882041023201049600 1
1.0%
4874038025104329728 1
1.0%

sido_nm
Categorical

Distinct15
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
경상북도
18 
전라남도
15 
경상남도
14 
경기도
12 
충청남도
8 
Other values (10)
33 

Length

Max length7
Median length4
Mean length4.1
Min length3

Unique

Unique3 ?
Unique (%)3.0%

Sample

1st row강원도
2nd row전라남도
3rd row부산광역시
4th row서울특별시
5th row경상남도

Common Values

ValueCountFrequency (%)
경상북도 18
18.0%
전라남도 15
15.0%
경상남도 14
14.0%
경기도 12
12.0%
충청남도 8
8.0%
충청북도 7
 
7.0%
강원도 6
 
6.0%
제주특별자치도 6
 
6.0%
전라북도 4
 
4.0%
울산광역시 3
 
3.0%
Other values (5) 7
 
7.0%

Length

2023-12-10T18:49:01.151693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경상북도 18
18.0%
전라남도 15
15.0%
경상남도 14
14.0%
경기도 12
12.0%
충청남도 8
8.0%
충청북도 7
 
7.0%
강원도 6
 
6.0%
제주특별자치도 6
 
6.0%
전라북도 4
 
4.0%
울산광역시 3
 
3.0%
Other values (5) 7
 
7.0%

sgg_nm
Text

Distinct67
Distinct (%)67.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:49:01.581988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.13
Min length2

Characters and Unicode

Total characters313
Distinct characters68
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

Unique49 ?
Unique (%)49.0%

Sample

1st row강릉시
2nd row순천시
3rd row북구
4th row구로구
5th row창원시 진해구
ValueCountFrequency (%)
경주시 6
 
5.8%
제주시 6
 
5.8%
안동시 5
 
4.8%
북구 3
 
2.9%
괴산군 3
 
2.9%
함안군 3
 
2.9%
여수시 3
 
2.9%
순천시 2
 
1.9%
김해시 2
 
1.9%
해남군 2
 
1.9%
Other values (61) 69
66.3%
2023-12-10T18:49:02.250283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 51
 
16.3%
군 44
 
14.1%
주 18
 
5.8%
안 12
 
3.8%
구 12
 
3.8%
동 11
 
3.5%
천 11
 
3.5%
산 9
 
2.9%
경 6
 
1.9%
제 6
 
1.9%
Other values (58) 133
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 309
98.7%
Space Separator 4
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 51
 
16.5%
군 44
 
14.2%
주 18
 
5.8%
안 12
 
3.9%
구 12
 
3.9%
동 11
 
3.6%
천 11
 
3.6%
산 9
 
2.9%
경 6
 
1.9%
제 6
 
1.9%
Other values (57) 129
41.7%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 309
98.7%
Common 4
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 51
 
16.5%
군 44
 
14.2%
주 18
 
5.8%
안 12
 
3.9%
구 12
 
3.9%
동 11
 
3.6%
천 11
 
3.6%
산 9
 
2.9%
경 6
 
1.9%
제 6
 
1.9%
Other values (57) 129
41.7%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 309
98.7%
ASCII 4
 
1.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 51
 
16.5%
군 44
 
14.2%
주 18
 
5.8%
안 12
 
3.9%
구 12
 
3.9%
동 11
 
3.6%
천 11
 
3.6%
산 9
 
2.9%
경 6
 
1.9%
제 6
 
1.9%
Other values (57) 129
41.7%
ASCII
ValueCountFrequency (%)
4
100.0%

bemd_nm
Text

Distinct92
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:49:02.682341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.97
Min length2

Characters and Unicode

Total characters297
Distinct characters94
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

Unique84 ?
Unique (%)84.0%

Sample

1st row옥천동
2nd row송광면
3rd row만덕동
4th row오류동
5th row경화동
ValueCountFrequency (%)
교동 2
 
2.0%
조천읍 2
 
2.0%
아산면 2
 
2.0%
풍산읍 2
 
2.0%
배동 2
 
2.0%
청천면 2
 
2.0%
대산면 2
 
2.0%
영산면 2
 
2.0%
이원면 1
 
1.0%
성남면 1
 
1.0%
Other values (82) 82
82.0%
2023-12-10T18:49:03.407938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
면 52
 
17.5%
동 34
 
11.4%
산 19
 
6.4%
읍 19
 
6.4%
천 9
 
3.0%
화 9
 
3.0%
양 7
 
2.4%
대 5
 
1.7%
봉 5
 
1.7%
남 4
 
1.3%
Other values (84) 134
45.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 297
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 52
 
17.5%
동 34
 
11.4%
산 19
 
6.4%
읍 19
 
6.4%
천 9
 
3.0%
화 9
 
3.0%
양 7
 
2.4%
대 5
 
1.7%
봉 5
 
1.7%
남 4
 
1.3%
Other values (84) 134
45.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 297
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 52
 
17.5%
동 34
 
11.4%
산 19
 
6.4%
읍 19
 
6.4%
천 9
 
3.0%
화 9
 
3.0%
양 7
 
2.4%
대 5
 
1.7%
봉 5
 
1.7%
남 4
 
1.3%
Other values (84) 134
45.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 297
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
면 52
 
17.5%
동 34
 
11.4%
산 19
 
6.4%
읍 19
 
6.4%
천 9
 
3.0%
화 9
 
3.0%
양 7
 
2.4%
대 5
 
1.7%
봉 5
 
1.7%
남 4
 
1.3%
Other values (84) 134
45.1%

ri_nm
Text

MISSING 

Distinct67
Distinct (%)95.7%
Missing30
Missing (%)30.0%
Memory size932.0 B
2023-12-10T18:49:03.839711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9428571
Min length2

Characters and Unicode

Total characters206
Distinct characters80
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

Unique64 ?
Unique (%)91.4%

Sample

1st row신평리
2nd row계진리
3rd row낭도리
4th row삼인리
5th row이목리
ValueCountFrequency (%)
서촌리 2
 
2.9%
화성리 2
 
2.9%
삼인리 2
 
2.9%
금성리 1
 
1.4%
군내리 1
 
1.4%
월하리 1
 
1.4%
노천리 1
 
1.4%
발포리 1
 
1.4%
옥하리 1
 
1.4%
방촌리 1
 
1.4%
Other values (57) 57
81.4%
2023-12-10T18:49:04.543134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 70
34.0%
산 7
 
3.4%
동 5
 
2.4%
화 5
 
2.4%
성 4
 
1.9%
계 4
 
1.9%
촌 4
 
1.9%
서 3
 
1.5%
하 3
 
1.5%
방 3
 
1.5%
Other values (70) 98
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 206
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 70
34.0%
산 7
 
3.4%
동 5
 
2.4%
화 5
 
2.4%
성 4
 
1.9%
계 4
 
1.9%
촌 4
 
1.9%
서 3
 
1.5%
하 3
 
1.5%
방 3
 
1.5%
Other values (70) 98
47.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 206
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 70
34.0%
산 7
 
3.4%
동 5
 
2.4%
화 5
 
2.4%
성 4
 
1.9%
계 4
 
1.9%
촌 4
 
1.9%
서 3
 
1.5%
하 3
 
1.5%
방 3
 
1.5%
Other values (70) 98
47.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 206
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 70
34.0%
산 7
 
3.4%
동 5
 
2.4%
화 5
 
2.4%
성 4
 
1.9%
계 4
 
1.9%
촌 4
 
1.9%
서 3
 
1.5%
하 3
 
1.5%
방 3
 
1.5%
Other values (70) 98
47.6%

beonji
Text

Distinct97
Distinct (%)98.0%
Missing1
Missing (%)1.0%
Memory size932.0 B
2023-12-10T18:49:05.028837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.2525253
Min length2

Characters and Unicode

Total characters421
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)96.0%

Sample

1st row332-5
2nd row12
3rd row810-27
4th row156-73
5th row1140-19
ValueCountFrequency (%)
산99-1 2
 
2.0%
산44 2
 
2.0%
1160 1
 
1.0%
1338 1
 
1.0%
1365 1
 
1.0%
627 1
 
1.0%
200-2 1
 
1.0%
461 1
 
1.0%
346-1 1
 
1.0%
산25-1 1
 
1.0%
Other values (87) 87
87.9%
2023-12-10T18:49:05.865455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 68
16.2%
- 55
13.1%
2 44
10.5%
3 44
10.5%
4 35
8.3%
6 34
8.1%
0 32
7.6%
5 26
 
6.2%
산 23
 
5.5%
7 23
 
5.5%
Other values (2) 37
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 343
81.5%
Dash Punctuation 55
 
13.1%
Other Letter 23
 
5.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 68
19.8%
2 44
12.8%
3 44
12.8%
4 35
10.2%
6 34
9.9%
0 32
9.3%
5 26
 
7.6%
7 23
 
6.7%
8 19
 
5.5%
9 18
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 55
100.0%
Other Letter
ValueCountFrequency (%)
산 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 398
94.5%
Hangul 23
 
5.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 68
17.1%
- 55
13.8%
2 44
11.1%
3 44
11.1%
4 35
8.8%
6 34
8.5%
0 32
8.0%
5 26
 
6.5%
7 23
 
5.8%
8 19
 
4.8%
Hangul
ValueCountFrequency (%)
산 23
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 398
94.5%
Hangul 23
 
5.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 68
17.1%
- 55
13.8%
2 44
11.1%
3 44
11.1%
4 35
8.8%
6 34
8.5%
0 32
8.0%
5 26
 
6.5%
7 23
 
5.8%
8 19
 
4.8%
Hangul
ValueCountFrequency (%)
산 23
100.0%

badm_cd
Real number (ℝ)

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3989556 × 109
Minimum1.1530108 × 109
Maximum5.011031 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:49:06.157052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1530108 × 109
5-th percentile2.8636244 × 109
Q14.2200116 × 109
median4.614035 × 109
Q34.7720343 × 109
95-th percentile5.0110113 × 109
Maximum5.011031 × 109
Range3.8580202 × 109
Interquartile range (IQR)5.5202268 × 108

Descriptive statistics

Standard deviation6.4070099 × 108
Coefficient of variation (CV)0.14564843
Kurtosis7.3938917
Mean4.3989556 × 109
Median Absolute Deviation (MAD)2.1197532 × 108
Skewness-2.4791607
Sum4.3989556 × 1011
Variance4.1049775 × 1017
MonotonicityNot monotonic
2023-12-10T18:49:06.436855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4873034026 2
 
2.0%
4579032036 2
 
2.0%
4713014300 2
 
2.0%
4374531021 1
 
1.0%
4613025021 1
 
1.0%
4677034031 1
 
1.0%
4677025027 1
 
1.0%
4680025328 1
 
1.0%
4682025036 1
 
1.0%
4376036051 1
 
1.0%
Other values (87) 87
87.0%
ValueCountFrequency (%)
1153010800 1
1.0%
2632010300 1
1.0%
2632010500 1
1.0%
2714014200 1
1.0%
2723011800 1
1.0%
2871025029 1
1.0%
3017010200 1
1.0%
3114010400 1
1.0%
3171034025 1
1.0%
3171036021 1
1.0%
ValueCountFrequency (%)
5011031023 1
1.0%
5011025929 1
1.0%
5011025924 1
1.0%
5011013900 1
1.0%
5011011600 1
1.0%
5011011300 1
1.0%
4886040021 1
1.0%
4885039025 1
1.0%
4882041023 1
1.0%
4874038025 1
1.0%

hadm_cd
Real number (ℝ)

Distinct92
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3989698 × 109
Minimum1.153078 × 109
Maximum5.011066 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:49:06.749016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.153078 × 109
5-th percentile2.8636276 × 109
Q14.2200598 × 109
median4.614035 × 109
Q34.7720342 × 109
95-th percentile5.0110259 × 109
Maximum5.011066 × 109
Range3.857988 × 109
Interquartile range (IQR)5.519745 × 108

Descriptive statistics

Standard deviation6.4069299 × 108
Coefficient of variation (CV)0.14564614
Kurtosis7.3937453
Mean4.3989698 × 109
Median Absolute Deviation (MAD)2.120185 × 108
Skewness-2.4791288
Sum4.3989698 × 1011
Variance4.104875 × 1017
MonotonicityNot monotonic
2023-12-10T18:49:07.008675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4376036000 2
 
2.0%
4717025000 2
 
2.0%
4825052000 2
 
2.0%
4579032000 2
 
2.0%
5011025900 2
 
2.0%
4713057000 2
 
2.0%
4873034000 2
 
2.0%
4874038000 2
 
2.0%
4373036000 1
 
1.0%
4677034000 1
 
1.0%
Other values (82) 82
82.0%
ValueCountFrequency (%)
1153078000 1
1.0%
2632051000 1
1.0%
2632057100 1
1.0%
2714076000 1
1.0%
2723077000 1
1.0%
2871025000 1
1.0%
3017054000 1
1.0%
3114054000 1
1.0%
3171034000 1
1.0%
3171036000 1
1.0%
ValueCountFrequency (%)
5011066000 1
1.0%
5011062000 1
1.0%
5011061000 1
1.0%
5011031000 1
1.0%
5011025900 2
2.0%
4886040000 1
1.0%
4885039000 1
1.0%
4882041000 1
1.0%
4874038000 2
2.0%
4873038000 1
1.0%

rd_cd
Real number (ℝ)

MISSING 

Distinct54
Distinct (%)100.0%
Missing46
Missing (%)46.0%
Infinite0
Infinite (%)0.0%
Mean4.2965739 × 1011
Minimum1.1530312 × 1011
Maximum5.0110335 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:49:07.262815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1530312 × 1011
5-th percentile2.6911786 × 1011
Q14.1730413 × 1011
median4.6460466 × 1011
Q34.7170472 × 1011
95-th percentile4.8830768 × 1011
Maximum5.0110335 × 1011
Range3.8580023 × 1011
Interquartile range (IQR)5.4400594 × 1010

Descriptive statistics

Standard deviation7.6196885 × 1010
Coefficient of variation (CV)0.17734336
Kurtosis5.0388979
Mean4.2965739 × 1011
Median Absolute Deviation (MAD)2.0200121 × 1010
Skewness-2.1787388
Sum2.3201499 × 1013
Variance5.8059654 × 1021
MonotonicityNot monotonic
2023-12-10T18:49:07.603968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
478503322012 1
 
1.0%
317104320026 1
 
1.0%
287104271263 1
 
1.0%
442304565950 1
 
1.0%
441314547784 1
 
1.0%
437454532080 1
 
1.0%
437404529142 1
 
1.0%
468204682274 1
 
1.0%
468004676167 1
 
1.0%
467704667727 1
 
1.0%
Other values (44) 44
44.0%
(Missing) 46
46.0%
ValueCountFrequency (%)
115303116009 1
1.0%
263203132012 1
1.0%
263204196294 1
1.0%
272302145001 1
1.0%
287104271263 1
1.0%
301703166028 1
1.0%
311403170033 1
1.0%
317104320026 1
1.0%
412504367186 1
1.0%
412734373122 1
1.0%
ValueCountFrequency (%)
501103349064 1
1.0%
488603019075 1
1.0%
488503344025 1
1.0%
488202328001 1
1.0%
482704808347 1
1.0%
482504805029 1
1.0%
482504805025 1
1.0%
481293331068 1
1.0%
478503322012 1
1.0%
477304745042 1
1.0%

rd_nm
Text

MISSING 

Distinct54
Distinct (%)100.0%
Missing46
Missing (%)46.0%
Memory size932.0 B
2023-12-10T18:49:08.008957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length4.1851852
Min length3

Characters and Unicode

Total characters226
Distinct characters102
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

Unique54 ?
Unique (%)100.0%

Sample

1st row동부시장길
2nd row송광사안길
3rd row상학산복길
4th row오류로
5th row태백로
ValueCountFrequency (%)
가락로93번길 1
 
1.9%
숭산로 1
 
1.9%
신등가회로 1
 
1.9%
칠곡중앙대로 1
 
1.9%
치술령길 1
 
1.9%
대산길 1
 
1.9%
황산벌로608번길 1
 
1.9%
화성2길 1
 
1.9%
상작길 1
 
1.9%
내동1길 1
 
1.9%
Other values (44) 44
81.5%
2023-12-10T18:49:08.664520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
길 36
 
15.9%
로 25
 
11.1%
동 6
 
2.7%
산 5
 
2.2%
번 5
 
2.2%
2 5
 
2.2%
사 4
 
1.8%
장 4
 
1.8%
대 4
 
1.8%
가 3
 
1.3%
Other values (92) 129
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 206
91.2%
Decimal Number 20
 
8.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 36
 
17.5%
로 25
 
12.1%
동 6
 
2.9%
산 5
 
2.4%
번 5
 
2.4%
사 4
 
1.9%
장 4
 
1.9%
대 4
 
1.9%
가 3
 
1.5%
양 3
 
1.5%
Other values (84) 111
53.9%
Decimal Number
ValueCountFrequency (%)
2 5
25.0%
9 3
15.0%
3 3
15.0%
1 2
 
10.0%
6 2
 
10.0%
0 2
 
10.0%
5 2
 
10.0%
8 1
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 206
91.2%
Common 20
 
8.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 36
 
17.5%
로 25
 
12.1%
동 6
 
2.9%
산 5
 
2.4%
번 5
 
2.4%
사 4
 
1.9%
장 4
 
1.9%
대 4
 
1.9%
가 3
 
1.5%
양 3
 
1.5%
Other values (84) 111
53.9%
Common
ValueCountFrequency (%)
2 5
25.0%
9 3
15.0%
3 3
15.0%
1 2
 
10.0%
6 2
 
10.0%
0 2
 
10.0%
5 2
 
10.0%
8 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 206
91.2%
ASCII 20
 
8.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
길 36
 
17.5%
로 25
 
12.1%
동 6
 
2.9%
산 5
 
2.4%
번 5
 
2.4%
사 4
 
1.9%
장 4
 
1.9%
대 4
 
1.9%
가 3
 
1.5%
양 3
 
1.5%
Other values (84) 111
53.9%
ASCII
ValueCountFrequency (%)
2 5
25.0%
9 3
15.0%
3 3
15.0%
1 2
 
10.0%
6 2
 
10.0%
0 2
 
10.0%
5 2
 
10.0%
8 1
 
5.0%

bld_num
Text

MISSING 

Distinct52
Distinct (%)96.3%
Missing46
Missing (%)46.0%
Memory size932.0 B
2023-12-10T18:49:09.089782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.4814815
Min length1

Characters and Unicode

Total characters188
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

Unique50 ?
Unique (%)92.6%

Sample

1st row40
2nd row100
3rd row209
4th row66-15
5th row29-4
ValueCountFrequency (%)
35 2
 
3.7%
40 2
 
3.7%
33-8 1
 
1.9%
275-209 1
 
1.9%
597 1
 
1.9%
7 1
 
1.9%
29 1
 
1.9%
36-3 1
 
1.9%
43 1
 
1.9%
44 1
 
1.9%
Other values (42) 42
77.8%
2023-12-10T18:49:10.251118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 32
17.0%
3 23
12.2%
2 21
11.2%
- 21
11.2%
0 16
8.5%
9 15
8.0%
5 14
7.4%
6 14
7.4%
4 12
 
6.4%
8 10
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 167
88.8%
Dash Punctuation 21
 
11.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 32
19.2%
3 23
13.8%
2 21
12.6%
0 16
9.6%
9 15
9.0%
5 14
8.4%
6 14
8.4%
4 12
 
7.2%
8 10
 
6.0%
7 10
 
6.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 188
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 32
17.0%
3 23
12.2%
2 21
11.2%
- 21
11.2%
0 16
8.5%
9 15
8.0%
5 14
7.4%
6 14
7.4%
4 12
 
6.4%
8 10
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 188
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 32
17.0%
3 23
12.2%
2 21
11.2%
- 21
11.2%
0 16
8.5%
9 15
8.0%
5 14
7.4%
6 14
7.4%
4 12
 
6.4%
8 10
 
5.3%

x
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.82295
Minimum126.16559
Maximum130.87115
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:49:10.566420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.16559
5-th percentile126.55907
Q1127.01523
median127.74182
Q3128.64338
95-th percentile129.20866
Maximum130.87115
Range4.7055579
Interquartile range (IQR)1.6281504

Descriptive statistics

Standard deviation0.95272473
Coefficient of variation (CV)0.0074534716
Kurtosis-0.5809297
Mean127.82295
Median Absolute Deviation (MAD)0.80068226
Skewness0.31450389
Sum12782.295
Variance0.90768441
MonotonicityNot monotonic
2023-12-10T18:49:10.859824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.901049073648 1
 
1.0%
127.612913968273 1
 
1.0%
127.769216544021 1
 
1.0%
127.714431861213 1
 
1.0%
127.336211405407 1
 
1.0%
127.28523939873 1
 
1.0%
126.950469670493 1
 
1.0%
126.594411502661 1
 
1.0%
127.90678236749 1
 
1.0%
127.926639141554 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
126.16558817689 1
1.0%
126.467853921553 1
1.0%
126.47460094268 1
1.0%
126.485421646069 1
1.0%
126.501600860646 1
1.0%
126.562090086355 1
1.0%
126.57142671626 1
1.0%
126.576329348806 1
1.0%
126.594411502661 1
1.0%
126.598528665934 1
1.0%
ValueCountFrequency (%)
130.871146092025 1
1.0%
129.313025652515 1
1.0%
129.230277957428 1
1.0%
129.227876026147 1
1.0%
129.212731073839 1
1.0%
129.208441268198 1
1.0%
129.185974953078 1
1.0%
129.162832193135 1
1.0%
129.107868431323 1
1.0%
129.102085253959 1
1.0%

y
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.976039
Minimum33.305519
Maximum38.17591
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:49:11.216649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.305519
5-th percentile33.536531
Q135.214013
median35.938899
Q336.751618
95-th percentile37.861988
Maximum38.17591
Range4.8703909
Interquartile range (IQR)1.5376055

Descriptive statistics

Standard deviation1.1886995
Coefficient of variation (CV)0.033041423
Kurtosis-0.42782273
Mean35.976039
Median Absolute Deviation (MAD)0.77441569
Skewness-0.11282571
Sum3597.6039
Variance1.4130066
MonotonicityNot monotonic
2023-12-10T18:49:11.924136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.7614276611126 1
 
1.0%
36.811184200601 1
 
1.0%
36.6039436588862 1
 
1.0%
34.6072613020045 1
 
1.0%
34.4841341185359 1
 
1.0%
34.6111192551308 1
 
1.0%
34.5477072683767 1
 
1.0%
34.5746892600701 1
 
1.0%
36.6687999557521 1
 
1.0%
36.2058926892796 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
33.3055189312845 1
1.0%
33.4289478114098 1
1.0%
33.4292782690313 1
1.0%
33.4432954180702 1
1.0%
33.5293616654404 1
1.0%
33.5369083894114 1
1.0%
34.4841341185359 1
1.0%
34.5070159339737 1
1.0%
34.5477072683767 1
1.0%
34.5746892600701 1
1.0%
ValueCountFrequency (%)
38.1759098681846 1
1.0%
38.1321070350527 1
1.0%
38.0063048029875 1
1.0%
37.9484795003554 1
1.0%
37.9442203429231 1
1.0%
37.8576601397872 1
1.0%
37.7718098330592 1
1.0%
37.7642106350154 1
1.0%
37.7633198602074 1
1.0%
37.7614276611126 1
1.0%

grid_cd
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:49:12.582064image/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

Unique100 ?
Unique (%)100.0%

Sample

1st row마사234744
2nd row다라795673
3rd row마라401924
4th row다사417436
5th row마라071850
ValueCountFrequency (%)
마사234744 1
 
1.0%
다바781620 1
 
1.0%
라라196236 1
 
1.0%
다라849100 1
 
1.0%
다라803241 1
 
1.0%
다라495172 1
 
1.0%
다라169204 1
 
1.0%
라바363523 1
 
1.0%
라바383010 1
 
1.0%
라바286809 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T18:49:13.515823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 73
 
9.1%
0 69
 
8.6%
4 68
 
8.5%
8 67
 
8.4%
9 59
 
7.4%
5 56
 
7.0%
2 54
 
6.8%
3 54
 
6.8%
마 53
 
6.6%
라 53
 
6.6%
Other values (7) 194
24.2%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 73
12.2%
0 69
11.5%
4 68
11.3%
8 67
11.2%
9 59
9.8%
5 56
9.3%
2 54
9.0%
3 54
9.0%
6 51
8.5%
7 49
8.2%
Other Letter
ValueCountFrequency (%)
마 53
26.5%
라 53
26.5%
다 46
23.0%
바 24
12.0%
사 16
 
8.0%
나 5
 
2.5%
아 3
 
1.5%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 73
12.2%
0 69
11.5%
4 68
11.3%
8 67
11.2%
9 59
9.8%
5 56
9.3%
2 54
9.0%
3 54
9.0%
6 51
8.5%
7 49
8.2%
Hangul
ValueCountFrequency (%)
마 53
26.5%
라 53
26.5%
다 46
23.0%
바 24
12.0%
사 16
 
8.0%
나 5
 
2.5%
아 3
 
1.5%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 73
12.2%
0 69
11.5%
4 68
11.3%
8 67
11.2%
9 59
9.8%
5 56
9.3%
2 54
9.0%
3 54
9.0%
6 51
8.5%
7 49
8.2%
Hangul
ValueCountFrequency (%)
마 53
26.5%
라 53
26.5%
다 46
23.0%
바 24
12.0%
사 16
 
8.0%
나 5
 
2.5%
아 3
 
1.5%

lst_updt_dt
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20210917100801
100 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210917100801
2nd row20210917100801
3rd row20210917100801
4th row20210917100801
5th row20210917100801

Common Values

ValueCountFrequency (%)
20210917100801 100
100.0%

Length

2023-12-10T18:49:13.800895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:49:14.029667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210917100801 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

2023-12-10T18:49:14.242572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:49:14.427845image/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_507_LLR_HISTST_2021
100 

Length

Max length22
Median length22
Mean length22
Min length22

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKC_507_LLR_HISTST_2021
2nd rowKC_507_LLR_HISTST_2021
3rd rowKC_507_LLR_HISTST_2021
4th rowKC_507_LLR_HISTST_2021
5th rowKC_507_LLR_HISTST_2021

Common Values

ValueCountFrequency (%)
KC_507_LLR_HISTST_2021 100
100.0%

Length

2023-12-10T18:49:14.649141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:49:14.814597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kc_507_llr_histst_2021 100
100.0%

base_ymd
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20210917
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210917
2nd row20210917
3rd row20210917
4th row20210917
5th row20210917

Common Values

ValueCountFrequency (%)
20210917 100
100.0%

Length

2023-12-10T18:49:15.001594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:49:15.176496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210917 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
0KCLHTPO21N000000001장소관광지142444사자암<NA><NA>180303암자4215010900103320064강원도강릉시옥천동<NA>332-542150109004215054000421504460352동부시장길40128.90104937.761428마사23474420210917100801KTKC_507_LLR_HISTST_202120210917
1KCLHTPO21N000007617장소관광지20637214송광사향로전<NA><NA>180303암자4615036023100120064전라남도순천시송광면신평리1246150360234615036000461504649532송광사안길100127.27550635.000957다라79567320210917100801KTKC_507_LLR_HISTST_202120210917
2KCLHTPO21N000000003장소관광지157800백천암<NA><NA>180303암자2632010300108100096부산광역시북구만덕동<NA>810-2726320103002632057100263204196294상학산복길209129.04028235.217431마라40192420210917100801KTKC_507_LLR_HISTST_202120210917
3KCLHTPO21N000000004장소관광지214928금강암<NA><NA>180303암자1153010800101560064서울특별시구로구오류동<NA>156-7311530108001153078000115303116009오류로66-15126.84127137.490519다사41743620210917100801KTKC_507_LLR_HISTST_202120210917
4KCLHTPO21N000000005장소관광지228110심오암<NA><NA>180303암자4812913900111399936경상남도창원시 진해구경화동<NA>1140-1948129139004812955000481293331068태백로29-4128.67665435.155114마라07185020210917100801KTKC_507_LLR_HISTST_202120210917
5KCLHTPO21N000000006장소관광지248527영도암<NA><NA>180303암자2632010500106999808부산광역시북구구포동<NA>700-626320105002632051000263203132012시랑로20-1129.00389935.203758마라36890820210917100801KTKC_507_LLR_HISTST_202120210917
6KCLHTPO21N000000007장소관광지730889선공암<NA><NA>180303암자4471025027104079872충청남도금산군금산읍계진리40844710250274471025000447104571585족실길122127.46412736.08298다마96787320210917100801KTKC_507_LLR_HISTST_202120210917
7KCLHTPO21N000007618장소관광지21144478여수낭도리공룡발자국화석산지<NA><NA>60603유명사적/유적지4613035027101150208전라남도여수시화정면낭도리115-246130350274613035000<NA><NA><NA>127.55617334.590668라라05121820210917100801KTKC_507_LLR_HISTST_202120210917
8KCLHTPO21N000000009장소관광지744924용문암<NA><NA>180303암자4579032036200990208전라북도고창군아산면삼인리산99-145790320364579032000<NA><NA><NA>126.5620935.478157다마14920620210917100801KTKC_507_LLR_HISTST_202120210917
9KCLHTPO21N000000010장소관광지746581괭이암<NA><NA>180303암자4613033028200359936전라남도여수시화양면이목리산36-346130330284613033000<NA><NA><NA>127.5533634.689738라라04832820210917100801KTKC_507_LLR_HISTST_202120210917
idlclasmlsfcid_poipoi_nmbranch_nmsub_nmmcate_cdmcate_nmpnusido_nmsgg_nmbemd_nmri_nmbeonjibadm_cdhadm_cdrd_cdrd_nmbld_numxygrid_cdlst_updt_dtdata_orgnfile_namebase_ymd
90KCLHTPO21N000000091장소관광지16496212인흥군묘신도비<NA><NA>60606비/탑/문/각4165036021200180224경기도포천시영중면양문리산18-641650360214165036000<NA><NA><NA>127.25074238.006305다아78100720210917100801KTKC_507_LLR_HISTST_202120210917
91KCLHTPO21N000000092장소관광지16510286안산대부광산퇴적암층<NA><NA>60603유명사적/유적지4127311300101479936경기도안산시 단원구선감동<NA>148-141273113004127361000412734373122본말길118-1126.63242537.217708다사23013520210917100801KTKC_507_LLR_HISTST_202120210917
92KCLHTPO21N000000093장소관광지16654695신효순심미선추모비<NA><NA>60606비/탑/문/각4163033025105430016경기도양주시광적면효촌리543-641630330254163033000<NA><NA><NA>126.94898337.85766다사51584320210917100801KTKC_507_LLR_HISTST_202120210917
93KCLHTPO21N000000094장소관광지16695634지산사유적지<NA><NA>60603유명사적/유적지4686037027102480384전라남도함평군해보면금계리248-146860370274686037000<NA><NA><NA>126.57632935.173853다라15886820210917100801KTKC_507_LLR_HISTST_202120210917
94KCLHTPO21N000000095장소관광지16933825빈동재사<NA><NA>60603유명사적/유적지4792025030109620224경상북도봉화군봉화읍문단리96247920250304792025000<NA><NA><NA>128.65211436.879071마바02676220210917100801KTKC_507_LLR_HISTST_202120210917
95KCLHTPO21N000000096장소관광지17005015남일대코끼리바위<NA><NA>110121바위4824011600106760192경상남도사천시향촌동<NA>676-148240116004824057000<NA><NA><NA>128.09777134.921092라라54658620210917100801KTKC_507_LLR_HISTST_202120210917
96KCLHTPO21N000000097장소관광지17043673직지사극락전<NA><NA>180303암자4715038022102160384경상북도김천시대항면운수리21647150380224715038000471504724525직지사길95128.00228936.116431라마45291120210917100801KTKC_507_LLR_HISTST_202120210917
97KCLHTPO21N000000098장소관광지17060805연동사지3층석탑<NA><NA>60606비/탑/문/각4671037025110219776전라남도담양군금성면금성리102246710370254671037000<NA><NA><NA>127.03209735.371994다마57408520210917100801KTKC_507_LLR_HISTST_202120210917
98KCLHTPO21N000000099장소관광지17701549김기량순교현양비<NA><NA>60606비/탑/문/각5011025924109400064제주특별자치도제주시조천읍함덕리940-250110259245011025900<NA><NA><NA>126.6708133.536908다다23005320210917100801KTKC_507_LLR_HISTST_202120210917
99KCLHTPO21N000000100장소관광지18936048운지암<NA><NA>180303암자3114010400108980224울산광역시남구신정동<NA>898-1131140104003114054000311403170033신남로69129.31302635.527632마마64327220210917100801KTKC_507_LLR_HISTST_202120210917