Overview

Dataset statistics

Number of variables27
Number of observations100
Missing cells333
Missing cells (%)12.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.4 KiB
Average record size in memory229.3 B

Variable types

Text9
Categorical9
Numeric7
Unsupported2

Alerts

lclas has constant value ""Constant
mlsfc has constant value ""Constant
mcate_cd has constant value ""Constant
mcate_nm 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 25 (25.0%) missing valuesMissing
rd_cd has 36 (36.0%) missing valuesMissing
rd_nm has 36 (36.0%) missing valuesMissing
bld_num has 36 (36.0%) missing valuesMissing
id has unique valuesUnique
id_poi has unique valuesUnique
x has unique valuesUnique
y 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 09:58:49.093165
Analysis finished2023-12-10 09:58:50.470375
Duration1.38 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

id
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:58:50.838936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters1900
Distinct characters17
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st rowKCMPLPO21N000000001
2nd rowKCMPLPO21N000000184
3rd rowKCMPLPO21N000000003
4th rowKCMPLPO21N000000004
5th rowKCMPLPO21N000000005
ValueCountFrequency (%)
kcmplpo21n000000001 1
 
1.0%
kcmplpo21n000000063 1
 
1.0%
kcmplpo21n000000074 1
 
1.0%
kcmplpo21n000000073 1
 
1.0%
kcmplpo21n000000072 1
 
1.0%
kcmplpo21n000000071 1
 
1.0%
kcmplpo21n000000070 1
 
1.0%
kcmplpo21n000000069 1
 
1.0%
kcmplpo21n000000068 1
 
1.0%
kcmplpo21n000000067 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T18:58:51.679495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 714
37.6%
P 200
 
10.5%
1 124
 
6.5%
2 118
 
6.2%
K 100
 
5.3%
C 100
 
5.3%
N 100
 
5.3%
O 100
 
5.3%
L 100
 
5.3%
M 100
 
5.3%
Other values (7) 144
 
7.6%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 714
64.9%
1 124
 
11.3%
2 118
 
10.7%
8 22
 
2.0%
4 21
 
1.9%
5 21
 
1.9%
6 21
 
1.9%
7 20
 
1.8%
9 20
 
1.8%
3 19
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
P 200
25.0%
K 100
12.5%
C 100
12.5%
N 100
12.5%
O 100
12.5%
L 100
12.5%
M 100
12.5%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 714
64.9%
1 124
 
11.3%
2 118
 
10.7%
8 22
 
2.0%
4 21
 
1.9%
5 21
 
1.9%
6 21
 
1.9%
7 20
 
1.8%
9 20
 
1.8%
3 19
 
1.7%
Latin
ValueCountFrequency (%)
P 200
25.0%
K 100
12.5%
C 100
12.5%
N 100
12.5%
O 100
12.5%
L 100
12.5%
M 100
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 714
37.6%
P 200
 
10.5%
1 124
 
6.5%
2 118
 
6.2%
K 100
 
5.3%
C 100
 
5.3%
N 100
 
5.3%
O 100
 
5.3%
L 100
 
5.3%
M 100
 
5.3%
Other values (7) 144
 
7.6%

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

2023-12-10T18:58:52.013185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:58:52.194611image/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

2023-12-10T18:58:52.384337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:58:52.549047image/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%
Mean12333755
Minimum4898815
Maximum21713053
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:58:52.797355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4898815
5-th percentile7984616.5
Q110252333
median10252403
Q316497653
95-th percentile18164117
Maximum21713053
Range16814238
Interquartile range (IQR)6245320.5

Descriptive statistics

Standard deviation3721170.7
Coefficient of variation (CV)0.30170623
Kurtosis-0.53040776
Mean12333755
Median Absolute Deviation (MAD)64574.5
Skewness0.65054115
Sum1.2333755 × 109
Variance1.3847111 × 1013
MonotonicityNot monotonic
2023-12-10T18:58:53.067859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7461518 1
 
1.0%
10252358 1
 
1.0%
8456608 1
 
1.0%
20174255 1
 
1.0%
10316988 1
 
1.0%
11399438 1
 
1.0%
10252361 1
 
1.0%
9653618 1
 
1.0%
16637622 1
 
1.0%
10252334 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
4898815 1
1.0%
5404922 1
1.0%
6854153 1
1.0%
7218849 1
1.0%
7461518 1
1.0%
8012148 1
1.0%
8012150 1
1.0%
8012155 1
1.0%
8012157 1
1.0%
8456608 1
1.0%
ValueCountFrequency (%)
21713053 1
1.0%
21073826 1
1.0%
20518086 1
1.0%
20174255 1
1.0%
19868757 1
1.0%
18074399 1
1.0%
17839984 1
1.0%
17765143 1
1.0%
17733908 1
1.0%
16914758 1
1.0%

poi_nm
Text

Distinct93
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:58:53.493261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length7.72
Min length3

Characters and Unicode

Total characters772
Distinct characters215
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique88 ?
Unique (%)88.0%

Sample

1st row전주영화종합촬영소
2nd rowMBC문화동산
3rd row시월애촬영지
4th row청춘촬영지
5th row드라마영광의재인촬영지
ValueCountFrequency (%)
겨울연가촬영지 3
 
3.0%
영화외출촬영지 3
 
3.0%
대장금촬영지 2
 
2.0%
봄날은간다촬영지 2
 
2.0%
상도촬영지 2
 
2.0%
전주영화종합촬영소 1
 
1.0%
신라밀레니엄파크선덕여왕촬영지 1
 
1.0%
순수의시대촬영지 1
 
1.0%
청석골드라마세트장 1
 
1.0%
고맙습니다촬영지 1
 
1.0%
Other values (83) 83
83.0%
2023-12-10T18:58:54.298664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
영 89
 
11.5%
촬 79
 
10.2%
지 74
 
9.6%
장 28
 
3.6%
마 14
 
1.8%
라 14
 
1.8%
세 13
 
1.7%
드 12
 
1.6%
의 12
 
1.6%
대 12
 
1.6%
Other values (205) 425
55.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 754
97.7%
Uppercase Letter 9
 
1.2%
Decimal Number 8
 
1.0%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 89
 
11.8%
촬 79
 
10.5%
지 74
 
9.8%
장 28
 
3.7%
마 14
 
1.9%
라 14
 
1.9%
세 13
 
1.7%
드 12
 
1.6%
의 12
 
1.6%
대 12
 
1.6%
Other values (191) 407
54.0%
Decimal Number
ValueCountFrequency (%)
1 2
25.0%
0 1
12.5%
2 1
12.5%
3 1
12.5%
5 1
12.5%
4 1
12.5%
9 1
12.5%
Uppercase Letter
ValueCountFrequency (%)
S 3
33.3%
B 2
22.2%
J 1
 
11.1%
A 1
 
11.1%
C 1
 
11.1%
M 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 754
97.7%
Latin 9
 
1.2%
Common 9
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 89
 
11.8%
촬 79
 
10.5%
지 74
 
9.8%
장 28
 
3.7%
마 14
 
1.9%
라 14
 
1.9%
세 13
 
1.7%
드 12
 
1.6%
의 12
 
1.6%
대 12
 
1.6%
Other values (191) 407
54.0%
Common
ValueCountFrequency (%)
1 2
22.2%
0 1
11.1%
2 1
11.1%
3 1
11.1%
& 1
11.1%
5 1
11.1%
4 1
11.1%
9 1
11.1%
Latin
ValueCountFrequency (%)
S 3
33.3%
B 2
22.2%
J 1
 
11.1%
A 1
 
11.1%
C 1
 
11.1%
M 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 754
97.7%
ASCII 18
 
2.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
영 89
 
11.8%
촬 79
 
10.5%
지 74
 
9.8%
장 28
 
3.7%
마 14
 
1.9%
라 14
 
1.9%
세 13
 
1.7%
드 12
 
1.6%
의 12
 
1.6%
대 12
 
1.6%
Other values (191) 407
54.0%
ASCII
ValueCountFrequency (%)
S 3
16.7%
B 2
11.1%
1 2
11.1%
0 1
 
5.6%
2 1
 
5.6%
3 1
 
5.6%
& 1
 
5.6%
J 1
 
5.6%
A 1
 
5.6%
C 1
 
5.6%
Other values (4) 4
22.2%

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
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
60515
100 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row60515
2nd row60515
3rd row60515
4th row60515
5th row60515

Common Values

ValueCountFrequency (%)
60515 100
100.0%

Length

2023-12-10T18:58:54.638956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:58:54.830949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
60515 100
100.0%

mcate_nm
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
드라마/영화촬영지
100 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row드라마/영화촬영지
2nd row드라마/영화촬영지
3rd row드라마/영화촬영지
4th row드라마/영화촬영지
5th row드라마/영화촬영지

Common Values

ValueCountFrequency (%)
드라마/영화촬영지 100
100.0%

Length

2023-12-10T18:58:55.041506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:58:55.319291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
드라마/영화촬영지 100
100.0%

pnu
Real number (ℝ)

Distinct95
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.2041648 × 1018
Minimum1.1110119 × 1018
Maximum5.013032 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:58:55.687536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110119 × 1018
5-th percentile2.5447103 × 1018
Q14.2037883 × 1018
median4.4470292 × 1018
Q34.7130118 × 1018
95-th percentile4.895245 × 1018
Maximum5.013032 × 1018
Range3.9020201 × 1018
Interquartile range (IQR)5.0922352 × 1017

Descriptive statistics

Standard deviation8.8813642 × 1017
Coefficient of variation (CV)0.21125157
Kurtosis5.2833064
Mean4.2041648 × 1018
Median Absolute Deviation (MAD)2.6548909 × 1017
Skewness-2.3480464
Sum-3.8586381 × 1018
Variance7.887863 × 1035
MonotonicityNot monotonic
2023-12-10T18:58:55.970892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4276038024107040005 4
 
4.0%
4889046037102560005 2
 
2.0%
2671025024101350000 2
 
2.0%
4511114500105400000 1
 
1.0%
4477034040100080012 1
 
1.0%
4137011000102450001 1
 
1.0%
4579031032200780000 1
 
1.0%
4713013600107190070 1
 
1.0%
4822036027200460001 1
 
1.0%
4278032022201330001 1
 
1.0%
Other values (85) 85
85.0%
ValueCountFrequency (%)
1111011900100010001 1
1.0%
1111014600100110016 1
1.0%
1117012900103930003 1
1.0%
1144010100107290001 1
1.0%
1171010100100400001 1
1.0%
2617010300107770002 1
1.0%
2671025024101350000 2
2.0%
2720010300121390011 1
1.0%
2871041021202490003 1
1.0%
2872031021100010011 1
1.0%
ValueCountFrequency (%)
5013032024136650011 1
1.0%
5013031028200900000 1
1.0%
5013025924100570000 1
1.0%
5013025327200680008 1
1.0%
5013025327129750000 1
1.0%
4889046037102560005 2
2.0%
4886031026100010001 1
1.0%
4885032034104820000 1
1.0%
4885032033107700001 1
1.0%
4884033026200480001 1
1.0%

sido_nm
Categorical

Distinct14
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
강원도
22 
경상북도
13 
경기도
12 
전라남도
10 
경상남도
9 
Other values (9)
34 

Length

Max length7
Median length5
Mean length3.94
Min length3

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row전라북도
2nd row경기도
3rd row인천광역시
4th row경상남도
5th row충청북도

Common Values

ValueCountFrequency (%)
강원도 22
22.0%
경상북도 13
13.0%
경기도 12
12.0%
전라남도 10
10.0%
경상남도 9
9.0%
충청남도 8
 
8.0%
전라북도 6
 
6.0%
서울특별시 5
 
5.0%
제주특별자치도 5
 
5.0%
인천광역시 3
 
3.0%
Other values (4) 7
 
7.0%

Length

2023-12-10T18:58:56.244274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강원도 22
22.0%
경상북도 13
13.0%
경기도 12
12.0%
전라남도 10
10.0%
경상남도 9
9.0%
충청남도 8
 
8.0%
전라북도 6
 
6.0%
서울특별시 5
 
5.0%
제주특별자치도 5
 
5.0%
인천광역시 3
 
3.0%
Other values (4) 7
 
7.0%

sgg_nm
Text

Distinct66
Distinct (%)66.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:58:56.699889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.3
Min length2

Characters and Unicode

Total characters330
Distinct characters83
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

Unique46 ?
Unique (%)46.0%

Sample

1st row전주시 완산구
2nd row양주시
3rd row강화군
4th row하동군
5th row청주시 상당구
ValueCountFrequency (%)
평창군 7
 
6.5%
서귀포시 5
 
4.7%
삼척시 4
 
3.7%
태안군 4
 
3.7%
경주시 3
 
2.8%
문경시 3
 
2.8%
기장군 2
 
1.9%
남구 2
 
1.9%
용인시 2
 
1.9%
고창군 2
 
1.9%
Other values (61) 73
68.2%
2023-12-10T18:58:57.890007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
군 51
 
15.5%
시 41
 
12.4%
구 17
 
5.2%
산 10
 
3.0%
창 9
 
2.7%
천 9
 
2.7%
포 9
 
2.7%
주 9
 
2.7%
안 8
 
2.4%
평 8
 
2.4%
Other values (73) 159
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 323
97.9%
Space Separator 7
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 51
 
15.8%
시 41
 
12.7%
구 17
 
5.3%
산 10
 
3.1%
창 9
 
2.8%
천 9
 
2.8%
포 9
 
2.8%
주 9
 
2.8%
안 8
 
2.5%
평 8
 
2.5%
Other values (72) 152
47.1%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 323
97.9%
Common 7
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 51
 
15.8%
시 41
 
12.7%
구 17
 
5.3%
산 10
 
3.1%
창 9
 
2.8%
천 9
 
2.8%
포 9
 
2.8%
주 9
 
2.8%
안 8
 
2.5%
평 8
 
2.5%
Other values (72) 152
47.1%
Common
ValueCountFrequency (%)
7
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 323
97.9%
ASCII 7
 
2.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
군 51
 
15.8%
시 41
 
12.7%
구 17
 
5.3%
산 10
 
3.1%
창 9
 
2.8%
천 9
 
2.8%
포 9
 
2.8%
주 9
 
2.8%
안 8
 
2.5%
평 8
 
2.5%
Other values (72) 152
47.1%
ASCII
ValueCountFrequency (%)
7
100.0%

bemd_nm
Text

Distinct83
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:58:58.332680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.04
Min length2

Characters and Unicode

Total characters304
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

Unique70 ?
Unique (%)70.0%

Sample

1st row상림동
2nd row삼숭동
3rd row삼산면
4th row악양면
5th row수동
ValueCountFrequency (%)
대관령면 6
 
6.0%
악양면 2
 
2.0%
가은읍 2
 
2.0%
삼동면 2
 
2.0%
북면 2
 
2.0%
기장읍 2
 
2.0%
한산면 2
 
2.0%
용주면 2
 
2.0%
남원읍 2
 
2.0%
부리면 2
 
2.0%
Other values (73) 76
76.0%
2023-12-10T18:58:58.983141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
면 62
20.4%
동 29
 
9.5%
읍 13
 
4.3%
산 12
 
3.9%
대 9
 
3.0%
북 8
 
2.6%
남 7
 
2.3%
령 6
 
2.0%
관 6
 
2.0%
삼 6
 
2.0%
Other values (84) 146
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 304
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 62
20.4%
동 29
 
9.5%
읍 13
 
4.3%
산 12
 
3.9%
대 9
 
3.0%
북 8
 
2.6%
남 7
 
2.3%
령 6
 
2.0%
관 6
 
2.0%
삼 6
 
2.0%
Other values (84) 146
48.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 304
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 62
20.4%
동 29
 
9.5%
읍 13
 
4.3%
산 12
 
3.9%
대 9
 
3.0%
북 8
 
2.6%
남 7
 
2.3%
령 6
 
2.0%
관 6
 
2.0%
삼 6
 
2.0%
Other values (84) 146
48.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 304
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
면 62
20.4%
동 29
 
9.5%
읍 13
 
4.3%
산 12
 
3.9%
대 9
 
3.0%
북 8
 
2.6%
남 7
 
2.3%
령 6
 
2.0%
관 6
 
2.0%
삼 6
 
2.0%
Other values (84) 146
48.0%

ri_nm
Text

MISSING 

Distinct63
Distinct (%)84.0%
Missing25
Missing (%)25.0%
Memory size932.0 B
2023-12-10T18:58:59.446135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0266667
Min length2

Characters and Unicode

Total characters227
Distinct characters82
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

Unique53 ?
Unique (%)70.7%

Sample

1st row석모리
2nd row봉대리
3rd row시도리
4th row산정리
5th row도경리
ValueCountFrequency (%)
횡계리 4
 
5.3%
물건리 2
 
2.7%
죽성리 2
 
2.7%
가호리 2
 
2.7%
왕능리 2
 
2.7%
위미리 2
 
2.7%
차항리 2
 
2.7%
시도리 2
 
2.7%
산정리 2
 
2.7%
수통리 2
 
2.7%
Other values (53) 53
70.7%
2023-12-10T18:59:00.298200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 75
33.0%
산 7
 
3.1%
정 4
 
1.8%
도 4
 
1.8%
곡 4
 
1.8%
상 4
 
1.8%
계 4
 
1.8%
동 4
 
1.8%
횡 4
 
1.8%
성 4
 
1.8%
Other values (72) 113
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 227
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 75
33.0%
산 7
 
3.1%
정 4
 
1.8%
도 4
 
1.8%
곡 4
 
1.8%
상 4
 
1.8%
계 4
 
1.8%
동 4
 
1.8%
횡 4
 
1.8%
성 4
 
1.8%
Other values (72) 113
49.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 227
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 75
33.0%
산 7
 
3.1%
정 4
 
1.8%
도 4
 
1.8%
곡 4
 
1.8%
상 4
 
1.8%
계 4
 
1.8%
동 4
 
1.8%
횡 4
 
1.8%
성 4
 
1.8%
Other values (72) 113
49.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 227
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 75
33.0%
산 7
 
3.1%
정 4
 
1.8%
도 4
 
1.8%
곡 4
 
1.8%
상 4
 
1.8%
계 4
 
1.8%
동 4
 
1.8%
횡 4
 
1.8%
성 4
 
1.8%
Other values (72) 113
49.8%

beonji
Text

Distinct94
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:59:00.752059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.31
Min length2

Characters and Unicode

Total characters431
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

Unique90 ?
Unique (%)90.0%

Sample

1st row540
2nd row207-12
3rd row산249-3
4th row770-1
5th row88-2
ValueCountFrequency (%)
704-5 4
 
4.0%
1-1 2
 
2.0%
135 2
 
2.0%
256-5 2
 
2.0%
66 1
 
1.0%
1004-3 1
 
1.0%
719-70 1
 
1.0%
산46-1 1
 
1.0%
산133-1 1
 
1.0%
1828 1
 
1.0%
Other values (84) 84
84.0%
2023-12-10T18:59:01.443567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 74
17.2%
- 61
14.2%
4 41
9.5%
2 40
9.3%
5 38
8.8%
7 33
7.7%
3 29
 
6.7%
8 28
 
6.5%
6 26
 
6.0%
0 22
 
5.1%
Other values (2) 39
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 349
81.0%
Dash Punctuation 61
 
14.2%
Other Letter 21
 
4.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 74
21.2%
4 41
11.7%
2 40
11.5%
5 38
10.9%
7 33
9.5%
3 29
 
8.3%
8 28
 
8.0%
6 26
 
7.4%
0 22
 
6.3%
9 18
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%
Other Letter
ValueCountFrequency (%)
산 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 410
95.1%
Hangul 21
 
4.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 74
18.0%
- 61
14.9%
4 41
10.0%
2 40
9.8%
5 38
9.3%
7 33
8.0%
3 29
 
7.1%
8 28
 
6.8%
6 26
 
6.3%
0 22
 
5.4%
Hangul
ValueCountFrequency (%)
산 21
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 410
95.1%
Hangul 21
 
4.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 74
18.0%
- 61
14.9%
4 41
10.0%
2 40
9.8%
5 38
9.3%
7 33
8.0%
3 29
 
7.1%
8 28
 
6.8%
6 26
 
6.3%
0 22
 
5.4%
Hangul
ValueCountFrequency (%)
산 21
100.0%

badm_cd
Real number (ℝ)

Distinct88
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.2041648 × 109
Minimum1.1110119 × 109
Maximum5.013032 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:59:01.764397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110119 × 109
5-th percentile2.5447103 × 109
Q14.2037883 × 109
median4.4470292 × 109
Q34.7130118 × 109
95-th percentile4.895245 × 109
Maximum5.013032 × 109
Range3.9020201 × 109
Interquartile range (IQR)5.0922352 × 108

Descriptive statistics

Standard deviation8.8813642 × 108
Coefficient of variation (CV)0.21125157
Kurtosis5.2833064
Mean4.2041648 × 109
Median Absolute Deviation (MAD)2.6548909 × 108
Skewness-2.3480464
Sum4.2041648 × 1011
Variance7.887863 × 1017
MonotonicityNot monotonic
2023-12-10T18:59:02.074860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4276038024 4
 
4.0%
4276038023 2
 
2.0%
4889046037 2
 
2.0%
4471033030 2
 
2.0%
4884033026 2
 
2.0%
2671025024 2
 
2.0%
4728025321 2
 
2.0%
5013025327 2
 
2.0%
4165039023 2
 
2.0%
2872031021 2
 
2.0%
Other values (78) 78
78.0%
ValueCountFrequency (%)
1111011900 1
1.0%
1111014600 1
1.0%
1117012900 1
1.0%
1144010100 1
1.0%
1171010100 1
1.0%
2617010300 1
1.0%
2671025024 2
2.0%
2720010300 1
1.0%
2871041021 1
1.0%
2872031021 2
2.0%
ValueCountFrequency (%)
5013032024 1
1.0%
5013031028 1
1.0%
5013025924 1
1.0%
5013025327 2
2.0%
4889046037 2
2.0%
4886031026 1
1.0%
4885032034 1
1.0%
4885032033 1
1.0%
4884033026 2
2.0%
4833034021 1
1.0%

hadm_cd
Real number (ℝ)

Distinct85
Distinct (%)85.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.2041767 × 109
Minimum1.11106 × 109
Maximum5.013032 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:59:02.401003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.11106 × 109
5-th percentile2.5447647 × 109
Q14.2037882 × 109
median4.4470292 × 109
Q34.7130388 × 109
95-th percentile4.895245 × 109
Maximum5.013032 × 109
Range3.901972 × 109
Interquartile range (IQR)5.092505 × 108

Descriptive statistics

Standard deviation8.881264 × 108
Coefficient of variation (CV)0.21124859
Kurtosis5.2832849
Mean4.2041767 × 109
Median Absolute Deviation (MAD)2.6549925 × 108
Skewness-2.3480465
Sum4.2041767 × 1011
Variance7.887685 × 1017
MonotonicityNot monotonic
2023-12-10T18:59:02.704106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4276038000 6
 
6.0%
4884033000 2
 
2.0%
4165039000 2
 
2.0%
4471033000 2
 
2.0%
2671025000 2
 
2.0%
4728025300 2
 
2.0%
4889046000 2
 
2.0%
2872031000 2
 
2.0%
4885032000 2
 
2.0%
4793031000 2
 
2.0%
Other values (75) 76
76.0%
ValueCountFrequency (%)
1111060000 1
1.0%
1111061500 1
1.0%
1117064000 1
1.0%
1144056500 1
1.0%
1171068000 1
1.0%
2617064500 1
1.0%
2671025000 2
2.0%
2720058600 1
1.0%
2871041000 1
1.0%
2872031000 2
2.0%
ValueCountFrequency (%)
5013032000 1
1.0%
5013031000 1
1.0%
5013025900 1
1.0%
5013025300 2
2.0%
4889046000 2
2.0%
4886031000 1
1.0%
4885032000 2
2.0%
4884033000 2
2.0%
4833034000 1
1.0%
4822036000 1
1.0%

rd_cd
Real number (ℝ)

MISSING 

Distinct59
Distinct (%)92.2%
Missing36
Missing (%)36.0%
Infinite0
Infinite (%)0.0%
Mean4.2008788 × 1011
Minimum1.111031 × 1011
Maximum5.0130335 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:59:02.991808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111031 × 1011
5-th percentile2.6251419 × 1011
Q14.2000445 × 1011
median4.3455824 × 1011
Q34.6960686 × 1011
95-th percentile4.8890335 × 1011
Maximum5.0130335 × 1011
Range3.9020025 × 1011
Interquartile range (IQR)4.9602404 × 1010

Descriptive statistics

Standard deviation8.7852831 × 1010
Coefficient of variation (CV)0.20912965
Kurtosis5.5070953
Mean4.2008788 × 1011
Median Absolute Deviation (MAD)2.5196403 × 1010
Skewness-2.3682075
Sum2.6885624 × 1013
Variance7.71812 × 1021
MonotonicityNot monotonic
2023-12-10T18:59:03.249925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
427604484055 4
 
4.0%
267104220086 2
 
2.0%
488903348035 2
 
2.0%
471113303014 1
 
1.0%
414614433546 1
 
1.0%
411153175040 1
 
1.0%
117103123023 1
 
1.0%
468004676465 1
 
1.0%
422304472307 1
 
1.0%
467803290003 1
 
1.0%
Other values (49) 49
49.0%
(Missing) 36
36.0%
ValueCountFrequency (%)
111103100005 1
1.0%
111104100106 1
1.0%
117103123023 1
1.0%
261704181385 1
1.0%
267104220086 2
2.0%
272003141013 1
1.0%
287204274122 1
1.0%
411153175040 1
1.0%
412853193007 1
1.0%
413104388131 1
1.0%
ValueCountFrequency (%)
501303350236 1
1.0%
501303350153 1
1.0%
501303349241 1
1.0%
488903348035 2
2.0%
488604835413 1
1.0%
488504832495 1
1.0%
488403343011 1
1.0%
483304814808 1
1.0%
477304745109 1
1.0%
472804736524 1
1.0%

rd_nm
Text

MISSING 

Distinct59
Distinct (%)92.2%
Missing36
Missing (%)36.0%
Memory size932.0 B
2023-12-10T18:59:03.714508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length4.25
Min length3

Characters and Unicode

Total characters272
Distinct characters120
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

Unique56 ?
Unique (%)87.5%

Sample

1st row원상림길
2nd row만송로
3rd row수암로
4th row시도로86번길
5th row도경1길
ValueCountFrequency (%)
꽃밭양지길 4
 
6.2%
합천호수로 2
 
3.1%
두호길 2
 
3.1%
오대산로 1
 
1.6%
용천드라마길 1
 
1.6%
정공단로11번가길 1
 
1.6%
엑스포로 1
 
1.6%
샛말1길 1
 
1.6%
화도길 1
 
1.6%
녹차로 1
 
1.6%
Other values (49) 49
76.6%
2023-12-10T18:59:04.417456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
길 35
 
12.9%
로 35
 
12.9%
지 7
 
2.6%
천 6
 
2.2%
도 6
 
2.2%
1 6
 
2.2%
호 5
 
1.8%
수 5
 
1.8%
번 4
 
1.5%
2 4
 
1.5%
Other values (110) 159
58.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 254
93.4%
Decimal Number 18
 
6.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 35
 
13.8%
로 35
 
13.8%
지 7
 
2.8%
천 6
 
2.4%
도 6
 
2.4%
호 5
 
2.0%
수 5
 
2.0%
번 4
 
1.6%
밭 4
 
1.6%
꽃 4
 
1.6%
Other values (101) 143
56.3%
Decimal Number
ValueCountFrequency (%)
1 6
33.3%
2 4
22.2%
8 2
 
11.1%
7 1
 
5.6%
9 1
 
5.6%
3 1
 
5.6%
0 1
 
5.6%
4 1
 
5.6%
6 1
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 254
93.4%
Common 18
 
6.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 35
 
13.8%
로 35
 
13.8%
지 7
 
2.8%
천 6
 
2.4%
도 6
 
2.4%
호 5
 
2.0%
수 5
 
2.0%
번 4
 
1.6%
밭 4
 
1.6%
꽃 4
 
1.6%
Other values (101) 143
56.3%
Common
ValueCountFrequency (%)
1 6
33.3%
2 4
22.2%
8 2
 
11.1%
7 1
 
5.6%
9 1
 
5.6%
3 1
 
5.6%
0 1
 
5.6%
4 1
 
5.6%
6 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 254
93.4%
ASCII 18
 
6.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
길 35
 
13.8%
로 35
 
13.8%
지 7
 
2.8%
천 6
 
2.4%
도 6
 
2.4%
호 5
 
2.0%
수 5
 
2.0%
번 4
 
1.6%
밭 4
 
1.6%
꽃 4
 
1.6%
Other values (101) 143
56.3%
ASCII
ValueCountFrequency (%)
1 6
33.3%
2 4
22.2%
8 2
 
11.1%
7 1
 
5.6%
9 1
 
5.6%
3 1
 
5.6%
0 1
 
5.6%
4 1
 
5.6%
6 1
 
5.6%

bld_num
Text

MISSING 

Distinct57
Distinct (%)89.1%
Missing36
Missing (%)36.0%
Memory size932.0 B
2023-12-10T18:59:04.823911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.234375
Min length1

Characters and Unicode

Total characters207
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

Unique52 ?
Unique (%)81.2%

Sample

1st row125-14
2nd row394-104
3rd row43
4th row404
5th row18
ValueCountFrequency (%)
708-9 4
 
6.2%
29-43 2
 
3.1%
757 2
 
3.1%
90 2
 
3.1%
23 2
 
3.1%
37 1
 
1.6%
332-13 1
 
1.6%
334 1
 
1.6%
1037 1
 
1.6%
68 1
 
1.6%
Other values (47) 47
73.4%
2023-12-10T18:59:05.447400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 34
16.4%
0 22
10.6%
2 22
10.6%
3 22
10.6%
7 21
10.1%
4 20
9.7%
9 18
8.7%
- 16
7.7%
5 13
 
6.3%
8 12
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 191
92.3%
Dash Punctuation 16
 
7.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 34
17.8%
0 22
11.5%
2 22
11.5%
3 22
11.5%
7 21
11.0%
4 20
10.5%
9 18
9.4%
5 13
 
6.8%
8 12
 
6.3%
6 7
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 207
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 34
16.4%
0 22
10.6%
2 22
10.6%
3 22
10.6%
7 21
10.1%
4 20
9.7%
9 18
8.7%
- 16
7.7%
5 13
 
6.3%
8 12
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 207
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 34
16.4%
0 22
10.6%
2 22
10.6%
3 22
10.6%
7 21
10.1%
4 20
9.7%
9 18
8.7%
- 16
7.7%
5 13
 
6.3%
8 12
 
5.8%

x
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.74645
Minimum126.15438
Maximum129.47236
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:59:05.785827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.15438
5-th percentile126.3276
Q1126.95883
median127.53847
Q3128.65291
95-th percentile129.27835
Maximum129.47236
Range3.3179805
Interquartile range (IQR)1.6940772

Descriptive statistics

Standard deviation0.98660844
Coefficient of variation (CV)0.0077231772
Kurtosis-1.2512999
Mean127.74645
Median Absolute Deviation (MAD)0.8862892
Skewness0.17461082
Sum12774.645
Variance0.97339622
MonotonicityNot monotonic
2023-12-10T18:59:06.108450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.075101851519 1
 
1.0%
127.079534640779 1
 
1.0%
128.523764412099 1
 
1.0%
127.064016302549 1
 
1.0%
126.695676062096 1
 
1.0%
129.29664779621 1
 
1.0%
128.460172103409 1
 
1.0%
127.479306344377 1
 
1.0%
126.161549952053 1
 
1.0%
127.08924499492 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
126.154383035644 1
1.0%
126.161549952053 1
1.0%
126.184783197346 1
1.0%
126.268500513621 1
1.0%
126.298109950731 1
1.0%
126.329148616341 1
1.0%
126.380342414438 1
1.0%
126.393685648081 1
1.0%
126.431825248566 1
1.0%
126.439371941636 1
1.0%
ValueCountFrequency (%)
129.472363545597 1
1.0%
129.389175756703 1
1.0%
129.373592445725 1
1.0%
129.356528776877 1
1.0%
129.29664779621 1
1.0%
129.277383365147 1
1.0%
129.248585472804 1
1.0%
129.248564589317 1
1.0%
129.226416937444 1
1.0%
129.19937071115 1
1.0%

y
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.412991
Minimum33.269418
Maximum38.485517
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:59:06.423320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.269418
5-th percentile34.134561
Q135.495131
median36.654213
Q337.544371
95-th percentile38.07201
Maximum38.485517
Range5.2160991
Interquartile range (IQR)2.04924

Descriptive statistics

Standard deviation1.2944769
Coefficient of variation (CV)0.035549865
Kurtosis-0.41896477
Mean36.412991
Median Absolute Deviation (MAD)0.93002261
Skewness-0.61796392
Sum3641.2991
Variance1.6756705
MonotonicityNot monotonic
2023-12-10T18:59:06.925256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.8147163300201 1
 
1.0%
36.0234847136081 1
 
1.0%
38.2076611705724 1
 
1.0%
37.1791820391832 1
 
1.0%
35.3815973395383 1
 
1.0%
35.8337729653332 1
 
1.0%
34.7226877823878 1
 
1.0%
38.1944442163634 1
 
1.0%
34.9475224570832 1
 
1.0%
34.7363609230588 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
33.2694181058355 1
1.0%
33.3206462205216 1
1.0%
33.3287485602214 1
1.0%
33.3923182020137 1
1.0%
33.4258356012807 1
1.0%
34.1718627559416 1
1.0%
34.3432646707616 1
1.0%
34.4666864834867 1
1.0%
34.7226877823878 1
1.0%
34.7363609230588 1
1.0%
ValueCountFrequency (%)
38.4855171674824 1
1.0%
38.2076611705724 1
1.0%
38.2028920317448 1
1.0%
38.1944442163634 1
1.0%
38.0751100938262 1
1.0%
38.0718468078589 1
1.0%
37.7953994839871 1
1.0%
37.791519059448 1
1.0%
37.7713324119362 1
1.0%
37.747645273089 1
1.0%

grid_cd
Text

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:59:07.668734image/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 row다마616576
2nd row다사649769
3rd row나사940676
4th row라라174841
5th row다바994498
ValueCountFrequency (%)
마사079727 2
 
2.0%
마바579992 1
 
1.0%
다마621808 1
 
1.0%
다사612090 1
 
1.0%
다마269098 1
 
1.0%
마마622611 1
 
1.0%
라라879368 1
 
1.0%
다아981215 1
 
1.0%
나라777622 1
 
1.0%
다라623380 1
 
1.0%
Other values (89) 89
89.0%
2023-12-10T18:59:09.007678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 73
 
9.1%
8 67
 
8.4%
4 66
 
8.2%
2 63
 
7.9%
6 61
 
7.6%
0 61
 
7.6%
9 61
 
7.6%
1 53
 
6.6%
7 51
 
6.4%
마 46
 
5.8%
Other values (7) 198
24.8%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 73
12.2%
8 67
11.2%
4 66
11.0%
2 63
10.5%
6 61
10.2%
0 61
10.2%
9 61
10.2%
1 53
8.8%
7 51
8.5%
3 44
7.3%
Other Letter
ValueCountFrequency (%)
마 46
23.0%
라 42
21.0%
다 42
21.0%
사 36
18.0%
바 16
 
8.0%
나 12
 
6.0%
아 6
 
3.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
5 73
12.2%
8 67
11.2%
4 66
11.0%
2 63
10.5%
6 61
10.2%
0 61
10.2%
9 61
10.2%
1 53
8.8%
7 51
8.5%
3 44
7.3%
Hangul
ValueCountFrequency (%)
마 46
23.0%
라 42
21.0%
다 42
21.0%
사 36
18.0%
바 16
 
8.0%
나 12
 
6.0%
아 6
 
3.0%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 73
12.2%
8 67
11.2%
4 66
11.0%
2 63
10.5%
6 61
10.2%
0 61
10.2%
9 61
10.2%
1 53
8.8%
7 51
8.5%
3 44
7.3%
Hangul
ValueCountFrequency (%)
마 46
23.0%
라 42
21.0%
다 42
21.0%
사 36
18.0%
바 16
 
8.0%
나 12
 
6.0%
아 6
 
3.0%

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

2023-12-10T18:59:09.329736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:59:09.602769image/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

2023-12-10T18:59:09.811784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:59:10.067258image/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_502_LLR_MOVIE_DRMA_PLCE_2021
100 

Length

Max length31
Median length31
Mean length31
Min length31

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKC_502_LLR_MOVIE_DRMA_PLCE_2021
2nd rowKC_502_LLR_MOVIE_DRMA_PLCE_2021
3rd rowKC_502_LLR_MOVIE_DRMA_PLCE_2021
4th rowKC_502_LLR_MOVIE_DRMA_PLCE_2021
5th rowKC_502_LLR_MOVIE_DRMA_PLCE_2021

Common Values

ValueCountFrequency (%)
KC_502_LLR_MOVIE_DRMA_PLCE_2021 100
100.0%

Length

2023-12-10T18:59:10.352757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:59:10.635179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kc_502_llr_movie_drma_plce_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

2023-12-10T18:59:10.969642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:59:11.164917image/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
0KCMPLPO21N000000001장소관광지7461518전주영화종합촬영소<NA><NA>60515드라마/영화촬영지4511114500105400000전라북도전주시 완산구상림동<NA>54045111145004511171400451114598286원상림길125-14127.07510235.814716다마61657620210917100801KTKC_502_LLR_MOVIE_DRMA_PLCE_202120210917
1KCMPLPO21N000000184장소관광지10252424MBC문화동산<NA><NA>60515드라마/영화촬영지4163010800102070012경기도양주시삼숭동<NA>207-1241630108004163052000416303212011만송로394-104127.10151937.791519다사64976920210917100801KTKC_502_LLR_MOVIE_DRMA_PLCE_202120210917
2KCMPLPO21N000000003장소관광지10252338시월애촬영지<NA><NA>60515드라마/영화촬영지2871041021202490003인천광역시강화군삼산면석모리산249-328710410212871041000<NA><NA><NA>126.2981137.702012나사94067620210917100801KTKC_502_LLR_MOVIE_DRMA_PLCE_202120210917
3KCMPLPO21N000000004장소관광지10252391청춘촬영지<NA><NA>60515드라마/영화촬영지4885032033107700001경상남도하동군악양면봉대리770-148850320334885032000<NA><NA><NA>127.6916235.152143라라17484120210917100801KTKC_502_LLR_MOVIE_DRMA_PLCE_202120210917
4KCMPLPO21N000000005장소관광지17765143드라마영광의재인촬영지<NA><NA>60515드라마/영화촬영지4311111200100880002충청북도청주시 상당구수동<NA>88-243111112004311152500431113236034수암로43127.49416436.646147다바99449820210917100801KTKC_502_LLR_MOVIE_DRMA_PLCE_202120210917
5KCMPLPO21N000000006장소관광지10252337슬픈연가세트장<NA><NA>60515드라마/영화촬영지2872031021100010011인천광역시옹진군북도면시도리1-1128720310212872031000287204274122시도로86번길404126.43937237.545179다사06350020210917100801KTKC_502_LLR_MOVIE_DRMA_PLCE_202120210917
6KCMPLPO21N000000007장소관광지13915741신데렐라언니촬영지<NA><NA>60515드라마/영화촬영지4165039023102910004경기도포천시영북면산정리291-441650390234165039000<NA><NA><NA>127.32087138.07511다아84208320210917100801KTKC_502_LLR_MOVIE_DRMA_PLCE_202120210917
7KCMPLPO21N000000185장소관광지16497655레드카펫촬영장<NA><NA>60515드라마/영화촬영지4773037046108450000경상북도의성군금성면도경리84547730370464773037000477304745109도경1길18128.64288136.240104마바02605320210917100801KTKC_502_LLR_MOVIE_DRMA_PLCE_202120210917
8KCMPLPO21N000000009장소관광지21713053낭만닥터김사부촬영지<NA><NA>60515드라마/영화촬영지4165039023102040001경기도포천시영북면산정리204-141650390234165039000416503213016산정호수로771127.32341238.071847다아84507920210917100801KTKC_502_LLR_MOVIE_DRMA_PLCE_202120210917
9KCMPLPO21N000000010장소관광지10252308봄날은간다촬영지<NA><NA>60515드라마/영화촬영지4277037021107700000강원도정선군여량면여량리77042770370214277037000427704487244아우라지길78128.7227837.477246마사08142720210917100801KTKC_502_LLR_MOVIE_DRMA_PLCE_202120210917
idlclasmlsfcid_poipoi_nmbranch_nmsub_nmmcate_cdmcate_nmpnusido_nmsgg_nmbemd_nmri_nmbeonjibadm_cdhadm_cdrd_cdrd_nmbld_numxygrid_cdlst_updt_dtdata_orgnfile_namebase_ymd
90KCMPLPO21N000000091장소관광지19868757겨울연가촬영지<NA><NA>60515드라마/영화촬영지4211040030101970000강원도춘천시남산면방하리19742110400304211040000421104454832남이섬길1127.52674337.795399라사02377320210917100801KTKC_502_LLR_MOVIE_DRMA_PLCE_202120210917
91KCMPLPO21N000000092장소관광지4898815한국민속촌다모드라마촬영지<NA><NA>60515드라마/영화촬영지4146310500100350000경기도용인시 기흥구보라동<NA>3541463105004146353500414633204030민속촌로90127.12285637.260654다사66518020210917100801KTKC_502_LLR_MOVIE_DRMA_PLCE_202120210917
92KCMPLPO21N000000093장소관광지8012148가을동화촬영장소<NA><NA>60515드라마/영화촬영지4276038024107040005강원도평창군대관령면횡계리704-542760380244276038000427604484055꽃밭양지길708-9128.72178737.740712마사07671920210917100801KTKC_502_LLR_MOVIE_DRMA_PLCE_202120210917
93KCMPLPO21N000000094장소관광지10316967번지점프를하다촬영장<NA><NA>60515드라마/영화촬영지4673034024200200001전라남도구례군마산면황전리산20-146730340244673037000467304664229연기암길332-13127.52797635.293452라라02599720210917100801KTKC_502_LLR_MOVIE_DRMA_PLCE_202120210917
94KCMPLPO21N000000095장소관광지7218849횡성테마랜드<NA><NA>60515드라마/영화촬영지4273031021105580001강원도횡성군우천면두곡리558-142730310214273025000<NA><NA><NA>128.03763337.476993라사47542120210917100801KTKC_502_LLR_MOVIE_DRMA_PLCE_202120210917
95KCMPLPO21N000000096장소관광지10252309봄날은간다촬영지<NA><NA>60515드라마/영화촬영지4223031021201500000강원도삼척시근덕면상맹방리산15042230310214223031000<NA><NA><NA>129.19937137.397097마사50434420210917100801KTKC_502_LLR_MOVIE_DRMA_PLCE_202120210917
96KCMPLPO21N000000097장소관광지10252350여름향기촬영지<NA><NA>60515드라마/영화촬영지4276036027200010000강원도평창군진부면동산리산142760360274276036000427603228020오대산로905-3128.59564737.771332라사96475120210917100801KTKC_502_LLR_MOVIE_DRMA_PLCE_202120210917
97KCMPLPO21N000000098장소관광지10252399친구촬영지<NA><NA>60515드라마/영화촬영지2617010300107770002부산광역시동구좌천동<NA>777-226170103002617064500261704181385정공단로11번가길21-2129.05207935.134085마라41483220210917100801KTKC_502_LLR_MOVIE_DRMA_PLCE_202120210917
98KCMPLPO21N000000099장소관광지16497663해변의여인촬영지<NA><NA>60515드라마/영화촬영지4482535025114140003충청남도태안군원북면신두리1414-344825350254482535000448254849141신두해변길149126.18478336.83729나바82771820210917100801KTKC_502_LLR_MOVIE_DRMA_PLCE_202120210917
99KCMPLPO21N000000100장소관광지16502352영화외출촬영지<NA><NA>60515드라마/영화촬영지4223010700100140000강원도삼척시갈천동<NA>1442230107004223053000422304472329테마타운길39129.16978337.467092마사47642120210917100801KTKC_502_LLR_MOVIE_DRMA_PLCE_202120210917