Overview

Dataset statistics

Number of variables27
Number of observations100
Missing cells400
Missing cells (%)14.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.4 KiB
Average record size in memory229.3 B

Variable types

Text9
Categorical10
Numeric6
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
mcate_cd is highly imbalanced (84.9%)Imbalance
mcate_nm is highly imbalanced (84.9%)Imbalance
rd_cd is highly imbalanced (84.4%)Imbalance
branch_nm has 100 (100.0%) missing valuesMissing
sub_nm has 100 (100.0%) missing valuesMissing
ri_nm has 8 (8.0%) missing valuesMissing
rd_nm has 95 (95.0%) missing valuesMissing
bld_num has 95 (95.0%) 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 10:09:59.060770
Analysis finished2023-12-10 10:09:59.830578
Duration0.77 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
2023-12-10T19:10:00.074778image/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 rowKCLANPO21N000000001
2nd rowKCLANPO21N000038438
3rd rowKCLANPO21N000000003
4th rowKCLANPO21N000000004
5th rowKCLANPO21N000000005
ValueCountFrequency (%)
kclanpo21n000000001 1
 
1.0%
kclanpo21n000000063 1
 
1.0%
kclanpo21n000000074 1
 
1.0%
kclanpo21n000000073 1
 
1.0%
kclanpo21n000000072 1
 
1.0%
kclanpo21n000000071 1
 
1.0%
kclanpo21n000000070 1
 
1.0%
kclanpo21n000000069 1
 
1.0%
kclanpo21n000000068 1
 
1.0%
kclanpo21n000000067 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T19:10:00.711902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 709
37.3%
N 200
 
10.5%
1 121
 
6.4%
2 118
 
6.2%
O 100
 
5.3%
C 100
 
5.3%
K 100
 
5.3%
P 100
 
5.3%
A 100
 
5.3%
L 100
 
5.3%
Other values (7) 152
 
8.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 709
64.5%
1 121
 
11.0%
2 118
 
10.7%
3 24
 
2.2%
4 24
 
2.2%
8 23
 
2.1%
9 21
 
1.9%
5 20
 
1.8%
6 20
 
1.8%
7 20
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
N 200
25.0%
O 100
12.5%
C 100
12.5%
K 100
12.5%
P 100
12.5%
A 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 (%)
0 709
64.5%
1 121
 
11.0%
2 118
 
10.7%
3 24
 
2.2%
4 24
 
2.2%
8 23
 
2.1%
9 21
 
1.9%
5 20
 
1.8%
6 20
 
1.8%
7 20
 
1.8%
Latin
ValueCountFrequency (%)
N 200
25.0%
O 100
12.5%
C 100
12.5%
K 100
12.5%
P 100
12.5%
A 100
12.5%
L 100
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 709
37.3%
N 200
 
10.5%
1 121
 
6.4%
2 118
 
6.2%
O 100
 
5.3%
C 100
 
5.3%
K 100
 
5.3%
P 100
 
5.3%
A 100
 
5.3%
L 100
 
5.3%
Other values (7) 152
 
8.0%

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

2023-12-10T19:10:00.946186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:10:01.069384image/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

2023-12-10T19:10:01.247409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:10:01.414488image/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%
Mean1454670.5
Minimum549380
Maximum22146369
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:10:01.653739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum549380
5-th percentile809629.65
Q1812960.25
median818626
Q3824097.75
95-th percentile829883.25
Maximum22146369
Range21596989
Interquartile range (IQR)11137.5

Descriptive statistics

Standard deviation3649840
Coefficient of variation (CV)2.5090493
Kurtosis29.894477
Mean1454670.5
Median Absolute Deviation (MAD)5739
Skewness5.5941631
Sum1.4546705 × 108
Variance1.3321332 × 1013
MonotonicityNot monotonic
2023-12-10T19:10:01.938074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
549380 1
 
1.0%
820807 1
 
1.0%
823518 1
 
1.0%
823442 1
 
1.0%
823050 1
 
1.0%
822888 1
 
1.0%
822257 1
 
1.0%
822153 1
 
1.0%
822129 1
 
1.0%
822048 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
549380 1
1.0%
808705 1
1.0%
808746 1
1.0%
809458 1
1.0%
809471 1
1.0%
809638 1
1.0%
809807 1
1.0%
809863 1
1.0%
810254 1
1.0%
810409 1
1.0%
ValueCountFrequency (%)
22146369 1
1.0%
22113578 1
1.0%
22051690 1
1.0%
830580 1
1.0%
830325 1
1.0%
829860 1
1.0%
829598 1
1.0%
829406 1
1.0%
829360 1
1.0%
829212 1
1.0%

poi_nm
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:10:02.388886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.77
Min length2

Characters and Unicode

Total characters477
Distinct characters124
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row구절리역(폐역)
2nd row토리딸기팜
3rd row대암소류지
4th row대양소류지
5th row대장저수지
ValueCountFrequency (%)
구절리역(폐역 1
 
1.0%
작은토골못 1
 
1.0%
화산저수지 1
 
1.0%
외동저수지 1
 
1.0%
사암지 1
 
1.0%
도천소류지 1
 
1.0%
도마수원지 1
 
1.0%
오전리저수지 1
 
1.0%
죽죽소류지 1
 
1.0%
저명곡저수지 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T19:10:03.096745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 77
 
16.1%
소 45
 
9.4%
류 44
 
9.2%
수 31
 
6.5%
저 27
 
5.7%
못 22
 
4.6%
골 15
 
3.1%
대 7
 
1.5%
산 7
 
1.5%
곡 6
 
1.3%
Other values (114) 196
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 472
99.0%
Decimal Number 3
 
0.6%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 77
16.3%
소 45
 
9.5%
류 44
 
9.3%
수 31
 
6.6%
저 27
 
5.7%
못 22
 
4.7%
골 15
 
3.2%
대 7
 
1.5%
산 7
 
1.5%
곡 6
 
1.3%
Other values (110) 191
40.5%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
1 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 472
99.0%
Common 5
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 77
16.3%
소 45
 
9.5%
류 44
 
9.3%
수 31
 
6.6%
저 27
 
5.7%
못 22
 
4.7%
골 15
 
3.2%
대 7
 
1.5%
산 7
 
1.5%
곡 6
 
1.3%
Other values (110) 191
40.5%
Common
ValueCountFrequency (%)
2 2
40.0%
) 1
20.0%
( 1
20.0%
1 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 472
99.0%
ASCII 5
 
1.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 77
16.3%
소 45
 
9.5%
류 44
 
9.3%
수 31
 
6.6%
저 27
 
5.7%
못 22
 
4.7%
골 15
 
3.2%
대 7
 
1.5%
산 7
 
1.5%
곡 6
 
1.3%
Other values (110) 191
40.5%
ASCII
ValueCountFrequency (%)
2 2
40.0%
) 1
20.0%
( 1
20.0%
1 1
20.0%

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
Categorical

IMBALANCE 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
110215
96 
60516
 
2
60513
 
1
60517
 
1

Length

Max length6
Median length6
Mean length5.96
Min length5

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row60513
2nd row60516
3rd row110215
4th row110215
5th row110215

Common Values

ValueCountFrequency (%)
110215 96
96.0%
60516 2
 
2.0%
60513 1
 
1.0%
60517 1
 
1.0%

Length

2023-12-10T19:10:03.384589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:10:03.556744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
110215 96
96.0%
60516 2
 
2.0%
60513 1
 
1.0%
60517 1
 
1.0%

mcate_nm
Categorical

IMBALANCE 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
지역호수/저수지
96 
관광농원/허브마을
 
2
일반관광지
 
1
먹거리/패션거리
 
1

Length

Max length9
Median length8
Mean length7.99
Min length5

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row일반관광지
2nd row관광농원/허브마을
3rd row지역호수/저수지
4th row지역호수/저수지
5th row지역호수/저수지

Common Values

ValueCountFrequency (%)
지역호수/저수지 96
96.0%
관광농원/허브마을 2
 
2.0%
일반관광지 1
 
1.0%
먹거리/패션거리 1
 
1.0%

Length

2023-12-10T19:10:03.765979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:10:04.012628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지역호수/저수지 96
96.0%
관광농원/허브마을 2
 
2.0%
일반관광지 1
 
1.0%
먹거리/패션거리 1
 
1.0%

pnu
Real number (ℝ)

Distinct99
Distinct (%)100.0%
Missing1
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean4.615413 × 1018
Minimum3.1200118 × 1018
Maximum4.889046 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:10:04.268267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.1200118 × 1018
5-th percentile4.0395259 × 1018
Q14.5780345 × 1018
median4.7280103 × 1018
Q34.878034 × 1018
95-th percentile4.8881259 × 1018
Maximum4.889046 × 1018
Range1.7690342 × 1018
Interquartile range (IQR)2.999995 × 1017

Descriptive statistics

Standard deviation3.9985331 × 1017
Coefficient of variation (CV)0.086634352
Kurtosis6.6492778
Mean4.615413 × 1018
Median Absolute Deviation (MAD)1.5097527 × 1017
Skewness-2.5391708
Sum-4.2427191 × 1018
Variance1.5988267 × 1035
MonotonicityNot monotonic
2023-12-10T19:10:04.515033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4277037023102900224 1
 
1.0%
4715011900117380096 1
 
1.0%
4476045028102260224 1
 
1.0%
4159012500102029824 1
 
1.0%
4671034032100119552 1
 
1.0%
4777032042102599680 1
 
1.0%
4887038022106630144 1
 
1.0%
4884037022114560000 1
 
1.0%
4143010500200039936 1
 
1.0%
4889046036107110400 1
 
1.0%
Other values (89) 89
89.0%
ValueCountFrequency (%)
3120011800107689984 1
1.0%
3171025333102720000 1
1.0%
3171025926105430016 1
1.0%
3171034023108879872 1
1.0%
3171034029109649920 1
1.0%
4136025021100340224 1
1.0%
4143010500200039936 1
1.0%
4150036021102329856 1
1.0%
4159012500102029824 1
1.0%
4161034025104370176 1
1.0%
ValueCountFrequency (%)
4889046036107110400 1
1.0%
4889044027104470016 1
1.0%
4889044024106600448 1
1.0%
4889038027104180224 1
1.0%
4889034023106400256 1
1.0%
4888025031116789760 1
1.0%
4888025031112000512 1
1.0%
4887038022106630144 1
1.0%
4887025026103029760 1
1.0%
4886040025106379776 1
1.0%

sido_nm
Categorical

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
경상남도
37 
경상북도
25 
전라남도
11 
충청북도
6 
경기도
6 
Other values (4)
15 

Length

Max length5
Median length4
Mean length3.96
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상남도 37
37.0%
경상북도 25
25.0%
전라남도 11
 
11.0%
충청북도 6
 
6.0%
경기도 6
 
6.0%
울산광역시 5
 
5.0%
전라북도 4
 
4.0%
강원도 3
 
3.0%
충청남도 3
 
3.0%

Length

2023-12-10T19:10:04.860467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:10:05.179911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 37
37.0%
경상북도 25
25.0%
전라남도 11
 
11.0%
충청북도 6
 
6.0%
경기도 6
 
6.0%
울산광역시 5
 
5.0%
전라북도 4
 
4.0%
강원도 3
 
3.0%
충청남도 3
 
3.0%

sgg_nm
Text

Distinct59
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:10:05.720212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.23
Min length2

Characters and Unicode

Total characters323
Distinct characters63
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)34.0%

Sample

1st row정선군
2nd row창원시 의창구
3rd row진주시
4th row보은군
5th row신안군
ValueCountFrequency (%)
합천군 5
 
4.7%
남해군 5
 
4.7%
북구 4
 
3.8%
고성군 4
 
3.8%
하동군 4
 
3.8%
울주군 4
 
3.8%
산청군 3
 
2.8%
김천시 3
 
2.8%
포항시 3
 
2.8%
의성군 3
 
2.8%
Other values (51) 68
64.2%
2023-12-10T19:10:06.458510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
군 64
19.8%
시 36
 
11.1%
천 17
 
5.3%
주 14
 
4.3%
성 11
 
3.4%
창 10
 
3.1%
구 9
 
2.8%
산 8
 
2.5%
의 7
 
2.2%
해 7
 
2.2%
Other values (53) 140
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 317
98.1%
Space Separator 6
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 64
20.2%
시 36
 
11.4%
천 17
 
5.4%
주 14
 
4.4%
성 11
 
3.5%
창 10
 
3.2%
구 9
 
2.8%
산 8
 
2.5%
의 7
 
2.2%
해 7
 
2.2%
Other values (52) 134
42.3%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 317
98.1%
Common 6
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 64
20.2%
시 36
 
11.4%
천 17
 
5.4%
주 14
 
4.4%
성 11
 
3.5%
창 10
 
3.2%
구 9
 
2.8%
산 8
 
2.5%
의 7
 
2.2%
해 7
 
2.2%
Other values (52) 134
42.3%
Common
ValueCountFrequency (%)
6
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 317
98.1%
ASCII 6
 
1.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
군 64
20.2%
시 36
 
11.4%
천 17
 
5.4%
주 14
 
4.4%
성 11
 
3.5%
창 10
 
3.2%
구 9
 
2.8%
산 8
 
2.5%
의 7
 
2.2%
해 7
 
2.2%
Other values (52) 134
42.3%
ASCII
ValueCountFrequency (%)
6
100.0%

bemd_nm
Text

Distinct92
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:10:06.946458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3
Min length2

Characters and Unicode

Total characters300
Distinct characters107
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 row여량면
2nd row동읍
3rd row집현면
4th row탄부면
5th row신의면
ValueCountFrequency (%)
덕곡면 2
 
2.0%
신광면 2
 
2.0%
창선면 2
 
2.0%
가회면 2
 
2.0%
안강읍 2
 
2.0%
거창읍 2
 
2.0%
옥종면 2
 
2.0%
웅촌면 2
 
2.0%
풍산면 1
 
1.0%
영덕읍 1
 
1.0%
Other values (82) 82
82.0%
2023-12-10T19:10:07.643409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
면 74
24.7%
읍 18
 
6.0%
동 12
 
4.0%
산 10
 
3.3%
덕 6
 
2.0%
촌 6
 
2.0%
곡 5
 
1.7%
창 5
 
1.7%
전 5
 
1.7%
도 4
 
1.3%
Other values (97) 155
51.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 300
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 74
24.7%
읍 18
 
6.0%
동 12
 
4.0%
산 10
 
3.3%
덕 6
 
2.0%
촌 6
 
2.0%
곡 5
 
1.7%
창 5
 
1.7%
전 5
 
1.7%
도 4
 
1.3%
Other values (97) 155
51.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 300
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 74
24.7%
읍 18
 
6.0%
동 12
 
4.0%
산 10
 
3.3%
덕 6
 
2.0%
촌 6
 
2.0%
곡 5
 
1.7%
창 5
 
1.7%
전 5
 
1.7%
도 4
 
1.3%
Other values (97) 155
51.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 300
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
면 74
24.7%
읍 18
 
6.0%
동 12
 
4.0%
산 10
 
3.3%
덕 6
 
2.0%
촌 6
 
2.0%
곡 5
 
1.7%
창 5
 
1.7%
전 5
 
1.7%
도 4
 
1.3%
Other values (97) 155
51.7%

ri_nm
Text

MISSING 

Distinct89
Distinct (%)96.7%
Missing8
Missing (%)8.0%
Memory size932.0 B
2023-12-10T19:10:08.052215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.923913
Min length2

Characters and Unicode

Total characters269
Distinct characters84
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

Unique86 ?
Unique (%)93.5%

Sample

1st row구절리
2nd row용잠리
3rd row대암리
4th row대양리
5th row상태서리
ValueCountFrequency (%)
신관리 2
 
2.2%
가지리 2
 
2.2%
대벽리 2
 
2.2%
두곡리 1
 
1.1%
구절리 1
 
1.1%
죽죽리 1
 
1.1%
죽곡리 1
 
1.1%
구미리 1
 
1.1%
반연리 1
 
1.1%
명산리 1
 
1.1%
Other values (79) 79
85.9%
2023-12-10T19:10:08.764774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 92
34.2%
대 12
 
4.5%
곡 8
 
3.0%
신 6
 
2.2%
산 6
 
2.2%
가 5
 
1.9%
용 5
 
1.9%
천 5
 
1.9%
정 5
 
1.9%
성 4
 
1.5%
Other values (74) 121
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 269
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 92
34.2%
대 12
 
4.5%
곡 8
 
3.0%
신 6
 
2.2%
산 6
 
2.2%
가 5
 
1.9%
용 5
 
1.9%
천 5
 
1.9%
정 5
 
1.9%
성 4
 
1.5%
Other values (74) 121
45.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 269
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 92
34.2%
대 12
 
4.5%
곡 8
 
3.0%
신 6
 
2.2%
산 6
 
2.2%
가 5
 
1.9%
용 5
 
1.9%
천 5
 
1.9%
정 5
 
1.9%
성 4
 
1.5%
Other values (74) 121
45.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 269
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 92
34.2%
대 12
 
4.5%
곡 8
 
3.0%
신 6
 
2.2%
산 6
 
2.2%
가 5
 
1.9%
용 5
 
1.9%
천 5
 
1.9%
정 5
 
1.9%
성 4
 
1.5%
Other values (74) 121
45.0%

beonji
Text

Distinct97
Distinct (%)98.0%
Missing1
Missing (%)1.0%
Memory size932.0 B
2023-12-10T19:10:09.430816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.1515152
Min length1

Characters and Unicode

Total characters411
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 row290-82
2nd row34-4
3rd row252-1
4th row499-2
5th row171-36
ValueCountFrequency (%)
638 2
 
2.0%
226 2
 
2.0%
946 1
 
1.0%
203-1 1
 
1.0%
260 1
 
1.0%
663-2 1
 
1.0%
1456-1 1
 
1.0%
산4-1 1
 
1.0%
711 1
 
1.0%
769-2 1
 
1.0%
Other values (87) 87
87.9%
2023-12-10T19:10:10.495873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 72
17.5%
2 56
13.6%
- 51
12.4%
3 42
10.2%
6 39
9.5%
4 34
8.3%
7 28
 
6.8%
8 24
 
5.8%
9 22
 
5.4%
5 18
 
4.4%
Other values (2) 25
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 353
85.9%
Dash Punctuation 51
 
12.4%
Other Letter 7
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 72
20.4%
2 56
15.9%
3 42
11.9%
6 39
11.0%
4 34
9.6%
7 28
 
7.9%
8 24
 
6.8%
9 22
 
6.2%
5 18
 
5.1%
0 18
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 51
100.0%
Other Letter
ValueCountFrequency (%)
산 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 404
98.3%
Hangul 7
 
1.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 72
17.8%
2 56
13.9%
- 51
12.6%
3 42
10.4%
6 39
9.7%
4 34
8.4%
7 28
 
6.9%
8 24
 
5.9%
9 22
 
5.4%
5 18
 
4.5%
Hangul
ValueCountFrequency (%)
산 7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 404
98.3%
Hangul 7
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 72
17.8%
2 56
13.9%
- 51
12.6%
3 42
10.4%
6 39
9.7%
4 34
8.4%
7 28
 
6.9%
8 24
 
5.9%
9 22
 
5.4%
5 18
 
4.5%
Hangul
ValueCountFrequency (%)
산 7
100.0%

badm_cd
Real number (ℝ)

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6134592 × 109
Minimum3.1200118 × 109
Maximum4.889046 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:10:10.879272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.1200118 × 109
5-th percentile4.0877755 × 109
Q14.5770345 × 109
median4.7255217 × 109
Q34.8760355 × 109
95-th percentile4.8880755 × 109
Maximum4.889046 × 109
Range1.7690342 × 109
Interquartile range (IQR)2.9900099 × 108

Descriptive statistics

Standard deviation3.9830817 × 108
Coefficient of variation (CV)0.08633612
Kurtosis6.6451201
Mean4.6134592 × 109
Median Absolute Deviation (MAD)1.4851386 × 108
Skewness-2.5285646
Sum4.6134592 × 1011
Variance1.586494 × 1017
MonotonicityNot monotonic
2023-12-10T19:10:11.159517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4888025031 2
 
2.0%
4884039024 2
 
2.0%
3171025333 1
 
1.0%
4671034032 1
 
1.0%
4777032042 1
 
1.0%
4887038022 1
 
1.0%
4884037022 1
 
1.0%
4143010500 1
 
1.0%
4889046036 1
 
1.0%
3120011800 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
3120011800 1
1.0%
3171025333 1
1.0%
3171025926 1
1.0%
3171034023 1
1.0%
3171034029 1
1.0%
4136025021 1
1.0%
4143010500 1
1.0%
4150036021 1
1.0%
4159012500 1
1.0%
4161034025 1
1.0%
ValueCountFrequency (%)
4889046036 1
1.0%
4889044027 1
1.0%
4889044024 1
1.0%
4889038027 1
1.0%
4889034023 1
1.0%
4888025031 2
2.0%
4887038022 1
1.0%
4887025026 1
1.0%
4886040025 1
1.0%
4886033021 1
1.0%

hadm_cd
Real number (ℝ)

Distinct93
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6134629 × 109
Minimum3.120054 × 109
Maximum4.889046 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:10:11.418579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.120054 × 109
5-th percentile4.0877754 × 109
Q14.5770345 × 109
median4.7255555 × 109
Q34.8760355 × 109
95-th percentile4.8880754 × 109
Maximum4.889046 × 109
Range1.768992 × 109
Interquartile range (IQR)2.99001 × 108

Descriptive statistics

Standard deviation3.983055 × 108
Coefficient of variation (CV)0.086335472
Kurtosis6.6452198
Mean4.6134629 × 109
Median Absolute Deviation (MAD)1.485215 × 108
Skewness-2.5285835
Sum4.6134629 × 1011
Variance1.5864727 × 1017
MonotonicityNot monotonic
2023-12-10T19:10:11.704155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4885041000 2
 
2.0%
3171034000 2
 
2.0%
4711331000 2
 
2.0%
4884039000 2
 
2.0%
4713025300 2
 
2.0%
4889044000 2
 
2.0%
4888025000 2
 
2.0%
4277037000 1
 
1.0%
4887038000 1
 
1.0%
4884037000 1
 
1.0%
Other values (83) 83
83.0%
ValueCountFrequency (%)
3120054000 1
1.0%
3171025300 1
1.0%
3171025900 1
1.0%
3171034000 2
2.0%
4136025000 1
1.0%
4143053000 1
1.0%
4150036000 1
1.0%
4159057000 1
1.0%
4161034000 1
1.0%
4165031000 1
1.0%
ValueCountFrequency (%)
4889046000 1
1.0%
4889044000 2
2.0%
4889038000 1
1.0%
4889034000 1
1.0%
4888025000 2
2.0%
4887038000 1
1.0%
4887025000 1
1.0%
4886040000 1
1.0%
4886033000 1
1.0%
4886031000 1
1.0%

rd_cd
Categorical

IMBALANCE 

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
95 
427703013007
 
1
481214781237
 
1
478404763267
 
1
488404829399
 
1

Length

Max length12
Median length4
Mean length4.4
Min length4

Unique

Unique5 ?
Unique (%)5.0%

Sample

1st row427703013007
2nd row481214781237
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 95
95.0%
427703013007 1
 
1.0%
481214781237 1
 
1.0%
478404763267 1
 
1.0%
488404829399 1
 
1.0%
431303238059 1
 
1.0%

Length

2023-12-10T19:10:12.053399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:10:12.297549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 95
95.0%
427703013007 1
 
1.0%
481214781237 1
 
1.0%
478404763267 1
 
1.0%
488404829399 1
 
1.0%
431303238059 1
 
1.0%

rd_nm
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing95
Missing (%)95.0%
Memory size932.0 B
2023-12-10T19:10:12.584342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.2
Min length3

Characters and Unicode

Total characters21
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

Unique5 ?
Unique (%)100.0%

Sample

1st row노추산로
2nd row무점길
3rd row신정3길
4th row화방사길
5th row첨단산업1로
ValueCountFrequency (%)
노추산로 1
20.0%
무점길 1
20.0%
신정3길 1
20.0%
화방사길 1
20.0%
첨단산업1로 1
20.0%
2023-12-10T19:10:13.485911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
길 3
14.3%
산 2
 
9.5%
로 2
 
9.5%
노 1
 
4.8%
화 1
 
4.8%
업 1
 
4.8%
단 1
 
4.8%
첨 1
 
4.8%
사 1
 
4.8%
방 1
 
4.8%
Other values (7) 7
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19
90.5%
Decimal Number 2
 
9.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 3
15.8%
산 2
 
10.5%
로 2
 
10.5%
노 1
 
5.3%
화 1
 
5.3%
업 1
 
5.3%
단 1
 
5.3%
첨 1
 
5.3%
사 1
 
5.3%
방 1
 
5.3%
Other values (5) 5
26.3%
Decimal Number
ValueCountFrequency (%)
3 1
50.0%
1 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19
90.5%
Common 2
 
9.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 3
15.8%
산 2
 
10.5%
로 2
 
10.5%
노 1
 
5.3%
화 1
 
5.3%
업 1
 
5.3%
단 1
 
5.3%
첨 1
 
5.3%
사 1
 
5.3%
방 1
 
5.3%
Other values (5) 5
26.3%
Common
ValueCountFrequency (%)
3 1
50.0%
1 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19
90.5%
ASCII 2
 
9.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
길 3
15.8%
산 2
 
10.5%
로 2
 
10.5%
노 1
 
5.3%
화 1
 
5.3%
업 1
 
5.3%
단 1
 
5.3%
첨 1
 
5.3%
사 1
 
5.3%
방 1
 
5.3%
Other values (5) 5
26.3%
ASCII
ValueCountFrequency (%)
3 1
50.0%
1 1
50.0%

bld_num
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing95
Missing (%)95.0%
Memory size932.0 B
2023-12-10T19:10:13.775685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4
Min length3

Characters and Unicode

Total characters20
Distinct characters10
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

Unique5 ?
Unique (%)100.0%

Sample

1st row745
2nd row34-18
3rd row2-19
4th row109-2
5th row137
ValueCountFrequency (%)
745 1
20.0%
34-18 1
20.0%
2-19 1
20.0%
109-2 1
20.0%
137 1
20.0%
2023-12-10T19:10:14.312489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4
20.0%
- 3
15.0%
7 2
10.0%
4 2
10.0%
3 2
10.0%
2 2
10.0%
9 2
10.0%
5 1
 
5.0%
8 1
 
5.0%
0 1
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17
85.0%
Dash Punctuation 3
 
15.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4
23.5%
7 2
11.8%
4 2
11.8%
3 2
11.8%
2 2
11.8%
9 2
11.8%
5 1
 
5.9%
8 1
 
5.9%
0 1
 
5.9%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4
20.0%
- 3
15.0%
7 2
10.0%
4 2
10.0%
3 2
10.0%
2 2
10.0%
9 2
10.0%
5 1
 
5.0%
8 1
 
5.0%
0 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4
20.0%
- 3
15.0%
7 2
10.0%
4 2
10.0%
3 2
10.0%
2 2
10.0%
9 2
10.0%
5 1
 
5.0%
8 1
 
5.0%
0 1
 
5.0%

x
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.03396
Minimum126.08457
Maximum129.43055
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:10:14.602321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.08457
5-th percentile126.70202
Q1127.47894
median128.02061
Q3128.51551
95-th percentile129.28435
Maximum129.43055
Range3.3459822
Interquartile range (IQR)1.0365723

Descriptive statistics

Standard deviation0.78913423
Coefficient of variation (CV)0.0061634758
Kurtosis-0.24556494
Mean128.03396
Median Absolute Deviation (MAD)0.54287907
Skewness-0.27165129
Sum12803.396
Variance0.62273283
MonotonicityNot monotonic
2023-12-10T19:10:14.887261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.728174559913 1
 
1.0%
128.092686210964 1
 
1.0%
127.022884943147 1
 
1.0%
127.006540650809 1
 
1.0%
127.042568246677 1
 
1.0%
129.309335256154 1
 
1.0%
127.692439860432 1
 
1.0%
127.868781961471 1
 
1.0%
127.001240888921 1
 
1.0%
128.03155502321 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
126.084570366499 1
1.0%
126.120580397884 1
1.0%
126.263981245113 1
1.0%
126.390298765908 1
1.0%
126.536121330197 1
1.0%
126.710750145914 1
1.0%
126.885937550989 1
1.0%
126.900040709631 1
1.0%
126.905750470651 1
1.0%
127.001240888921 1
1.0%
ValueCountFrequency (%)
129.430552599439 1
1.0%
129.42918859738 1
1.0%
129.366869712209 1
1.0%
129.355169122273 1
1.0%
129.309335256154 1
1.0%
129.283031496988 1
1.0%
129.253923098739 1
1.0%
129.24844656485 1
1.0%
129.19929185135 1
1.0%
129.198490651543 1
1.0%

y
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.77192
Minimum34.434187
Maximum37.865269
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:10:15.180545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.434187
5-th percentile34.851967
Q135.206914
median35.634604
Q336.214812
95-th percentile37.316205
Maximum37.865269
Range3.4310819
Interquartile range (IQR)1.0078982

Descriptive statistics

Standard deviation0.75984921
Coefficient of variation (CV)0.021241499
Kurtosis0.032393083
Mean35.77192
Median Absolute Deviation (MAD)0.50964441
Skewness0.74315893
Sum3577.192
Variance0.57737082
MonotonicityNot monotonic
2023-12-10T19:10:15.459685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5169326710367 1
 
1.0%
36.0961869083748 1
 
1.0%
36.2835006590044 1
 
1.0%
37.2060495016178 1
 
1.0%
35.18262677736 1
 
1.0%
36.3403432432867 1
 
1.0%
35.6768964571592 1
 
1.0%
34.868655673554 1
 
1.0%
37.3565002769659 1
 
1.0%
35.5507280944714 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
34.4341872021838 1
1.0%
34.5600985087101 1
1.0%
34.5988596645843 1
1.0%
34.745179336591 1
1.0%
34.8124501687133 1
1.0%
34.854046893313 1
1.0%
34.868655673554 1
1.0%
34.8773429367366 1
1.0%
34.9079362233632 1
1.0%
34.9170283802737 1
1.0%
ValueCountFrequency (%)
37.8652691111148 1
1.0%
37.5941091753836 1
1.0%
37.5169326710367 1
1.0%
37.4702305016427 1
1.0%
37.3565002769659 1
1.0%
37.3140841560101 1
1.0%
37.2060495016178 1
1.0%
37.202950637256 1
1.0%
37.1751924349075 1
1.0%
36.9899623558039 1
1.0%

grid_cd
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:10:15.966409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters800
Distinct characters16
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 row마사085471
2nd row마라084996
3rd row라라527976
4th row라바253240
5th row나라702236
ValueCountFrequency (%)
마사085471 1
 
1.0%
마마503317 1
 
1.0%
다사562120 1
 
1.0%
다라583875 1
 
1.0%
마바623174 1
 
1.0%
라마174423 1
 
1.0%
라라337527 1
 
1.0%
다사558287 1
 
1.0%
라마481284 1
 
1.0%
마마746387 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T19:10:16.669637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
라 81
10.1%
8 77
9.6%
5 70
8.8%
2 70
8.8%
마 67
8.4%
1 65
8.1%
7 63
7.9%
3 58
7.2%
4 56
7.0%
0 55
 
6.9%
Other values (6) 138
17.2%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 77
12.8%
5 70
11.7%
2 70
11.7%
1 65
10.8%
7 63
10.5%
3 58
9.7%
4 56
9.3%
0 55
9.2%
6 45
7.5%
9 41
6.8%
Other Letter
ValueCountFrequency (%)
라 81
40.5%
마 67
33.5%
다 22
 
11.0%
바 17
 
8.5%
사 9
 
4.5%
나 4
 
2.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
8 77
12.8%
5 70
11.7%
2 70
11.7%
1 65
10.8%
7 63
10.5%
3 58
9.7%
4 56
9.3%
0 55
9.2%
6 45
7.5%
9 41
6.8%
Hangul
ValueCountFrequency (%)
라 81
40.5%
마 67
33.5%
다 22
 
11.0%
바 17
 
8.5%
사 9
 
4.5%
나 4
 
2.0%

Most occurring blocks

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

Most frequent character per block

Hangul
ValueCountFrequency (%)
라 81
40.5%
마 67
33.5%
다 22
 
11.0%
바 17
 
8.5%
사 9
 
4.5%
나 4
 
2.0%
ASCII
ValueCountFrequency (%)
8 77
12.8%
5 70
11.7%
2 70
11.7%
1 65
10.8%
7 63
10.5%
3 58
9.7%
4 56
9.3%
0 55
9.2%
6 45
7.5%
9 41
6.8%

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

2023-12-10T19:10:16.976479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:10:17.156319image/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

2023-12-10T19:10:17.322349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:10:17.503768image/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_495_LLR_ATRCTN_2021
100 

Length

Max length22
Median length22
Mean length22
Min length22

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKC_495_LLR_ATRCTN_2021
2nd rowKC_495_LLR_ATRCTN_2021
3rd rowKC_495_LLR_ATRCTN_2021
4th rowKC_495_LLR_ATRCTN_2021
5th rowKC_495_LLR_ATRCTN_2021

Common Values

ValueCountFrequency (%)
KC_495_LLR_ATRCTN_2021 100
100.0%

Length

2023-12-10T19:10:17.737088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:10:18.019621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kc_495_llr_atrctn_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

2023-12-10T19:10:18.396503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:10:18.571206image/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
0KCLANPO21N000000001장소관광지549380구절리역(폐역)<NA><NA>60513일반관광지4277037023102900224강원도정선군여량면구절리290-8242770370234277037000427703013007노추산로745128.72817537.516933마사08547120210916170801KTKC_495_LLR_ATRCTN_202120210916
1KCLANPO21N000038438장소관광지22051690토리딸기팜<NA><NA>60516관광농원/허브마을4812125032100339712경상남도창원시 의창구동읍용잠리34-448121250324812125000481214781237무점길34-18128.69213135.286686마라08499620210916170801KTKC_495_LLR_ATRCTN_202120210916
2KCLANPO21N000000003장소관광지808705대암소류지<NA><NA>110215지역호수/저수지4817042024102519808경상남도진주시집현면대암리252-148170420244817042000<NA><NA><NA>128.07970935.272747라라52797620210916170801KTKC_495_LLR_ATRCTN_202120210916
3KCLANPO21N000000004장소관광지808746대양소류지<NA><NA>110215지역호수/저수지4372034028104990208충청북도보은군탄부면대양리499-243720340284372034000<NA><NA><NA>127.7823436.413646라바25324020210916170801KTKC_495_LLR_ATRCTN_202120210916
4KCLANPO21N000000005장소관광지809458대장저수지<NA><NA>110215지역호수/저수지4691038021101710336전라남도신안군신의면상태서리171-3646910380214691038000<NA><NA><NA>126.0845734.59886나라70223620210916170801KTKC_495_LLR_ATRCTN_202120210916
5KCLANPO21N000000006장소관광지809471미천제2소류지<NA><NA>110215지역호수/저수지4812534034113019904경상남도창원시 마산합포구진전면평암리1302-648125340344812534000<NA><NA><NA>128.40223435.148722라라82184020210916170801KTKC_495_LLR_ATRCTN_202120210916
6KCLANPO21N000000007장소관광지809638진가저수지<NA><NA>110215지역호수/저수지4150036021102329856경기도이천시모가면진가리233-141500360214150036000<NA><NA><NA>127.47530637.175192다사97808420210916170801KTKC_495_LLR_ATRCTN_202120210916
7KCLANPO21N000038439장소관광지22113578고성만해지개길<NA><NA>60517먹거리/패션거리4882031026202179584경상남도고성군삼산면판곡리산218-448820310264882031000<NA><NA><NA>128.31040234.944001라라74061320210916170801KTKC_495_LLR_ATRCTN_202120210916
8KCLANPO21N000000009장소관광지809807미산소류지<NA><NA>110215지역호수/저수지4672031030100400128전라남도곡성군오곡면미산리40-246720310304672031000<NA><NA><NA>127.30849235.243575다라82594220210916170801KTKC_495_LLR_ATRCTN_202120210916
9KCLANPO21N000000010장소관광지809863대촌못<NA><NA>110215지역호수/저수지3171025926105430016울산광역시울주군범서읍두산리54331710259263171025900<NA><NA><NA>129.28303135.639646마마61439620210916170801KTKC_495_LLR_ATRCTN_202120210916
idlclasmlsfcid_poipoi_nmbranch_nmsub_nmmcate_cdmcate_nmpnusido_nmsgg_nmbemd_nmri_nmbeonjibadm_cdhadm_cdrd_cdrd_nmbld_numxygrid_cdlst_updt_dtdata_orgnfile_namebase_ymd
90KCLANPO21N000000091장소관광지828762야북골못<NA><NA>110215지역호수/저수지4711331028109939712경상북도포항시 북구신광면안덕리994-147113310284711331000<NA><NA><NA>129.25392336.159332마마57797220210916170801KTKC_495_LLR_ATRCTN_202120210916
91KCLANPO21N000000092장소관광지828896옥산1소류지<NA><NA>110215지역호수/저수지4831034025103229952경상남도거제시거제면옥산리32348310340254831034000<NA><NA><NA>128.57726234.877343라라98454120210916170801KTKC_495_LLR_ATRCTN_202120210916
92KCLANPO21N000000093장소관광지828928새못<NA><NA>110215지역호수/저수지4782025325103620096경상북도청도군청도읍내리36247820253254782025300<NA><NA><NA>128.75039435.681978마마13143520210916170801KTKC_495_LLR_ATRCTN_202120210916
93KCLANPO21N000000094장소관광지829212갓골저수지<NA><NA>110215지역호수/저수지4874034021100680192경상남도창녕군이방면안리6848740340214874034000<NA><NA><NA>128.39476335.590696라마81033120210916170801KTKC_495_LLR_ATRCTN_202120210916
94KCLANPO21N000000095장소관광지829360새터골못<NA><NA>110215지역호수/저수지4313033531106379776충청북도충주시대소원면본리63843130335314313033500431303238059첨단산업1로137127.83172836.989962라바29587920210916170801KTKC_495_LLR_ATRCTN_202120210916
95KCLANPO21N000000096장소관광지829406새터못<NA><NA>110215지역호수/저수지4783031034104210432경상북도고령군덕곡면백리42147830310344783031000<NA><NA><NA>128.19280235.816181라마62557920210916170801KTKC_495_LLR_ATRCTN_202120210916
96KCLANPO21N000000097장소관광지829598갈마지못<NA><NA>110215지역호수/저수지4723012700107629568경상북도영천시매산동<NA>76347230127004723052000<NA><NA><NA>128.91846736.017838마마27881020210916170801KTKC_495_LLR_ATRCTN_202120210916
97KCLANPO21N000000098장소관광지829860소류지<NA><NA>110215지역호수/저수지4872037023111789568경상남도의령군지정면두곡리117948720370234872037000<NA><NA><NA>128.38251135.400138라마80111920210916170801KTKC_495_LLR_ATRCTN_202120210916
98KCLANPO21N000000099장소관광지830325대벽소류지<NA><NA>110215지역호수/저수지4884039024109460480경상남도남해군창선면대벽리94648840390244884039000<NA><NA><NA>128.00204634.907936라라45857120210916170801KTKC_495_LLR_ATRCTN_202120210916
99KCLANPO21N000000100장소관광지830580안못<NA><NA>110215지역호수/저수지4713025332200810496경상북도경주시안강읍산대리산81-147130253324713025300<NA><NA><NA>129.17850136.009505마마51280420210916170801KTKC_495_LLR_ATRCTN_202120210916