Overview

Dataset statistics

Number of variables31
Number of observations100
Missing cells72
Missing cells (%)2.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory25.4 KiB
Average record size in memory260.3 B

Variable types

Text8
Categorical13
Numeric8
Boolean2

Alerts

lclas has constant value ""Constant
mlsfc has constant value ""Constant
data_stdde 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
hmpg is highly imbalanced (71.2%)Imbalance
pbctlt_pos_yn is highly imbalanced (85.9%)Imbalance
opnng_yy has 13 (13.0%) missing valuesMissing
telno has 59 (59.0%) missing valuesMissing
id has unique valuesUnique
fclt_name has unique valuesUnique
rdnm_addr has unique valuesUnique
x_cd has unique valuesUnique
y_cd has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:01:24.558840
Analysis finished2023-12-10 10:01:25.934565
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
2023-12-10T19:01:26.290834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length16
Min length16

Characters and Unicode

Total characters1600
Distinct characters14
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 rowKC483PC19N000001
2nd rowKC483PC19N000002
3rd rowKC483PC19N000003
4th rowKC483PC19N000004
5th rowKC483PC19N000005
ValueCountFrequency (%)
kc483pc19n000001 1
 
1.0%
kc483pc19n000063 1
 
1.0%
kc483pc19n000074 1
 
1.0%
kc483pc19n000073 1
 
1.0%
kc483pc19n000072 1
 
1.0%
kc483pc19n000071 1
 
1.0%
kc483pc19n000070 1
 
1.0%
kc483pc19n000069 1
 
1.0%
kc483pc19n000068 1
 
1.0%
kc483pc19n000067 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T19:01:26.926785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 419
26.2%
C 200
12.5%
1 121
 
7.6%
4 120
 
7.5%
8 120
 
7.5%
3 120
 
7.5%
9 120
 
7.5%
K 100
 
6.2%
P 100
 
6.2%
N 100
 
6.2%
Other values (4) 80
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1100
68.8%
Uppercase Letter 500
31.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 419
38.1%
1 121
 
11.0%
4 120
 
10.9%
8 120
 
10.9%
3 120
 
10.9%
9 120
 
10.9%
5 20
 
1.8%
6 20
 
1.8%
7 20
 
1.8%
2 20
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
C 200
40.0%
K 100
20.0%
P 100
20.0%
N 100
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1100
68.8%
Latin 500
31.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 419
38.1%
1 121
 
11.0%
4 120
 
10.9%
8 120
 
10.9%
3 120
 
10.9%
9 120
 
10.9%
5 20
 
1.8%
6 20
 
1.8%
7 20
 
1.8%
2 20
 
1.8%
Latin
ValueCountFrequency (%)
C 200
40.0%
K 100
20.0%
P 100
20.0%
N 100
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1600
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 419
26.2%
C 200
12.5%
1 121
 
7.6%
4 120
 
7.5%
8 120
 
7.5%
3 120
 
7.5%
9 120
 
7.5%
K 100
 
6.2%
P 100
 
6.2%
N 100
 
6.2%
Other values (4) 80
 
5.0%

lclas
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
쇼핑 100
100.0%

Length

2023-12-10T19:01:27.194598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:01:27.369799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
쇼핑 100
100.0%

mlsfc
Categorical

CONSTANT 

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

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전통시장 100
100.0%

Length

2023-12-10T19:01:27.607869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:01:27.776026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전통시장 100
100.0%

fclt_name
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:01:28.105566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length6.59
Min length4

Characters and Unicode

Total characters659
Distinct characters137
Distinct categories5 ?
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 row대정오일시장
2nd row서귀포매일올레시장
3rd row중문오일시장
4th row모슬포중앙시장
5th row서귀포향토오일시장
ValueCountFrequency (%)
대정오일시장 1
 
1.0%
항동시장 1
 
1.0%
남해전통시장 1
 
1.0%
동부시장 1
 
1.0%
영암읍5일시장 1
 
1.0%
조성5일시장 1
 
1.0%
이동시장(이동공설시장 1
 
1.0%
동계시장 1
 
1.0%
자유시장 1
 
1.0%
청호시장 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T19:01:28.751684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 106
 
16.1%
장 105
 
15.9%
일 35
 
5.3%
5 19
 
2.9%
동 12
 
1.8%
포 11
 
1.7%
산 11
 
1.7%
중 11
 
1.7%
) 10
 
1.5%
( 9
 
1.4%
Other values (127) 330
50.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 618
93.8%
Decimal Number 19
 
2.9%
Close Punctuation 10
 
1.5%
Open Punctuation 9
 
1.4%
Other Punctuation 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 106
 
17.2%
장 105
 
17.0%
일 35
 
5.7%
동 12
 
1.9%
포 11
 
1.8%
산 11
 
1.8%
중 11
 
1.8%
주 9
 
1.5%
남 9
 
1.5%
성 9
 
1.5%
Other values (123) 300
48.5%
Decimal Number
ValueCountFrequency (%)
5 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 618
93.8%
Common 41
 
6.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 106
 
17.2%
장 105
 
17.0%
일 35
 
5.7%
동 12
 
1.9%
포 11
 
1.8%
산 11
 
1.8%
중 11
 
1.8%
주 9
 
1.5%
남 9
 
1.5%
성 9
 
1.5%
Other values (123) 300
48.5%
Common
ValueCountFrequency (%)
5 19
46.3%
) 10
24.4%
( 9
22.0%
, 3
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 618
93.8%
ASCII 41
 
6.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 106
 
17.2%
장 105
 
17.0%
일 35
 
5.7%
동 12
 
1.9%
포 11
 
1.8%
산 11
 
1.8%
중 11
 
1.8%
주 9
 
1.5%
남 9
 
1.5%
성 9
 
1.5%
Other values (123) 300
48.5%
ASCII
ValueCountFrequency (%)
5 19
46.3%
) 10
24.4%
( 9
22.0%
, 3
 
7.3%

ctprvn_nm
Categorical

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
전라남도
61 
제주특별자치도
19 
경상남도
16 
부산광역시
 
1
대구광역시
 
1
Other values (2)
 
2

Length

Max length7
Median length4
Mean length4.59
Min length3

Unique

Unique4 ?
Unique (%)4.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라남도 61
61.0%
제주특별자치도 19
 
19.0%
경상남도 16
 
16.0%
부산광역시 1
 
1.0%
대구광역시 1
 
1.0%
경기도 1
 
1.0%
서울특별시 1
 
1.0%

Length

2023-12-10T19:01:29.028051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:01:29.287619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 61
61.0%
제주특별자치도 19
 
19.0%
경상남도 16
 
16.0%
부산광역시 1
 
1.0%
대구광역시 1
 
1.0%
경기도 1
 
1.0%
서울특별시 1
 
1.0%

sgnr_nm
Categorical

Distinct26
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
여수시
12 
제주시
12 
서귀포시
7 
거제시
7 
보성군
7 
Other values (21)
55 

Length

Max length4
Median length3
Mean length3.08
Min length3

Unique

Unique10 ?
Unique (%)10.0%

Sample

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

Common Values

ValueCountFrequency (%)
여수시 12
12.0%
제주시 12
12.0%
서귀포시 7
 
7.0%
거제시 7
 
7.0%
보성군 7
 
7.0%
목포시 6
 
6.0%
해남군 6
 
6.0%
고흥군 5
 
5.0%
장흥군 5
 
5.0%
영암군 5
 
5.0%
Other values (16) 28
28.0%

Length

2023-12-10T19:01:29.506830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
여수시 12
12.0%
제주시 12
12.0%
서귀포시 7
 
7.0%
거제시 7
 
7.0%
보성군 7
 
7.0%
목포시 6
 
6.0%
해남군 6
 
6.0%
고흥군 5
 
5.0%
장흥군 5
 
5.0%
영암군 5
 
5.0%
Other values (16) 28
28.0%

legaldong_cd
Real number (ℝ)

Distinct82
Distinct (%)82.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6747113 × 109
Minimum1.1230103 × 109
Maximum5.0130259 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:01:29.737011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1230103 × 109
5-th percentile4.6110102 × 109
Q14.6215157 × 109
median4.6820355 × 109
Q34.8310106 × 109
95-th percentile5.0130105 × 109
Maximum5.0130259 × 109
Range3.8900156 × 109
Interquartile range (IQR)2.0949494 × 108

Descriptive statistics

Standard deviation4.8730649 × 108
Coefficient of variation (CV)0.10424312
Kurtosis33.181026
Mean4.6747113 × 109
Median Absolute Deviation (MAD)69024222
Skewness-5.3274619
Sum4.6747113 × 1011
Variance2.3746762 × 1017
MonotonicityNot monotonic
2023-12-10T19:01:30.374485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4613012800 4
 
4.0%
5011010300 4
 
4.0%
4613010800 3
 
3.0%
4611010200 3
 
3.0%
4831010600 3
 
3.0%
5013025022 2
 
2.0%
5011010100 2
 
2.0%
4613011300 2
 
2.0%
4690025025 2
 
2.0%
4689025021 2
 
2.0%
Other values (72) 73
73.0%
ValueCountFrequency (%)
1123010300 1
 
1.0%
2653010400 1
 
1.0%
2726011200 1
 
1.0%
4139012700 1
 
1.0%
4611010100 1
 
1.0%
4611010200 3
3.0%
4611012400 1
 
1.0%
4611016000 1
 
1.0%
4613010700 1
 
1.0%
4613010800 3
3.0%
ValueCountFrequency (%)
5013025924 1
1.0%
5013025921 1
1.0%
5013025022 2
2.0%
5013011200 1
1.0%
5013010500 1
1.0%
5013010100 1
1.0%
5011025628 1
1.0%
5011025023 1
1.0%
5011012900 1
1.0%
5011012700 1
1.0%

legalemd_nm
Text

Distinct77
Distinct (%)77.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:01:30.852239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.02
Min length2

Characters and Unicode

Total characters302
Distinct characters86
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

Unique61 ?
Unique (%)61.0%

Sample

1st row대정읍
2nd row서귀동
3rd row중문동
4th row대정읍
5th row동홍동
ValueCountFrequency (%)
학동 4
 
4.0%
이도일동 4
 
4.0%
교동 3
 
3.0%
옥포동 3
 
3.0%
산정동 3
 
3.0%
일도일동 2
 
2.0%
능포동 2
 
2.0%
벌교읍 2
 
2.0%
완도읍 2
 
2.0%
중앙동 2
 
2.0%
Other values (67) 73
73.0%
2023-12-10T19:01:31.563321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 52
 
17.2%
읍 27
 
8.9%
면 26
 
8.6%
도 15
 
5.0%
일 13
 
4.3%
산 11
 
3.6%
이 7
 
2.3%
교 7
 
2.3%
포 6
 
2.0%
학 5
 
1.7%
Other values (76) 133
44.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 301
99.7%
Decimal Number 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 52
 
17.3%
읍 27
 
9.0%
면 26
 
8.6%
도 15
 
5.0%
일 13
 
4.3%
산 11
 
3.7%
이 7
 
2.3%
교 7
 
2.3%
포 6
 
2.0%
학 5
 
1.7%
Other values (75) 132
43.9%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 301
99.7%
Common 1
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 52
 
17.3%
읍 27
 
9.0%
면 26
 
8.6%
도 15
 
5.0%
일 13
 
4.3%
산 11
 
3.7%
이 7
 
2.3%
교 7
 
2.3%
포 6
 
2.0%
학 5
 
1.7%
Other values (75) 132
43.9%
Common
ValueCountFrequency (%)
1 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 301
99.7%
ASCII 1
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 52
 
17.3%
읍 27
 
9.0%
면 26
 
8.6%
도 15
 
5.0%
일 13
 
4.3%
산 11
 
3.7%
이 7
 
2.3%
교 7
 
2.3%
포 6
 
2.0%
학 5
 
1.7%
Other values (75) 132
43.9%
ASCII
ValueCountFrequency (%)
1 1
100.0%

adstrd_cd
Real number (ℝ)

Distinct79
Distinct (%)79.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6747338 × 109
Minimum1.1230545 × 109
Maximum5.013061 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:01:31.844116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1230545 × 109
5-th percentile4.6110556 × 109
Q14.6215475 × 109
median4.6820355 × 109
Q34.8310562 × 109
95-th percentile5.013025 × 109
Maximum5.013061 × 109
Range3.8900065 × 109
Interquartile range (IQR)2.0950875 × 108

Descriptive statistics

Standard deviation4.8730266 × 108
Coefficient of variation (CV)0.1042418
Kurtosis33.181067
Mean4.6747338 × 109
Median Absolute Deviation (MAD)68975250
Skewness-5.3274437
Sum4.6747338 × 1011
Variance2.3746388 × 1017
MonotonicityNot monotonic
2023-12-10T19:01:32.108047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4613078000 4
 
4.0%
4613057000 4
 
4.0%
5011053000 4
 
4.0%
4831056000 3
 
3.0%
5013025000 2
 
2.0%
4689025000 2
 
2.0%
4831053000 2
 
2.0%
4678025300 2
 
2.0%
4613063500 2
 
2.0%
4682025000 2
 
2.0%
Other values (69) 73
73.0%
ValueCountFrequency (%)
1123054500 1
1.0%
2653062000 1
1.0%
2726065200 1
1.0%
4139058100 1
1.0%
4611051000 1
1.0%
4611055800 1
1.0%
4611064000 1
1.0%
4611064500 1
1.0%
4611065500 1
1.0%
4611075700 1
1.0%
ValueCountFrequency (%)
5013061000 1
 
1.0%
5013057000 1
 
1.0%
5013053000 1
 
1.0%
5013025900 2
2.0%
5013025000 2
2.0%
5011069000 1
 
1.0%
5011057000 1
 
1.0%
5011054000 1
 
1.0%
5011053000 4
4.0%
5011052000 1
 
1.0%

adstrd_nm
Text

Distinct77
Distinct (%)77.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:01:32.755573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.2
Min length2

Characters and Unicode

Total characters320
Distinct characters92
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

Unique63 ?
Unique (%)63.0%

Sample

1st row대정읍
2nd row중앙동
3rd row중문동
4th row대정읍
5th row동홍동
ValueCountFrequency (%)
중앙동 6
 
6.0%
쌍봉동 4
 
4.0%
이도1동 4
 
4.0%
옥포2동 3
 
3.0%
서강동 2
 
2.0%
진도읍 2
 
2.0%
능포동 2
 
2.0%
해남읍 2
 
2.0%
벌교읍 2
 
2.0%
대정읍 2
 
2.0%
Other values (67) 71
71.0%
2023-12-10T19:01:33.485037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 53
 
16.6%
읍 27
 
8.4%
면 26
 
8.1%
도 15
 
4.7%
중 8
 
2.5%
1 8
 
2.5%
산 8
 
2.5%
이 7
 
2.2%
2 6
 
1.9%
앙 6
 
1.9%
Other values (82) 156
48.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 306
95.6%
Decimal Number 14
 
4.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 53
 
17.3%
읍 27
 
8.8%
면 26
 
8.5%
도 15
 
4.9%
중 8
 
2.6%
산 8
 
2.6%
이 7
 
2.3%
앙 6
 
2.0%
포 6
 
2.0%
장 5
 
1.6%
Other values (80) 145
47.4%
Decimal Number
ValueCountFrequency (%)
1 8
57.1%
2 6
42.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 306
95.6%
Common 14
 
4.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 53
 
17.3%
읍 27
 
8.8%
면 26
 
8.5%
도 15
 
4.9%
중 8
 
2.6%
산 8
 
2.6%
이 7
 
2.3%
앙 6
 
2.0%
포 6
 
2.0%
장 5
 
1.6%
Other values (80) 145
47.4%
Common
ValueCountFrequency (%)
1 8
57.1%
2 6
42.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 306
95.6%
ASCII 14
 
4.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 53
 
17.3%
읍 27
 
8.8%
면 26
 
8.5%
도 15
 
4.9%
중 8
 
2.6%
산 8
 
2.6%
이 7
 
2.3%
앙 6
 
2.0%
포 6
 
2.0%
장 5
 
1.6%
Other values (80) 145
47.4%
ASCII
ValueCountFrequency (%)
1 8
57.1%
2 6
42.9%

rdnmaddr_cd
Real number (ℝ)

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6747306 × 1011
Minimum1.1230412 × 1011
Maximum5.0130485 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:01:33.774401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1230412 × 1011
5-th percentile4.6110328 × 1011
Q14.6215328 × 1011
median4.6820399 × 1011
Q34.8310481 × 1011
95-th percentile5.0130335 × 1011
Maximum5.0130485 × 1011
Range3.8900074 × 1011
Interquartile range (IQR)2.0951527 × 1010

Descriptive statistics

Standard deviation4.8730586 × 1010
Coefficient of variation (CV)0.10424256
Kurtosis33.180745
Mean4.6747306 × 1011
Median Absolute Deviation (MAD)6.900706 × 109
Skewness-5.3274258
Sum4.6747306 × 1013
Variance2.37467 × 1021
MonotonicityNot monotonic
2023-12-10T19:01:34.141943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
483103337031 2
 
2.0%
461304646937 2
 
2.0%
461303282072 2
 
2.0%
461303282071 1
 
1.0%
488403343044 1
 
1.0%
461104643513 1
 
1.0%
468304685347 1
 
1.0%
467803290012 1
 
1.0%
488404829233 1
 
1.0%
467704667557 1
 
1.0%
Other values (87) 87
87.0%
ValueCountFrequency (%)
112304115261 1
1.0%
265303132023 1
1.0%
272604238344 1
1.0%
413903012020 1
1.0%
461103281032 1
1.0%
461103281043 1
1.0%
461103281065 1
1.0%
461103281075 1
1.0%
461104643402 1
1.0%
461104643513 1
1.0%
ValueCountFrequency (%)
501304850848 1
1.0%
501304850829 1
1.0%
501304850552 1
1.0%
501303350250 1
1.0%
501303350155 1
1.0%
501303350122 1
1.0%
501303350018 1
1.0%
501104849019 1
1.0%
501104848759 1
1.0%
501104848350 1
1.0%

rdnm_addr
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:01:34.931693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length29
Mean length22.86
Min length18

Characters and Unicode

Total characters2286
Distinct characters161
Distinct categories7 ?
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 row제주특별자치도 서귀포시 대정읍 신영로36번길 65
2nd row제주특별자치도 서귀포시 중앙로62번길 20 (서귀동)
3rd row제주특별자치도 서귀포시 천제연로188번길 12 (중문동)
4th row제주특별자치도 서귀포시 대정읍 상모로 325
5th row제주특별자치도 서귀포시 정방연로 47-8 (동홍동)
ValueCountFrequency (%)
전라남도 61
 
12.1%
제주특별자치도 19
 
3.8%
경상남도 16
 
3.2%
제주시 12
 
2.4%
여수시 12
 
2.4%
보성군 7
 
1.4%
거제시 7
 
1.4%
서귀포시 7
 
1.4%
목포시 6
 
1.2%
해남군 6
 
1.2%
Other values (270) 350
69.6%
2023-12-10T19:01:37.123667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
403
 
17.6%
도 120
 
5.2%
남 96
 
4.2%
1 79
 
3.5%
시 74
 
3.2%
동 69
 
3.0%
전 63
 
2.8%
라 62
 
2.7%
로 61
 
2.7%
길 56
 
2.4%
Other values (151) 1203
52.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1464
64.0%
Space Separator 403
 
17.6%
Decimal Number 290
 
12.7%
Close Punctuation 47
 
2.1%
Open Punctuation 47
 
2.1%
Dash Punctuation 32
 
1.4%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 120
 
8.2%
남 96
 
6.6%
시 74
 
5.1%
동 69
 
4.7%
전 63
 
4.3%
라 62
 
4.2%
로 61
 
4.2%
길 56
 
3.8%
군 45
 
3.1%
제 40
 
2.7%
Other values (136) 778
53.1%
Decimal Number
ValueCountFrequency (%)
1 79
27.2%
2 45
15.5%
4 27
 
9.3%
8 25
 
8.6%
5 24
 
8.3%
3 22
 
7.6%
0 19
 
6.6%
9 17
 
5.9%
6 16
 
5.5%
7 16
 
5.5%
Space Separator
ValueCountFrequency (%)
403
100.0%
Close Punctuation
ValueCountFrequency (%)
) 47
100.0%
Open Punctuation
ValueCountFrequency (%)
( 47
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1464
64.0%
Common 822
36.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 120
 
8.2%
남 96
 
6.6%
시 74
 
5.1%
동 69
 
4.7%
전 63
 
4.3%
라 62
 
4.2%
로 61
 
4.2%
길 56
 
3.8%
군 45
 
3.1%
제 40
 
2.7%
Other values (136) 778
53.1%
Common
ValueCountFrequency (%)
403
49.0%
1 79
 
9.6%
) 47
 
5.7%
( 47
 
5.7%
2 45
 
5.5%
- 32
 
3.9%
4 27
 
3.3%
8 25
 
3.0%
5 24
 
2.9%
3 22
 
2.7%
Other values (5) 71
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1464
64.0%
ASCII 822
36.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
403
49.0%
1 79
 
9.6%
) 47
 
5.7%
( 47
 
5.7%
2 45
 
5.5%
- 32
 
3.9%
4 27
 
3.3%
8 25
 
3.0%
5 24
 
2.9%
3 22
 
2.7%
Other values (5) 71
 
8.6%
Hangul
ValueCountFrequency (%)
도 120
 
8.2%
남 96
 
6.6%
시 74
 
5.1%
동 69
 
4.7%
전 63
 
4.3%
라 62
 
4.2%
로 61
 
4.2%
길 56
 
3.8%
군 45
 
3.1%
제 40
 
2.7%
Other values (136) 778
53.1%

zip_cd
Real number (ℝ)

Distinct92
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57619.51
Minimum2570
Maximum63643
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:01:37.482909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2570
5-th percentile52399.7
Q158380.25
median59222.5
Q359732.5
95-th percentile63511.8
Maximum63643
Range61073
Interquartile range (IQR)1352.25

Descriptive statistics

Standard deviation7998.045
Coefficient of variation (CV)0.13880793
Kurtosis29.849667
Mean57619.51
Median Absolute Deviation (MAD)616.5
Skewness-4.9692204
Sum5761951
Variance63968723
MonotonicityNot monotonic
2023-12-10T19:01:37.797583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
59677 3
 
3.0%
63192 3
 
3.0%
53223 2
 
2.0%
59752 2
 
2.0%
59425 2
 
2.0%
63264 2
 
2.0%
59458 1
 
1.0%
52415 1
 
1.0%
58652 1
 
1.0%
58416 1
 
1.0%
Other values (82) 82
82.0%
ValueCountFrequency (%)
2570 1
1.0%
15069 1
1.0%
42212 1
1.0%
46968 1
1.0%
52318 1
1.0%
52404 1
1.0%
52415 1
1.0%
52431 1
1.0%
52437 1
1.0%
52566 1
1.0%
ValueCountFrequency (%)
63643 1
1.0%
63640 1
1.0%
63597 1
1.0%
63591 1
1.0%
63546 1
1.0%
63510 1
1.0%
63506 1
1.0%
63361 1
1.0%
63264 2
2.0%
63254 1
1.0%

grid_cd
Text

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:01:38.278296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters800
Distinct characters15
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

Unique95 ?
Unique (%)95.0%

Sample

1st row나나833706
2nd row다나127736
3rd row나나997737
4th row나나839707
5th row다나139738
ValueCountFrequency (%)
라라150410 3
 
3.0%
다다095026 2
 
2.0%
라라209385 1
 
1.0%
나나833706 1
 
1.0%
라라360496 1
 
1.0%
나라987461 1
 
1.0%
다라268454 1
 
1.0%
다라767458 1
 
1.0%
라라415452 1
 
1.0%
다라848429 1
 
1.0%
Other values (87) 87
87.0%
2023-12-10T19:01:39.041341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
라 98
12.2%
0 73
9.1%
1 70
8.8%
다 69
8.6%
4 67
8.4%
5 65
8.1%
3 63
7.9%
8 56
7.0%
9 55
6.9%
2 53
6.6%
Other values (5) 131
16.4%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 73
12.2%
1 70
11.7%
4 67
11.2%
5 65
10.8%
3 63
10.5%
8 56
9.3%
9 55
9.2%
2 53
8.8%
6 50
8.3%
7 48
8.0%
Other Letter
ValueCountFrequency (%)
라 98
49.0%
다 69
34.5%
나 21
 
10.5%
마 10
 
5.0%
사 2
 
1.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 73
12.2%
1 70
11.7%
4 67
11.2%
5 65
10.8%
3 63
10.5%
8 56
9.3%
9 55
9.2%
2 53
8.8%
6 50
8.3%
7 48
8.0%
Hangul
ValueCountFrequency (%)
라 98
49.0%
다 69
34.5%
나 21
 
10.5%
마 10
 
5.0%
사 2
 
1.0%

Most occurring blocks

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

Most frequent character per block

Hangul
ValueCountFrequency (%)
라 98
49.0%
다 69
34.5%
나 21
 
10.5%
마 10
 
5.0%
사 2
 
1.0%
ASCII
ValueCountFrequency (%)
0 73
12.2%
1 70
11.7%
4 67
11.2%
5 65
10.8%
3 63
10.5%
8 56
9.3%
9 55
9.2%
2 53
8.8%
6 50
8.3%
7 48
8.0%

x_cd
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.15464
Minimum126.19213
Maximum128.98417
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:01:39.306762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.19213
5-th percentile126.27362
Q1126.53873
median126.92436
Q3127.70474
95-th percentile128.6901
Maximum128.98417
Range2.792043
Interquartile range (IQR)1.166003

Descriptive statistics

Standard deviation0.73150267
Coefficient of variation (CV)0.0057528588
Kurtosis-0.34505674
Mean127.15464
Median Absolute Deviation (MAD)0.4332635
Skewness0.79175442
Sum12715.464
Variance0.53509616
MonotonicityNot monotonic
2023-12-10T19:01:39.603087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.247964 1
 
1.0%
127.640531 1
 
1.0%
128.424603 1
 
1.0%
127.894362 1
 
1.0%
126.393356 1
 
1.0%
126.700786 1
 
1.0%
127.245838 1
 
1.0%
127.953855 1
 
1.0%
127.334679 1
 
1.0%
126.403262 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
126.19213 1
1.0%
126.247964 1
1.0%
126.254648 1
1.0%
126.25745 1
1.0%
126.26473 1
1.0%
126.274089 1
1.0%
126.312661 1
1.0%
126.37736 1
1.0%
126.386854 1
1.0%
126.393191 1
1.0%
ValueCountFrequency (%)
128.984173 1
1.0%
128.73189 1
1.0%
128.730839 1
1.0%
128.729536 1
1.0%
128.69062 1
1.0%
128.690077 1
1.0%
128.689199 1
1.0%
128.631871 1
1.0%
128.613071 1
1.0%
128.424603 1
1.0%

y_cd
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.558071
Minimum33.220605
Maximum37.58153
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:01:39.918875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.220605
5-th percentile33.411789
Q134.46078
median34.752118
Q334.846019
95-th percentile35.020521
Maximum37.58153
Range4.360925
Interquartile range (IQR)0.38523875

Descriptive statistics

Standard deviation0.69743243
Coefficient of variation (CV)0.020181463
Kurtosis5.057173
Mean34.558071
Median Absolute Deviation (MAD)0.1443045
Skewness0.74146771
Sum3455.8071
Variance0.48641199
MonotonicityNot monotonic
2023-12-10T19:01:40.210290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.220605 1
 
1.0%
34.789392 1
 
1.0%
34.845263 1
 
1.0%
34.840604 1
 
1.0%
34.80454 1
 
1.0%
34.801036 1
 
1.0%
34.806545 1
 
1.0%
34.80084 1
 
1.0%
34.781236 1
 
1.0%
34.792917 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
33.220605 1
1.0%
33.222123 1
1.0%
33.250451 1
1.0%
33.250811 1
1.0%
33.252095 1
1.0%
33.420194 1
1.0%
33.45183 1
1.0%
33.464087 1
1.0%
33.496362 1
1.0%
33.497295 1
1.0%
ValueCountFrequency (%)
37.58153 1
1.0%
37.339387 1
1.0%
35.820916 1
1.0%
35.163631 1
1.0%
35.113755 1
1.0%
35.015614 1
1.0%
34.943801 1
1.0%
34.938195 1
1.0%
34.932152 1
1.0%
34.92888 1
1.0%

mrkt_ty
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
5일장
50 
상설장
50 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5일장
2nd row상설장
3rd row5일장
4th row상설장
5th row5일장

Common Values

ValueCountFrequency (%)
5일장 50
50.0%
상설장 50
50.0%

Length

2023-12-10T19:01:40.454982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:01:40.801973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5일장 50
50.0%
상설장 50
50.0%

mrkt_opn_cycle
Categorical

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
5일
50 
상설장
48 
6일
 
1
상시
 
1

Length

Max length3
Median length2
Mean length2.48
Min length2

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row5일
2nd row상설장
3rd row5일
4th row상설장
5th row5일

Common Values

ValueCountFrequency (%)
5일 50
50.0%
상설장 48
48.0%
6일 1
 
1.0%
상시 1
 
1.0%

Length

2023-12-10T19:01:41.087461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:01:41.313318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5일 50
50.0%
상설장 48
48.0%
6일 1
 
1.0%
상시 1
 
1.0%

stor_cnt
Real number (ℝ)

Distinct82
Distinct (%)82.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean223.39
Minimum6
Maximum4310
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:01:41.578500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile17
Q143.75
median85
Q3176.75
95-th percentile760.75
Maximum4310
Range4304
Interquartile range (IQR)133

Descriptive statistics

Standard deviation524.84691
Coefficient of variation (CV)2.3494647
Kurtosis41.246828
Mean223.39
Median Absolute Deviation (MAD)54.5
Skewness5.9682725
Sum22339
Variance275464.28
MonotonicityNot monotonic
2023-12-10T19:01:41.865501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50 4
 
4.0%
52 2
 
2.0%
34 2
 
2.0%
95 2
 
2.0%
32 2
 
2.0%
70 2
 
2.0%
140 2
 
2.0%
28 2
 
2.0%
17 2
 
2.0%
40 2
 
2.0%
Other values (72) 78
78.0%
ValueCountFrequency (%)
6 1
1.0%
7 1
1.0%
12 1
1.0%
15 1
1.0%
17 2
2.0%
19 1
1.0%
20 1
1.0%
22 2
2.0%
23 1
1.0%
28 2
2.0%
ValueCountFrequency (%)
4310 1
1.0%
2620 1
1.0%
1111 1
1.0%
1050 1
1.0%
965 1
1.0%
750 1
1.0%
661 1
1.0%
610 1
1.0%
553 1
1.0%
503 1
1.0%

trt_itm
Text

Distinct56
Distinct (%)56.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:01:42.257776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length38
Mean length33.08
Min length7

Characters and Unicode

Total characters3308
Distinct characters33
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

Unique39 ?
Unique (%)39.0%

Sample

1st row농산물+축산물+수산물+의류및신발+가정용품+음식점업+기타소매업 등
2nd row농산물+수산물+음식점업 등
3rd row가공식품+의류및신발+가정용품+음식점업+기타소매업+근린생활서비스 등
4th row농산물+축산물+가공식품+의류및신발+가정용품+음식점업+기타소매업 등
5th row의류및신발+가정용품+기타소매업+근린생활서비스 등
ValueCountFrequency (%)
등 95
48.7%
농산물+축산물+수산물+가공식품+의류및신발+가정용품+음식점업+기타소매업+근린생활서비스 24
 
12.3%
의류및신발 5
 
2.6%
의류및신발+기타소매업 3
 
1.5%
농산물+축산물+수산물+의류및신발+가정용품+음식점업+기타소매업+근린생활서비스 3
 
1.5%
농산물+수산물+가공식품+의류및신발+가정용품+음식점업+기타소매업+근린생활서비스 2
 
1.0%
농산물+축산물+수산물+의류및신발+가정용품+음식점업+기타소매업 2
 
1.0%
농산물+축산물+수산물+가공식품+의류및신발+가정용품+음식점업 2
 
1.0%
농산물+축산물+수산물+가공식품+의류및신발+음식점업+근린생활서비스 2
 
1.0%
농산물+축산물+수산물+의류및신발+가정용품+음식점업 2
 
1.0%
Other values (47) 55
28.2%
2023-12-10T19:01:42.879345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
+ 501
 
15.1%
물 199
 
6.0%
산 199
 
6.0%
업 153
 
4.6%
식 139
 
4.2%
품 127
 
3.8%
가 127
 
3.8%
등 95
 
2.9%
95
 
2.9%
류 81
 
2.4%
Other values (23) 1592
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2712
82.0%
Math Symbol 501
 
15.1%
Space Separator 95
 
2.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
물 199
 
7.3%
산 199
 
7.3%
업 153
 
5.6%
식 139
 
5.1%
품 127
 
4.7%
가 127
 
4.7%
등 95
 
3.5%
류 81
 
3.0%
및 81
 
3.0%
신 81
 
3.0%
Other values (21) 1430
52.7%
Math Symbol
ValueCountFrequency (%)
+ 501
100.0%
Space Separator
ValueCountFrequency (%)
95
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2712
82.0%
Common 596
 
18.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
물 199
 
7.3%
산 199
 
7.3%
업 153
 
5.6%
식 139
 
5.1%
품 127
 
4.7%
가 127
 
4.7%
등 95
 
3.5%
류 81
 
3.0%
및 81
 
3.0%
신 81
 
3.0%
Other values (21) 1430
52.7%
Common
ValueCountFrequency (%)
+ 501
84.1%
95
 
15.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2712
82.0%
ASCII 596
 
18.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
+ 501
84.1%
95
 
15.9%
Hangul
ValueCountFrequency (%)
물 199
 
7.3%
산 199
 
7.3%
업 153
 
5.6%
식 139
 
5.1%
품 127
 
4.7%
가 127
 
4.7%
등 95
 
3.5%
류 81
 
3.0%
및 81
 
3.0%
신 81
 
3.0%
Other values (21) 1430
52.7%

use_psbl_gcct
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
온누리상품권
75 
-
25 

Length

Max length6
Median length6
Mean length4.75
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
온누리상품권 75
75.0%
- 25
 
25.0%

Length

2023-12-10T19:01:43.370883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:01:43.715559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
온누리상품권 75
75.0%
25
 
25.0%

hmpg
Categorical

IMBALANCE 

Distinct14
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
-
86 
미보유
 
2
sgp.market.jeju.kr
 
1
http://sgp5.market.jeju.kr/
 
1
http://jeju5.market.jeju.kr/
 
1
Other values (9)
9 

Length

Max length32
Median length1
Mean length3.5
Min length1

Unique

Unique12 ?
Unique (%)12.0%

Sample

1st row-
2nd rowsgp.market.jeju.kr
3rd row-
4th row-
5th rowhttp://sgp5.market.jeju.kr/

Common Values

ValueCountFrequency (%)
- 86
86.0%
미보유 2
 
2.0%
sgp.market.jeju.kr 1
 
1.0%
http://sgp5.market.jeju.kr/ 1
 
1.0%
http://jeju5.market.jeju.kr/ 1
 
1.0%
http://dm.market.jeju.kr/ 1
 
1.0%
http://sm.market.jeju.kr/ 1
 
1.0%
<NA> 1
 
1.0%
www.app eout et.kr 1
 
1.0%
http://jnjmarket.modoo.at/ 1
 
1.0%
Other values (4) 4
 
4.0%

Length

2023-12-10T19:01:44.000168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
86
82.7%
미보유 2
 
1.9%
http://www.seou 1
 
1.0%
og.naver.com/tyjamarket 1
 
1.0%
http://b 1
 
1.0%
mokpodongbu.com 1
 
1.0%
www.mpsusan.co.kr 1
 
1.0%
http://jnjmarket.modoo.at 1
 
1.0%
et.kr 1
 
1.0%
eout 1
 
1.0%
Other values (8) 8
 
7.7%

pbctlt_pos_yn
Boolean

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
True
98 
False
 
2
ValueCountFrequency (%)
True 98
98.0%
False 2
 
2.0%
2023-12-10T19:01:44.229962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

prklt_pos_yn
Boolean

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
True
80 
False
20 
ValueCountFrequency (%)
True 80
80.0%
False 20
 
20.0%
2023-12-10T19:01:44.421758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

opnng_yy
Real number (ℝ)

MISSING 

Distinct37
Distinct (%)42.5%
Missing13
Missing (%)13.0%
Infinite0
Infinite (%)0.0%
Mean1996.8736
Minimum1945
Maximum2013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:01:44.722839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1945
5-th percentile1963.6
Q11991.5
median2003
Q32008
95-th percentile2012
Maximum2013
Range68
Interquartile range (IQR)16.5

Descriptive statistics

Standard deviation15.987498
Coefficient of variation (CV)0.0080062648
Kurtosis1.6712069
Mean1996.8736
Median Absolute Deviation (MAD)7
Skewness-1.4898497
Sum173728
Variance255.60011
MonotonicityNot monotonic
2023-12-10T19:01:45.448435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
2008 9
 
9.0%
2005 7
 
7.0%
2004 6
 
6.0%
2002 5
 
5.0%
2013 4
 
4.0%
2011 4
 
4.0%
2012 4
 
4.0%
2007 3
 
3.0%
2010 3
 
3.0%
1995 3
 
3.0%
Other values (27) 39
39.0%
(Missing) 13
 
13.0%
ValueCountFrequency (%)
1945 1
 
1.0%
1950 1
 
1.0%
1952 1
 
1.0%
1954 1
 
1.0%
1963 1
 
1.0%
1965 1
 
1.0%
1972 1
 
1.0%
1974 3
3.0%
1975 2
2.0%
1976 1
 
1.0%
ValueCountFrequency (%)
2013 4
4.0%
2012 4
4.0%
2011 4
4.0%
2010 3
 
3.0%
2009 1
 
1.0%
2008 9
9.0%
2007 3
 
3.0%
2006 2
 
2.0%
2005 7
7.0%
2004 6
6.0%

telno
Text

MISSING 

Distinct40
Distinct (%)97.6%
Missing59
Missing (%)59.0%
Memory size932.0 B
2023-12-10T19:01:45.919660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.926829
Min length11

Characters and Unicode

Total characters489
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

Unique39 ?
Unique (%)95.1%

Sample

1st row064-762-1949
2nd row064-763-0965
3rd row064-723-1510
4th row064-757-8805
5th row064-743-5985
ValueCountFrequency (%)
061-245-5096 2
 
4.9%
061-642-6720 1
 
2.4%
061-276-5787 1
 
2.4%
061-641-0159 1
 
2.4%
061-682-3131 1
 
2.4%
061-852-3142 1
 
2.4%
061-247-8272 1
 
2.4%
061-284-4389 1
 
2.4%
061-245-1615 1
 
2.4%
054-372-3193 1
 
2.4%
Other values (30) 30
73.2%
2023-12-10T19:01:46.637546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 82
16.8%
0 60
12.3%
6 60
12.3%
5 48
9.8%
3 40
8.2%
2 39
8.0%
4 39
8.0%
1 38
7.8%
8 33
6.7%
7 29
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 407
83.2%
Dash Punctuation 82
 
16.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 60
14.7%
6 60
14.7%
5 48
11.8%
3 40
9.8%
2 39
9.6%
4 39
9.6%
1 38
9.3%
8 33
8.1%
7 29
7.1%
9 21
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 489
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 82
16.8%
0 60
12.3%
6 60
12.3%
5 48
9.8%
3 40
8.2%
2 39
8.0%
4 39
8.0%
1 38
7.8%
8 33
6.7%
7 29
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 489
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 82
16.8%
0 60
12.3%
6 60
12.3%
5 48
9.8%
3 40
8.2%
2 39
8.0%
4 39
8.0%
1 38
7.8%
8 33
6.7%
7 29
 
5.9%

data_stdde
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20190404
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20190404
2nd row20190404
3rd row20190404
4th row20190404
5th row20190404

Common Values

ValueCountFrequency (%)
20190404 100
100.0%

Length

2023-12-10T19:01:46.991904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:01:47.189533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20190404 100
100.0%

lst_updt_dt
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20191113
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20191113
2nd row20191113
3rd row20191113
4th row20191113
5th row20191113

Common Values

ValueCountFrequency (%)
20191113 100
100.0%

Length

2023-12-10T19:01:47.397684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:01:47.674262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20191113 100
100.0%

data_orgn
Categorical

CONSTANT 

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

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
소상공인진흥공단 100
100.0%

Length

2023-12-10T19:01:47.851653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:01:48.024223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소상공인진흥공단 100
100.0%

FILE_NAME
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
KC_483_DMSTC_MCST_TRNMKT_2019
100 

Length

Max length29
Median length29
Mean length29
Min length29

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKC_483_DMSTC_MCST_TRNMKT_2019
2nd rowKC_483_DMSTC_MCST_TRNMKT_2019
3rd rowKC_483_DMSTC_MCST_TRNMKT_2019
4th rowKC_483_DMSTC_MCST_TRNMKT_2019
5th rowKC_483_DMSTC_MCST_TRNMKT_2019

Common Values

ValueCountFrequency (%)
KC_483_DMSTC_MCST_TRNMKT_2019 100
100.0%

Length

2023-12-10T19:01:48.198169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:01:48.383014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kc_483_dmstc_mcst_trnmkt_2019 100
100.0%

base_ymd
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20191125
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20191125
2nd row20191125
3rd row20191125
4th row20191125
5th row20191125

Common Values

ValueCountFrequency (%)
20191125 100
100.0%

Length

2023-12-10T19:01:48.595338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:01:48.781303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20191125 100
100.0%

Sample

idlclasmlsfcfclt_namectprvn_nmsgnr_nmlegaldong_cdlegalemd_nmadstrd_cdadstrd_nmrdnmaddr_cdrdnm_addrzip_cdgrid_cdx_cdy_cdmrkt_tymrkt_opn_cyclestor_cnttrt_itmuse_psbl_gccthmpgpbctlt_pos_ynprklt_pos_ynopnng_yytelnodata_stddelst_updt_dtdata_orgnFILE_NAMEbase_ymd
0KC483PC19N000001쇼핑전통시장대정오일시장제주특별자치도서귀포시5013025022대정읍5013025000대정읍501304850552제주특별자치도 서귀포시 대정읍 신영로36번길 6563506나나833706126.24796433.2206055일장5일52농산물+축산물+수산물+의류및신발+가정용품+음식점업+기타소매업 등온누리상품권-YY<NA><NA>2019040420191113소상공인진흥공단KC_483_DMSTC_MCST_TRNMKT_201920191125
1KC483PC19N000002쇼핑전통시장서귀포매일올레시장제주특별자치도서귀포시5013010100서귀동5013053000중앙동501304850829제주특별자치도 서귀포시 중앙로62번길 20 (서귀동)63591다나127736126.56334233.250451상설장상설장35농산물+수산물+음식점업 등온누리상품권sgp.market.jeju.krYY2010064-762-19492019040420191113소상공인진흥공단KC_483_DMSTC_MCST_TRNMKT_201920191125
2KC483PC19N000003쇼핑전통시장중문오일시장제주특별자치도서귀포시5013011200중문동5013061000중문동501304850848제주특별자치도 서귀포시 천제연로188번길 12 (중문동)63546나나997737126.42407633.2508115일장5일179가공식품+의류및신발+가정용품+음식점업+기타소매업+근린생활서비스 등온누리상품권-YN<NA><NA>2019040420191113소상공인진흥공단KC_483_DMSTC_MCST_TRNMKT_201920191125
3KC483PC19N000004쇼핑전통시장모슬포중앙시장제주특별자치도서귀포시5013025022대정읍5013025000대정읍501303350122제주특별자치도 서귀포시 대정읍 상모로 32563510나나839707126.25464833.222123상설장상설장58농산물+축산물+가공식품+의류및신발+가정용품+음식점업+기타소매업 등온누리상품권-YY2008<NA>2019040420191113소상공인진흥공단KC_483_DMSTC_MCST_TRNMKT_201920191125
4KC483PC19N000005쇼핑전통시장서귀포향토오일시장제주특별자치도서귀포시5013010500동홍동5013057000동홍동501303350250제주특별자치도 서귀포시 정방연로 47-8 (동홍동)63597다나139738126.57614933.2520955일장5일125의류및신발+가정용품+기타소매업+근린생활서비스 등온누리상품권http://sgp5.market.jeju.kr/YY1995064-763-09652019040420191113소상공인진흥공단KC_483_DMSTC_MCST_TRNMKT_201920191125
5KC483PC19N000006쇼핑전통시장제주칠성로상점가(칠성로상점가)제주특별자치도제주시5011025023한림읍5011025000한림읍501104849019제주특별자치도 제주시 한림읍 한수풀로4길 1063026나나860927126.27408933.4201945일장5일44농산물+축산물+수산물+가공식품+의류및신발+가정용품+기타소매업+근린생활서비스 등온누리상품권-YY2004064-723-15102019040420191113소상공인진흥공단KC_483_DMSTC_MCST_TRNMKT_201920191125
6KC483PC19N000007쇼핑전통시장고성오일시장제주특별자치도서귀포시5013025924성산읍5013025900성산읍501303350018제주특별자치도 서귀포시 성산읍 고성오조로 9363640다나454957126.9131833.451835일장5일100농산물+축산물+수산물+가공식품+의류및신발+가정용품+음식점업+기타소매업+근린생활서비스 등온누리상품권-YY2008<NA>2019040420191113소상공인진흥공단KC_483_DMSTC_MCST_TRNMKT_201920191125
7KC483PC19N000008쇼핑전통시장성산오일시장제주특별자치도서귀포시5013025921성산읍5013025900성산읍501303350155제주특별자치도 서귀포시 성산읍 성산중앙로 41-863643다나473970126.93333733.4640875일장5일90농산물+축산물+수산물+가공식품+의류및신발+가정용품+음식점업+기타소매업+근린생활서비스 등온누리상품권-YN<NA><NA>2019040420191113소상공인진흥공단KC_483_DMSTC_MCST_TRNMKT_201920191125
8KC483PC19N000009쇼핑전통시장도남시장제주특별자치도제주시5011012900도남동5011054000이도2동501103349116제주특별자치도 제주시 신성로 91 (도남동, 성환아파트)63200다다097009126.52896933.496362상설장상설장363농산물+축산물+수산물+가공식품+의류및신발+가정용품+음식점업+기타소매업+근린생활서비스 등온누리상품권-YY1991064-757-88052019040420191113소상공인진흥공단KC_483_DMSTC_MCST_TRNMKT_201920191125
9KC483PC19N000010쇼핑전통시장제주시민속오일시장제주특별자치도제주시5011012700도두일동5011069000도두동501104848346제주특별자치도 제주시 오일장동길 51 (도두일동)63116다다049010126.47637633.4972955일장5일233의류및신발+가정용품+음식점업+기타소매업+근린생활서비스 등온누리상품권http://jeju5.market.jeju.kr/YY1998064-743-59852019040420191113소상공인진흥공단KC_483_DMSTC_MCST_TRNMKT_201920191125
idlclasmlsfcfclt_namectprvn_nmsgnr_nmlegaldong_cdlegalemd_nmadstrd_cdadstrd_nmrdnmaddr_cdrdnm_addrzip_cdgrid_cdx_cdy_cdmrkt_tymrkt_opn_cyclestor_cnttrt_itmuse_psbl_gccthmpgpbctlt_pos_ynprklt_pos_ynopnng_yytelnodata_stddelst_updt_dtdata_orgnFILE_NAMEbase_ymd
90KC483PC19N000091쇼핑전통시장도일시장경기도시흥시4139012700거모동4139058100군자동413903012020경기도 시흥시 도일로 100-4 (거모동)15069다사365269126.78404337.339387상설장5일81농산물가공식품의류및신발가정용품음식점업기타소매업근린생활서비스온누리상품권-NN<NA><NA>2019040420191113소상공인진흥공단KC_483_DMSTC_MCST_TRNMKT_201920191125
91KC483PC19N000092쇼핑전통시장서울약령시장서울특별시동대문구1123010300제기동1123054500제기동112304115261서울특별시 동대문구 약령중앙로8길 10 (제기동)2570다사591536127.03774237.58153상설장상설장95농산물+축산물+수산물+가공식품+의류및신발+가정용품+음식점업+기타소매업+근린생활서비스 등온누리상품권http://www.seou ya.com/YY200202-969-47932019040420191113소상공인진흥공단KC_483_DMSTC_MCST_TRNMKT_201920191125
92KC483PC19N000093쇼핑전통시장북천공설시장경상남도하동군4885039023북천면4885039000북천면488502332001경상남도 하동군 북천면 경서대로 2439-152318라라357799127.89203635.1137555일장5일110농산물+수산물+가공식품+의류및신발+가정용품+음식점업+기타소매업 등--YY2006<NA>2019040420191113소상공인진흥공단KC_483_DMSTC_MCST_TRNMKT_201920191125
93KC483PC19N000094쇼핑전통시장고현공설시장경상남도남해군4884037027고현면4884037000고현면488403343040경상남도 남해군 고현면 탑동로 68-252404라라340558127.87284534.8971065일장5일553의류및신발 등--YN<NA><NA>2019040420191113소상공인진흥공단KC_483_DMSTC_MCST_TRNMKT_201920191125
94KC483PC19N000095쇼핑전통시장삼천포용궁수산시장(구,삼천포서부시장))경상남도사천시4824010100동동4824051000동서동482404802481경상남도 사천시 어시장길 64 (동동)52569라라521593128.07113334.927432상설장상설장148농산물+축산물+수산물+가공식품+음식점업+근린생활서비스 등온누리상품권-YY2013<NA>2019040420191113소상공인진흥공단KC_483_DMSTC_MCST_TRNMKT_201920191125
95KC483PC19N000096쇼핑전통시장삼천포중앙시장경상남도사천시4824010300선구동4824052000선구동482404802637경상남도 사천시 중앙시장2길 37 (선구동)52568라라526594128.07668334.92888상설장상설장428농산물+축산물+수산물+가공식품+의류및신발+가정용품+음식점업+기타소매업+근린생활서비스 등온누리상품권-YY1974055-834-86762019040420191113소상공인진흥공단KC_483_DMSTC_MCST_TRNMKT_201920191125
96KC483PC19N000097쇼핑전통시장세지5일장전라남도나주시4617031028세지면4617031000세지면461703284041전라남도 나주시 세지면 세지로 409-458318다라309584126.74440434.9187945일장5일17축산물+의류및신발+음식점업+기타소매업+근린생활서비스 등온누리상품권-YY<NA><NA>2019040420191113소상공인진흥공단KC_483_DMSTC_MCST_TRNMKT_201920191125
97KC483PC19N000098쇼핑전통시장삼천포종합시장경상남도사천시4824010400동금동4824053000동서금동482404802335경상남도 사천시 새시장길 19 (동금동)52566라라528598128.07859134.9321525일장5일220농산물+축산물+수산물+가공식품+기타소매업 등온누리상품권-YY1990055-833-06622019040420191113소상공인진흥공단KC_483_DMSTC_MCST_TRNMKT_201920191125
98KC483PC19N000099쇼핑전통시장중마시장전라남도광양시4623010600중동4623053000중마동462303285041전라남도 광양시 중마중앙로 88 (중동)57787라라181603127.69885534.938195상설장상설장216농산물+축산물+수산물+가공식품+의류및신발+가정용품+음식점업+기타소매업+근린생활서비스 등온누리상품권-YY2005061-795-34842019040420191113소상공인진흥공단KC_483_DMSTC_MCST_TRNMKT_201920191125
99KC483PC19N000100쇼핑전통시장역전시장전라남도순천시4615011300덕암동4615057000덕연동461504649666전라남도 순천시 역전장길 9 (덕암동)57963라라003609127.50357134.943801상설장상설장36농산물+축산물+가공식품+의류및신발+가정용품+음식점업+기타소매업+근린생활서비스 등온누리상품권-YY1979061-245-50962019040420191113소상공인진흥공단KC_483_DMSTC_MCST_TRNMKT_201920191125