Overview

Dataset statistics

Number of variables33
Number of observations100
Missing cells171
Missing cells (%)5.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.1 KiB
Average record size in memory277.3 B

Variable types

Text13
Categorical10
Numeric10

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
supt_instt has 51 (51.0%) missing valuesMissing
telno has 2 (2.0%) missing valuesMissing
hmpg has 42 (42.0%) missing valuesMissing
rlt_inf has 76 (76.0%) missing valuesMissing
id has unique valuesUnique

Reproduction

Analysis started2023-12-10 09:39:58.825072
Analysis finished2023-12-10 09:40:00.742309
Duration1.92 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
2023-12-10T18:40:00.954079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length16
Min length16

Characters and Unicode

Total characters1600
Distinct characters15
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 rowKC488PO19N000001
2nd rowKC488PO19N000002
3rd rowKC488PO19N000003
4th rowKC488PO19N000004
5th rowKC488PO19N000005
ValueCountFrequency (%)
kc488po19n000001 1
 
1.0%
kc488po19n000064 1
 
1.0%
kc488po19n000075 1
 
1.0%
kc488po19n000074 1
 
1.0%
kc488po19n000073 1
 
1.0%
kc488po19n000072 1
 
1.0%
kc488po19n000071 1
 
1.0%
kc488po19n000070 1
 
1.0%
kc488po19n000069 1
 
1.0%
kc488po19n000068 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T18:40:01.758997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 419
26.2%
8 219
13.7%
1 127
 
7.9%
4 120
 
7.5%
9 115
 
7.2%
K 100
 
6.2%
C 100
 
6.2%
P 100
 
6.2%
O 100
 
6.2%
N 100
 
6.2%
Other values (5) 100
 
6.2%

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%
8 219
19.9%
1 127
 
11.5%
4 120
 
10.9%
9 115
 
10.5%
3 21
 
1.9%
5 21
 
1.9%
2 20
 
1.8%
6 19
 
1.7%
7 19
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
K 100
20.0%
C 100
20.0%
P 100
20.0%
O 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%
8 219
19.9%
1 127
 
11.5%
4 120
 
10.9%
9 115
 
10.5%
3 21
 
1.9%
5 21
 
1.9%
2 20
 
1.8%
6 19
 
1.7%
7 19
 
1.7%
Latin
ValueCountFrequency (%)
K 100
20.0%
C 100
20.0%
P 100
20.0%
O 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%
8 219
13.7%
1 127
 
7.9%
4 120
 
7.5%
9 115
 
7.2%
K 100
 
6.2%
C 100
 
6.2%
P 100
 
6.2%
O 100
 
6.2%
N 100
 
6.2%
Other values (5) 100
 
6.2%

lclas
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
행사 100
100.0%

Length

2023-12-10T18:40:01.982958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:40:02.178354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
행사 100
100.0%

mlsfc
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
행사 100
100.0%

Length

2023-12-10T18:40:02.392691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:40:02.617136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
행사 100
100.0%

fclt_name
Text

Distinct92
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:40:02.928725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length16
Mean length10.62
Min length4

Characters and Unicode

Total characters1062
Distinct characters231
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
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 row제13회 영동포도축제
2nd row제50회 영동난계국악축제
3rd row제8회 대한민국와인축제
4th row2017 영동곶감축제
5th row제22회 과천축제
ValueCountFrequency (%)
축제 8
 
3.8%
2019 4
 
1.9%
도봉 4
 
1.9%
구리 4
 
1.9%
코스모스 3
 
1.4%
유채꽃 3
 
1.4%
및 3
 
1.4%
제15회 3
 
1.4%
제16회 2
 
1.0%
구리한강 2
 
1.0%
Other values (149) 173
82.8%
2023-12-10T18:40:03.598891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 115
 
10.8%
109
 
10.3%
축 63
 
5.9%
회 39
 
3.7%
1 24
 
2.3%
정 19
 
1.8%
2 18
 
1.7%
도 16
 
1.5%
산 15
 
1.4%
의 15
 
1.4%
Other values (221) 629
59.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 864
81.4%
Space Separator 109
 
10.3%
Decimal Number 87
 
8.2%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 115
 
13.3%
축 63
 
7.3%
회 39
 
4.5%
정 19
 
2.2%
도 16
 
1.9%
산 15
 
1.7%
의 15
 
1.7%
봉 14
 
1.6%
대 14
 
1.6%
스 13
 
1.5%
Other values (209) 541
62.6%
Decimal Number
ValueCountFrequency (%)
1 24
27.6%
2 18
20.7%
0 11
12.6%
9 7
 
8.0%
3 6
 
6.9%
7 6
 
6.9%
6 5
 
5.7%
5 5
 
5.7%
8 3
 
3.4%
4 2
 
2.3%
Space Separator
ValueCountFrequency (%)
109
100.0%
Other Punctuation
ValueCountFrequency (%)
· 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 864
81.4%
Common 198
 
18.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 115
 
13.3%
축 63
 
7.3%
회 39
 
4.5%
정 19
 
2.2%
도 16
 
1.9%
산 15
 
1.7%
의 15
 
1.7%
봉 14
 
1.6%
대 14
 
1.6%
스 13
 
1.5%
Other values (209) 541
62.6%
Common
ValueCountFrequency (%)
109
55.1%
1 24
 
12.1%
2 18
 
9.1%
0 11
 
5.6%
9 7
 
3.5%
3 6
 
3.0%
7 6
 
3.0%
6 5
 
2.5%
5 5
 
2.5%
8 3
 
1.5%
Other values (2) 4
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 864
81.4%
ASCII 196
 
18.5%
None 2
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 115
 
13.3%
축 63
 
7.3%
회 39
 
4.5%
정 19
 
2.2%
도 16
 
1.9%
산 15
 
1.7%
의 15
 
1.7%
봉 14
 
1.6%
대 14
 
1.6%
스 13
 
1.5%
Other values (209) 541
62.6%
ASCII
ValueCountFrequency (%)
109
55.6%
1 24
 
12.2%
2 18
 
9.2%
0 11
 
5.6%
9 7
 
3.6%
3 6
 
3.1%
7 6
 
3.1%
6 5
 
2.6%
5 5
 
2.6%
8 3
 
1.5%
None
ValueCountFrequency (%)
· 2
100.0%

ctprvn_nm
Categorical

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
경기도
29 
충청북도
17 
서울특별시
15 
경상북도
10 
전라남도
8 
Other values (6)
21 

Length

Max length5
Median length4
Mean length3.9
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row충청북도
2nd row충청북도
3rd row충청북도
4th row충청북도
5th row경기도

Common Values

ValueCountFrequency (%)
경기도 29
29.0%
충청북도 17
17.0%
서울특별시 15
15.0%
경상북도 10
 
10.0%
전라남도 8
 
8.0%
전라북도 7
 
7.0%
경상남도 4
 
4.0%
울산광역시 4
 
4.0%
충청남도 2
 
2.0%
강원도 2
 
2.0%

Length

2023-12-10T18:40:03.884979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 29
29.0%
충청북도 17
17.0%
서울특별시 15
15.0%
경상북도 10
 
10.0%
전라남도 8
 
8.0%
전라북도 7
 
7.0%
경상남도 4
 
4.0%
울산광역시 4
 
4.0%
충청남도 2
 
2.0%
강원도 2
 
2.0%

sgnr_nm
Categorical

Distinct26
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
의정부시
16 
도봉구
14 
괴산군
8 
정읍시
7 
용인시 수지구
6 
Other values (21)
49 

Length

Max length7
Median length3
Mean length3.39
Min length2

Unique

Unique9 ?
Unique (%)9.0%

Sample

1st row영동군
2nd row영동군
3rd row영동군
4th row영동군
5th row과천시

Common Values

ValueCountFrequency (%)
의정부시 16
16.0%
도봉구 14
14.0%
괴산군 8
 
8.0%
정읍시 7
 
7.0%
용인시 수지구 6
 
6.0%
장성군 5
 
5.0%
파주시 5
 
5.0%
영동군 4
 
4.0%
통영시 4
 
4.0%
제천시 4
 
4.0%
Other values (16) 27
27.0%

Length

2023-12-10T18:40:04.137052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
의정부시 16
15.0%
도봉구 14
13.1%
괴산군 8
 
7.5%
정읍시 7
 
6.5%
용인시 6
 
5.6%
수지구 6
 
5.6%
장성군 5
 
4.7%
파주시 5
 
4.7%
영동군 4
 
3.7%
통영시 4
 
3.7%
Other values (18) 32
29.9%

legaldong_cd
Real number (ℝ)

Distinct59
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.8260286 × 109
Minimum1.1320106 × 109
Maximum4.822037 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:40:04.369544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1320106 × 109
5-th percentile1.1320106 × 109
Q14.1150101 × 109
median4.2325325 × 109
Q34.5180117 × 109
95-th percentile4.794025 × 109
Maximum4.822037 × 109
Range3.6900264 × 109
Interquartile range (IQR)4.030016 × 108

Descriptive statistics

Standard deviation1.2053431 × 109
Coefficient of variation (CV)0.31503766
Kurtosis1.0371575
Mean3.8260286 × 109
Median Absolute Deviation (MAD)2.6448518 × 108
Skewness-1.6035739
Sum3.8260286 × 1011
Variance1.452852 × 1018
MonotonicityNot monotonic
2023-12-10T18:40:04.662998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4115010100 10
 
10.0%
1132010600 8
 
8.0%
4146510300 6
 
6.0%
1132010800 6
 
6.0%
4315011300 4
 
4.0%
4794025024 4
 
4.0%
4374025028 3
 
3.0%
4115011100 3
 
3.0%
4518011700 2
 
2.0%
4476025028 2
 
2.0%
Other values (49) 52
52.0%
ValueCountFrequency (%)
1132010600 8
8.0%
1132010800 6
6.0%
1144012500 1
 
1.0%
2824510200 1
 
1.0%
2826011900 1
 
1.0%
3111010500 1
 
1.0%
3114010200 1
 
1.0%
3114010500 1
 
1.0%
3114011900 1
 
1.0%
4115010100 10
10.0%
ValueCountFrequency (%)
4822037021 1
 
1.0%
4822036025 1
 
1.0%
4822035021 1
 
1.0%
4822011700 1
 
1.0%
4794025024 4
4.0%
4790025025 1
 
1.0%
4773043030 1
 
1.0%
4773038040 1
 
1.0%
4773025031 1
 
1.0%
4725025025 1
 
1.0%

legalemd_nm
Text

Distinct57
Distinct (%)57.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:40:05.257945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.07
Min length2

Characters and Unicode

Total characters307
Distinct characters78
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

Unique43 ?
Unique (%)43.0%

Sample

1st row영동읍
2nd row영동읍
3rd row영동읍
4th row영동읍
5th row중앙동
ValueCountFrequency (%)
의정부동 10
 
10.0%
방학동 8
 
8.0%
동천동 6
 
6.0%
도봉동 6
 
6.0%
영동읍 4
 
4.0%
청전동 4
 
4.0%
울릉읍 4
 
4.0%
녹양동 3
 
3.0%
부전동 2
 
2.0%
감물면 2
 
2.0%
Other values (47) 51
51.0%
2023-12-10T18:40:05.932621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 66
21.5%
면 23
 
7.5%
읍 21
 
6.8%
부 14
 
4.6%
의 11
 
3.6%
정 10
 
3.3%
천 9
 
2.9%
방 8
 
2.6%
학 8
 
2.6%
도 7
 
2.3%
Other values (68) 130
42.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 307
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 66
21.5%
면 23
 
7.5%
읍 21
 
6.8%
부 14
 
4.6%
의 11
 
3.6%
정 10
 
3.3%
천 9
 
2.9%
방 8
 
2.6%
학 8
 
2.6%
도 7
 
2.3%
Other values (68) 130
42.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 307
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 66
21.5%
면 23
 
7.5%
읍 21
 
6.8%
부 14
 
4.6%
의 11
 
3.6%
정 10
 
3.3%
천 9
 
2.9%
방 8
 
2.6%
학 8
 
2.6%
도 7
 
2.3%
Other values (68) 130
42.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 307
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 66
21.5%
면 23
 
7.5%
읍 21
 
6.8%
부 14
 
4.6%
의 11
 
3.6%
정 10
 
3.3%
천 9
 
2.9%
방 8
 
2.6%
학 8
 
2.6%
도 7
 
2.3%
Other values (68) 130
42.3%

adstrd_cd
Real number (ℝ)

Distinct61
Distinct (%)61.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.8260552 × 109
Minimum1.1320521 × 109
Maximum4.822067 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:40:06.239608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1320521 × 109
5-th percentile1.1320522 × 109
Q14.115052 × 109
median4.2325325 × 109
Q34.5180538 × 109
95-th percentile4.794025 × 109
Maximum4.822067 × 109
Range3.6900149 × 109
Interquartile range (IQR)4.0300175 × 108

Descriptive statistics

Standard deviation1.2053289 × 109
Coefficient of variation (CV)0.31503177
Kurtosis1.0371909
Mean3.8260552 × 109
Median Absolute Deviation (MAD)2.64498 × 108
Skewness-1.6035888
Sum3.8260552 × 1011
Variance1.4528178 × 1018
MonotonicityNot monotonic
2023-12-10T18:40:06.525533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4115052000 9
 
9.0%
1132069000 6
 
6.0%
4146556000 6
 
6.0%
4374025000 4
 
4.0%
4315059000 4
 
4.0%
4794025000 4
 
4.0%
1132052100 4
 
4.0%
4115062000 3
 
3.0%
4376031000 2
 
2.0%
4476025000 2
 
2.0%
Other values (51) 56
56.0%
ValueCountFrequency (%)
1132052100 4
4.0%
1132052200 2
 
2.0%
1132069000 6
6.0%
1132070000 2
 
2.0%
1144073000 1
 
1.0%
2824561200 1
 
1.0%
2826072000 1
 
1.0%
3111058500 1
 
1.0%
3114057000 1
 
1.0%
3114060000 1
 
1.0%
ValueCountFrequency (%)
4822067000 1
 
1.0%
4822037000 1
 
1.0%
4822036000 1
 
1.0%
4822035000 1
 
1.0%
4794025000 4
4.0%
4790025000 1
 
1.0%
4773043000 1
 
1.0%
4773038000 1
 
1.0%
4773025000 1
 
1.0%
4725052000 1
 
1.0%

adstrd_nm
Text

Distinct60
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:40:06.965122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.59
Min length2

Characters and Unicode

Total characters359
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

Unique44 ?
Unique (%)44.0%

Sample

1st row영동읍
2nd row영동읍
3rd row영동읍
4th row영동읍
5th row중앙동
ValueCountFrequency (%)
의정부2동 9
 
9.0%
방학제1동 6
 
6.0%
동천동 6
 
6.0%
영동읍 4
 
4.0%
도봉제1동 4
 
4.0%
울릉읍 4
 
4.0%
청전동 4
 
4.0%
녹양동 3
 
3.0%
중앙동 2
 
2.0%
도봉제2동 2
 
2.0%
Other values (50) 56
56.0%
2023-12-10T18:40:07.651045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 66
18.4%
면 23
 
6.4%
읍 21
 
5.8%
2 18
 
5.0%
제 16
 
4.5%
부 12
 
3.3%
의 11
 
3.1%
정 10
 
2.8%
1 10
 
2.8%
산 10
 
2.8%
Other values (76) 162
45.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 330
91.9%
Decimal Number 29
 
8.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 66
20.0%
면 23
 
7.0%
읍 21
 
6.4%
제 16
 
4.8%
부 12
 
3.6%
의 11
 
3.3%
정 10
 
3.0%
산 10
 
3.0%
천 9
 
2.7%
방 8
 
2.4%
Other values (73) 144
43.6%
Decimal Number
ValueCountFrequency (%)
2 18
62.1%
1 10
34.5%
3 1
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 330
91.9%
Common 29
 
8.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 66
20.0%
면 23
 
7.0%
읍 21
 
6.4%
제 16
 
4.8%
부 12
 
3.6%
의 11
 
3.3%
정 10
 
3.0%
산 10
 
3.0%
천 9
 
2.7%
방 8
 
2.4%
Other values (73) 144
43.6%
Common
ValueCountFrequency (%)
2 18
62.1%
1 10
34.5%
3 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 330
91.9%
ASCII 29
 
8.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 66
20.0%
면 23
 
7.0%
읍 21
 
6.4%
제 16
 
4.8%
부 12
 
3.6%
의 11
 
3.3%
정 10
 
3.0%
산 10
 
3.0%
천 9
 
2.7%
방 8
 
2.4%
Other values (73) 144
43.6%
ASCII
ValueCountFrequency (%)
2 18
62.1%
1 10
34.5%
3 1
 
3.4%

rdnmaddr_cd
Real number (ℝ)

Distinct68
Distinct (%)68.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.8260452 × 1011
Minimum1.1320311 × 1011
Maximum4.822048 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:40:07.902779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1320311 × 1011
5-th percentile1.1320311 × 1011
Q14.1150318 × 1011
median4.2325323 × 1011
Q34.5180327 × 1011
95-th percentile4.7940478 × 1011
Maximum4.822048 × 1011
Range3.6900169 × 1011
Interquartile range (IQR)4.0300089 × 1010

Descriptive statistics

Standard deviation1.2053379 × 1011
Coefficient of variation (CV)0.31503495
Kurtosis1.03717
Mean3.8260452 × 1011
Median Absolute Deviation (MAD)2.6450039 × 1010
Skewness-1.6035802
Sum3.8260452 × 1013
Variance1.4528395 × 1022
MonotonicityNot monotonic
2023-12-10T18:40:08.455699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
414654853115 6
 
6.0%
113203109006 6
 
6.0%
411503181037 5
 
5.0%
431502239002 4
 
4.0%
113204127198 4
 
4.0%
479404778013 3
 
3.0%
411503181048 3
 
3.0%
437403243054 3
 
3.0%
411503181060 2
 
2.0%
414803206068 2
 
2.0%
Other values (58) 62
62.0%
ValueCountFrequency (%)
113203109006 6
6.0%
113204127075 2
 
2.0%
113204127135 2
 
2.0%
113204127198 4
4.0%
114403113018 1
 
1.0%
282453008034 1
 
1.0%
282603156173 1
 
1.0%
311103169016 1
 
1.0%
311403169026 1
 
1.0%
311403170054 1
 
1.0%
ValueCountFrequency (%)
482204799204 1
 
1.0%
482203333022 1
 
1.0%
482203333016 1
 
1.0%
482203333003 1
 
1.0%
479404778037 1
 
1.0%
479404778013 3
3.0%
479003307052 1
 
1.0%
477304745121 1
 
1.0%
477303018058 1
 
1.0%
477302018002 1
 
1.0%

rdnm_addr
Text

Distinct70
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:40:09.231293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length19.44
Min length13

Characters and Unicode

Total characters1944
Distinct characters152
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

Unique56 ?
Unique (%)56.0%

Sample

1st row충청북도 영동군 영동읍 영동황간로 122
2nd row충청북도 영동군 영동읍 학산영동로 1244-1
3rd row충청북도 영동군 영동읍 학산영동로 1244-1
4th row충청북도 영동군 영동읍 학산영동로 1244-1
5th row경기도 과천시 통영로 5
ValueCountFrequency (%)
경기도 29
 
6.4%
충청북도 17
 
3.8%
의정부시 16
 
3.5%
서울특별시 15
 
3.3%
도봉구 14
 
3.1%
경상북도 10
 
2.2%
전라남도 8
 
1.8%
괴산군 8
 
1.8%
정읍시 7
 
1.6%
전라북도 7
 
1.6%
Other values (193) 320
71.0%
2023-12-10T18:40:10.028669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
351
 
18.1%
도 107
 
5.5%
로 83
 
4.3%
시 69
 
3.5%
1 61
 
3.1%
2 57
 
2.9%
경 44
 
2.3%
북 37
 
1.9%
길 36
 
1.9%
4 35
 
1.8%
Other values (142) 1064
54.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1237
63.6%
Space Separator 351
 
18.1%
Decimal Number 334
 
17.2%
Dash Punctuation 22
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 107
 
8.6%
로 83
 
6.7%
시 69
 
5.6%
경 44
 
3.6%
북 37
 
3.0%
길 36
 
2.9%
정 34
 
2.7%
군 33
 
2.7%
산 31
 
2.5%
의 30
 
2.4%
Other values (130) 733
59.3%
Decimal Number
ValueCountFrequency (%)
1 61
18.3%
2 57
17.1%
4 35
10.5%
5 34
10.2%
3 28
8.4%
9 28
8.4%
0 26
7.8%
6 24
 
7.2%
7 22
 
6.6%
8 19
 
5.7%
Space Separator
ValueCountFrequency (%)
351
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1237
63.6%
Common 707
36.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 107
 
8.6%
로 83
 
6.7%
시 69
 
5.6%
경 44
 
3.6%
북 37
 
3.0%
길 36
 
2.9%
정 34
 
2.7%
군 33
 
2.7%
산 31
 
2.5%
의 30
 
2.4%
Other values (130) 733
59.3%
Common
ValueCountFrequency (%)
351
49.6%
1 61
 
8.6%
2 57
 
8.1%
4 35
 
5.0%
5 34
 
4.8%
3 28
 
4.0%
9 28
 
4.0%
0 26
 
3.7%
6 24
 
3.4%
7 22
 
3.1%
Other values (2) 41
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1237
63.6%
ASCII 707
36.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
351
49.6%
1 61
 
8.6%
2 57
 
8.1%
4 35
 
5.0%
5 34
 
4.8%
3 28
 
4.0%
9 28
 
4.0%
0 26
 
3.7%
6 24
 
3.4%
7 22
 
3.1%
Other values (2) 41
 
5.8%
Hangul
ValueCountFrequency (%)
도 107
 
8.6%
로 83
 
6.7%
시 69
 
5.6%
경 44
 
3.6%
북 37
 
3.0%
길 36
 
2.9%
정 34
 
2.7%
군 33
 
2.7%
산 31
 
2.5%
의 30
 
2.4%
Other values (130) 733
59.3%

zip_cd
Real number (ℝ)

Distinct68
Distinct (%)68.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26561.07
Minimum1300
Maximum58571
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:40:10.308000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1300
5-th percentile1330
Q111622
median27152
Q340222
95-th percentile57205.9
Maximum58571
Range57271
Interquartile range (IQR)28600

Descriptive statistics

Standard deviation18721.798
Coefficient of variation (CV)0.70485859
Kurtosis-1.1238036
Mean26561.07
Median Absolute Deviation (MAD)15530
Skewness0.34058093
Sum2656107
Variance3.5050574 × 108
MonotonicityNot monotonic
2023-12-10T18:40:10.579046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11622 7
 
7.0%
16802 6
 
6.0%
27152 4
 
4.0%
1300 4
 
4.0%
1331 4
 
4.0%
29149 3
 
3.0%
40222 3
 
3.0%
11606 3
 
3.0%
57205 2
 
2.0%
10808 2
 
2.0%
Other values (58) 62
62.0%
ValueCountFrequency (%)
1300 4
4.0%
1330 2
2.0%
1331 4
4.0%
1358 2
2.0%
1390 2
2.0%
3953 1
 
1.0%
10808 2
2.0%
10825 1
 
1.0%
10859 1
 
1.0%
10881 1
 
1.0%
ValueCountFrequency (%)
58571 1
1.0%
58504 1
1.0%
57250 1
1.0%
57231 1
1.0%
57223 1
1.0%
57205 2
2.0%
57103 1
1.0%
56204 1
1.0%
56198 2
2.0%
56164 1
1.0%

grid_cd
Text

Distinct71
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:40:11.188525image/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

Unique56 ?
Unique (%)56.0%

Sample

1st row라마253963
2nd row라마246974
3rd row라마246974
4th row라마246974
5th row다사548366
ValueCountFrequency (%)
다사628271 6
 
6.0%
다사589705 5
 
5.0%
다사600633 4
 
4.0%
라사636057 4
 
4.0%
라마246974 3
 
3.0%
다사584734 3
 
3.0%
사사011482 3
 
3.0%
다사592625 2
 
2.0%
다사601635 2
 
2.0%
다사588631 2
 
2.0%
Other values (61) 66
66.0%
2023-12-10T18:40:12.060925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 75
9.4%
5 73
9.1%
1 65
 
8.1%
2 63
 
7.9%
다 62
 
7.8%
사 58
 
7.2%
8 57
 
7.1%
7 57
 
7.1%
3 57
 
7.1%
4 53
 
6.6%
Other values (7) 180
22.5%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 75
12.5%
5 73
12.2%
1 65
10.8%
2 63
10.5%
8 57
9.5%
7 57
9.5%
3 57
9.5%
4 53
8.8%
0 52
8.7%
9 48
8.0%
Other Letter
ValueCountFrequency (%)
다 62
31.0%
사 58
29.0%
라 36
18.0%
마 24
 
12.0%
바 17
 
8.5%
아 2
 
1.0%
나 1
 
0.5%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
6 75
12.5%
5 73
12.2%
1 65
10.8%
2 63
10.5%
8 57
9.5%
7 57
9.5%
3 57
9.5%
4 53
8.8%
0 52
8.7%
9 48
8.0%
Hangul
ValueCountFrequency (%)
다 62
31.0%
사 58
29.0%
라 36
18.0%
마 24
 
12.0%
바 17
 
8.5%
아 2
 
1.0%
나 1
 
0.5%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 75
12.5%
5 73
12.2%
1 65
10.8%
2 63
10.5%
8 57
9.5%
7 57
9.5%
3 57
9.5%
4 53
8.8%
0 52
8.7%
9 48
8.0%
Hangul
ValueCountFrequency (%)
다 62
31.0%
사 58
29.0%
라 36
18.0%
마 24
 
12.0%
바 17
 
8.5%
아 2
 
1.0%
나 1
 
0.5%

x_cd
Real number (ℝ)

Distinct71
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.86519
Minimum34.633364
Maximum38.439744
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:40:12.309081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.633364
5-th percentile35.091591
Q136.173627
median37.342841
Q337.685654
95-th percentile37.792115
Maximum38.439744
Range3.8063803
Interquartile range (IQR)1.5120269

Descriptive statistics

Standard deviation0.99523874
Coefficient of variation (CV)0.026996707
Kurtosis-0.84540974
Mean36.86519
Median Absolute Deviation (MAD)0.43132429
Skewness-0.69724522
Sum3686.519
Variance0.99050015
MonotonicityNot monotonic
2023-12-10T18:40:12.623990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.342841 6
 
6.0%
37.7333859484 5
 
5.0%
37.6686287 4
 
4.0%
37.1486851887 4
 
4.0%
37.7600129873 3
 
3.0%
37.48430421 3
 
3.0%
36.1736274 3
 
3.0%
37.6707774 2
 
2.0%
37.6864694 2
 
2.0%
37.66667 2
 
2.0%
Other values (61) 66
66.0%
ValueCountFrequency (%)
34.63336365 1
1.0%
34.75930638 1
1.0%
34.82567453 1
1.0%
34.84549681 1
1.0%
34.860212 1
1.0%
35.103769 1
1.0%
35.182511 1
1.0%
35.252498 1
1.0%
35.320062 1
1.0%
35.372009 1
1.0%
ValueCountFrequency (%)
38.4397439656 1
 
1.0%
38.375898 1
 
1.0%
37.8893177 2
2.0%
37.864271 1
 
1.0%
37.7883176 1
 
1.0%
37.7600129873 3
3.0%
37.7447300381 1
 
1.0%
37.7437951815 1
 
1.0%
37.7396594 1
 
1.0%
37.739235 1
 
1.0%

y_cd
Real number (ℝ)

Distinct71
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.53269
Minimum126.3322
Maximum130.90564
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:40:13.010639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.3322
5-th percentile126.69899
Q1127.01155
median127.04725
Q3127.90336
95-th percentile129.33007
Maximum130.90564
Range4.5734458
Interquartile range (IQR)0.89181002

Descriptive statistics

Standard deviation0.97660554
Coefficient of variation (CV)0.0076576879
Kurtosis3.765327
Mean127.53269
Median Absolute Deviation (MAD)0.24589939
Skewness1.8842064
Sum12753.269
Variance0.95375838
MonotonicityNot monotonic
2023-12-10T18:40:13.283909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.081044 6
 
6.0%
127.0341283858 5
 
5.0%
127.0470496 4
 
4.0%
128.2168544304 4
 
4.0%
127.0279670699 3
 
3.0%
130.9056438274 3
 
3.0%
127.7739921 3
 
3.0%
127.0483768 2
 
2.0%
127.033968 2
 
2.0%
127.03375 2
 
2.0%
Other values (61) 66
66.0%
ValueCountFrequency (%)
126.332198 1
1.0%
126.463925 1
1.0%
126.530051 1
1.0%
126.6074636869 1
1.0%
126.6867920691 1
1.0%
126.6996301 1
1.0%
126.727118 1
1.0%
126.7289967898 1
1.0%
126.7400657 2
2.0%
126.746613 1
1.0%
ValueCountFrequency (%)
130.9056438274 3
3.0%
130.902073429 1
 
1.0%
129.3869567 1
 
1.0%
129.327076 1
 
1.0%
129.3257957 1
 
1.0%
129.2939697 1
 
1.0%
128.6768191 1
 
1.0%
128.5824608 1
 
1.0%
128.5100671 1
 
1.0%
128.4649304 1
 
1.0%

opmt_plce
Text

Distinct80
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:40:13.597717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length22
Mean length11.06
Min length3

Characters and Unicode

Total characters1106
Distinct characters191
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

Unique65 ?
Unique (%)65.0%

Sample

1st row영동군 영동읍 영동군체육관 일원
2nd row영동군 영동읍 영동천 일원(하상주차장, 난계사 등)
3rd row영동군 영동읍 영동천일원(하상주차장)
4th row영동군 영동읍 영동천일원(하상주차장)
5th row과천청사 잔디마당 등 과천시 일원
ValueCountFrequency (%)
일원 21
 
9.0%
광장 8
 
3.4%
구리한강 6
 
2.6%
도봉구청 6
 
2.6%
시민공원 6
 
2.6%
등 5
 
2.1%
일대 4
 
1.7%
영동군 4
 
1.7%
영동읍 4
 
1.7%
중랑천변 4
 
1.7%
Other values (139) 165
70.8%
2023-12-10T18:40:14.228998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
133
 
12.0%
원 62
 
5.6%
일 40
 
3.6%
장 28
 
2.5%
동 28
 
2.5%
공 25
 
2.3%
시 23
 
2.1%
의 21
 
1.9%
천 19
 
1.7%
도 18
 
1.6%
Other values (181) 709
64.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 930
84.1%
Space Separator 133
 
12.0%
Other Punctuation 18
 
1.6%
Close Punctuation 11
 
1.0%
Open Punctuation 11
 
1.0%
Decimal Number 2
 
0.2%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 62
 
6.7%
일 40
 
4.3%
장 28
 
3.0%
동 28
 
3.0%
공 25
 
2.7%
시 23
 
2.5%
의 21
 
2.3%
천 19
 
2.0%
도 18
 
1.9%
정 18
 
1.9%
Other values (175) 648
69.7%
Space Separator
ValueCountFrequency (%)
133
100.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 930
84.1%
Common 176
 
15.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 62
 
6.7%
일 40
 
4.3%
장 28
 
3.0%
동 28
 
3.0%
공 25
 
2.7%
시 23
 
2.5%
의 21
 
2.3%
천 19
 
2.0%
도 18
 
1.9%
정 18
 
1.9%
Other values (175) 648
69.7%
Common
ValueCountFrequency (%)
133
75.6%
, 18
 
10.2%
) 11
 
6.2%
( 11
 
6.2%
1 2
 
1.1%
~ 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 930
84.1%
ASCII 176
 
15.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
133
75.6%
, 18
 
10.2%
) 11
 
6.2%
( 11
 
6.2%
1 2
 
1.1%
~ 1
 
0.6%
Hangul
ValueCountFrequency (%)
원 62
 
6.7%
일 40
 
4.3%
장 28
 
3.0%
동 28
 
3.0%
공 25
 
2.7%
시 23
 
2.5%
의 21
 
2.3%
천 19
 
2.0%
도 18
 
1.9%
정 18
 
1.9%
Other values (175) 648
69.7%

fstvl_bgn_dt
Real number (ℝ)

Distinct75
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20179799
Minimum20150305
Maximum20200917
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:40:14.527647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20150305
5-th percentile20150891
Q120170922
median20190330
Q320190815
95-th percentile20191026
Maximum20200917
Range50612
Interquartile range (IQR)19893

Descriptive statistics

Standard deviation14852.119
Coefficient of variation (CV)0.00073598944
Kurtosis-0.31382525
Mean20179799
Median Absolute Deviation (MAD)781.5
Skewness-1.0536935
Sum2.0179799 × 109
Variance2.2058544 × 108
MonotonicityNot monotonic
2023-12-10T18:40:14.828542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190504 3
 
3.0%
20151009 3
 
3.0%
20191012 2
 
2.0%
20181005 2
 
2.0%
20190427 2
 
2.0%
20190511 2
 
2.0%
20190525 2
 
2.0%
20170921 2
 
2.0%
20191026 2
 
2.0%
20191004 2
 
2.0%
Other values (65) 78
78.0%
ValueCountFrequency (%)
20150305 2
2.0%
20150428 2
2.0%
20150508 1
 
1.0%
20150911 2
2.0%
20151002 2
2.0%
20151009 3
3.0%
20151016 2
2.0%
20151023 2
2.0%
20160513 1
 
1.0%
20160923 1
 
1.0%
ValueCountFrequency (%)
20200917 1
1.0%
20191221 1
1.0%
20191122 1
1.0%
20191102 1
1.0%
20191026 2
2.0%
20191020 1
1.0%
20191019 2
2.0%
20191018 2
2.0%
20191017 1
1.0%
20191012 2
2.0%

fstvl_end_dt
Real number (ℝ)

Distinct73
Distinct (%)73.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20179905
Minimum20150305
Maximum20200918
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:40:15.505437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20150305
5-th percentile20150999
Q120170924
median20190369
Q320190818
95-th percentile20191026
Maximum20200918
Range50613
Interquartile range (IQR)19894.25

Descriptive statistics

Standard deviation14925.687
Coefficient of variation (CV)0.00073963115
Kurtosis-0.33082546
Mean20179905
Median Absolute Deviation (MAD)746
Skewness-1.0283252
Sum2.0179905 × 109
Variance2.2277612 × 108
MonotonicityNot monotonic
2023-12-10T18:40:15.863215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20191020 7
 
7.0%
20170924 3
 
3.0%
20181014 3
 
3.0%
20151028 2
 
2.0%
20191026 2
 
2.0%
20181020 2
 
2.0%
20190526 2
 
2.0%
20190428 2
 
2.0%
20191005 2
 
2.0%
20171029 2
 
2.0%
Other values (63) 73
73.0%
ValueCountFrequency (%)
20150305 2
2.0%
20150510 1
1.0%
20150930 2
2.0%
20151003 2
2.0%
20151009 2
2.0%
20151011 1
1.0%
20151017 2
2.0%
20151022 2
2.0%
20151028 2
2.0%
20160515 1
1.0%
ValueCountFrequency (%)
20200918 1
 
1.0%
20200127 1
 
1.0%
20191124 1
 
1.0%
20191106 1
 
1.0%
20191031 1
 
1.0%
20191026 2
 
2.0%
20191020 7
7.0%
20191013 1
 
1.0%
20191012 1
 
1.0%
20191006 1
 
1.0%

fstvl_cn
Text

Distinct86
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:40:16.353495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length80
Median length40
Mean length23.14
Min length3

Characters and Unicode

Total characters2314
Distinct characters318
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)75.0%

Sample

1st row포도축제
2nd row국악축제
3rd row와인축제
4th row곶감축제
5th row문화예술 퍼포먼스, 시민참여 프로그램, 플리마켓 등
ValueCountFrequency (%)
등 48
 
9.2%
및 26
 
5.0%
체험 13
 
2.5%
공연 12
 
2.3%
전시 8
 
1.5%
체험행사 7
 
1.3%
홍보 7
 
1.3%
축제 6
 
1.1%
행사 6
 
1.1%
공연,체험,전시행사 5
 
1.0%
Other values (283) 385
73.6%
2023-12-10T18:40:17.142456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
423
 
18.3%
, 161
 
7.0%
등 55
 
2.4%
기 47
 
2.0%
체 47
 
2.0%
전 46
 
2.0%
험 45
 
1.9%
연 44
 
1.9%
사 42
 
1.8%
제 37
 
1.6%
Other values (308) 1367
59.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1697
73.3%
Space Separator 423
 
18.3%
Other Punctuation 169
 
7.3%
Decimal Number 12
 
0.5%
Open Punctuation 4
 
0.2%
Close Punctuation 4
 
0.2%
Uppercase Letter 2
 
0.1%
Math Symbol 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
등 55
 
3.2%
기 47
 
2.8%
체 47
 
2.8%
전 46
 
2.7%
험 45
 
2.7%
연 44
 
2.6%
사 42
 
2.5%
제 37
 
2.2%
행 36
 
2.1%
시 34
 
2.0%
Other values (293) 1264
74.5%
Decimal Number
ValueCountFrequency (%)
0 3
25.0%
9 3
25.0%
1 3
25.0%
2 2
16.7%
5 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 161
95.3%
· 8
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
R 1
50.0%
A 1
50.0%
Space Separator
ValueCountFrequency (%)
423
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
i 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1697
73.3%
Common 614
 
26.5%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
등 55
 
3.2%
기 47
 
2.8%
체 47
 
2.8%
전 46
 
2.7%
험 45
 
2.7%
연 44
 
2.6%
사 42
 
2.5%
제 37
 
2.2%
행 36
 
2.1%
시 34
 
2.0%
Other values (293) 1264
74.5%
Common
ValueCountFrequency (%)
423
68.9%
, 161
 
26.2%
· 8
 
1.3%
( 4
 
0.7%
) 4
 
0.7%
0 3
 
0.5%
9 3
 
0.5%
1 3
 
0.5%
2 2
 
0.3%
5 1
 
0.2%
Other values (2) 2
 
0.3%
Latin
ValueCountFrequency (%)
R 1
33.3%
A 1
33.3%
i 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1697
73.3%
ASCII 609
 
26.3%
None 8
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
423
69.5%
, 161
 
26.4%
( 4
 
0.7%
) 4
 
0.7%
0 3
 
0.5%
9 3
 
0.5%
1 3
 
0.5%
2 2
 
0.3%
5 1
 
0.2%
~ 1
 
0.2%
Other values (4) 4
 
0.7%
Hangul
ValueCountFrequency (%)
등 55
 
3.2%
기 47
 
2.8%
체 47
 
2.8%
전 46
 
2.7%
험 45
 
2.7%
연 44
 
2.6%
사 42
 
2.5%
제 37
 
2.2%
행 36
 
2.1%
시 34
 
2.0%
Other values (293) 1264
74.5%
None
ValueCountFrequency (%)
· 8
100.0%

mnnst
Text

Distinct68
Distinct (%)68.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:40:17.613652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length15
Mean length10.41
Min length3

Characters and Unicode

Total characters1041
Distinct characters187
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)59.0%

Sample

1st row(재)영동축제관광재단, (사)영동포도연합회
2nd row(재)영동축제관광재단, (사)난계기념사업회
3rd row(재)영동축제관광재단, 영동와인연구회
4th row(재)영동축제관광재단, 영동곶감연합회
5th row(재)과천축제
ValueCountFrequency (%)
서울특별시 14
 
10.0%
도봉구청 14
 
10.0%
사)한국예총 6
 
4.3%
구리지회 6
 
4.3%
의정부예술의전당 4
 
2.9%
정읍시 4
 
2.9%
재)영동축제관광재단 4
 
2.9%
의정부시장애인체육회 3
 
2.1%
장성군축제위원회 3
 
2.1%
재)제천문화재단 3
 
2.1%
Other values (75) 79
56.4%
2023-12-10T18:40:18.340013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
회 50
 
4.8%
40
 
3.8%
원 39
 
3.7%
제 34
 
3.3%
시 33
 
3.2%
위 31
 
3.0%
축 27
 
2.6%
구 24
 
2.3%
) 23
 
2.2%
( 23
 
2.2%
Other values (177) 717
68.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 944
90.7%
Space Separator 40
 
3.8%
Close Punctuation 23
 
2.2%
Open Punctuation 23
 
2.2%
Other Punctuation 7
 
0.7%
Math Symbol 2
 
0.2%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 50
 
5.3%
원 39
 
4.1%
제 34
 
3.6%
시 33
 
3.5%
위 31
 
3.3%
축 27
 
2.9%
구 24
 
2.5%
청 21
 
2.2%
정 21
 
2.2%
의 20
 
2.1%
Other values (169) 644
68.2%
Other Punctuation
ValueCountFrequency (%)
, 6
85.7%
/ 1
 
14.3%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
S 1
50.0%
Space Separator
ValueCountFrequency (%)
40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 944
90.7%
Common 95
 
9.1%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 50
 
5.3%
원 39
 
4.1%
제 34
 
3.6%
시 33
 
3.5%
위 31
 
3.3%
축 27
 
2.9%
구 24
 
2.5%
청 21
 
2.2%
정 21
 
2.2%
의 20
 
2.1%
Other values (169) 644
68.2%
Common
ValueCountFrequency (%)
40
42.1%
) 23
24.2%
( 23
24.2%
, 6
 
6.3%
+ 2
 
2.1%
/ 1
 
1.1%
Latin
ValueCountFrequency (%)
K 1
50.0%
S 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 944
90.7%
ASCII 97
 
9.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
회 50
 
5.3%
원 39
 
4.1%
제 34
 
3.6%
시 33
 
3.5%
위 31
 
3.3%
축 27
 
2.9%
구 24
 
2.5%
청 21
 
2.2%
정 21
 
2.2%
의 20
 
2.1%
Other values (169) 644
68.2%
ASCII
ValueCountFrequency (%)
40
41.2%
) 23
23.7%
( 23
23.7%
, 6
 
6.2%
+ 2
 
2.1%
/ 1
 
1.0%
K 1
 
1.0%
S 1
 
1.0%

auspc_instt
Categorical

Distinct49
Distinct (%)49.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울특별시 도봉구청
10 
괴산군
8 
정읍시
7 
경기도 구리시
 
6
의정부예술의전당
 
5
Other values (44)
64 

Length

Max length21
Median length17
Mean length8.34
Min length3

Unique

Unique31 ?
Unique (%)31.0%

Sample

1st row충청북도 영동군청, 영동군축제추진위원회
2nd row충청북도 영동군청, 영동군축제추진위원회
3rd row충청북도 영동군청, 영동군축제추진위원회
4th row충청북도 영동군청, 영동군축제추진위원회
5th row과천시

Common Values

ValueCountFrequency (%)
서울특별시 도봉구청 10
 
10.0%
괴산군 8
 
8.0%
정읍시 7
 
7.0%
경기도 구리시 6
 
6.0%
의정부예술의전당 5
 
5.0%
충청북도 영동군청, 영동군축제추진위원회 4
 
4.0%
울릉군 4
 
4.0%
(재)제천문화재단 3
 
3.0%
파주시 3
 
3.0%
전라남도 장성군 3
 
3.0%
Other values (39) 47
47.0%

Length

2023-12-10T18:40:18.610290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 15
 
10.3%
도봉구청 12
 
8.2%
경기도 9
 
6.2%
괴산군 8
 
5.5%
정읍시 7
 
4.8%
구리시 6
 
4.1%
의정부예술의전당 5
 
3.4%
영동군축제추진위원회 4
 
2.7%
울릉군 4
 
2.7%
영동군청 4
 
2.7%
Other values (49) 72
49.3%

supt_instt
Text

MISSING 

Distinct36
Distinct (%)73.5%
Missing51
Missing (%)51.0%
Memory size932.0 B
2023-12-10T18:40:19.081402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length31
Mean length15.061224
Min length1

Characters and Unicode

Total characters738
Distinct characters132
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)59.2%

Sample

1st row충청북도, 메이빌 농산물공동브랜드
2nd row문화체육관광부, 충청북도, 국립국악원, 한국관광공사, 한국지역진흥재단, 한국문황예술위원회
3rd row한국농수산식품유통공사, 충청북도, 영동군 농산물공동브랜드
4th row충청북도, 메이빌 농산물공동브랜드
5th row한국마사회 등
ValueCountFrequency (%)
등 9
 
7.6%
충청북도 6
 
5.0%
기관단체 6
 
5.0%
경기도+한국관광공사+경기관광공사 4
 
3.4%
제천시 4
 
3.4%
의성군 3
 
2.5%
3
 
2.5%
한국관광공사 3
 
2.5%
농산물공동브랜드 3
 
2.5%
통영시 3
 
2.5%
Other values (64) 75
63.0%
2023-12-10T18:40:19.852611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
70
 
9.5%
, 44
 
6.0%
관 34
 
4.6%
기 28
 
3.8%
도 26
 
3.5%
사 26
 
3.5%
공 23
 
3.1%
경 22
 
3.0%
한 22
 
3.0%
광 22
 
3.0%
Other values (122) 421
57.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 589
79.8%
Space Separator 70
 
9.5%
Other Punctuation 49
 
6.6%
Math Symbol 15
 
2.0%
Uppercase Letter 5
 
0.7%
Dash Punctuation 4
 
0.5%
Decimal Number 3
 
0.4%
Lowercase Letter 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 34
 
5.8%
기 28
 
4.8%
도 26
 
4.4%
사 26
 
4.4%
공 23
 
3.9%
경 22
 
3.7%
한 22
 
3.7%
광 22
 
3.7%
국 21
 
3.6%
단 16
 
2.7%
Other values (106) 349
59.3%
Uppercase Letter
ValueCountFrequency (%)
N 1
20.0%
H 1
20.0%
S 1
20.0%
K 1
20.0%
B 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 44
89.8%
/ 3
 
6.1%
. 2
 
4.1%
Lowercase Letter
ValueCountFrequency (%)
o 1
33.3%
i 1
33.3%
l 1
33.3%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%
Space Separator
ValueCountFrequency (%)
70
100.0%
Math Symbol
ValueCountFrequency (%)
+ 15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 589
79.8%
Common 141
 
19.1%
Latin 8
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 34
 
5.8%
기 28
 
4.8%
도 26
 
4.4%
사 26
 
4.4%
공 23
 
3.9%
경 22
 
3.7%
한 22
 
3.7%
광 22
 
3.7%
국 21
 
3.6%
단 16
 
2.7%
Other values (106) 349
59.3%
Common
ValueCountFrequency (%)
70
49.6%
, 44
31.2%
+ 15
 
10.6%
- 4
 
2.8%
/ 3
 
2.1%
. 2
 
1.4%
2 2
 
1.4%
8 1
 
0.7%
Latin
ValueCountFrequency (%)
N 1
12.5%
H 1
12.5%
S 1
12.5%
o 1
12.5%
i 1
12.5%
l 1
12.5%
K 1
12.5%
B 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 589
79.8%
ASCII 149
 
20.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
70
47.0%
, 44
29.5%
+ 15
 
10.1%
- 4
 
2.7%
/ 3
 
2.0%
. 2
 
1.3%
2 2
 
1.3%
8 1
 
0.7%
N 1
 
0.7%
H 1
 
0.7%
Other values (6) 6
 
4.0%
Hangul
ValueCountFrequency (%)
관 34
 
5.8%
기 28
 
4.8%
도 26
 
4.4%
사 26
 
4.4%
공 23
 
3.9%
경 22
 
3.7%
한 22
 
3.7%
광 22
 
3.7%
국 21
 
3.6%
단 16
 
2.7%
Other values (106) 349
59.3%

telno
Text

MISSING 

Distinct66
Distinct (%)67.3%
Missing2
Missing (%)2.0%
Memory size932.0 B
2023-12-10T18:40:20.323931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.928571
Min length11

Characters and Unicode

Total characters1169
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

Unique51 ?
Unique (%)52.0%

Sample

1st row043-745-8918
2nd row043-745-8917
3rd row043-745-8914
4th row043-745-8918
5th row02-504-0945
ValueCountFrequency (%)
031-550-2065 6
 
6.1%
02-905-4026 6
 
6.1%
061-390-7242 5
 
5.1%
02-2091-2254 4
 
4.1%
031-850-5755 4
 
4.1%
063-539-5233 3
 
3.1%
043-641-4870 3
 
3.1%
02-2091-2316 2
 
2.0%
031-828-5832 2
 
2.0%
031-850-5757 2
 
2.0%
Other values (56) 61
62.2%
2023-12-10T18:40:21.188306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 196
16.8%
0 190
16.3%
5 129
11.0%
2 128
10.9%
3 126
10.8%
4 90
7.7%
1 82
7.0%
6 65
 
5.6%
8 65
 
5.6%
9 59
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 973
83.2%
Dash Punctuation 196
 
16.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 190
19.5%
5 129
13.3%
2 128
13.2%
3 126
12.9%
4 90
9.2%
1 82
8.4%
6 65
 
6.7%
8 65
 
6.7%
9 59
 
6.1%
7 39
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1169
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 196
16.8%
0 190
16.3%
5 129
11.0%
2 128
10.9%
3 126
10.8%
4 90
7.7%
1 82
7.0%
6 65
 
5.6%
8 65
 
5.6%
9 59
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1169
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 196
16.8%
0 190
16.3%
5 129
11.0%
2 128
10.9%
3 126
10.8%
4 90
7.7%
1 82
7.0%
6 65
 
5.6%
8 65
 
5.6%
9 59
 
5.0%

hmpg
Text

MISSING 

Distinct32
Distinct (%)55.2%
Missing42
Missing (%)42.0%
Memory size932.0 B
2023-12-10T18:40:21.595206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length27
Mean length21.896552
Min length11

Characters and Unicode

Total characters1270
Distinct characters34
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)37.9%

Sample

1st rowwww.ydft.kr
2nd rowwww.ydft.kr
3rd rowwww.ydft.kr
4th rowwww.ydft.kr
5th rowhttp://www.gcfest.or.kr
ValueCountFrequency (%)
http://www.guri.go.kr 6
 
10.3%
http://tour.jangseong.go.kr 6
 
10.3%
www.ydft.kr 4
 
6.9%
http://www.uac.or.kr 4
 
6.9%
http://tour.usc.go.kr 3
 
5.2%
http://www.ulleung.go.kr/tour 3
 
5.2%
http://tour.paju.go.kr 3
 
5.2%
www.jcac.or.kr 3
 
5.2%
http://science.dobong.go.kr 2
 
3.4%
http://tour.muan.go.kr 2
 
3.4%
Other values (22) 22
37.9%
2023-12-10T18:40:22.212698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 154
12.1%
t 126
 
9.9%
w 113
 
8.9%
/ 111
 
8.7%
r 91
 
7.2%
o 88
 
6.9%
g 64
 
5.0%
h 56
 
4.4%
u 55
 
4.3%
p 54
 
4.3%
Other values (24) 358
28.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 950
74.8%
Other Punctuation 312
 
24.6%
Other Letter 8
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 126
13.3%
w 113
11.9%
r 91
9.6%
o 88
9.3%
g 64
 
6.7%
h 56
 
5.9%
u 55
 
5.8%
p 54
 
5.7%
k 53
 
5.6%
n 36
 
3.8%
Other values (13) 214
22.5%
Other Letter
ValueCountFrequency (%)
부 1
12.5%
여 1
12.5%
서 1
12.5%
동 1
12.5%
연 1
12.5%
꽃 1
12.5%
축 1
12.5%
제 1
12.5%
Other Punctuation
ValueCountFrequency (%)
. 154
49.4%
/ 111
35.6%
: 47
 
15.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 950
74.8%
Common 312
 
24.6%
Hangul 8
 
0.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 126
13.3%
w 113
11.9%
r 91
9.6%
o 88
9.3%
g 64
 
6.7%
h 56
 
5.9%
u 55
 
5.8%
p 54
 
5.7%
k 53
 
5.6%
n 36
 
3.8%
Other values (13) 214
22.5%
Hangul
ValueCountFrequency (%)
부 1
12.5%
여 1
12.5%
서 1
12.5%
동 1
12.5%
연 1
12.5%
꽃 1
12.5%
축 1
12.5%
제 1
12.5%
Common
ValueCountFrequency (%)
. 154
49.4%
/ 111
35.6%
: 47
 
15.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1262
99.4%
Hangul 8
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 154
12.2%
t 126
 
10.0%
w 113
 
9.0%
/ 111
 
8.8%
r 91
 
7.2%
o 88
 
7.0%
g 64
 
5.1%
h 56
 
4.4%
u 55
 
4.4%
p 54
 
4.3%
Other values (16) 350
27.7%
Hangul
ValueCountFrequency (%)
부 1
12.5%
여 1
12.5%
서 1
12.5%
동 1
12.5%
연 1
12.5%
꽃 1
12.5%
축 1
12.5%
제 1
12.5%

rlt_inf
Text

MISSING 

Distinct22
Distinct (%)91.7%
Missing76
Missing (%)76.0%
Memory size932.0 B
2023-12-10T18:40:22.656110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length30.5
Mean length24.208333
Min length4

Characters and Unicode

Total characters581
Distinct characters192
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

Unique20 ?
Unique (%)83.3%

Sample

1st row포도따기, 포도밟기 등 체험, 농특산물 판매, 전시, 추풍령가요제, 영동포도마라톤 대회
2nd row어가행렬, 종묘제례, 국악기제작 및 연주체험, 퓨전국악공연, 영동와인축제와 연계
3rd row와인전시, 시음행사, 와인판매, 난계국악축제와 연계
4th row곶감따기, 곶감 시식, 판매, 공연 프로그램
5th row서울대공원,서울랜드,과천과학관
ValueCountFrequency (%)
등 3
 
2.6%
행사 3
 
2.6%
판매 3
 
2.6%
장성호관광지 2
 
1.8%
연계 2
 
1.8%
백양사 2
 
1.8%
수 2
 
1.8%
즐길 2
 
1.8%
있는 2
 
1.8%
고구려대장간마을 2
 
1.8%
Other values (91) 91
79.8%
2023-12-10T18:40:23.504812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
90
 
15.5%
, 36
 
6.2%
사 13
 
2.2%
행 11
 
1.9%
시 10
 
1.7%
을 8
 
1.4%
제 8
 
1.4%
축 8
 
1.4%
연 8
 
1.4%
고 8
 
1.4%
Other values (182) 381
65.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 455
78.3%
Space Separator 90
 
15.5%
Other Punctuation 36
 
6.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 13
 
2.9%
행 11
 
2.4%
시 10
 
2.2%
을 8
 
1.8%
제 8
 
1.8%
축 8
 
1.8%
연 8
 
1.8%
고 8
 
1.8%
도 7
 
1.5%
이 7
 
1.5%
Other values (180) 367
80.7%
Space Separator
ValueCountFrequency (%)
90
100.0%
Other Punctuation
ValueCountFrequency (%)
, 36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 455
78.3%
Common 126
 
21.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 13
 
2.9%
행 11
 
2.4%
시 10
 
2.2%
을 8
 
1.8%
제 8
 
1.8%
축 8
 
1.8%
연 8
 
1.8%
고 8
 
1.8%
도 7
 
1.5%
이 7
 
1.5%
Other values (180) 367
80.7%
Common
ValueCountFrequency (%)
90
71.4%
, 36
 
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 455
78.3%
ASCII 126
 
21.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
90
71.4%
, 36
 
28.6%
Hangul
ValueCountFrequency (%)
사 13
 
2.9%
행 11
 
2.4%
시 10
 
2.2%
을 8
 
1.8%
제 8
 
1.8%
축 8
 
1.8%
연 8
 
1.8%
고 8
 
1.8%
도 7
 
1.5%
이 7
 
1.5%
Other values (180) 367
80.7%

data_stdde
Real number (ℝ)

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20187414
Minimum20180220
Maximum20191018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:40:23.930566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20180220
5-th percentile20180223
Q120180514
median20190701
Q320190916
95-th percentile20190930
Maximum20191018
Range10798
Interquartile range (IQR)10402

Descriptive statistics

Standard deviation4880.577
Coefficient of variation (CV)0.00024176336
Kurtosis-1.4864531
Mean20187414
Median Absolute Deviation (MAD)217.5
Skewness-0.73446394
Sum2.0187414 × 109
Variance23820032
MonotonicityNot monotonic
2023-12-10T18:40:24.440790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
20190701 16
16.0%
20180501 14
14.0%
20190930 11
11.0%
20190916 8
 
8.0%
20190723 6
 
6.0%
20180514 6
 
6.0%
20190909 5
 
5.0%
20190902 4
 
4.0%
20190923 4
 
4.0%
20190731 4
 
4.0%
Other values (12) 22
22.0%
ValueCountFrequency (%)
20180220 1
 
1.0%
20180221 2
 
2.0%
20180223 4
 
4.0%
20180501 14
14.0%
20180514 6
6.0%
20180615 2
 
2.0%
20180731 1
 
1.0%
20180809 1
 
1.0%
20181001 2
 
2.0%
20190522 3
 
3.0%
ValueCountFrequency (%)
20191018 1
 
1.0%
20190930 11
11.0%
20190923 4
 
4.0%
20190920 1
 
1.0%
20190917 3
 
3.0%
20190916 8
8.0%
20190909 5
5.0%
20190902 4
 
4.0%
20190829 1
 
1.0%
20190731 4
 
4.0%

prvd_agnc_cd
Real number (ℝ)

Distinct24
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4221800
Minimum3090000
Maximum5710000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:40:24.699348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3090000
5-th percentile3090000
Q13820000
median4255000
Q34690000
95-th percentile5263500
Maximum5710000
Range2620000
Interquartile range (IQR)870000

Descriptive statistics

Standard deviation695864.23
Coefficient of variation (CV)0.16482643
Kurtosis-0.86997612
Mean4221800
Median Absolute Deviation (MAD)435000
Skewness-0.046272348
Sum4.2218 × 108
Variance4.8422703 × 1011
MonotonicityNot monotonic
2023-12-10T18:40:24.963244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
3820000 16
16.0%
3090000 14
14.0%
4460000 8
 
8.0%
4690000 7
 
7.0%
3980000 6
 
6.0%
4980000 6
 
6.0%
4060000 5
 
5.0%
4440000 4
 
4.0%
5330000 4
 
4.0%
4400000 4
 
4.0%
Other values (14) 26
26.0%
ValueCountFrequency (%)
3090000 14
14.0%
3130000 1
 
1.0%
3550000 1
 
1.0%
3560000 1
 
1.0%
3700000 4
 
4.0%
3820000 16
16.0%
3970000 1
 
1.0%
3980000 6
 
6.0%
4060000 5
 
5.0%
4170000 1
 
1.0%
ValueCountFrequency (%)
5710000 1
 
1.0%
5330000 4
4.0%
5260000 4
4.0%
5230000 1
 
1.0%
5150000 3
3.0%
5110000 2
 
2.0%
4980000 6
6.0%
4950000 2
 
2.0%
4690000 7
7.0%
4570000 2
 
2.0%

prvd_agnc_nm
Categorical

Distinct24
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
경기도 의정부시
16 
서울특별시 도봉구
14 
충청북도 괴산군
8 
전라북도 정읍시
7 
경기도 구리시
6 
Other values (19)
49 

Length

Max length9
Median length8
Mean length8.01
Min length7

Unique

Unique7 ?
Unique (%)7.0%

Sample

1st row충청북도 영동군
2nd row충청북도 영동군
3rd row충청북도 영동군
4th row충청북도 영동군
5th row경기도 과천시

Common Values

ValueCountFrequency (%)
경기도 의정부시 16
16.0%
서울특별시 도봉구 14
14.0%
충청북도 괴산군 8
 
8.0%
전라북도 정읍시 7
 
7.0%
경기도 구리시 6
 
6.0%
전라남도 장성군 6
 
6.0%
경기도 파주시 5
 
5.0%
충청북도 영동군 4
 
4.0%
경상남도 통영시 4
 
4.0%
충청북도 제천시 4
 
4.0%
Other values (14) 26
26.0%

Length

2023-12-10T18:40:25.426806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 29
14.5%
충청북도 17
 
8.5%
의정부시 16
 
8.0%
서울특별시 15
 
7.5%
도봉구 14
 
7.0%
경상북도 10
 
5.0%
괴산군 8
 
4.0%
전라남도 8
 
4.0%
전라북도 7
 
3.5%
정읍시 7
 
3.5%
Other values (25) 69
34.5%

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

2023-12-10T18:40:25.747780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:40:25.926626image/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
문화체육관광부
100 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
문화체육관광부 100
100.0%

Length

2023-12-10T18:40:26.155813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:40:26.325737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문화체육관광부 100
100.0%

FILE_NAME
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
KC_488_WNTY_CLTFSTVL_2019
100 

Length

Max length25
Median length25
Mean length25
Min length25

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKC_488_WNTY_CLTFSTVL_2019
2nd rowKC_488_WNTY_CLTFSTVL_2019
3rd rowKC_488_WNTY_CLTFSTVL_2019
4th rowKC_488_WNTY_CLTFSTVL_2019
5th rowKC_488_WNTY_CLTFSTVL_2019

Common Values

ValueCountFrequency (%)
KC_488_WNTY_CLTFSTVL_2019 100
100.0%

Length

2023-12-10T18:40:26.496018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:40:26.648271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kc_488_wnty_cltfstvl_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

2023-12-10T18:40:26.800788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:40:26.968901image/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_cdopmt_plcefstvl_bgn_dtfstvl_end_dtfstvl_cnmnnstauspc_insttsupt_instttelnohmpgrlt_infdata_stddeprvd_agnc_cdprvd_agnc_nmlst_updt_dtdata_orgnFILE_NAMEbase_ymd
0KC488PO19N000001행사행사제13회 영동포도축제충청북도영동군4374025027영동읍4374025000영동읍437403243040충청북도 영동군 영동읍 영동황간로 12229150라마25396336.164205127.781975영동군 영동읍 영동군체육관 일원2017082420170827포도축제(재)영동축제관광재단, (사)영동포도연합회충청북도 영동군청, 영동군축제추진위원회충청북도, 메이빌 농산물공동브랜드043-745-8918www.ydft.kr포도따기, 포도밟기 등 체험, 농특산물 판매, 전시, 추풍령가요제, 영동포도마라톤 대회201802234440000충청북도 영동군20191113문화체육관광부KC_488_WNTY_CLTFSTVL_201920191125
1KC488PO19N000002행사행사제50회 영동난계국악축제충청북도영동군4374025028영동읍4374025000영동읍437403243054충청북도 영동군 영동읍 학산영동로 1244-129149라마24697436.173627127.773992영동군 영동읍 영동천 일원(하상주차장, 난계사 등)2017092120170924국악축제(재)영동축제관광재단, (사)난계기념사업회충청북도 영동군청, 영동군축제추진위원회문화체육관광부, 충청북도, 국립국악원, 한국관광공사, 한국지역진흥재단, 한국문황예술위원회043-745-8917www.ydft.kr어가행렬, 종묘제례, 국악기제작 및 연주체험, 퓨전국악공연, 영동와인축제와 연계201802234440000충청북도 영동군20191113문화체육관광부KC_488_WNTY_CLTFSTVL_201920191125
2KC488PO19N000003행사행사제8회 대한민국와인축제충청북도영동군4374025028영동읍4374025000영동읍437403243054충청북도 영동군 영동읍 학산영동로 1244-129149라마24697436.173627127.773992영동군 영동읍 영동천일원(하상주차장)2017092120170924와인축제(재)영동축제관광재단, 영동와인연구회충청북도 영동군청, 영동군축제추진위원회한국농수산식품유통공사, 충청북도, 영동군 농산물공동브랜드043-745-8914www.ydft.kr와인전시, 시음행사, 와인판매, 난계국악축제와 연계201802234440000충청북도 영동군20191113문화체육관광부KC_488_WNTY_CLTFSTVL_201920191125
3KC488PO19N000004행사행사2017 영동곶감축제충청북도영동군4374025028영동읍4374025000영동읍437403243054충청북도 영동군 영동읍 학산영동로 1244-129149라마24697436.173627127.773992영동군 영동읍 영동천일원(하상주차장)2017121520171217곶감축제(재)영동축제관광재단, 영동곶감연합회충청북도 영동군청, 영동군축제추진위원회충청북도, 메이빌 농산물공동브랜드043-745-8918www.ydft.kr곶감따기, 곶감 시식, 판매, 공연 프로그램201802234440000충청북도 영동군20191113문화체육관광부KC_488_WNTY_CLTFSTVL_201920191125
4KC488PO19N000005행사행사제22회 과천축제경기도과천시4129010700중앙동4129051000중앙동412903195051경기도 과천시 통영로 513807다사54836637.427909126.989504과천청사 잔디마당 등 과천시 일원2018091320180916문화예술 퍼포먼스, 시민참여 프로그램, 플리마켓 등(재)과천축제과천시한국마사회 등02-504-0945http://www.gcfest.or.kr서울대공원,서울랜드,과천과학관201807313970000경기도 과천시20191113문화체육관광부KC_488_WNTY_CLTFSTVL_201920191125
5KC488PO19N000006행사행사제11회 마포나루새우젓축제서울특별시마포구1144012500성산동1144073000성산제2동114403113018서울특별시 마포구 월드컵로 2073953다사47151837.56425126.901951서울월드컵공원 평화의 광장 일원2018101920181021개장식, 기념식, 문화행사, 체험행사, 판매행사마포문화원서울특별시 마포구S-oil, 우리은행, KB손해보험02-3153-8352<NA><NA>201802203130000서울특별시 마포구20191113문화체육관광부KC_488_WNTY_CLTFSTVL_201920191125
6KC488PO19N000007행사행사함창명주페스티벌경상북도상주시4725025025함창읍4725025000함창읍472503018045경상북도 상주시 함창읍 무운로 159337110라바59042236.576525128.160039명주테마공원2018090720180909누에고치 체험, 천연염색 등상주슬로시티주민협의회, 명주잠업영농조합법인경상북도 상주시청경상북도/상주시/한국슬로시티본부054-531-9763<NA>잠사곤충사업장201802215110000경상북도 상주시20191113문화체육관광부KC_488_WNTY_CLTFSTVL_201920191125
7KC488PO19N000008행사행사상주 이야기축제경상북도상주시4725010700남성동4725052000남원동472503311032경상북도 상주시 상산로 22337211라바59023936.410959128.158961상주 북천시민공원일원2018101220181014다양한 이야기 체험 및 전시 공연 등상주시축제추진위원회경상북도 상주시청경상북도/상주시054-537-7108http://www.sangjustory.com/<NA>201802215110000경상북도 상주시20191113문화체육관광부KC_488_WNTY_CLTFSTVL_201920191125
8KC488PO19N000009행사행사정의공주와 함께 하는 도봉 한글잔치서울특별시도봉구1132010600방학동1132070000방학제2동113204127075서울특별시 도봉구 도당로13마길 51358다사58863137.66667127.03375방학동 원당샘공원2015100920151009문화예술공연, 백일장 및 사생대회, 전통놀이체험 등서울특별시 도봉구청서울특별시 도봉구청, 도봉문화원<NA>02-905-4026<NA><NA>201805013090000서울특별시 도봉구20191113문화체육관광부KC_488_WNTY_CLTFSTVL_201920191125
9KC488PO19N000010행사행사정월대보름 큰잔치서울특별시도봉구1132010800도봉동1132052200도봉제2동113203109006서울특별시 도봉구 마들로 684-201330다사60163537.670777127.048377도봉구청 광장, 중랑천변2015030520150305길놀이, 풍물놀이, 소원지 붙이기, 달집태우기, 민속놀이 체험마당,청소년 동아리 프로그램 공연 및 솟대외줄타기 공연서울특별시 도봉구청서울특별시 도봉구청<NA>02-2091-2254<NA><NA>201805013090000서울특별시 도봉구20191113문화체육관광부KC_488_WNTY_CLTFSTVL_201920191125
idlclasmlsfcfclt_namectprvn_nmsgnr_nmlegaldong_cdlegalemd_nmadstrd_cdadstrd_nmrdnmaddr_cdrdnm_addrzip_cdgrid_cdx_cdy_cdopmt_plcefstvl_bgn_dtfstvl_end_dtfstvl_cnmnnstauspc_insttsupt_instttelnohmpgrlt_infdata_stddeprvd_agnc_cdprvd_agnc_nmlst_updt_dtdata_orgnFILE_NAMEbase_ymd
90KC488PO19N000092행사행사제16회 구리한강 유채꽃 축제경기도용인시 수지구4146510300동천동4146556000동천동414654853115경기도 용인시 수지구 동천로192번길 35-216802다사62827137.342841127.081044구리한강 시민공원2016051320160515유채꽃 축제(사)한국예총 구리지회경기도 구리시경기도+한국관광공사+경기관광공사031-550-2065http://www.guri.go.kr<NA>201907233980000경기도 구리시20191113문화체육관광부KC_488_WNTY_CLTFSTVL_201920191125
91KC488PO19N000093행사행사제16회 구리 코스모스 축제경기도용인시 수지구4146510300동천동4146556000동천동414654853115경기도 용인시 수지구 동천로192번길 35-216802다사62827137.342841127.081044구리한강 시민공원2016092320160925코스모스 축제(사)한국예총 구리지회경기도 구리시경기도+한국관광공사+경기관광공사031-550-2065http://www.guri.go.kr<NA>201907233980000경기도 구리시20191113문화체육관광부KC_488_WNTY_CLTFSTVL_201920191125
92KC488PO19N000094행사행사제17회 구리 유채꽃 축제경기도용인시 수지구4146510300동천동4146556000동천동414654853115경기도 용인시 수지구 동천로192번길 35-216802다사62827137.342841127.081044구리한강 시민공원2017051220170514무대공연, 체험부스운영, 먹거리 체험, 꽃 관람(사)한국예총 구리지회경기도 구리시경기도+한국관광공사+경기관광공사031-550-2065http://www.guri.go.kr<NA>201907233980000경기도 구리시20191113문화체육관광부KC_488_WNTY_CLTFSTVL_201920191125
93KC488PO19N000095행사행사제17회 구리 코스모스 축제경기도용인시 수지구4146510300동천동4146556000동천동414654853115경기도 용인시 수지구 동천로192번길 35-216802다사62827137.342841127.081044구리한강 시민공원2017092220170924무대공연, 체험부스운영, 먹거리 체험, 꽃 관람(사)한국예총 구리지회경기도 구리시경기도+한국관광공사+경기관광공사031-550-2065http://www.guri.go.kr<NA>201907233980000경기도 구리시20191113문화체육관광부KC_488_WNTY_CLTFSTVL_201920191125
94KC488PO19N000100행사행사청풍호벚꽃축제충청북도제천시4315011300청전동4315059000청전동431502239002충청북도 제천시 의림대로 24227152라사63605737.148685128.216854청풍면2019040620190408벚꽃축제(재)제천문화재단(재)제천문화재단제천시043-641-4870www.jcac.or.kr<NA>201909234400000충청북도 제천시20191113문화체육관광부KC_488_WNTY_CLTFSTVL_201920191125
95KC488PO19N000101행사행사제천국제음악영화제충청북도제천시4315011300청전동4315059000청전동431502239002충청북도 제천시 의림대로 24227152라사63605737.148685128.216854시내일원,청풍면,의림지2019080820190813음악영화제제천국제음악영화제집행위원회제천국제음악영화제집행위원회제천시043-646-2242www.jimff.org<NA>201909234400000충청북도 제천시20191113문화체육관광부KC_488_WNTY_CLTFSTVL_201920191125
96KC488PO19N000102행사행사제천의병제충청북도제천시4315011300청전동4315059000청전동431502239002충청북도 제천시 의림대로 24227152라사63605737.148685128.216854구동명초부지2018101920181020의병제(재)제천문화재단(재)제천문화재단제천시043-641-4870www.jcac.or.kr<NA>201909234400000충청북도 제천시20191113문화체육관광부KC_488_WNTY_CLTFSTVL_201920191125
97KC488PO19N000103행사행사겨울왕국 제천페스티벌충청북도제천시4315011300청전동4315059000청전동431502239002충청북도 제천시 의림대로 24227152라사63605737.148685128.216854시내 및 의림지 일원2019122120200127겨울벚꽃 및 얼음 축제(재)제천문화재단(재)제천문화재단제천시043-641-4870www.jcac.or.kr<NA>201909234400000충청북도 제천시20191113문화체육관광부KC_488_WNTY_CLTFSTVL_201920191125
98KC488PO19N000104행사행사제27회 용문산 영목제경기도양평군4183040033용문면4183040000용문면418303217020경기도 양평군 용문면 용문산로 65512510라사07249637.54617127.582161용문산관광지내2019101220191012산신제, 헌주제, 기원제양평문화원용문분원양평군031-774-3866<NA><NA>201909204170000경기도 양평군20191113문화체육관광부KC_488_WNTY_CLTFSTVL_201920191125
99KC488PO19N000105행사행사계양산국악제인천광역시계양구2824510200계산동2824561200계산2동282453008034인천광역시 계양구 주부토로 57021030다사31849837.545044126.728997계산체육공원2019042720190428국악경연대회계양구계양구<NA>032-450-5874<NA><NA>201910183550000인천광역시 계양구20191113문화체육관광부KC_488_WNTY_CLTFSTVL_201920191125