Overview

Dataset statistics

Number of variables46
Number of observations100
Missing cells19
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory37.1 KiB
Average record size in memory380.3 B

Variable types

Text20
Categorical17
Numeric9

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
frst_dnt_arko is highly imbalanced (72.2%)Imbalance
frst_dnt_etc is highly imbalanced (56.8%)Imbalance
frst_dnt_tot has 2 (2.0%) missing valuesMissing
bdg_stts_ntrs has 7 (7.0%) missing valuesMissing
bdg_stts_onslf has 5 (5.0%) missing valuesMissing
biz_stts_tot has 2 (2.0%) missing valuesMissing
id has unique valuesUnique
fclt_name has unique valuesUnique
rdnmaddr_cd has unique valuesUnique
rdnm_addr has unique valuesUnique
zip_cd has unique valuesUnique
grid_cd has unique valuesUnique
x_cd has unique valuesUnique
y_cd has unique valuesUnique
fond_mclnc has unique valuesUnique
cof has unique valuesUnique
cttpc has unique valuesUnique
fond_dt has unique valuesUnique
main_biz has unique valuesUnique

Reproduction

Analysis started2023-12-10 09:54:42.818448
Analysis finished2023-12-10 09:54:45.443468
Duration2.63 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

id
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:54:45.778105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters1900
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 rowKCDMMCC21N000000001
2nd rowKCDMMCC21N000000101
3rd rowKCDMMCC21N000000003
4th rowKCDMMCC21N000000004
5th rowKCDMMCC21N000000005
ValueCountFrequency (%)
kcdmmcc21n000000001 1
 
1.0%
kcdmmcc21n000000063 1
 
1.0%
kcdmmcc21n000000074 1
 
1.0%
kcdmmcc21n000000073 1
 
1.0%
kcdmmcc21n000000072 1
 
1.0%
kcdmmcc21n000000071 1
 
1.0%
kcdmmcc21n000000070 1
 
1.0%
kcdmmcc21n000000069 1
 
1.0%
kcdmmcc21n000000068 1
 
1.0%
kcdmmcc21n000000067 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T18:54:46.616932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 717
37.7%
C 300
15.8%
M 200
 
10.5%
1 125
 
6.6%
2 119
 
6.3%
K 100
 
5.3%
D 100
 
5.3%
N 100
 
5.3%
3 20
 
1.1%
4 20
 
1.1%
Other values (5) 99
 
5.2%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 717
65.2%
1 125
 
11.4%
2 119
 
10.8%
3 20
 
1.8%
4 20
 
1.8%
5 20
 
1.8%
6 20
 
1.8%
7 20
 
1.8%
9 20
 
1.8%
8 19
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
C 300
37.5%
M 200
25.0%
K 100
 
12.5%
D 100
 
12.5%
N 100
 
12.5%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 717
65.2%
1 125
 
11.4%
2 119
 
10.8%
3 20
 
1.8%
4 20
 
1.8%
5 20
 
1.8%
6 20
 
1.8%
7 20
 
1.8%
9 20
 
1.8%
8 19
 
1.7%
Latin
ValueCountFrequency (%)
C 300
37.5%
M 200
25.0%
K 100
 
12.5%
D 100
 
12.5%
N 100
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 717
37.7%
C 300
15.8%
M 200
 
10.5%
1 125
 
6.6%
2 119
 
6.3%
K 100
 
5.3%
D 100
 
5.3%
N 100
 
5.3%
3 20
 
1.1%
4 20
 
1.1%
Other values (5) 99
 
5.2%

lclas
Categorical

CONSTANT 

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

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
문화시설 100
100.0%

Length

2023-12-10T18:54:46.932394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:54:47.183213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문화시설 100
100.0%

mlsfc
Categorical

CONSTANT 

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

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지역문화재단 100
100.0%

Length

2023-12-10T18:54:47.606203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:54:47.929523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지역문화재단 100
100.0%

fclt_name
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:54:48.232749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length6
Mean length6.67
Min length6

Characters and Unicode

Total characters667
Distinct characters100
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

Unique100 ?
Unique (%)100.0%

Sample

1st row서울문화재단
2nd row아산문화재단
3rd row대구문화재단
4th row인천문화재단
5th row광주문화재단
ValueCountFrequency (%)
서울문화재단 1
 
1.0%
금정문화재단 1
 
1.0%
창원문화재단 1
 
1.0%
김해문화재단 1
 
1.0%
거제시문화예술재단 1
 
1.0%
포항문화재단 1
 
1.0%
영주문화관광재단 1
 
1.0%
영양축제관광재단 1
 
1.0%
청도우리정신문화재단 1
 
1.0%
청송문화관광재단 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T18:54:48.956213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
100
15.0%
99
14.8%
98
14.7%
97
14.5%
13
 
1.9%
11
 
1.6%
10
 
1.5%
10
 
1.5%
8
 
1.2%
7
 
1.0%
Other values (90) 214
32.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 667
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
100
15.0%
99
14.8%
98
14.7%
97
14.5%
13
 
1.9%
11
 
1.6%
10
 
1.5%
10
 
1.5%
8
 
1.2%
7
 
1.0%
Other values (90) 214
32.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 667
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
100
15.0%
99
14.8%
98
14.7%
97
14.5%
13
 
1.9%
11
 
1.6%
10
 
1.5%
10
 
1.5%
8
 
1.2%
7
 
1.0%
Other values (90) 214
32.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 667
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
100
15.0%
99
14.8%
98
14.7%
97
14.5%
13
 
1.9%
11
 
1.6%
10
 
1.5%
10
 
1.5%
8
 
1.2%
7
 
1.0%
Other values (90) 214
32.1%

ctprvn_nm
Categorical

Distinct16
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울특별시
21 
경기도
16 
강원도
11 
경상북도
대구광역시
Other values (11)
37 

Length

Max length7
Median length5
Mean length4.13
Min length3

Unique

Unique4 ?
Unique (%)4.0%

Sample

1st row서울특별시
2nd row충청남도
3rd row대구광역시
4th row인천광역시
5th row광주광역시

Common Values

ValueCountFrequency (%)
서울특별시 21
21.0%
경기도 16
16.0%
강원도 11
11.0%
경상북도 8
 
8.0%
대구광역시 7
 
7.0%
경상남도 7
 
7.0%
전라남도 6
 
6.0%
충청북도 5
 
5.0%
전라북도 5
 
5.0%
충청남도 4
 
4.0%
Other values (6) 10
10.0%

Length

2023-12-10T18:54:49.427153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 21
21.0%
경기도 16
16.0%
강원도 11
11.0%
경상북도 8
 
8.0%
대구광역시 7
 
7.0%
경상남도 7
 
7.0%
전라남도 6
 
6.0%
충청북도 5
 
5.0%
전라북도 5
 
5.0%
충청남도 4
 
4.0%
Other values (6) 10
10.0%
Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:54:50.181282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length3
Mean length3.43
Min length2

Characters and Unicode

Total characters343
Distinct characters89
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)98.0%

Sample

1st row서울 종로구
2nd row아산시
3rd row대구 중구
4th row인천 중구
5th row광주 남구
ValueCountFrequency (%)
중구 5
 
4.3%
남구 3
 
2.6%
수원시 2
 
1.7%
전주시 2
 
1.7%
청주시 2
 
1.7%
춘천시 2
 
1.7%
종로구 2
 
1.7%
부평구 1
 
0.9%
아산시 1
 
0.9%
김해시 1
 
0.9%
Other values (94) 94
81.7%
2023-12-10T18:54:51.118946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
43
 
12.5%
38
 
11.1%
22
 
6.4%
15
 
4.4%
14
 
4.1%
13
 
3.8%
9
 
2.6%
8
 
2.3%
6
 
1.7%
6
 
1.7%
Other values (79) 169
49.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 328
95.6%
Space Separator 15
 
4.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
43
 
13.1%
38
 
11.6%
22
 
6.7%
14
 
4.3%
13
 
4.0%
9
 
2.7%
8
 
2.4%
6
 
1.8%
6
 
1.8%
6
 
1.8%
Other values (78) 163
49.7%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 328
95.6%
Common 15
 
4.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
43
 
13.1%
38
 
11.6%
22
 
6.7%
14
 
4.3%
13
 
4.0%
9
 
2.7%
8
 
2.4%
6
 
1.8%
6
 
1.8%
6
 
1.8%
Other values (78) 163
49.7%
Common
ValueCountFrequency (%)
15
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 328
95.6%
ASCII 15
 
4.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
43
 
13.1%
38
 
11.6%
22
 
6.7%
14
 
4.3%
13
 
4.0%
9
 
2.7%
8
 
2.4%
6
 
1.8%
6
 
1.8%
6
 
1.8%
Other values (78) 163
49.7%
ASCII
ValueCountFrequency (%)
15
100.0%

legaldong_cd
Real number (ℝ)

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4888767 × 109
Minimum1.1110168 × 109
Maximum5.0110103 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:51.467568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110168 × 109
5-th percentile1.1286353 × 109
Q12.720762 × 109
median4.1517604 × 109
Q34.5118366 × 109
95-th percentile4.8251108 × 109
Maximum5.0110103 × 109
Range3.8999935 × 109
Interquartile range (IQR)1.7910747 × 109

Descriptive statistics

Standard deviation1.365594 × 109
Coefficient of variation (CV)0.39141367
Kurtosis-0.87402165
Mean3.4888767 × 109
Median Absolute Deviation (MAD)5.6725045 × 108
Skewness-0.84543213
Sum3.4888767 × 1011
Variance1.864847 × 1018
MonotonicityNot monotonic
2023-12-10T18:54:51.860622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1111016800 2
 
2.0%
4717011300 1
 
1.0%
4824011700 1
 
1.0%
4812112800 1
 
1.0%
4825010800 1
 
1.0%
4831010200 1
 
1.0%
4711110200 1
 
1.0%
4721010400 1
 
1.0%
4776025022 1
 
1.0%
4782035043 1
 
1.0%
Other values (89) 89
89.0%
ValueCountFrequency (%)
1111016800 2
2.0%
1114016300 1
1.0%
1120010700 1
1.0%
1121510500 1
1.0%
1129010300 1
1.0%
1130510300 1
1.0%
1132010700 1
1.0%
1135010600 1
1.0%
1138010200 1
1.0%
1144010800 1
1.0%
ValueCountFrequency (%)
5011010300 1
1.0%
4889038024 1
1.0%
4888025025 1
1.0%
4831010200 1
1.0%
4827010300 1
1.0%
4825010800 1
1.0%
4824011700 1
1.0%
4812112800 1
1.0%
4790036046 1
1.0%
4782035043 1
1.0%
Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:54:52.678153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.94
Min length2

Characters and Unicode

Total characters394
Distinct characters125
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

Unique94 ?
Unique (%)94.0%

Sample

1st row동숭동
2nd row염치읍 송곡리
3rd row대봉동
4th row해안동2가
5th row구동
ValueCountFrequency (%)
동숭동 2
 
1.6%
신정동 2
 
1.6%
교동 2
 
1.6%
남북리 1
 
0.8%
읍내리 1
 
0.8%
효자동 1
 
0.8%
운곡리 1
 
0.8%
용진읍 1
 
0.8%
김천리 1
 
0.8%
거창읍 1
 
0.8%
Other values (109) 109
89.3%
2023-12-10T18:54:53.827942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
82
 
20.8%
22
 
5.6%
22
 
5.6%
20
 
5.1%
7
 
1.8%
7
 
1.8%
7
 
1.8%
6
 
1.5%
6
 
1.5%
5
 
1.3%
Other values (115) 210
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 368
93.4%
Space Separator 22
 
5.6%
Decimal Number 4
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
82
22.3%
22
 
6.0%
20
 
5.4%
7
 
1.9%
7
 
1.9%
7
 
1.9%
6
 
1.6%
6
 
1.6%
5
 
1.4%
5
 
1.4%
Other values (111) 201
54.6%
Decimal Number
ValueCountFrequency (%)
3 2
50.0%
1 1
25.0%
2 1
25.0%
Space Separator
ValueCountFrequency (%)
22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 368
93.4%
Common 26
 
6.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
82
22.3%
22
 
6.0%
20
 
5.4%
7
 
1.9%
7
 
1.9%
7
 
1.9%
6
 
1.6%
6
 
1.6%
5
 
1.4%
5
 
1.4%
Other values (111) 201
54.6%
Common
ValueCountFrequency (%)
22
84.6%
3 2
 
7.7%
1 1
 
3.8%
2 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 368
93.4%
ASCII 26
 
6.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
82
22.3%
22
 
6.0%
20
 
5.4%
7
 
1.9%
7
 
1.9%
7
 
1.9%
6
 
1.6%
6
 
1.6%
5
 
1.4%
5
 
1.4%
Other values (111) 201
54.6%
ASCII
ValueCountFrequency (%)
22
84.6%
3 2
 
7.7%
1 1
 
3.8%
2 1
 
3.8%

adstrd_cd
Real number (ℝ)

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4889136 × 109
Minimum1.111064 × 109
Maximum5.011053 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:54.237807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111064 × 109
5-th percentile1.1286852 × 109
Q12.720821 × 109
median4.1518045 × 109
Q34.511879 × 109
95-th percentile4.825154 × 109
Maximum5.011053 × 109
Range3.899989 × 109
Interquartile range (IQR)1.791058 × 109

Descriptive statistics

Standard deviation1.3655847 × 109
Coefficient of variation (CV)0.39140685
Kurtosis-0.87401458
Mean3.4889136 × 109
Median Absolute Deviation (MAD)5.67251 × 108
Skewness-0.84543849
Sum3.4889136 × 1011
Variance1.8648216 × 1018
MonotonicityNot monotonic
2023-12-10T18:54:54.734904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1111064000 2
 
2.0%
4511153000 2
 
2.0%
4812155000 1
 
1.0%
4825054000 1
 
1.0%
4831051000 1
 
1.0%
4711152500 1
 
1.0%
4721060000 1
 
1.0%
4776025000 1
 
1.0%
4782035000 1
 
1.0%
4775031500 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
1111064000 2
2.0%
1114061500 1
1.0%
1120056000 1
1.0%
1121584000 1
1.0%
1129059000 1
1.0%
1130566000 1
1.0%
1132051500 1
1.0%
1135061900 1
1.0%
1138051000 1
1.0%
1144060000 1
1.0%
ValueCountFrequency (%)
5011053000 1
1.0%
4889038000 1
1.0%
4888025000 1
1.0%
4831051000 1
1.0%
4827055000 1
1.0%
4825054000 1
1.0%
4824051000 1
1.0%
4812155000 1
1.0%
4790036000 1
1.0%
4782035000 1
1.0%
Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:54:55.447001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.42
Min length2

Characters and Unicode

Total characters342
Distinct characters118
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

Unique94 ?
Unique (%)94.0%

Sample

1st row이화동
2nd row염치읍
3rd row대봉1동
4th row신포동
5th row사직동
ValueCountFrequency (%)
이화동 2
 
2.0%
풍남동 2
 
2.0%
중앙동 2
 
2.0%
인제읍 1
 
1.0%
야음장생포동 1
 
1.0%
장승포동 1
 
1.0%
상대동 1
 
1.0%
휴천2동 1
 
1.0%
영양읍 1
 
1.0%
운문면 1
 
1.0%
Other values (87) 87
87.0%
2023-12-10T18:54:56.524087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
82
24.0%
17
 
5.0%
1 17
 
5.0%
2 9
 
2.6%
7
 
2.0%
7
 
2.0%
3 6
 
1.8%
5
 
1.5%
5
 
1.5%
4
 
1.2%
Other values (108) 183
53.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 305
89.2%
Decimal Number 36
 
10.5%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
82
26.9%
17
 
5.6%
7
 
2.3%
7
 
2.3%
5
 
1.6%
5
 
1.6%
4
 
1.3%
4
 
1.3%
4
 
1.3%
4
 
1.3%
Other values (101) 166
54.4%
Decimal Number
ValueCountFrequency (%)
1 17
47.2%
2 9
25.0%
3 6
 
16.7%
5 2
 
5.6%
6 1
 
2.8%
8 1
 
2.8%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 305
89.2%
Common 37
 
10.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
82
26.9%
17
 
5.6%
7
 
2.3%
7
 
2.3%
5
 
1.6%
5
 
1.6%
4
 
1.3%
4
 
1.3%
4
 
1.3%
4
 
1.3%
Other values (101) 166
54.4%
Common
ValueCountFrequency (%)
1 17
45.9%
2 9
24.3%
3 6
 
16.2%
5 2
 
5.4%
. 1
 
2.7%
6 1
 
2.7%
8 1
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 305
89.2%
ASCII 37
 
10.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
82
26.9%
17
 
5.6%
7
 
2.3%
7
 
2.3%
5
 
1.6%
5
 
1.6%
4
 
1.3%
4
 
1.3%
4
 
1.3%
4
 
1.3%
Other values (101) 166
54.4%
ASCII
ValueCountFrequency (%)
1 17
45.9%
2 9
24.3%
3 6
 
16.2%
5 2
 
5.4%
. 1
 
2.7%
6 1
 
2.7%
8 1
 
2.7%

rdnmaddr_cd
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4888962 × 1011
Minimum1.111041 × 1011
Maximum5.0110335 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:57.379960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111041 × 1011
5-th percentile1.1286657 × 1011
Q12.7207842 × 1011
median4.1517761 × 1011
Q34.511861 × 1011
95-th percentile4.8251239 × 1011
Maximum5.0110335 × 1011
Range3.8999925 × 1011
Interquartile range (IQR)1.7910769 × 1011

Descriptive statistics

Standard deviation1.3655917 × 1011
Coefficient of variation (CV)0.39141082
Kurtosis-0.87401841
Mean3.4888962 × 1011
Median Absolute Deviation (MAD)5.6725698 × 1010
Skewness-0.84543476
Sum3.4888962 × 1013
Variance1.8648407 × 1022
MonotonicityNot monotonic
2023-12-10T18:54:58.208924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
111104100075 1
 
1.0%
471703307030 1
 
1.0%
482402334003 1
 
1.0%
481212327003 1
 
1.0%
482502335001 1
 
1.0%
483103337039 1
 
1.0%
471112303004 1
 
1.0%
472103309076 1
 
1.0%
477604751035 1
 
1.0%
478204857701 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
111104100075 1
1.0%
111104100245 1
1.0%
111403101011 1
1.0%
112004109004 1
1.0%
112153104007 1
1.0%
112904121403 1
1.0%
113053108001 1
1.0%
113204127025 1
1.0%
113503110007 1
1.0%
113803111002 1
1.0%
ValueCountFrequency (%)
501103349055 1
1.0%
488904844648 1
1.0%
488803346035 1
1.0%
483103337039 1
1.0%
482703336020 1
1.0%
482502335001 1
1.0%
482402334003 1
1.0%
481212327003 1
1.0%
479003351075 1
1.0%
478204857701 1
1.0%

rdnm_addr
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:54:59.271475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length16.34
Min length12

Characters and Unicode

Total characters1634
Distinct characters181
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row서울 종로구 동숭길 122
2nd row충남 아산시 염치읍 은행나무길 293
3rd row대구 중구 대봉로 260
4th row인천 중구 신포로15번길 64
5th row광주 남구 천변좌로338번길 7
ValueCountFrequency (%)
서울 21
 
4.8%
경기 16
 
3.7%
강원 11
 
2.5%
경북 8
 
1.8%
대구 7
 
1.6%
경남 7
 
1.6%
전남 6
 
1.4%
전북 5
 
1.1%
충북 5
 
1.1%
중구 5
 
1.1%
Other values (301) 345
79.1%
2023-12-10T18:55:01.422798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
336
 
20.6%
90
 
5.5%
60
 
3.7%
1 60
 
3.7%
2 49
 
3.0%
45
 
2.8%
35
 
2.1%
35
 
2.1%
27
 
1.7%
4 27
 
1.7%
Other values (171) 870
53.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 996
61.0%
Space Separator 336
 
20.6%
Decimal Number 295
 
18.1%
Dash Punctuation 7
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
90
 
9.0%
60
 
6.0%
45
 
4.5%
35
 
3.5%
35
 
3.5%
27
 
2.7%
27
 
2.7%
26
 
2.6%
25
 
2.5%
24
 
2.4%
Other values (159) 602
60.4%
Decimal Number
ValueCountFrequency (%)
1 60
20.3%
2 49
16.6%
4 27
9.2%
5 27
9.2%
0 25
8.5%
3 24
 
8.1%
6 22
 
7.5%
8 22
 
7.5%
7 21
 
7.1%
9 18
 
6.1%
Space Separator
ValueCountFrequency (%)
336
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 996
61.0%
Common 638
39.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
90
 
9.0%
60
 
6.0%
45
 
4.5%
35
 
3.5%
35
 
3.5%
27
 
2.7%
27
 
2.7%
26
 
2.6%
25
 
2.5%
24
 
2.4%
Other values (159) 602
60.4%
Common
ValueCountFrequency (%)
336
52.7%
1 60
 
9.4%
2 49
 
7.7%
4 27
 
4.2%
5 27
 
4.2%
0 25
 
3.9%
3 24
 
3.8%
6 22
 
3.4%
8 22
 
3.4%
7 21
 
3.3%
Other values (2) 25
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 996
61.0%
ASCII 638
39.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
336
52.7%
1 60
 
9.4%
2 49
 
7.7%
4 27
 
4.2%
5 27
 
4.2%
0 25
 
3.9%
3 24
 
3.8%
6 22
 
3.4%
8 22
 
3.4%
7 21
 
3.3%
Other values (2) 25
 
3.9%
Hangul
ValueCountFrequency (%)
90
 
9.0%
60
 
6.0%
45
 
4.5%
35
 
3.5%
35
 
3.5%
27
 
2.7%
27
 
2.7%
26
 
2.6%
25
 
2.5%
24
 
2.4%
Other values (159) 602
60.4%

zip_cd
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28467.89
Minimum1036
Maximum63196
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:55:01.757642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1036
5-th percentile3087.8
Q112859
median26176
Q342195
95-th percentile58427.3
Maximum63196
Range62160
Interquartile range (IQR)29336

Descriptive statistics

Standard deviation18222.685
Coefficient of variation (CV)0.64011364
Kurtosis-1.1527534
Mean28467.89
Median Absolute Deviation (MAD)15721
Skewness0.22343266
Sum2846789
Variance3.3206624 × 108
MonotonicityNot monotonic
2023-12-10T18:55:02.372789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3084 1
 
1.0%
36709 1
 
1.0%
52555 1
 
1.0%
51435 1
 
1.0%
50943 1
 
1.0%
53322 1
 
1.0%
37832 1
 
1.0%
36133 1
 
1.0%
36541 1
 
1.0%
38367 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1036 1
1.0%
1403 1
1.0%
1736 1
1.0%
2827 1
1.0%
3084 1
1.0%
3088 1
1.0%
3381 1
1.0%
4136 1
1.0%
4569 1
1.0%
4744 1
1.0%
ValueCountFrequency (%)
63196 1
1.0%
61636 1
1.0%
59232 1
1.0%
58724 1
1.0%
58566 1
1.0%
58420 1
1.0%
57941 1
1.0%
57344 1
1.0%
56441 1
1.0%
55352 1
1.0%

grid_cd
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:55:02.976111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters800
Distinct characters17
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row다사561539
2nd row다바570670
3rd row라마993633
4th row다사223418
5th row다라460837
ValueCountFrequency (%)
다사561539 1
 
1.0%
마라450956 1
 
1.0%
마라076933 1
 
1.0%
마라245951 1
 
1.0%
마라118531 1
 
1.0%
마마681808 1
 
1.0%
라바995682 1
 
1.0%
마바445529 1
 
1.0%
마마286477 1
 
1.0%
마바442212 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T18:55:03.887191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 80
10.0%
4 78
9.8%
2 64
 
8.0%
3 62
 
7.8%
60
 
7.5%
6 60
 
7.5%
1 59
 
7.4%
9 58
 
7.2%
52
 
6.5%
8 49
 
6.1%
Other values (7) 178
22.2%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 80
13.3%
4 78
13.0%
2 64
10.7%
3 62
10.3%
6 60
10.0%
1 59
9.8%
9 58
9.7%
8 49
8.2%
0 47
7.8%
7 43
7.2%
Other Letter
ValueCountFrequency (%)
60
30.0%
52
26.0%
40
20.0%
33
16.5%
13
 
6.5%
1
 
0.5%
1
 
0.5%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
5 80
13.3%
4 78
13.0%
2 64
10.7%
3 62
10.3%
6 60
10.0%
1 59
9.8%
9 58
9.7%
8 49
8.2%
0 47
7.8%
7 43
7.2%
Hangul
ValueCountFrequency (%)
60
30.0%
52
26.0%
40
20.0%
33
16.5%
13
 
6.5%
1
 
0.5%
1
 
0.5%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 80
13.3%
4 78
13.0%
2 64
10.7%
3 62
10.3%
6 60
10.0%
1 59
9.8%
9 58
9.7%
8 49
8.2%
0 47
7.8%
7 43
7.2%
Hangul
ValueCountFrequency (%)
60
30.0%
52
26.0%
40
20.0%
33
16.5%
13
 
6.5%
1
 
0.5%
1
 
0.5%

x_cd
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.694128
Minimum33.503187
Maximum38.060674
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:55:04.163732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.503187
5-th percentile34.864518
Q135.862149
median37.174516
Q337.516062
95-th percentile37.691188
Maximum38.060674
Range4.5574867
Interquartile range (IQR)1.6539128

Descriptive statistics

Standard deviation1.0040619
Coefficient of variation (CV)0.027363014
Kurtosis-0.34384414
Mean36.694128
Median Absolute Deviation (MAD)0.4751311
Skewness-0.80544246
Sum3669.4128
Variance1.0081404
MonotonicityNot monotonic
2023-12-10T18:55:04.426110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.583699 1
 
1.0%
36.5605065 1
 
1.0%
34.9322942 1
 
1.0%
35.2293871 1
 
1.0%
35.2437338 1
 
1.0%
34.8671784 1
 
1.0%
36.0096118 1
 
1.0%
36.8070011 1
 
1.0%
36.6634721 1
 
1.0%
35.7180765 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
33.5031874 1
1.0%
34.6385143 1
1.0%
34.7915678 1
1.0%
34.7931322 1
1.0%
34.8139775 1
1.0%
34.8671784 1
1.0%
34.9322942 1
1.0%
34.9542463 1
1.0%
35.1479059 1
1.0%
35.2293871 1
1.0%
ValueCountFrequency (%)
38.0606741 1
1.0%
37.8824403 1
1.0%
37.8726158 1
1.0%
37.7504033 1
1.0%
37.7333846 1
1.0%
37.6889674 1
1.0%
37.6527101 1
1.0%
37.6502369 1
1.0%
37.6490565 1
1.0%
37.6409898 1
1.0%

y_cd
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.58622
Minimum126.38293
Maximum129.38729
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:55:04.746992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.38293
5-th percentile126.65588
Q1126.94149
median127.13594
Q3128.47283
95-th percentile129.10904
Maximum129.38729
Range3.0043604
Interquartile range (IQR)1.5313335

Descriptive statistics

Standard deviation0.85315611
Coefficient of variation (CV)0.0066868985
Kurtosis-1.0396673
Mean127.58622
Median Absolute Deviation (MAD)0.4311874
Skewness0.63963486
Sum12758.622
Variance0.72787534
MonotonicityNot monotonic
2023-12-10T18:55:05.137215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0037167 1
 
1.0%
128.7306335 1
 
1.0%
128.0523348 1
 
1.0%
128.6831193 1
 
1.0%
128.8694108 1
 
1.0%
128.7233576 1
 
1.0%
129.3660209 1
 
1.0%
128.6161424 1
 
1.0%
129.1175295 1
 
1.0%
128.9223074 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
126.3829337 1
1.0%
126.4581042 1
1.0%
126.5340156 1
1.0%
126.62147 1
1.0%
126.6374833 1
1.0%
126.656843 1
1.0%
126.6711028 1
1.0%
126.67798 1
1.0%
126.685372 1
1.0%
126.7045756 1
1.0%
ValueCountFrequency (%)
129.3872941 1
1.0%
129.3660209 1
1.0%
129.3128667 1
1.0%
129.2059962 1
1.0%
129.1175295 1
1.0%
129.108596 1
1.0%
129.0944742 1
1.0%
128.9852903 1
1.0%
128.9223074 1
1.0%
128.8898121 1
1.0%

fond_mclnc
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:55:05.781358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length29
Mean length23.81
Min length13

Characters and Unicode

Total characters2381
Distinct characters122
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
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 row서울특별시 재단법인 서울문화재단 설립 및 운영에 관한 조례
2nd row아산문화재단 설립 및 운영에 관한 조례
3rd row대구광역시 문화재단 설립 및 운영 조례
4th row인천광역시 문화재단 설립 및 운영에 관한 조례
5th row광주광역시 광주문화재단 설립 및 운영조례
ValueCountFrequency (%)
설립 95
15.0%
95
15.0%
조례 89
14.0%
관한 67
10.6%
운영에 64
10.1%
문화재단 25
 
3.9%
서울특별시 21
 
3.3%
운영 16
 
2.5%
운영조례 7
 
1.1%
대구광역시 7
 
1.1%
Other values (133) 149
23.5%
2023-12-10T18:55:07.132638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
539
22.6%
104
 
4.4%
102
 
4.3%
100
 
4.2%
100
 
4.2%
99
 
4.2%
98
 
4.1%
97
 
4.1%
97
 
4.1%
96
 
4.0%
Other values (112) 949
39.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1837
77.2%
Space Separator 539
 
22.6%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
104
 
5.7%
102
 
5.6%
100
 
5.4%
100
 
5.4%
99
 
5.4%
98
 
5.3%
97
 
5.3%
97
 
5.3%
96
 
5.2%
96
 
5.2%
Other values (106) 848
46.2%
Open Punctuation
ValueCountFrequency (%)
1
50.0%
( 1
50.0%
Close Punctuation
ValueCountFrequency (%)
1
50.0%
) 1
50.0%
Space Separator
ValueCountFrequency (%)
539
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1837
77.2%
Common 544
 
22.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
104
 
5.7%
102
 
5.6%
100
 
5.4%
100
 
5.4%
99
 
5.4%
98
 
5.3%
97
 
5.3%
97
 
5.3%
96
 
5.2%
96
 
5.2%
Other values (106) 848
46.2%
Common
ValueCountFrequency (%)
539
99.1%
1
 
0.2%
1
 
0.2%
· 1
 
0.2%
( 1
 
0.2%
) 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1837
77.2%
ASCII 541
 
22.7%
None 3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
539
99.6%
( 1
 
0.2%
) 1
 
0.2%
Hangul
ValueCountFrequency (%)
104
 
5.7%
102
 
5.6%
100
 
5.4%
100
 
5.4%
99
 
5.4%
98
 
5.3%
97
 
5.3%
97
 
5.3%
96
 
5.2%
96
 
5.2%
Other values (106) 848
46.2%
None
ValueCountFrequency (%)
1
33.3%
1
33.3%
· 1
33.3%

cof
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:55:07.722498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length18
Mean length9.62
Min length3

Characters and Unicode

Total characters962
Distinct characters147
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 row이경자,(한국작가회의 이사장)
2nd row오세현,(시장)
3rd row권영진,(대구광역시장)
4th row박남춘,(시장)
5th row이용섭,(광주광역시장)
ValueCountFrequency (%)
이사장 3
 
2.7%
정헌율,(시장 1
 
0.9%
박일호,(시장 1
 
0.9%
안병용,(시장 1
 
0.9%
허성무,(시장 1
 
0.9%
허성곤,(시장 1
 
0.9%
변광용,(시장 1
 
0.9%
이강덕,(포항시장 1
 
0.9%
장욱현,(시장 1
 
0.9%
오도창,(군수 1
 
0.9%
Other values (100) 100
89.3%
2023-12-10T18:55:08.634908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 93
 
9.7%
) 93
 
9.7%
, 92
 
9.6%
72
 
7.5%
66
 
6.9%
39
 
4.1%
28
 
2.9%
23
 
2.4%
21
 
2.2%
20
 
2.1%
Other values (137) 415
43.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 616
64.0%
Other Punctuation 94
 
9.8%
Open Punctuation 93
 
9.7%
Close Punctuation 93
 
9.7%
Space Separator 66
 
6.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
72
 
11.7%
39
 
6.3%
28
 
4.5%
23
 
3.7%
21
 
3.4%
20
 
3.2%
20
 
3.2%
19
 
3.1%
15
 
2.4%
11
 
1.8%
Other values (132) 348
56.5%
Other Punctuation
ValueCountFrequency (%)
, 92
97.9%
/ 2
 
2.1%
Open Punctuation
ValueCountFrequency (%)
( 93
100.0%
Close Punctuation
ValueCountFrequency (%)
) 93
100.0%
Space Separator
ValueCountFrequency (%)
66
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 616
64.0%
Common 346
36.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
72
 
11.7%
39
 
6.3%
28
 
4.5%
23
 
3.7%
21
 
3.4%
20
 
3.2%
20
 
3.2%
19
 
3.1%
15
 
2.4%
11
 
1.8%
Other values (132) 348
56.5%
Common
ValueCountFrequency (%)
( 93
26.9%
) 93
26.9%
, 92
26.6%
66
19.1%
/ 2
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 616
64.0%
ASCII 346
36.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 93
26.9%
) 93
26.9%
, 92
26.6%
66
19.1%
/ 2
 
0.6%
Hangul
ValueCountFrequency (%)
72
 
11.7%
39
 
6.3%
28
 
4.5%
23
 
3.7%
21
 
3.4%
20
 
3.2%
20
 
3.2%
19
 
3.1%
15
 
2.4%
11
 
1.8%
Other values (132) 348
56.5%

cttpc
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:55:09.150759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length29
Mean length27.75
Min length9

Characters and Unicode

Total characters2775
Distinct characters18
Distinct categories7 ?
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 rowT)02-3290-7000,F)02-6008-7346
2nd rowT)041-540-2550,F)041-534-2633
3rd rowT)053-430-1200,F)053-422-1214
4th rowT)032-455-7100,F)032-772-7190
5th rowT)062-670-7400,F)062-670-7489
ValueCountFrequency (%)
t 3
 
2.7%
t)02-3290-7000,f)02-6008-7346 1
 
0.9%
t)051-512-3455,f)051-512-3453 1
 
0.9%
t)054-289-7999,f)054-274-6830 1
 
0.9%
t)054-630-8702,f)054-633-0152 1
 
0.9%
t)054-683-7300,f)054-683-7301 1
 
0.9%
t)054-370-7300,f)054-371-9954 1
 
0.9%
t)054-874-0101,f)054-874-0509 1
 
0.9%
t)054-748-7722,f)054-760-7479 1
 
0.9%
054-852-9230 1
 
0.9%
Other values (100) 100
89.3%
2023-12-10T18:55:10.132305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 441
15.9%
- 381
13.7%
3 254
9.2%
2 210
7.6%
) 191
 
6.9%
5 182
 
6.6%
1 164
 
5.9%
9 149
 
5.4%
4 143
 
5.2%
6 137
 
4.9%
Other values (8) 523
18.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1906
68.7%
Dash Punctuation 381
 
13.7%
Close Punctuation 191
 
6.9%
Uppercase Letter 190
 
6.8%
Other Punctuation 92
 
3.3%
Space Separator 13
 
0.5%
Math Symbol 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 441
23.1%
3 254
13.3%
2 210
11.0%
5 182
9.5%
1 164
 
8.6%
9 149
 
7.8%
4 143
 
7.5%
6 137
 
7.2%
8 128
 
6.7%
7 98
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
T 99
52.1%
F 91
47.9%
Other Punctuation
ValueCountFrequency (%)
, 91
98.9%
/ 1
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 381
100.0%
Close Punctuation
ValueCountFrequency (%)
) 191
100.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2585
93.2%
Latin 190
 
6.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 441
17.1%
- 381
14.7%
3 254
9.8%
2 210
8.1%
) 191
7.4%
5 182
7.0%
1 164
 
6.3%
9 149
 
5.8%
4 143
 
5.5%
6 137
 
5.3%
Other values (6) 333
12.9%
Latin
ValueCountFrequency (%)
T 99
52.1%
F 91
47.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2775
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 441
15.9%
- 381
13.7%
3 254
9.2%
2 210
7.6%
) 191
 
6.9%
5 182
 
6.6%
1 164
 
5.9%
9 149
 
5.4%
4 143
 
5.2%
6 137
 
4.9%
Other values (8) 523
18.8%

hmpg
Text

Distinct99
Distinct (%)100.0%
Missing1
Missing (%)1.0%
Memory size932.0 B
2023-12-10T18:55:10.741616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length14
Mean length15.020202
Min length11

Characters and Unicode

Total characters1487
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique99 ?
Unique (%)100.0%

Sample

1st rowwww.sfac.or.kr
2nd rowculture.asan.go.kr/_culture/new/
3rd rowwww.dgfc.or.kr
4th rowwww.ifac.or.kr
5th rowwww.gjcf.or.kr
ValueCountFrequency (%)
www.sfac.or.kr 1
 
1.0%
www.mycf.or.kr 1
 
1.0%
www.cwcf.or.kr 1
 
1.0%
www.ghcf.or.kr 1
 
1.0%
www.geojeart.or.kr 1
 
1.0%
www.phcf.or.kr 1
 
1.0%
http://www.yctf.or.kr 1
 
1.0%
www.yftf.kr 1
 
1.0%
www.cdws.or.kr 1
 
1.0%
www.cctf.or.kr 1
 
1.0%
Other values (89) 89
89.9%
2023-12-10T18:55:11.653104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 298
20.0%
. 283
19.0%
r 203
13.7%
c 102
 
6.9%
o 99
 
6.7%
k 96
 
6.5%
f 77
 
5.2%
a 57
 
3.8%
t 39
 
2.6%
g 33
 
2.2%
Other values (17) 200
13.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1182
79.5%
Other Punctuation 304
 
20.4%
Connector Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 298
25.2%
r 203
17.2%
c 102
 
8.6%
o 99
 
8.4%
k 96
 
8.1%
f 77
 
6.5%
a 57
 
4.8%
t 39
 
3.3%
g 33
 
2.8%
s 23
 
1.9%
Other values (13) 155
13.1%
Other Punctuation
ValueCountFrequency (%)
. 283
93.1%
/ 16
 
5.3%
: 5
 
1.6%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1182
79.5%
Common 305
 
20.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 298
25.2%
r 203
17.2%
c 102
 
8.6%
o 99
 
8.4%
k 96
 
8.1%
f 77
 
6.5%
a 57
 
4.8%
t 39
 
3.3%
g 33
 
2.8%
s 23
 
1.9%
Other values (13) 155
13.1%
Common
ValueCountFrequency (%)
. 283
92.8%
/ 16
 
5.2%
: 5
 
1.6%
_ 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1487
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 298
20.0%
. 283
19.0%
r 203
13.7%
c 102
 
6.9%
o 99
 
6.7%
k 96
 
6.5%
f 77
 
5.2%
a 57
 
3.8%
t 39
 
2.6%
g 33
 
2.2%
Other values (17) 200
13.4%

fond_dt
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:55:12.351016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.58
Min length5

Characters and Unicode

Total characters1058
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

Unique100 ?
Unique (%)100.0%

Sample

1st row2004.3.15.
2nd row2008.10.16.
3rd row2009.4.16
4th row2004.12.10.
5th row2010.12.27.
ValueCountFrequency (%)
2017.03.24 2
 
2.0%
2006.06.14 2
 
2.0%
2008.10.16 1
 
1.0%
2005.02.07 1
 
1.0%
2003.10.06 1
 
1.0%
2016.12.26 1
 
1.0%
2016.05.18 1
 
1.0%
2015.03.19 1
 
1.0%
2013.12.31 1
 
1.0%
2013.06.20 1
 
1.0%
Other values (88) 88
88.0%
2023-12-10T18:55:13.336414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 271
25.6%
0 232
21.9%
2 172
16.3%
1 169
16.0%
9 39
 
3.7%
3 35
 
3.3%
7 33
 
3.1%
6 30
 
2.8%
8 30
 
2.8%
5 29
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 787
74.4%
Other Punctuation 271
 
25.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 232
29.5%
2 172
21.9%
1 169
21.5%
9 39
 
5.0%
3 35
 
4.4%
7 33
 
4.2%
6 30
 
3.8%
8 30
 
3.8%
5 29
 
3.7%
4 18
 
2.3%
Other Punctuation
ValueCountFrequency (%)
. 271
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1058
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 271
25.6%
0 232
21.9%
2 172
16.3%
1 169
16.0%
9 39
 
3.7%
3 35
 
3.3%
7 33
 
3.1%
6 30
 
2.8%
8 30
 
2.8%
5 29
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1058
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 271
25.6%
0 232
21.9%
2 172
16.3%
1 169
16.0%
9 39
 
3.7%
3 35
 
3.3%
7 33
 
3.1%
6 30
 
2.8%
8 30
 
2.8%
5 29
 
2.7%

frst_dnt_arko
Categorical

IMBALANCE 

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
-
88 
<NA>
 
8
10
 
1
0
 
1
4
 
1

Length

Max length4
Median length1
Mean length1.28
Min length1

Unique

Unique4 ?
Unique (%)4.0%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-

Common Values

ValueCountFrequency (%)
- 88
88.0%
<NA> 8
 
8.0%
10 1
 
1.0%
0 1
 
1.0%
4 1
 
1.0%
44.1 1
 
1.0%

Length

2023-12-10T18:55:13.659012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:55:13.903745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
88
88.0%
na 8
 
8.0%
10 1
 
1.0%
0 1
 
1.0%
4 1
 
1.0%
44.1 1
 
1.0%

frst_dnt_ctprvn
Categorical

Distinct48
Distinct (%)48.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0.1
24 
-
1
0.5
 
5
3
 
5
Other values (43)
53 

Length

Max length5
Median length4
Mean length2.42
Min length1

Unique

Unique37 ?
Unique (%)37.0%

Sample

1st row500
2nd row2
3rd row215
4th row59.3
5th row53

Common Values

ValueCountFrequency (%)
0.1 24
24.0%
- 7
 
7.0%
1 6
 
6.0%
0.5 5
 
5.0%
3 5
 
5.0%
2 4
 
4.0%
10 4
 
4.0%
4 2
 
2.0%
9 2
 
2.0%
53 2
 
2.0%
Other values (38) 39
39.0%

Length

2023-12-10T18:55:14.210420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0.1 24
24.0%
7
 
7.0%
1 6
 
6.0%
0.5 5
 
5.0%
3 5
 
5.0%
2 4
 
4.0%
10 4
 
4.0%
17 2
 
2.0%
53 2
 
2.0%
9 2
 
2.0%
Other values (38) 39
39.0%

frst_dnt_etc
Categorical

IMBALANCE 

Distinct13
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
-
75 
<NA>
0
 
3
0.5
 
3
0.1
 
2
Other values (8)

Length

Max length4
Median length1
Mean length1.45
Min length1

Unique

Unique7 ?
Unique (%)7.0%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-

Common Values

ValueCountFrequency (%)
- 75
75.0%
<NA> 8
 
8.0%
0 3
 
3.0%
0.5 3
 
3.0%
0.1 2
 
2.0%
1 2
 
2.0%
16 1
 
1.0%
41 1
 
1.0%
2.4 1
 
1.0%
1.8 1
 
1.0%
Other values (3) 3
 
3.0%

Length

2023-12-10T18:55:14.577097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
75
75.0%
na 8
 
8.0%
0 3
 
3.0%
0.5 3
 
3.0%
0.1 2
 
2.0%
1 2
 
2.0%
16 1
 
1.0%
41 1
 
1.0%
2.4 1
 
1.0%
1.8 1
 
1.0%
Other values (3) 3
 
3.0%

frst_dnt_tot
Text

MISSING 

Distinct52
Distinct (%)53.1%
Missing2
Missing (%)2.0%
Memory size932.0 B
2023-12-10T18:55:14.913344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.5918367
Min length1

Characters and Unicode

Total characters254
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)41.8%

Sample

1st row500
2nd row2
3rd row215
4th row59.3
5th row53
ValueCountFrequency (%)
0.1 24
24.5%
0.5 7
 
7.1%
1 6
 
6.1%
2 4
 
4.1%
3
 
3.1%
10 3
 
3.1%
4 2
 
2.0%
11.6 2
 
2.0%
9 2
 
2.0%
53 2
 
2.0%
Other values (42) 43
43.9%
2023-12-10T18:55:15.608514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 57
22.4%
1 57
22.4%
0 46
18.1%
5 25
9.8%
2 19
 
7.5%
3 14
 
5.5%
9 10
 
3.9%
7 8
 
3.1%
4 6
 
2.4%
8 5
 
2.0%
Other values (2) 7
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 194
76.4%
Other Punctuation 57
 
22.4%
Dash Punctuation 3
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 57
29.4%
0 46
23.7%
5 25
12.9%
2 19
 
9.8%
3 14
 
7.2%
9 10
 
5.2%
7 8
 
4.1%
4 6
 
3.1%
8 5
 
2.6%
6 4
 
2.1%
Other Punctuation
ValueCountFrequency (%)
. 57
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 254
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 57
22.4%
1 57
22.4%
0 46
18.1%
5 25
9.8%
2 19
 
7.5%
3 14
 
5.5%
9 10
 
3.9%
7 8
 
3.1%
4 6
 
2.4%
8 5
 
2.0%
Other values (2) 7
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 254
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 57
22.4%
1 57
22.4%
0 46
18.1%
5 25
9.8%
2 19
 
7.5%
3 14
 
5.5%
9 10
 
3.9%
7 8
 
3.1%
4 6
 
2.4%
8 5
 
2.0%
Other values (2) 7
 
2.8%

fund_size
Categorical

Distinct37
Distinct (%)37.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
-
50 
<NA>
11 
0.1
 
3
217
 
2
1
 
2
Other values (32)
32 

Length

Max length17
Median length1
Mean length2.24
Min length1

Unique

Unique32 ?
Unique (%)32.0%

Sample

1st row897
2nd row-
3rd row217
4th row547.7
5th row95.2

Common Values

ValueCountFrequency (%)
- 50
50.0%
<NA> 11
 
11.0%
0.1 3
 
3.0%
217 2
 
2.0%
1 2
 
2.0%
58.5 1
 
1.0%
0 1
 
1.0%
57.2 1
 
1.0%
145 1
 
1.0%
292 1
 
1.0%
Other values (27) 27
27.0%

Length

2023-12-10T18:55:15.939658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
50
49.0%
na 11
 
10.8%
0.1 3
 
2.9%
217 2
 
2.0%
1 2
 
2.0%
24.5 1
 
1.0%
55.2 1
 
1.0%
31 1
 
1.0%
5.1 1
 
1.0%
54.6 1
 
1.0%
Other values (29) 29
28.4%

main_biz
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:55:16.474901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length353
Median length139.5
Mean length127.39
Min length16

Characters and Unicode

Total characters12739
Distinct characters376
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks7 ?
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 rowㅇ예술창작 활성화, 문예지원 및 창작공간 사업,ㅇ문화예술교육, 예술치유,ㅇ지역문화진흥 시민 문화활성화, 축제, 생활문화,ㅇ문화정책사업 및 공간기반 문화협치 확산
2nd rowㅇ문화예술 활동의 지원,ㅇ문화예술 정책연구와 제안,ㅇ문화예술의 창작, 보급과 조사연구,ㅇ국내․외 문화예술 교류,ㅇ문화유산을 발굴․육성과 보전,ㅇ위탁받은 축제행사,ㅇ문화예술진흥 발전을 위하여 시장이 위탁하는 사업,ㅇ위탁받은 문화시설에 대한 관리·운영 및 전대, 대관사업,ㅇ문화예술 전시 및 교육사업,ㅇ위 각호의 수익사업,ㅇ기타 법인의 목적달성에 필요한 사업
3rd rowㅇ문화예술 창작보급 및 문화예술활동 지원,ㅇ시민 문화향수 기회 확대 및 창의성 제고,ㅇ전통문화예술의 계승과 발전,ㅇ문화예술진흥을 위한 정책개발, 자문 및 교육, 연구,ㅇ국내외 문화예술 교류,ㅇ문화예술 정보 축적 및 네트워크서비스사업
4th rowㅇ문화예술 기금지원 사업,ㅇ시민문화 활성화사업,ㅇ문화예술정책연구사업,ㅇ문화예술교류사업,ㅇ문화예술교육사업,ㅇ인천아트플랫폼 운영,ㅇ한국근대문학관 운영,ㅇ트라이보울 운영 ,ㅇ강화/인천지역 역사연구,ㅇ남북문화교류사업 ,ㅇ인천시위탁사업 등
5th rowㅇ문화예술정책개발 및 사업실행,ㅇ문화관광진흥사업,ㅇ문화예술기금지원사업,ㅇ문화예술교육사업,ㅇ문화예술교류사업,ㅇ축제행사,ㅇ빛고을 시민문화관 운용 및 지원사업
ValueCountFrequency (%)
315
 
14.0%
운영 68
 
3.0%
사업 54
 
2.4%
위한 35
 
1.6%
문화예술 33
 
1.5%
개발 32
 
1.4%
30
 
1.3%
관리 30
 
1.3%
위하여 29
 
1.3%
지원 27
 
1.2%
Other values (958) 1605
71.1%
2023-12-10T18:55:17.386367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2530
 
19.9%
, 643
 
5.0%
586
 
4.6%
533
 
4.2%
514
 
4.0%
342
 
2.7%
339
 
2.7%
319
 
2.5%
284
 
2.2%
262
 
2.1%
Other values (366) 6387
50.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9358
73.5%
Space Separator 2530
 
19.9%
Other Punctuation 733
 
5.8%
Close Punctuation 32
 
0.3%
Open Punctuation 30
 
0.2%
Uppercase Letter 20
 
0.2%
Decimal Number 18
 
0.1%
Other Symbol 11
 
0.1%
Math Symbol 5
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
586
 
6.3%
533
 
5.7%
514
 
5.5%
342
 
3.7%
339
 
3.6%
319
 
3.4%
284
 
3.0%
262
 
2.8%
248
 
2.7%
229
 
2.4%
Other values (332) 5702
60.9%
Uppercase Letter
ValueCountFrequency (%)
D 5
25.0%
B 3
15.0%
I 2
 
10.0%
F 2
 
10.0%
M 2
 
10.0%
O 1
 
5.0%
S 1
 
5.0%
E 1
 
5.0%
C 1
 
5.0%
K 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 643
87.7%
· 51
 
7.0%
14
 
1.9%
. 9
 
1.2%
: 5
 
0.7%
/ 5
 
0.7%
' 4
 
0.5%
" 2
 
0.3%
Decimal Number
ValueCountFrequency (%)
2 4
22.2%
1 3
16.7%
4 3
16.7%
3 3
16.7%
5 2
11.1%
9 2
11.1%
7 1
 
5.6%
Close Punctuation
ValueCountFrequency (%)
) 30
93.8%
2
 
6.2%
Open Punctuation
ValueCountFrequency (%)
( 28
93.3%
2
 
6.7%
Space Separator
ValueCountFrequency (%)
2530
100.0%
Other Symbol
ValueCountFrequency (%)
11
100.0%
Math Symbol
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9358
73.5%
Common 3361
 
26.4%
Latin 20
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
586
 
6.3%
533
 
5.7%
514
 
5.5%
342
 
3.7%
339
 
3.6%
319
 
3.4%
284
 
3.0%
262
 
2.8%
248
 
2.7%
229
 
2.4%
Other values (332) 5702
60.9%
Common
ValueCountFrequency (%)
2530
75.3%
, 643
 
19.1%
· 51
 
1.5%
) 30
 
0.9%
( 28
 
0.8%
14
 
0.4%
11
 
0.3%
. 9
 
0.3%
: 5
 
0.1%
5
 
0.1%
Other values (13) 35
 
1.0%
Latin
ValueCountFrequency (%)
D 5
25.0%
B 3
15.0%
I 2
 
10.0%
F 2
 
10.0%
M 2
 
10.0%
O 1
 
5.0%
S 1
 
5.0%
E 1
 
5.0%
C 1
 
5.0%
K 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8765
68.8%
ASCII 3296
 
25.9%
Compat Jamo 593
 
4.7%
None 55
 
0.4%
Punctuation 14
 
0.1%
Geometric Shapes 11
 
0.1%
Math Operators 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2530
76.8%
, 643
 
19.5%
) 30
 
0.9%
( 28
 
0.8%
. 9
 
0.3%
: 5
 
0.2%
D 5
 
0.2%
/ 5
 
0.2%
2 4
 
0.1%
' 4
 
0.1%
Other values (18) 33
 
1.0%
Compat Jamo
ValueCountFrequency (%)
586
98.8%
7
 
1.2%
Hangul
ValueCountFrequency (%)
533
 
6.1%
514
 
5.9%
342
 
3.9%
339
 
3.9%
319
 
3.6%
284
 
3.2%
262
 
3.0%
248
 
2.8%
229
 
2.6%
167
 
1.9%
Other values (330) 5528
63.1%
None
ValueCountFrequency (%)
· 51
92.7%
2
 
3.6%
2
 
3.6%
Punctuation
ValueCountFrequency (%)
14
100.0%
Geometric Shapes
ValueCountFrequency (%)
11
100.0%
Math Operators
ValueCountFrequency (%)
5
100.0%
Distinct80
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:55:17.905061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length16
Mean length7.53
Min length2

Characters and Unicode

Total characters753
Distinct characters57
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

Unique71 ?
Unique (%)71.0%

Sample

1st row2실 5본부
2nd row1사무국4팀
3rd row3본부 9팀 1센터
4th row2실 3부,2센터 3관
5th row1처 2실 1단 2관 13팀
ValueCountFrequency (%)
1국 16
 
7.7%
4팀 15
 
7.2%
3팀 12
 
5.7%
5팀 8
 
3.8%
1실 8
 
3.8%
2본부 8
 
3.8%
1처 7
 
3.3%
1본부 7
 
3.3%
1관 6
 
2.9%
3본부 6
 
2.9%
Other values (70) 116
55.5%
2023-12-10T18:55:18.725338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
109
14.5%
1 100
13.3%
87
 
11.6%
44
 
5.8%
2 41
 
5.4%
3 39
 
5.2%
33
 
4.4%
, 29
 
3.9%
29
 
3.9%
4 22
 
2.9%
Other values (47) 220
29.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 347
46.1%
Decimal Number 250
33.2%
Space Separator 109
 
14.5%
Other Punctuation 29
 
3.9%
Uppercase Letter 10
 
1.3%
Close Punctuation 4
 
0.5%
Open Punctuation 4
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
87
25.1%
44
12.7%
33
 
9.5%
29
 
8.4%
20
 
5.8%
18
 
5.2%
17
 
4.9%
12
 
3.5%
11
 
3.2%
11
 
3.2%
Other values (31) 65
18.7%
Decimal Number
ValueCountFrequency (%)
1 100
40.0%
2 41
16.4%
3 39
 
15.6%
4 22
 
8.8%
5 16
 
6.4%
6 9
 
3.6%
7 8
 
3.2%
0 7
 
2.8%
9 5
 
2.0%
8 3
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
F 5
50.0%
T 5
50.0%
Space Separator
ValueCountFrequency (%)
109
100.0%
Other Punctuation
ValueCountFrequency (%)
, 29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 396
52.6%
Hangul 347
46.1%
Latin 10
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
87
25.1%
44
12.7%
33
 
9.5%
29
 
8.4%
20
 
5.8%
18
 
5.2%
17
 
4.9%
12
 
3.5%
11
 
3.2%
11
 
3.2%
Other values (31) 65
18.7%
Common
ValueCountFrequency (%)
109
27.5%
1 100
25.3%
2 41
 
10.4%
3 39
 
9.8%
, 29
 
7.3%
4 22
 
5.6%
5 16
 
4.0%
6 9
 
2.3%
7 8
 
2.0%
0 7
 
1.8%
Other values (4) 16
 
4.0%
Latin
ValueCountFrequency (%)
F 5
50.0%
T 5
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 406
53.9%
Hangul 347
46.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
109
26.8%
1 100
24.6%
2 41
 
10.1%
3 39
 
9.6%
, 29
 
7.1%
4 22
 
5.4%
5 16
 
3.9%
6 9
 
2.2%
7 8
 
2.0%
0 7
 
1.7%
Other values (6) 26
 
6.4%
Hangul
ValueCountFrequency (%)
87
25.1%
44
12.7%
33
 
9.5%
29
 
8.4%
20
 
5.8%
18
 
5.2%
17
 
4.9%
12
 
3.5%
11
 
3.2%
11
 
3.2%
Other values (31) 65
18.7%

hr_tot
Real number (ℝ)

Distinct65
Distinct (%)65.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.69
Minimum5
Maximum614
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:55:19.025601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile7
Q120
median44.5
Q380
95-th percentile204.5
Maximum614
Range609
Interquartile range (IQR)60

Descriptive statistics

Standard deviation85.53252
Coefficient of variation (CV)1.2635917
Kurtosis18.593338
Mean67.69
Median Absolute Deviation (MAD)27.5
Skewness3.7375635
Sum6769
Variance7315.812
MonotonicityNot monotonic
2023-12-10T18:55:19.331776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7 5
 
5.0%
21 4
 
4.0%
20 3
 
3.0%
80 3
 
3.0%
11 3
 
3.0%
72 3
 
3.0%
35 3
 
3.0%
15 3
 
3.0%
90 2
 
2.0%
14 2
 
2.0%
Other values (55) 69
69.0%
ValueCountFrequency (%)
5 2
 
2.0%
7 5
5.0%
8 1
 
1.0%
9 1
 
1.0%
10 1
 
1.0%
11 3
3.0%
14 2
 
2.0%
15 3
3.0%
16 2
 
2.0%
18 1
 
1.0%
ValueCountFrequency (%)
614 1
1.0%
388 1
1.0%
350 1
1.0%
226 1
1.0%
214 1
1.0%
204 1
1.0%
180 1
1.0%
178 1
1.0%
153 1
1.0%
140 1
1.0%

hr_rgllbr
Real number (ℝ)

Distinct62
Distinct (%)62.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.14
Minimum0
Maximum362
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:55:19.624696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.95
Q111
median32.5
Q360
95-th percentile116.45
Maximum362
Range362
Interquartile range (IQR)49

Descriptive statistics

Standard deviation55.768283
Coefficient of variation (CV)1.2086754
Kurtosis14.668755
Mean46.14
Median Absolute Deviation (MAD)22.5
Skewness3.3239509
Sum4614
Variance3110.1014
MonotonicityNot monotonic
2023-12-10T18:55:19.921411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 5
 
5.0%
18 5
 
5.0%
7 5
 
5.0%
40 4
 
4.0%
68 4
 
4.0%
44 4
 
4.0%
8 3
 
3.0%
10 3
 
3.0%
2 3
 
3.0%
11 3
 
3.0%
Other values (52) 61
61.0%
ValueCountFrequency (%)
0 1
 
1.0%
2 3
3.0%
3 1
 
1.0%
4 1
 
1.0%
6 5
5.0%
7 5
5.0%
8 3
3.0%
9 1
 
1.0%
10 3
3.0%
11 3
3.0%
ValueCountFrequency (%)
362 1
1.0%
314 1
1.0%
187 1
1.0%
173 1
1.0%
144 1
1.0%
115 1
1.0%
109 1
1.0%
107 1
1.0%
102 1
1.0%
93 1
1.0%

hr_irgllbr
Categorical

Distinct45
Distinct (%)45.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
4
 
6
3
 
5
10
 
5
0
 
5
6
 
5
Other values (40)
74 

Length

Max length19
Median length13
Mean length1.84
Min length1

Unique

Unique21 ?
Unique (%)21.0%

Sample

1st row38
2nd row9
3rd row30
4th row34
5th row45

Common Values

ValueCountFrequency (%)
4 6
 
6.0%
3 5
 
5.0%
10 5
 
5.0%
0 5
 
5.0%
6 5
 
5.0%
7 4
 
4.0%
5 4
 
4.0%
1 4
 
4.0%
36 4
 
4.0%
18 3
 
3.0%
Other values (35) 55
55.0%

Length

2023-12-10T18:55:20.811648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
4 6
 
5.9%
10 6
 
5.9%
0 5
 
4.9%
6 5
 
4.9%
3 5
 
4.9%
7 4
 
3.9%
5 4
 
3.9%
1 4
 
3.9%
36 4
 
3.9%
22 3
 
2.9%
Other values (36) 56
54.9%
Distinct95
Distinct (%)96.0%
Missing1
Missing (%)1.0%
Memory size932.0 B
2023-12-10T18:55:21.300751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length3.2121212
Min length1

Characters and Unicode

Total characters318
Distinct characters20
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique91 ?
Unique (%)91.9%

Sample

1st row574
2nd row25
3rd row150
4th row178
5th row94
ValueCountFrequency (%)
63 2
 
2.0%
10.5 2
 
2.0%
18 2
 
2.0%
92 2
 
2.0%
1.1,(국고보조금 1
 
1.0%
32.5 1
 
1.0%
185 1
 
1.0%
23 1
 
1.0%
108 1
 
1.0%
5.7 1
 
1.0%
Other values (85) 85
85.9%
2023-12-10T18:55:22.155032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 53
16.7%
. 44
13.8%
5 39
12.3%
2 31
9.7%
8 30
9.4%
4 25
7.9%
3 22
6.9%
6 21
 
6.6%
7 18
 
5.7%
9 14
 
4.4%
Other values (10) 21
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 265
83.3%
Other Punctuation 45
 
14.2%
Other Letter 5
 
1.6%
Dash Punctuation 1
 
0.3%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 53
20.0%
5 39
14.7%
2 31
11.7%
8 30
11.3%
4 25
9.4%
3 22
8.3%
6 21
 
7.9%
7 18
 
6.8%
9 14
 
5.3%
0 12
 
4.5%
Other Letter
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Other Punctuation
ValueCountFrequency (%)
. 44
97.8%
, 1
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 313
98.4%
Hangul 5
 
1.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 53
16.9%
. 44
14.1%
5 39
12.5%
2 31
9.9%
8 30
9.6%
4 25
8.0%
3 22
7.0%
6 21
 
6.7%
7 18
 
5.8%
9 14
 
4.5%
Other values (5) 16
 
5.1%
Hangul
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 313
98.4%
Hangul 5
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 53
16.9%
. 44
14.1%
5 39
12.5%
2 31
9.9%
8 30
9.6%
4 25
8.0%
3 22
7.0%
6 21
 
6.7%
7 18
 
5.8%
9 14
 
4.5%
Other values (5) 16
 
5.1%
Hangul
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

bdg_stts_ntrs
Text

MISSING 

Distinct47
Distinct (%)50.5%
Missing7
Missing (%)7.0%
Memory size932.0 B
2023-12-10T18:55:22.553725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length1
Mean length1.9892473
Min length1

Characters and Unicode

Total characters185
Distinct characters20
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)40.9%

Sample

1st row-
2nd row0
3rd row80
4th row75
5th row74
ValueCountFrequency (%)
0 24
25.8%
14
 
15.1%
1 4
 
4.3%
0.2 3
 
3.2%
1.6 2
 
2.2%
80 2
 
2.2%
29 2
 
2.2%
2 2
 
2.2%
4 2
 
2.2%
20.6 1
 
1.1%
Other values (37) 37
39.8%
2023-12-10T18:55:23.386133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 36
19.5%
. 30
16.2%
1 18
9.7%
2 18
9.7%
- 14
 
7.6%
3 12
 
6.5%
4 11
 
5.9%
8 11
 
5.9%
7 9
 
4.9%
5 7
 
3.8%
Other values (10) 19
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 133
71.9%
Other Punctuation 31
 
16.8%
Dash Punctuation 14
 
7.6%
Other Letter 5
 
2.7%
Open Punctuation 1
 
0.5%
Close Punctuation 1
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 36
27.1%
1 18
13.5%
2 18
13.5%
3 12
 
9.0%
4 11
 
8.3%
8 11
 
8.3%
7 9
 
6.8%
5 7
 
5.3%
9 7
 
5.3%
6 4
 
3.0%
Other Letter
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Other Punctuation
ValueCountFrequency (%)
. 30
96.8%
, 1
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 180
97.3%
Hangul 5
 
2.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 36
20.0%
. 30
16.7%
1 18
10.0%
2 18
10.0%
- 14
 
7.8%
3 12
 
6.7%
4 11
 
6.1%
8 11
 
6.1%
7 9
 
5.0%
5 7
 
3.9%
Other values (5) 14
 
7.8%
Hangul
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 180
97.3%
Hangul 5
 
2.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 36
20.0%
. 30
16.7%
1 18
10.0%
2 18
10.0%
- 14
 
7.8%
3 12
 
6.7%
4 11
 
6.1%
8 11
 
6.1%
7 9
 
5.0%
5 7
 
3.9%
Other values (5) 14
 
7.8%
Hangul
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

bdg_stts_onslf
Text

MISSING 

Distinct61
Distinct (%)64.2%
Missing5
Missing (%)5.0%
Memory size932.0 B
2023-12-10T18:55:23.779707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1263158
Min length1

Characters and Unicode

Total characters202
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)54.7%

Sample

1st row-
2nd row0
3rd row42
4th row14
5th row10
ValueCountFrequency (%)
18
 
18.9%
0 9
 
9.5%
10 3
 
3.2%
1 3
 
3.2%
14 2
 
2.1%
3 2
 
2.1%
16 2
 
2.1%
2 2
 
2.1%
5 2
 
2.1%
28 1
 
1.1%
Other values (51) 51
53.7%
2023-12-10T18:55:24.593101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 32
15.8%
1 30
14.9%
2 23
11.4%
5 20
9.9%
0 19
9.4%
- 18
8.9%
4 16
7.9%
3 14
6.9%
7 10
 
5.0%
6 8
 
4.0%
Other values (2) 12
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 152
75.2%
Other Punctuation 32
 
15.8%
Dash Punctuation 18
 
8.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 30
19.7%
2 23
15.1%
5 20
13.2%
0 19
12.5%
4 16
10.5%
3 14
9.2%
7 10
 
6.6%
6 8
 
5.3%
8 7
 
4.6%
9 5
 
3.3%
Other Punctuation
ValueCountFrequency (%)
. 32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 202
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 32
15.8%
1 30
14.9%
2 23
11.4%
5 20
9.9%
0 19
9.4%
- 18
8.9%
4 16
7.9%
3 14
6.9%
7 10
 
5.0%
6 8
 
4.0%
Other values (2) 12
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 202
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 32
15.8%
1 30
14.9%
2 23
11.4%
5 20
9.9%
0 19
9.4%
- 18
8.9%
4 16
7.9%
3 14
6.9%
7 10
 
5.0%
6 8
 
4.0%
Other values (2) 12
 
5.9%

bdg_stts_etc
Categorical

Distinct35
Distinct (%)35.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
-
29 
0
22 
<NA>
3
 
3
1
 
3
Other values (30)
35 

Length

Max length5
Median length1
Mean length1.87
Min length1

Unique

Unique26 ?
Unique (%)26.0%

Sample

1st row100
2nd row0
3rd row3
4th row3
5th row1

Common Values

ValueCountFrequency (%)
- 29
29.0%
0 22
22.0%
<NA> 8
 
8.0%
3 3
 
3.0%
1 3
 
3.0%
10 3
 
3.0%
0.2 2
 
2.0%
0.1 2
 
2.0%
1.8 2
 
2.0%
15.7 1
 
1.0%
Other values (25) 25
25.0%

Length

2023-12-10T18:55:24.882407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
29
29.0%
0 22
22.0%
na 8
 
8.0%
3 3
 
3.0%
1 3
 
3.0%
10 3
 
3.0%
0.2 2
 
2.0%
0.1 2
 
2.0%
1.8 2
 
2.0%
0.07 1
 
1.0%
Other values (25) 25
25.0%

bdg_stts_tot
Real number (ℝ)

Distinct97
Distinct (%)98.0%
Missing1
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean114.02262
Minimum2.2
Maximum847
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:55:25.209215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.2
5-th percentile13.89
Q133.6
median72
Q3166.5
95-th percentile328.02
Maximum847
Range844.8
Interquartile range (IQR)132.9

Descriptive statistics

Standard deviation122.46471
Coefficient of variation (CV)1.0740387
Kurtosis12.683509
Mean114.02262
Median Absolute Deviation (MAD)47.6
Skewness2.8410049
Sum11288.239
Variance14997.605
MonotonicityNot monotonic
2023-12-10T18:55:25.504632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
210.0 2
 
2.0%
33.6 2
 
2.0%
847.0 1
 
1.0%
34.4 1
 
1.0%
330.0 1
 
1.0%
38.0 1
 
1.0%
147.0 1
 
1.0%
26.3 1
 
1.0%
13.9 1
 
1.0%
24.0 1
 
1.0%
Other values (87) 87
87.0%
ValueCountFrequency (%)
2.2 1
1.0%
3.6 1
1.0%
4.4 1
1.0%
7.0 1
1.0%
13.8 1
1.0%
13.9 1
1.0%
16.42 1
1.0%
17.7 1
1.0%
17.71 1
1.0%
18.0 1
1.0%
ValueCountFrequency (%)
847.0 1
1.0%
471.8 1
1.0%
415.7 1
1.0%
338.0 1
1.0%
330.0 1
1.0%
327.8 1
1.0%
298.0 1
1.0%
294.6 1
1.0%
275.0 1
1.0%
270.0 1
1.0%
Distinct33
Distinct (%)33.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
5
13 
-
6
2
1
Other values (28)
58 

Length

Max length4
Median length1
Mean length1.43
Min length1

Unique

Unique12 ?
Unique (%)12.0%

Sample

1st row8
2nd row5
3rd row12
4th row18
5th row14

Common Values

ValueCountFrequency (%)
5 13
 
13.0%
- 8
 
8.0%
6 7
 
7.0%
2 7
 
7.0%
1 7
 
7.0%
8 6
 
6.0%
7 5
 
5.0%
0 4
 
4.0%
10 3
 
3.0%
16 3
 
3.0%
Other values (23) 37
37.0%

Length

2023-12-10T18:55:25.766033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5 13
 
13.0%
8
 
8.0%
6 7
 
7.0%
2 7
 
7.0%
1 7
 
7.0%
8 6
 
6.0%
7 5
 
5.0%
0 4
 
4.0%
16 3
 
3.0%
11 3
 
3.0%
Other values (23) 37
37.0%

biz_stts_edu_biz
Categorical

Distinct24
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2
12 
4
11 
7
-
5
Other values (19)
56 

Length

Max length4
Median length1
Mean length1.32
Min length1

Unique

Unique6 ?
Unique (%)6.0%

Sample

1st row7
2nd row4
3rd row9
4th row13
5th row4

Common Values

ValueCountFrequency (%)
2 12
12.0%
4 11
11.0%
7 7
 
7.0%
- 7
 
7.0%
5 7
 
7.0%
1 7
 
7.0%
3 6
 
6.0%
6 6
 
6.0%
0 5
 
5.0%
10 5
 
5.0%
Other values (14) 27
27.0%

Length

2023-12-10T18:55:26.044575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2 12
12.0%
4 11
11.0%
7 7
 
7.0%
7
 
7.0%
5 7
 
7.0%
1 7
 
7.0%
3 6
 
6.0%
6 6
 
6.0%
0 5
 
5.0%
10 5
 
5.0%
Other values (14) 27
27.0%
Distinct26
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
-
22 
3
10 
4
0
2
Other values (21)
45 

Length

Max length4
Median length1
Mean length1.41
Min length1

Unique

Unique13 ?
Unique (%)13.0%

Sample

1st row13
2nd row3
3rd row11
4th row25
5th row6

Common Values

ValueCountFrequency (%)
- 22
22.0%
3 10
10.0%
4 8
 
8.0%
0 8
 
8.0%
2 7
 
7.0%
<NA> 6
 
6.0%
6 6
 
6.0%
1 5
 
5.0%
7 4
 
4.0%
11 4
 
4.0%
Other values (16) 20
20.0%

Length

2023-12-10T18:55:26.323675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
22
22.0%
3 10
10.0%
4 8
 
8.0%
0 8
 
8.0%
2 7
 
7.0%
na 6
 
6.0%
6 6
 
6.0%
1 5
 
5.0%
11 4
 
4.0%
7 4
 
4.0%
Other values (16) 20
20.0%

biz_stts_etc_biz
Categorical

Distinct40
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
8
4
10
 
6
20
 
5
1
 
4
Other values (35)
69 

Length

Max length4
Median length2
Mean length1.68
Min length1

Unique

Unique16 ?
Unique (%)16.0%

Sample

1st row17
2nd row11
3rd row10
4th row29
5th row40

Common Values

ValueCountFrequency (%)
8 9
 
9.0%
4 7
 
7.0%
10 6
 
6.0%
20 5
 
5.0%
1 4
 
4.0%
11 4
 
4.0%
2 4
 
4.0%
3 4
 
4.0%
14 3
 
3.0%
21 3
 
3.0%
Other values (30) 51
51.0%

Length

2023-12-10T18:55:26.624699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
8 9
 
9.0%
4 7
 
7.0%
10 6
 
6.0%
20 5
 
5.0%
1 4
 
4.0%
11 4
 
4.0%
2 4
 
4.0%
3 4
 
4.0%
7 3
 
3.0%
6 3
 
3.0%
Other values (30) 51
51.0%

biz_stts_tot
Text

MISSING 

Distinct59
Distinct (%)60.2%
Missing2
Missing (%)2.0%
Memory size932.0 B
2023-12-10T18:55:27.047313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length1.9693878
Min length1

Characters and Unicode

Total characters193
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)38.8%

Sample

1st row45
2nd row23
3rd row42
4th row85
5th row64
ValueCountFrequency (%)
15 5
 
5.1%
37 5
 
5.1%
50 4
 
4.1%
39 4
 
4.1%
25 4
 
4.1%
54 4
 
4.1%
22 3
 
3.1%
14 3
 
3.1%
2 3
 
3.1%
24 3
 
3.1%
Other values (49) 60
61.2%
2023-12-10T18:55:27.808524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 30
15.5%
5 28
14.5%
1 26
13.5%
4 25
13.0%
3 21
10.9%
7 15
7.8%
0 13
6.7%
9 12
 
6.2%
6 11
 
5.7%
8 8
 
4.1%
Other values (2) 4
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 189
97.9%
Other Punctuation 3
 
1.6%
Dash Punctuation 1
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 30
15.9%
5 28
14.8%
1 26
13.8%
4 25
13.2%
3 21
11.1%
7 15
7.9%
0 13
6.9%
9 12
 
6.3%
6 11
 
5.8%
8 8
 
4.2%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 193
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 30
15.5%
5 28
14.5%
1 26
13.5%
4 25
13.0%
3 21
10.9%
7 15
7.8%
0 13
6.7%
9 12
 
6.2%
6 11
 
5.7%
8 8
 
4.1%
Other values (2) 4
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 193
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 30
15.5%
5 28
14.5%
1 26
13.5%
4 25
13.0%
3 21
10.9%
7 15
7.8%
0 13
6.7%
9 12
 
6.2%
6 11
 
5.7%
8 8
 
4.1%
Other values (2) 4
 
2.1%
Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:55:28.264729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length167
Median length18
Mean length13.37
Min length4

Characters and Unicode

Total characters1337
Distinct characters68
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique96 ?
Unique (%)96.0%

Sample

1st row자체,( 2367.41㎡)
2nd row위탁,(824.1㎡)
3rd row임대,(1305.83㎡)
4th row자체,(808.4㎡)
5th row무상임대,(824㎡)
ValueCountFrequency (%)
자체 13
 
9.8%
무상임대,(140㎡ 2
 
1.5%
148.2㎡ 2
 
1.5%
무상임대,(141.13㎡ 1
 
0.8%
산격1동(106㎡ 1
 
0.8%
노원동(68.7㎡ 1
 
0.8%
90㎡ 1
 
0.8%
고성동 1
 
0.8%
1
 
0.8%
937㎡),작은도서관 1
 
0.8%
Other values (109) 109
82.0%
2023-12-10T18:55:29.077538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 120
 
9.0%
109
 
8.2%
( 103
 
7.7%
) 103
 
7.7%
1 76
 
5.7%
63
 
4.7%
62
 
4.6%
. 59
 
4.4%
2 53
 
4.0%
3 50
 
3.7%
Other values (58) 539
40.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 454
34.0%
Other Letter 344
25.7%
Other Punctuation 179
 
13.4%
Other Symbol 109
 
8.2%
Open Punctuation 103
 
7.7%
Close Punctuation 103
 
7.7%
Space Separator 33
 
2.5%
Dash Punctuation 8
 
0.6%
Other Number 2
 
0.1%
Lowercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
63
18.3%
62
18.0%
45
13.1%
45
13.1%
29
8.4%
28
8.1%
6
 
1.7%
5
 
1.5%
4
 
1.2%
4
 
1.2%
Other values (39) 53
15.4%
Decimal Number
ValueCountFrequency (%)
1 76
16.7%
2 53
11.7%
3 50
11.0%
4 45
9.9%
0 43
9.5%
5 41
9.0%
7 41
9.0%
8 40
8.8%
6 33
7.3%
9 32
7.0%
Other Punctuation
ValueCountFrequency (%)
, 120
67.0%
. 59
33.0%
Other Symbol
ValueCountFrequency (%)
109
100.0%
Open Punctuation
ValueCountFrequency (%)
( 103
100.0%
Close Punctuation
ValueCountFrequency (%)
) 103
100.0%
Space Separator
ValueCountFrequency (%)
33
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Other Number
ValueCountFrequency (%)
² 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 991
74.1%
Hangul 344
 
25.7%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
63
18.3%
62
18.0%
45
13.1%
45
13.1%
29
8.4%
28
8.1%
6
 
1.7%
5
 
1.5%
4
 
1.2%
4
 
1.2%
Other values (39) 53
15.4%
Common
ValueCountFrequency (%)
, 120
12.1%
109
11.0%
( 103
10.4%
) 103
10.4%
1 76
 
7.7%
. 59
 
6.0%
2 53
 
5.3%
3 50
 
5.0%
4 45
 
4.5%
0 43
 
4.3%
Other values (8) 230
23.2%
Latin
ValueCountFrequency (%)
m 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 882
66.0%
Hangul 344
 
25.7%
CJK Compat 109
 
8.2%
None 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 120
13.6%
( 103
11.7%
) 103
11.7%
1 76
8.6%
. 59
 
6.7%
2 53
 
6.0%
3 50
 
5.7%
4 45
 
5.1%
0 43
 
4.9%
5 41
 
4.6%
Other values (7) 189
21.4%
CJK Compat
ValueCountFrequency (%)
109
100.0%
Hangul
ValueCountFrequency (%)
63
18.3%
62
18.0%
45
13.1%
45
13.1%
29
8.4%
28
8.1%
6
 
1.7%
5
 
1.5%
4
 
1.2%
4
 
1.2%
Other values (39) 53
15.4%
None
ValueCountFrequency (%)
² 2
100.0%

lst_updt_dt
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20210215123123
100 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210215123123
2nd row20210215123123
3rd row20210215123123
4th row20210215123123
5th row20210215123123

Common Values

ValueCountFrequency (%)
20210215123123 100
100.0%

Length

2023-12-10T18:55:29.367051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:55:29.581334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210215123123 100
100.0%

data_orgn
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
문화데이터총람 2020
100 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row문화데이터총람 2020
2nd row문화데이터총람 2020
3rd row문화데이터총람 2020
4th row문화데이터총람 2020
5th row문화데이터총람 2020

Common Values

ValueCountFrequency (%)
문화데이터총람 2020 100
100.0%

Length

2023-12-10T18:55:29.804823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:55:30.114830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문화데이터총람 100
50.0%
2020 100
50.0%

file_name
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
KC_482_DMSTC_MCST_CLTPLC_2021
100 

Length

Max length29
Median length29
Mean length29
Min length29

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKC_482_DMSTC_MCST_CLTPLC_2021
2nd rowKC_482_DMSTC_MCST_CLTPLC_2021
3rd rowKC_482_DMSTC_MCST_CLTPLC_2021
4th rowKC_482_DMSTC_MCST_CLTPLC_2021
5th rowKC_482_DMSTC_MCST_CLTPLC_2021

Common Values

ValueCountFrequency (%)
KC_482_DMSTC_MCST_CLTPLC_2021 100
100.0%

Length

2023-12-10T18:55:30.372491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:55:30.542319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kc_482_dmstc_mcst_cltplc_2021 100
100.0%

base_ymd
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20200101
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20200101
2nd row20200101
3rd row20200101
4th row20200101
5th row20200101

Common Values

ValueCountFrequency (%)
20200101 100
100.0%

Length

2023-12-10T18:55:30.743281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:55:30.932718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20200101 100
100.0%

Sample

idlclasmlsfcfclt_namectprvn_nmsgnr_nmlegaldong_cdlegalemd_nmadstrd_cdadstrd_nmrdnmaddr_cdrdnm_addrzip_cdgrid_cdx_cdy_cdfond_mclnccofcttpchmpgfond_dtfrst_dnt_arkofrst_dnt_ctprvnfrst_dnt_etcfrst_dnt_totfund_sizemain_bizorg_sttshr_tothr_rgllbrhr_irgllbrbdg_stts_lgov_asstbdg_stts_ntrsbdg_stts_onslfbdg_stts_etcbdg_stts_totbiz_stts_suppt_bizbiz_stts_edu_bizbiz_stts_fclt_bizbiz_stts_etc_bizbiz_stts_totofce_aealst_updt_dtdata_orgnfile_namebase_ymd
0KCDMMCC21N000000001문화시설지역문화재단서울문화재단서울특별시서울 종로구1111016800동숭동1111064000이화동111104100075서울 종로구 동숭길 1223084다사56153937.583699127.003717서울특별시 재단법인 서울문화재단 설립 및 운영에 관한 조례이경자,(한국작가회의 이사장)T)02-3290-7000,F)02-6008-7346www.sfac.or.kr2004.3.15.-500-500897ㅇ예술창작 활성화, 문예지원 및 창작공간 사업,ㅇ문화예술교육, 예술치유,ㅇ지역문화진흥 시민 문화활성화, 축제, 생활문화,ㅇ문화정책사업 및 공간기반 문화협치 확산2실 5본부22617338574--100847.087131745자체,( 2367.41㎡)20210215123123문화데이터총람 2020KC_482_DMSTC_MCST_CLTPLC_202120200101
1KCDMMCC21N000000101문화시설지역문화재단아산문화재단충청남도아산시4420025032염치읍 송곡리4420025000염치읍442004559688충남 아산시 염치읍 은행나무길 29331450다바57067036.800445127.018897아산문화재단 설립 및 운영에 관한 조례오세현,(시장)T)041-540-2550,F)041-534-2633culture.asan.go.kr/_culture/new/2008.10.16.-2-2-ㅇ문화예술 활동의 지원,ㅇ문화예술 정책연구와 제안,ㅇ문화예술의 창작, 보급과 조사연구,ㅇ국내․외 문화예술 교류,ㅇ문화유산을 발굴․육성과 보전,ㅇ위탁받은 축제행사,ㅇ문화예술진흥 발전을 위하여 시장이 위탁하는 사업,ㅇ위탁받은 문화시설에 대한 관리·운영 및 전대, 대관사업,ㅇ문화예술 전시 및 교육사업,ㅇ위 각호의 수익사업,ㅇ기타 법인의 목적달성에 필요한 사업1사무국4팀14492500025.05431123위탁,(824.1㎡)20210215123123문화데이터총람 2020KC_482_DMSTC_MCST_CLTPLC_202120200101
2KCDMMCC21N000000003문화시설지역문화재단대구문화재단대구광역시대구 중구2711015700대봉동2711068000대봉1동271103141012대구 중구 대봉로 26041950라마99363335.861527128.600746대구광역시 문화재단 설립 및 운영 조례권영진,(대구광역시장)T)053-430-1200,F)053-422-1214www.dgfc.or.kr2009.4.16-215-215217ㅇ문화예술 창작보급 및 문화예술활동 지원,ㅇ시민 문화향수 기회 확대 및 창의성 제고,ㅇ전통문화예술의 계승과 발전,ㅇ문화예술진흥을 위한 정책개발, 자문 및 교육, 연구,ㅇ국내외 문화예술 교류,ㅇ문화예술 정보 축적 및 네트워크서비스사업3본부 9팀 1센터56263015080423275.0129111042임대,(1305.83㎡)20210215123123문화데이터총람 2020KC_482_DMSTC_MCST_CLTPLC_202120200101
3KCDMMCC21N000000004문화시설지역문화재단인천문화재단인천광역시인천 중구2811010600해안동2가2811053000신포동281104247167인천 중구 신포로15번길 6422314다사22341837.472407126.62147인천광역시 문화재단 설립 및 운영에 관한 조례박남춘,(시장)T)032-455-7100,F)032-772-7190www.ifac.or.kr2004.12.10.-59.3-59.3547.7ㅇ문화예술 기금지원 사업,ㅇ시민문화 활성화사업,ㅇ문화예술정책연구사업,ㅇ문화예술교류사업,ㅇ문화예술교육사업,ㅇ인천아트플랫폼 운영,ㅇ한국근대문학관 운영,ㅇ트라이보울 운영 ,ㅇ강화/인천지역 역사연구,ㅇ남북문화교류사업 ,ㅇ인천시위탁사업 등2실 3부,2센터 3관80463417875143270.01813252985자체,(808.4㎡)20210215123123문화데이터총람 2020KC_482_DMSTC_MCST_CLTPLC_202120200101
4KCDMMCC21N000000005문화시설지역문화재단광주문화재단광주광역시광주 남구2915510200구동2915554500사직동291553009007광주 남구 천변좌로338번길 761636다라46083735.147906126.907897광주광역시 광주문화재단 설립 및 운영조례이용섭,(광주광역시장)T)062-670-7400,F)062-670-7489www.gjcf.or.kr2010.12.27.-53-5395.2ㅇ문화예술정책개발 및 사업실행,ㅇ문화관광진흥사업,ㅇ문화예술기금지원사업,ㅇ문화예술교육사업,ㅇ문화예술교류사업,ㅇ축제행사,ㅇ빛고을 시민문화관 운용 및 지원사업1처 2실 1단 2관 13팀10459459474101179.014464064무상임대,(824㎡)20210215123123문화데이터총람 2020KC_482_DMSTC_MCST_CLTPLC_202120200101
5KCDMMCC21N000000006문화시설지역문화재단대전문화재단대전광역시대전 중구3014011600문화동3014072000문화1동301403164033대전 중구 중앙로 3234944다바92413936.322453127.4161대전문화재단 설립 및 운영조례정윤기,(행정부시장)T)042-480- 1000,F)042-480-1099www.dcaf.or.kr2009.9.23.-89.2-89.2124ㅇ문화예술 창작, 보급, 활동 지원사업,ㅇ시민의 문화향수 기회 확대를 위한 사업,ㅇ전통문화예술의 계승과 발전사업,ㅇ문화예술진흥을 위한 정책자문 및 교육, 조사연구사업,ㅇ국내외 문화예술 교류사업,ㅇ문화예술 정보의 축적 및 서비스 제공사업,ㅇ재단의 목적 달성을 위하여 필요한 사업 ,ㅇ그 밖에 문화예술진흥을 위하여 대전광역시장이 위탁하는 사업1본부 1관 9팀515011554830206.013551437무상임대,(26309㎡)20210215123123문화데이터총람 2020KC_482_DMSTC_MCST_CLTPLC_202120200101
6KCDMMCC21N000000007문화시설지역문화재단울산문화재단울산광역시울산 남구3114010400신정동3114053000신정3동311403170051울산 남구 중앙로 20244690마마64328535.53893129.312867울산광역시 문화재단 설립 및 운영에 관한 조례송철호,(시장)T)052-259-7906,F)052-256-3726www.uacf.or.kr2016.12.28.-13.7-13.723.8ㅇ문화예술기금지원사업,ㅇ축제발굴 및 시행,ㅇ문화예술교육사업,ㅇ문화복지사업,ㅇ문화시설 위탁 운영1처 4팀242316329-193.01041722임대,(503.44㎡)20210215123123문화데이터총람 2020KC_482_DMSTC_MCST_CLTPLC_202120200101
7KCDMMCC21N000000102문화시설지역문화재단천안문화재단충청남도천안시4413310200성정동4413351000성정1동441334550357충남 천안시 서북구 성정8길 531142다바68068936.817928127.141324천안문화재단 설립 및 운영에 관한 조례구본영,(이사장/현천안시장)T)041-900-0211~2,F)041-900-0213www.cfac.or.kr2012.02.09.-11.6-11.611.6ㅇ흥타령춤축제 및 국제춤축제연맹(FIDAF) 운영,ㅇ아우내봉화제, 찾아가는 예술무대 및 거리공연,ㅇ천안예술의전당(공연장, 미술관, 아카데미) 운영,ㅇ생활문화동호회 네트워크 교류 및 지역문화매개자 인력양성,ㅇ청년문화·지역문화연구기획 지원,ㅇ문화예술지원사업,ㅇ한 뼘 미술관 운영·관리,ㅇ도솔문예지 발행,ㅇ천안문화예술뱅크(문화예술DB) 사업운영1국 7팀 1전당45321363306.50101.0213814임대,(392.67㎡)20210215123123문화데이터총람 2020KC_482_DMSTC_MCST_CLTPLC_202120200101
8KCDMMCC21N000000009문화시설지역문화재단경기문화재단경기도경기 수원시4111514100인계동4111573000인계동411153176010경기 수원시 팔달구 인계로 17816488다사58918637.265775127.036882경기문화재단 설립 및 운영에 관한 조례김학민T)031-231-7200,F)031-236-3708www.ggcf.or.kr1997.7.3-250-2501051ㅇ역사∙문화유산의 발굴∙보존∙현대화,ㅇ문화예술 창작∙교육∙ 보급지원과 환경조성,ㅇ문화예술 정책개발 및 자문,ㅇ문화예술단체 및 예술인 육성 지원․문화예술 정보화 및 홍보,ㅇ국제문화예술 교류 ,ㅇ지방향토사 연구,ㅇ도 문화예술시설의 관리 및 운영 ,ㅇ정부 및 지방자치단체장의 위탁사무 등2실, 1센터, 3본부, 7소속기관614187427391.8080-471.889231454자체 및 무상임대,(5772㎡)20210215123123문화데이터총람 2020KC_482_DMSTC_MCST_CLTPLC_202120200101
9KCDMMCC21N000000010문화시설지역문화재단강원문화재단강원도강원 춘천시4211011500소양로3가4211058000소양동421103218004강원 춘천시 금강로 1124272라사19686937.88244127.724006강원도 문화예술진흥 조례강금실,(이사장)T)033-240-1311,F)033-251-3408www.gwcf.or.kr1999.12.28.1042-52217ㅇ지역문화예술진흥사업(창작지원, 교육지원 등),ㅇ강원국악예술회관 위탁관리,ㅇ평창대관령음악제,ㅇ강원국제예술제,ㅇ강원영상위원회2본부 2실,1위원회,,12팀725814121.758.845.115.4241.09502135임대,(1,289㎡)20210215123123문화데이터총람 2020KC_482_DMSTC_MCST_CLTPLC_202120200101
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90KCDMMCC21N000000091문화시설지역문화재단원주문화재단강원도원주시4213010600명륜동4213054100명륜1동421302219001강원 원주시 서원대로 33126447라사39326337.335437127.944606원주문화재단 설립 및 운영에 관한 조례원창묵,(시장)T)033-763-9114,F)033-763-9631www.wcf.of.kr2010.12.03.-10-10-ㅇ문화예술지원사업,ㅇ문화시설운영,ㅇ원주다이내믹댄싱카니발,ㅇ청년플랫폼 활성화사업,ㅇ생활문화동아리 지원 및 센터 운영,ㅇ원주문화특화지역조성사업 및 문화도시 지정준비,ㅇ 문화예술 진흥 시책 수립 지원,ㅇ국가와 도 및 시가 하는 사업의 대행 및 위탁하는 사업,ㅇ커뮤니티 카페 운영,ㅇ기타 재단의 목적에 적합한 사업1실 7팀3224885420.291.21612-2654무상임대,(140㎡)20210215123123문화데이터총람 2020KC_482_DMSTC_MCST_CLTPLC_202120200101
91KCDMMCC21N000000092문화시설지역문화재단평창문화예술재단강원도평창군4276036021진부면 하진부리4276036000진부면427603000145강원 평창군 진부면 경강로 355425332라사93259737.632121128.556492평창군 문화예술재단 설립 운영 조례김도영,((주)케이프라이드 사장)T)033-336-7107,F)033-336-7106www.artpc.co.kr2012.11.30.-0111ㅇ문화예술육성지원사업,ㅇ평창 청소년 교육 사업,ㅇ평창올림픽 관련 사업 및 평창평화페스티벌,ㅇ찾아가는 문화사업1국 3팀77016.61--17.712238무상임대,(368.73㎡)20210215123123문화데이터총람 2020KC_482_DMSTC_MCST_CLTPLC_202120200101
92KCDMMCC21N000000093문화시설지역문화재단영월문화재단강원도영월군4275025021영월읍 영흥리4275025000영월읍427503227006강원 영월군 영월읍 단종로 2426227라사85910137.186096128.468183영월군 영월문화재단 설립 및 운영에 관한 조례최명서,(군수)T)033-375-6353,F)033-374-6353www.ywcf.or.kr2015.12.29.-0.1--5· 지역 문화예술 진흥 및 육성,· 지역 문화제 및 축제 기획 운영,· 문화예술회관 운영 및 관리 등1국3팀15114381.61-41.052-815무상임대,(128㎡)20210215123123문화데이터총람 2020KC_482_DMSTC_MCST_CLTPLC_202120200101
93KCDMMCC21N000000094문화시설지역문화재단홍천문화재단강원도홍천군4272025024홍천읍 갈마곡리4272025000홍천읍427203000146강원 홍천군 홍천읍 설악로 179225150라사34865537.688967127.895471홍천문화재단 설립 및 운영에 관한 조례허필홍,(군수)T)033-439-5800www.hccf.or.kr2016.06.17.--4242-ㅇ지역문화진흥, 문화복지증진, 축제활성화,ㅇ관광진흥사업 등1실 2부231853200032.000044자체,( 148.2㎡)20210215123123문화데이터총람 2020KC_482_DMSTC_MCST_CLTPLC_202120200101
94KCDMMCC21N000000095문화시설지역문화재단횡성문화재단강원도횡성군4273025022횡성읍 읍하리4273025000횡성읍427303226020강원 횡성군 횡성읍 문예로 7525236라사42043337.488638127.975199횡성문화재단 설립 및 운영에 관한 조례채용식,(이사장)1522-1099www.hscf.or.kr2017.08.03.-33.6-33.6-ㅇ문화정책수립, 문화지표 개발, 국.도비 공모사업 추진,ㅇ우수문화예술공연유치,기획공연개발,ㅇ문화예술교육및문화소외계층찾아가는문화사업,ㅇ문화예술지원사업추진,ㅇ횡성군 대표축제 운영(횡성한우축제)1국 2팀77-33.60--33.6102-315무상임대,(113㎡)20210215123123문화데이터총람 2020KC_482_DMSTC_MCST_CLTPLC_202120200101
95KCDMMCC21N000000096문화시설지역문화재단태백시문화재단강원도태백시4219010100황지동4219054000상장동421903222006강원 태백시 번영로 22026023마사31808137.162936128.98529태백시문화재단 설립 및 운영에 관한 조례류태호,(시장)T)033-550-6900,F)033-550-6910www.tbcf.or.kr2019.11.22-3---ㅇ 문화예술업무 국.도비 공모사업 추진,ㅇ 지역문화예술단체지원사업,ㅇ 태백산눈축제, 한강낙동강발원지 축제 등 대표축제 추진1국 2팀862,(공무원)18.9---18.9---22자체,( 148.2㎡)20210215123123문화데이터총람 2020KC_482_DMSTC_MCST_CLTPLC_202120200101
96KCDMMCC21N000000097문화시설지역문화재단청주시문화산업진흥재단충청북도청주시4311410200내덕동4311453000내덕2동431143236027충북 청주시 청원구 상당로 31428501다바99350936.656196127.492382청주시문화산업진흥재단 설립 및 운영 지원 조례한범덕 ,(청주시장)T)043-219-1006,F)043-219-1234www.cjculture.org2001.12.12.-1-154ㅇ문화사업과 문화산업 진흥을 위한 계획수립 및 시행,ㅇ문화산업단지 관리운영 및 시설물 관리,ㅇ청주국제공예비엔날레 행사 추진1사무국,1실 7팀99633684.82915.246.5175.53161121자체자산,(890㎡)20210215123123문화데이터총람 2020KC_482_DMSTC_MCST_CLTPLC_202120200101
97KCDMMCC21N000000098문화시설지역문화재단충주중원문화재단충청북도충주시4313010100성내동4313051500성내.충인동431303238091충북 충주시 중앙로 12827388라바38985836.970619127.937221충주중원문화재단 설치 및 운영에 관한 조례조길형,(충주시장)T)043-851-7981,F)043-851-7983www.cjcf.or.kr2006.09.15.-1-11ㅇ중원문화의 전승발전 및 보급,ㅇ문화·예술 진흥, 정책개발 및 자문,ㅇ문화·예술 창작 및 보급, 활동지원,ㅇ문화행사 및 축제와 관련된 사업,ㅇ문화협력 및 연계·교류사업,ㅇ문화·예술 교육·연구사업,ㅇ문화시설 운영관리 및 문화예술 위탁사업 등2처 4팀21111016.12100026.12632920임대,(370.68㎡)20210215123123문화데이터총람 2020KC_482_DMSTC_MCST_CLTPLC_202120200101
98KCDMMCC21N000000099문화시설지역문화재단영동축제관광재단충청북도영동군4374025027영동읍 매천리4374025000영동읍437403243040충북 영동군 영동읍 영동황간로 12229150라마25396336.164016127.781948영동군 재단법인 영동축제관광재단 설립 및 지원조례박세복,(이사장/현 영동군수)T)043-745-8912,F)043-745-8621www.ydft.kr2017.03.24<NA>2.5<NA>2.5<NA>영동4대축제 및 관광업무 총괄1사무국,3팀764180.2<NA><NA>18.0---0.20.2무상임대,(132.23㎡)20210215123123문화데이터총람 2020KC_482_DMSTC_MCST_CLTPLC_202120200101
99KCDMMCC21N000000100문화시설지역문화재단제천문화재단충청북도제천시4315011300청전동4315059000청전동431502239002충북 제천시 의림대로 24227152라사63505837.149342128.216086제천문화재단 설립 및 운영에 관한 조례김연호,(이사장)T)043-645-4998www.jccf.or.kr2019.03.12-29.5-29.5<NA>ㅇ지역문화예술진흥 및 지원,ㅇ지역문화예술진흥정책 개발 및 연구,ㅇ생활문화진흥,ㅇ예술창작·활동 지원,ㅇ문화예술교육 확대,ㅇ지역주민 문화향유 진흥 및 지원,ㅇ문화인력 양성,ㅇ문화기반시설 운영 및 관리,ㅇ지역 문화콘텐츠 산업 진흥,ㅇ영상물 제작 및 촬영 유치·지원1사무국 3팀181261.20.222.69.633.654-2029무상임대,(117.3㎡)20210215123123문화데이터총람 2020KC_482_DMSTC_MCST_CLTPLC_202120200101